drug development research project

Username or Email Address

Remember Me

Drug Discovery and Development: A Step by Step Guide

Drug discovery and development can be described as the sum total of steps taken by research-intensive entity to identify a new chemical or biological substance and transform it into a product approved for use by patients.

This highly knowledge and capital intensive process takes, on average, 10-15 years and over $2 billion (2021 figures), to pull off.

But exactly what is involved? Who does what and when? In this article, we outline key concepts of drug discovery and development, including target identification, clinical trials, pharmaceutical development and commercialisation.

Drug Development

Drug development covers all the activities undertaken to transform the compound obtained during drug discovery into a product that is approved for launch into the market by regulatory agencies. This is a pivotal process, and a lot rides on its success, thus, efficiency is absolutely critical, but mainly for two key points:

Firstly, development is expensive – accounting for 70% of the total R&D costs. Even though the number of projects is much smaller compared with those under discovery, the cost per project is significant, and increases exponentially as the project progresses through into the latter stages.

Secondly, speed is the essence in drug development as it determines how soon the company can start earning a return on the huge investment ploughed into the project. Besides, any delays eat away into exclusivity arrangements granted by patents and time before generic manufacturers can launch me-too products.

For clarity, drug development is presented as an operation that’s distinct from discovery. In reality, the distinction is not as clear cut. Often, different activities are being undertaken concurrently, and in deed, some processes that were traditionally undertaken much later on are increasingly being brought much forward. The idea is to identify compounds that have the highest chances of success much earlier and focus on those.

Components of drug development

The key activities involved in the development of a typical are summarised in the diagram below, showing the different tasks that are undertaken during this process. Generally, these tasks can be divided into three parts: technical; investigative and administrative.

General Perspective – New Drug Discovery and Development

T he process of creating a new drug product can be broadly divided into three main phases:

• Drug discovery – entailing the conceptualisation of the therapeutic into a molecule with known pharmacologic effects
• Drug development – covering the steps taken to convert the molecule above into an approved and registered drug product
• Commercialisation – which includes all the steps taken to convert the product into an approved therapeutic, launch into the market and to generate sales

These processes are schematically illustrated below, which is greatly oversimplified:

Historically, these functions were performed, respectively by the Research, Development and Marketing departments. Nowadays though, a number of these functions are outsourced to other companies that specialise in one or more aspects of these activities.

It’s worth emphasising that many activities described in the above scheme may proceed in parallel and other may spill out into other phases. For example, development activities, such as clinical trials or additional testing of formulations, generally continue well beyond registration of the drug product. Such tests may be driven by the requirement for more understanding about the new drug or the need to extend use beyond the main therapeutic applications.

The job of the discovery teams does not end with product registration and market launch. Many discovery scientists will carry out more research looking for other candidates to serves as backups in case the lead compound fails or as follow-on compounds that might have better safety or efficacy profiles over the lead compounds.

Finally, the three processes listed in the new drug development scheme above are not independent and consecutive. Rather, they are coordinated with each other because the performance of each process influences decisions taken in another stage.

Understandably, there are many competing interests as the new drug progresses through its journey. To successfully fit in and integrate all the different interests and cultures, effective project management skills are required.

Therapeutic Concept Selection

Therapeutic concept selection is about deciding whether or not to embark on a new 0project. Success at this stage is measured in terms of agreeing and signed off a drug discovery program with a clear-cut aim and timeline.

Exactly where the idea originates varies from company to company. Some companies have very strong exploratory research teams that undertake research internally and discover new knowledge on diseases and druggable targets. Others are more open minded, preferring to purchase new molecules in for further development. Often, it’s a mixture of both approaches.

Generally, the decision to select a particular program will be guided by three things: company strategy, technical capabilities and operational constraints.

• Should the company do it? (Strategy)
• Could the company do it? )scientific and technical capabilities)
• Can the company deliver it? (operational constraints)

These three factors are summarised below:

Drug Discovery

The drug discovery process technically starts with choice of a disease area and a definition of the therapeutic need that should be addressed. Once this is done, the process proceeds to identification of the physiological mechanisms that need to be targeted, and ideally, identification of a specific molecular ‘drug target’.

During this phase, effort is focussed on identifying a lead chemical structure, designing, testing and fine-tuning it and ensure that it meets all the criteria required for development into a drug product.

An overview of the main stages that constitute a typical drug discovery project, from the point of identification of a target to the production of a candidate drug is shown below this process is shown below:

Discovery can at first appear like a shot in the dark. At the start, scientists will be dealing with a huge number of compounds (10 20 ), which have to be filtered, mainly via computer simulations (in silico) into manageable number capable of being further optimised.

High throughput screening (HTS) is then applied to identify ‘HITS’ which demonstrate interesting activity. Since HTS can throw up a huge number of ‘HITS’ these are further optimised and validated to remove any artefacts or ‘noise’ from the screen.

A key aspect of validation stage is to find relationships between chemical structure and biological activity, and to find out if the compounds belong to any existing families of compounds (known as hits series).

Validated hits are therefore further studied, especially in terms of their pharmacokinetic profiles and toxicity. At this point, the number of compounds has reduced to a handful. It is these handful of substances that are subsequently entered into the lead optimisation programme.

Lead optimization is a critical process in drug discovery since it’s determines whether a suitable compound can be identified for taking forward into preclinical and clinical studies. Therefore, the goal of this stage is to scrutinise and fine-tune, typically in parallel, both the biological activity and the physicochemical properties of the lead series.

During this stage, rigorous data is generated in a precise, timely manner to quickly determine the compounds to progress the compounds, and the series, toward the ideal candidate profile. The higher the quality of these candidates, the higher the chances of successful progression into clinical trials.

“MAGIC BULLETS”

The term ‘magic bullet’ was coined by Paul Ehrlich (1854 – 1915), a Germany medical scientist and winner of the Nobel Prize in Physiology or Medicine in 1908. Ehrlich envisaged a compound (the bullet) capable of attacking a pathogen and destroying it while leaving its host intact. Nowadays, pharmaceutical scientists are developing targeted and personalised cancer therapies, and these, many argue, are modern realisations of Ehrlich’s idea.

Technical development – solving technical issues related to synthesis and formulation of the drug substance with the aim of ensuring the quality and safety of the drug product. The key functions involved here are chemical, manufacturing and formulation development.

Investigative studies – establishing the safety and efficacy of the product, including assessment of whether it’s pharmacokinetically suitable for clinical use. The main function involved here are safety pharmacology, toxicology and clinical development.

Administrative functions – coordinating and managing quality control, logistics, communications and decision making to ensure high quality data are generated and to minimise any delays. The main function involved here is project management.

In addition, there will be a team coordinating and liaising with regulatory authories, collating data, liaising with material suppliers and writing dossiers for presentation to authorities in order to gain approval in a timely manner.

Pharmaceutical Development

This stage is also known as pharmaceutical development. Since pure drug substances are rarely suited for clinic use, they need to be formulated; by combining them with excipients, into tablets, capsules, injections, etc.

Pharmaceutical development refers to all the different tasks undertaken to transform the drug substance identified as a candidate during the discovery phase into a dosage form that is able to reliably deliver the drug into the body in a safe and reliable way.

Designing a formulation can be as equally time consuming and complex as drug discovery. In order to mitigate some of the issues that crop up, initial studies are undertaken during lead optimisation, before development actually starts.

For conventional drug substances, the desired route of administration is the oral route. Alternatives are considered, particularly if sufficient bioavailability cannot be achieved orally.

The different tasks undertaken in pharmaceutical development can be grouped into two:

• Preformulation studies which specifically investigate physical and chemical properties of the drug substance, such as solubility and dissolution rates; acidity and alkalinity (pKa), chemical and physical stability, lipophilicity, particle morphology, melting point and fracture behaviour, etc.
• Formulation studies which are essentially, chemical engineering effort aimed at converting a powder or a liquid form of the drug substance into a stable and deliverable product. During this process, formulation scientists will take into account all the known properties of the drug substance and the desired drug delivery system that best meets the therapeutic objectives of the compound.

Clinical Development

Clinical development is an umbrella terms to describe the whole set of activities undertaken by the team in support of testing of a new drug substance in humans. It includes the following clinical trials, which refer to administration into man the new drug under controlled conditions to investigate bioavailability, efficacy, safety, tolerability and acceptability.

Clinical development of new drugs has been described as both a science and an art, since it requires technical expertise, sound judgement and commercial acumen.

Executed well, clinical development brings new medicines quickly and safely to patients who need them, while also managing to return on the financial investment.

At the time of writing this post In 2021, estimates of the investment required for clinical development studies vary, but most sources agree that, including the cost of failures and capital invested, the total cost of bringing a new drug to market is $2-3 billion, spread over a 12-year development cycle. Out of this cost, two-thirds is spent on clinical development.

The clinical development process is divided into four phases, summarised in the table below.

• Phase I: first introduction and safety assessment in man, typically in healthy volunteers
• Phase II: early exploratory and dose-finding studies in patients
• Phase III: large scale studies in patients
• Phase IV: post-marketing safety monitoring of patients.

In almost every country on earth today, clinical trials are a legal requirement before a new drug can be sold or claims made for its safety of benefits. This does not include alternative remedies, however. In addition, all clinical trials, include Phase I studies, are subject to international, national and in most cases, institutional regulations.

The different international regulations and requirements are set out in guidelines published by the International Conference on Harmonisation (ICH), an organisation that was set up to harmonise pharmaceutical regulations across Europe, United States and Japan.

It is a requirement that clinical development procedures be done under ICH guidelines if the results are to be accepted for registration in the three ICH guidelines. This does not mean that the studies need to be done there – they only have to comply with these guidelines.

In addition to ICH guidelines, human studies are required to be undertaken according to an ethical framework defined code, known as the The Declaration of Helsinki (2000). This code, in a nutshell, requires the principal investigator (physician) to protect life, health, privacy and dignity.

Regulatory Affairs

A fundamental maxim in pharmaceutical new product development is the basic division of responsibilities whereby the health authority, such as the US FDA, is responsible for safeguarding the public’s health against defective and unsafe products, and the pharmaceutical company being responsible for all aspects of drug product development (quality, safety and efficacy).

The regulatory authority develops regulations and guidelines for companies and others in the value chain to follow. The approval of a pharmaceutical product is a contract between the regulatory authority on behalf of the public, and the pharmaceutical company.

The regulatory authority is responsible for approving clinical trial applications, approving marketing authorisation applications, and monitoring safety and efficacy claims of the marketed drugs. Authorities can withdraw the approval at any point where there are cases of non-compliance.

The conditions of the approval are set out in a dossier and appear in the prescribing information. Changes to these terms have to be pre-approved and authorised before they can be implemented.

Within pharmaceutical companies, the regulatory affairs department is the one responsible for obtaining approval for the new pharmaceutical product and working to ensure that this approval is maintained for as long as the company desires so.

Regulatory affairs professionals work at the interface between the regulatory authority and the project team, and they’re often the channel of communication between external and internal stake holders with respect project’s regulatory standing and progress.

Milestones and Decision Points

The decision to advance a drug candidate into early development is the first of several key strategic decision points in a new drug development project. The timing, naming and decision-making process vary from company to company, the one conceptualised below was developed by Norvatis:

Early selection point (ESP

Is the decision to take the drug candidate molecule into early (preclinical) development.

Decision to develop in man (DDM)

Is the decision to enter the compound into Phase 1, based on information obtained during preclinical development phase. Once this decision is made, the company will aim to produce between 2 and 10kg of clinical grade material.

Full development decision point (FDP)

This point is reached after Phase I and Phase IIa studies have been completed. At this point, the company has some preliminary evidence about clinical efficacy in man. From here on, the project costs skyrocket and the company must be confident on commercial returns.

Submission decision point (SDP)

This is the final point when a decision is taken to apply for registration, based on the data collected and its quality.

Summary Points about Drug Discovery and Development

Pharmaceutical companies undertake research for commercial reasons and their overarching objective is a return on capital invested. This is not to say a few companies include altruistic motives, the fact of the matter is that it takes less priority.

For this reason, the research a company pursues has to be in line with its commercial goals. Curiosity-driven research is generally left to Universities and other institutes. That said, there are territories where the two universes overlap, namely, applied research. Many recent innovations in medicine, such as monoclonal antibodies, fall into this domain, and both pharmaceutical companies, and universities have contributed to their development.

Finally, it should be stated that drug discovery and development is unlike any other type of development or innovation process, such as developing a new car. Drug discovery and development carries far greater uncertainty, and the outcome is rarely assured.

Resources Used

Pharmacentral has a strict referencing policy and only uses peer-reviewed studies and reputable academic sources. We avoid use of personal anecdotes and opinions to ensure the content we present is accurate and reliable

• R.G. Hill, H.P. Rang, Preface to 2nd Edition, in: R.G. Hill, H.P. Rang (Eds.) Drug Discovery and Development (Second Edition), Churchill Livingstone 2013
• Orloff et a.,l The future of drug development: advancing clinical trial design. Nat Rev Drug Discov 8, 949–957 (2009). https://doi.org/10.1038/nrd3025

Related blog posts

The United States Pharmacopoeia

The european pharmacopoeia.

Pharmaceutical Matrix Forming Excipients: Overview, Types, and Selection Criteria

Pharmaceutical Suspending Agents: Overview, Types, and Selection Criteria

Pharmaceutical Thickeners (Viscosity-Increasing Agents): Overview, Types, and Functions

Transforming academic translational research

Expertise in drug discovery research

Developing for the future

What’s New?

JHDD researchers lead a breakthrough study published in Science Advances showing anti-cancer effects of novel compound DRP-104 that is the basis of a current clinical trial

Click here to read more

JHDD-developed glutamine antagonist receives Fast Track designation from FDA for small-cell lung cancer

JHDD-cofounded PSMA Therapeutics acquired by Bayer AG

JHDD coauthors a report showing glutamine antagonism overcomes tumor immune invasion [ Science]

JHDD received a UG3 grant through the HEAL initiative to develop new a new treatment for neuropathic pain

Building innovative partnerships

Our high throughput screening  collaboration with Eisai represents an innovative way to create synergy between complimentary organizations to develop new therapeutics.

Interested in Working With Us?

We welcome opportunities to discuss how we can work together in a  drug discovery collaboration .

• Open access
• Published: 23 June 2020

Exploring different approaches to improve the success of drug discovery and development projects: a review

• Geoffrey Kabue Kiriiri   ORCID: orcid.org/0000-0001-9814-2258 1 ,
• Peter Mbugua Njogu 2 &
• Alex Njoroge Mwangi 1  

Future Journal of Pharmaceutical Sciences volume  6 , Article number:  27 ( 2020 ) Cite this article

59k Accesses

82 Citations

Metrics details

There has been a significant increase in the cost and timeline of delivering new drugs for clinical use over the last three decades. Despite the increased investments in research infrastructure by pharmaceutical companies and technological advances in the scientific tools available, efforts to increase the number of molecules coming through the drug development pipeline have largely been unfruitful.

A non-systematic review of the current literature was undertaken to enumerate the various strategies employed to improve the success rates in the pharmaceutical research and development. The review covers the exploitation of genomics and proteomics, complementarity of target-based and phenotypic efficacy screening platforms, drug repurposing and repositioning, collaborative research, focusing on underserved therapeutic fields, outsourcing strategy, and pharmaceutical modeling and artificial intelligence. Examples of successful drug discoveries achieved through application of these strategies are highlighted and discussed herein.

Conclusions

Genomics and proteomics have uncovered a wide array of potential drug targets and are facilitative of enhanced scrupulous target identification and validation thus reducing efficacy-related drug attrition. When used complementarily, phenotypic and target-based screening platforms would likely allow serendipitous drug discovery while increasing rationality in drug design. Drug repurposing and repositioning reduces financial risks in drug development accompanied by cost and time savings, while prolonging patent exclusivity hence increased returns on investment to the innovator company. Equally important, collaborative research is facilitative of cross-fertilization and refinement of ideas, while sharing resources and expertise, hence reducing overhead costs in the early stages of drug discovery. Underserved therapeutic fields are niche drug discovery areas that may be used to experiment and launch novel drug targets, while exploiting incentivized benefits afforded by drug regulatory authorities. Outsourcing allows the pharma industries to focus on their core competencies while deriving greater efficiency of specialist contract research organizations. The existing and emerging pharmaceutical modeling and artificial intelligence softwares and tools allow for in silico computation enabling more efficient computer-aided drug design. Careful selection and application of these strategies, singly or in combination, may potentially harness pharmaceutical research and innovation.

Humans have been in a perpetual tug-of-war with diseases since the ancient days. Efforts to contain plagues have been recorded in historical artifacts over the course of our existence. While many remedies had been discovered in the early centuries, it cannot be gainsaid that the twentieth century was a pharmaceutical golden era that brought the bulk of the current repertoire of drugs at our disposal [ 1 ]. The accelerated speed at which drugs were discovered can be attributed in part by a significant leap in the scientific disciplines of biology and organic chemistry. The former facilitated a thorough understanding of the pathophysiological basis of the diseases hence enabled scientists to accurately detail the underlying biochemical derangements leading to the observed disease phenotype. Organic chemistry, on the other hand, was instrumental in the synthetic and/or semi-synthetic derivation of novel drug molecules to address the existing and emerging unmet medical needs [ 2 ]. Serendipitous drug discovery also played a critical role in drug discoveries as exemplified by the manner that penicillins were discovered by the English bacteriologist Alexander Fleming in the year 1928. The golden era of drug discoveries continued for five decades following the discovery of penicillin. The resultant effects of drug discoveries were felt across all spheres of the human race most notably the significant improvements in the quality of life and the prolonged longevity enabling humans to live much longer than ever before [ 3 ].

The number of new drug molecules coming through the drug discovery and development pipeline started dwindling in the 1980s [ 4 ]. A review of the literature reveals that less than one in 10,000 potential drug compounds that begin the drug discovery journey find their way to the clinic [ 5 ]. It is hypothesized that we may have exhausted the low hanging fruits and thereby greater efforts are needed to bring new drugs to the market. The entry bar for new molecules entering clinical utilization has been raised by regulatory agencies which demand that significant advantages over existing therapeutic options be evident for the new drugs to be considered for marketing authorization. These attributes include increased efficacy, higher potency, reduced toxicity, ease of administration, and affordability [ 6 ]. The overreliance on high technology platforms to identify lead compounds coupled with combinatorial chemistry have been associated with yielding highly lipophilic (greasy) molecules that exhibit poor aqueous solubility resulting in poor pharmacokinetics profiles [ 7 ]. These factors have individually and collectively conspired to increase the cost of identifying and developing new drug molecules with the costs currently hovering above US $2.6 billion per molecule. The number of pharma companies with such financial clout and willing to take the financial risk has gradually decreased through mergers and acquisitions over the years [ 8 ].

While most of the diseases that affect humans have satisfactory therapeutic options available, others have limited or ineffective treatment alternatives and continue exerting a heavy burden on countries and societies. Some of the diseases with huge unmet medical need include neoplastic conditions, diabetes, Alzheimer’s disease, immunological disorders, the human immunodeficiency virus-associated acquired immune deficiency syndrome (HIV-AIDs) [ 9 ], neglected tropical diseases (NTDs), and rare diseases [ 10 ]. Absolute curative therapies for these diseases remain elusive providing a compelling necessity for continued search for new drug molecules.

Figure 1 summarizes the drug discovery and development process. Though a highly lucrative and rewarding enterprise, the process of drug discovery and development is a complicated and arduous scientific journey that begins with identification of a disease or disease area with an unmet medical need. The pharmaceutical or biopharmaceutical firm embarks on the pre-discovery phase which entails elucidation of underlying molecular basis of the disease and development of appropriate animal disease models as well as assay platforms. This is followed by identification of putative targets whose chemical modulation may lead to a therapeutic effect. Upon target identification and validation, the drug discovery team embarks on identifying molecules with the desired pharmacological activity starting with primary hit compounds that are systematically modified to enhance the potency, decrease unwanted effects, and improve desirable physicochemical attributes during the hit-to-lead discovery phase. The end product of the drug discovery process is a candidate drug that is taken through pre-clinical studies and later drug development that transforms the molecule to a clinically useful medicinal product whose efficacy, safety, dosing, and tolerability is established through elaborately designed and executed clinical trials [ 11 ].

Generic outline of the drug discovery and development process

Strategies for improved success in the drug discovery and development process

Key approaches.

Several strategic approaches to enhance efficiency in the drug discovery and development process have been proposed, adopted, and exploited to varied extent in the pharmaceutical research and development (R&D) projects. They include exploitation of genomics and proteomics, the complementarity of phenotypic and target-based screening platforms, expanding the use of existing drug molecules through repurposing and repositioning, use of collaborative research, exploring under-served therapeutic areas, outsourcing approach, and pharmaceutical modeling and artificial intelligence.

Exploitation of genomics and proteomics

It is an established fact that majority of diseases have a molecular or genetic etiology [ 12 , 13 ]. Some conditions including sickle cell disease, cystic fibrosis, muscular dystrophy, and Huntington disease are caused by single gene mutations [ 14 ]. Syndromic conditions such as diabetes and cardiovascular diseases have multifactorial causes including multiple gene mutations confounded by environmental and lifestyle factors [ 12 ]. In the concept of drug discovery, genes have therefore been classified as disease genes, disease-modifying genes, and druggable genes [ 15 ]. Disease genes are those whose mutations cause or predispose a person to the development of a given disease [ 16 ]. Disease-modifying genes encode functional proteins whose altered expression is directly linked to the etiology and progression of a given disease. Druggable genes encode proteins that possess recognition domains capable of interacting with drug molecules eliciting a pharmacological response [ 17 ].

In the current era of target-based drug discovery, it is imperative that the target is scrupulously identified and validated to establish its essentiality in the disease phenotype. This prevents downstream attrition with available data indicating that a significant proportion (52%) of drug failure in clinical trials is due to poor efficacy. Figure 2 depicts the various causes of attrition [ 18 , 19 ]. Classical cases of the drugs imatinib and trastuzumab exemplifies the value of careful target identification and validation in enhancing the success of the drug discovery process [ 20 , 21 , 22 ]. While the above were new molecules carefully designed with the knowledge of the underlying genetic mutation, existing drugs may find new applications through repositioning from their approved indications based on information obtained through genomics [ 23 ]. Genomics can be used to identify and validate druggable genes thus expanding the number of targets available for exploration in drug discovery [ 17 , 24 ]. The use of genomics in target validation has expansively widened through advancement in antisense technology, small interfering RNA (siRNA) that mimic the natural RNA interference (RNAi) and transgenic animal models [ 25 ].

Causes of attrition in drug discovery and development

Exploitation of genomics is not restricted to target identification and validation. Rather, recent trends in pharma R&D show that genomics may be employed in the recruitment of study participants for clinical trials with the selection favoring those subjects more likely to benefit from the intervention being trialed. This ensures that the effect of the drug will be evident if the drug is indeed effective against the target disease and absent if ineffective. The outcome so observed would therefore be attributable to the therapeutic intervention and shielded from other confounders. Genomics can also be used as a predictive tool to forecast potential toxicities emanating from a specific molecule [ 22 ]. Not surprising, the discipline of pharmacogenomics where drugs are adapted to meet individual profiles is fast gaining traction among researchers and medical practitioners, and has positively impacted the process of drug discovery and development [ 22 ].

The human genome was fully described in the year 2002, uncovering a vast treasure trove from which a wide array of novel drug targets could be discovered. Nonetheless, the scientific hype that was associated with the genome project has not been followed with solid benefits as less than 500 of the potential 10,000 targets have been utilized according to the repertoire of drugs registered by the United States Food and Drug Administration (US-FDA) [ 1 , 26 ]. These targets are protein molecules including DNA, RNA, G protein-coupled receptors (GPCRs), enzymes, and ion channels. The GPCRs constitute the largest proportion of targets for currently registered molecules [ 27 ]. It is however expected that the genomic revolution will enhance the drug discovery process significantly given the intensive research currently being done in this field [ 28 ].

Proteomics which is a subset of genomics has been widely explored as an avenue of drug discovery [ 29 ]. Proteomics entails identification, characterization, and quantification of cellular proteins with the aim of establishing their role in the disease progression and the underlying potential for chemotherapeutic manipulation [ 25 ]. Proteomics has been applied widely in drug discovery projects for antineoplastics, neurological, cardiovascular, and rare diseases [ 30 ]. Technologies used in proteomics include gel electrophoresis for protein separation and characterization, mass spectrometry (MS) for identification, and yeast hybrid systems to study protein-protein interactions [ 31 ]. These approaches have the potential to identify novel drug targets and their corresponding genes.

Complementarity of phenotypic and target-based screening platforms

Two distinct screening approaches are routinely employed in the efficacy studies, namely phenotypic (whole-cell) screening and target-based (biochemical) screening. Phenotypic screening evaluates the effects of potential drugs on cultured cell lines (in vitro), isolated tissues/organs (ex-vivo), or in whole animals (in vivo) while target-based screening involves testing the molecules on purified target proteins in vitro [ 32 ]. In the first instance, phenotypic screens are primarily aimed at identifying molecules capable of eliciting the desired pharmacological effect without necessarily elucidating the underlying mechanism of action at the molecular level. They are therefore empirically driven as they focus on phenotypic endpoints. Phenotypic drug screening is information-rich, and the therapeutic relevance of the drug is established much earlier in the drug discovery process. The approach is more physiologically relevant as it is conducted in biological systems that simulate the real physiological environment where cognizance that pharmacological effects result from an interplay of many factors is well appreciated [ 33 , 34 ]. It also provides a huge biological space for serendipitous drug discoveries [ 32 , 35 ]. On the contrary, target-based screening is hypothesis-driven, systematic, and rational. Of essence, it requires identification and isolation of a biochemical target whose modulation leads to a desired pharmacological effect. It employs advanced molecular technologies and biological methods that are facilitative of high throughput screening (HTS) platforms [ 36 ].

Whereas phenotypic screening predominated in the decades before 1980, it has largely been de-emphasized as advances in molecular biology, and genomics took root and favored the target-based screening [ 37 ]. The significant decline in the discovery of first-in-class molecules has in part been attributed to an increasing emphasis on the target-based drug discovery approach [ 34 ]. Analysis of data of the drugs registered by the US-FDA reveals that phenotypic drug discovery has yielded more first-in-class molecules than target-based screening [ 38 ]. These findings have been challenged by a study that established that 78 of 113 first-in-class molecules registered between years 1999 and 2013 were discovered using target-based screening approaches [ 39 ]. The key disadvantages of phenotypic assays include low screening capacity when whole animals are used and the impracticality or difficulty of developing appropriate disease models such as for Alzheimer’s disease [ 40 ]. Numerous reports have demonstrated the inaccuracy of animal models as tools in predicting therapeutic efficacy in humans [ 41 ].

Target-based drug discovery has been the predominant approach of screening putative molecules in the last three decades [ 33 , 42 ]. This has majorly been due to advances in cloning technologies that allow isolation of pure proteins that are then used to screen a large library of compounds using HTS. The high screening capacity afforded by this approach has cemented target-based platform as the default drug discovery approach as companies seek a competitive edge to deliver novel molecules to the market [ 36 ]. Target-based drug discovery begins with understanding the pathophysiological basis of the disease and subsequent identification of the errant biochemical pathway that leads to the disease phenotype. The specific protein that is aberrantly expressed is identified, isolated and its role in the disease phenotype validated by modulation using genomic or pharmacological approaches.

Target-based drug discovery, therefore, elucidates the specific mechanism through which potential drugs produce a pharmacological response. While it lags behind the phenotypic drug discovery approach in yielding first-in-class molecules, target-based drug discovery is unrivalled in producing the best-in-class follower molecules [ 38 ]. This is due in part to the rational, hypothesis and systematic approach employed leading to highly selective, potent molecules with better pharmacokinetic and toxicological profiles. Target based-drug discovery has the advantages of being simpler to undertake, enable faster development, and it enables elucidation of the underlying mechanism of action. It also enables the utilization of modern technological advances including computational modeling, molecular biology, combinatorial chemistry, proteomics, and genomics. Conversely, since the approach is based on the modulation of isolated protein targets, the observed effect may have little physiological relevance as there is oversimplification of the physiological environment in which the drug molecules are evaluated [ 43 ].

Pharmacological effects derive from complex interactions in intact physiological systems that are best simulated by phenotypic drug discovery and are therefore more predictive of the ultimate therapeutic effect in human disease compared to target-based approaches. It is however imperative that drugs be rationally designed to afford specificity thus improved toxicological profiles, while also providing well-defined mechanisms of action of the pharmacologically active molecules offering a firm foundation upon which drugs with better pharmacokinetics and pharmacodynamics profiles may be developed. Therefore, complementary application of both approaches will invariably lead to increased efficiency in drug discovery with the phenotypic approach delivering first-in-class molecules with proven efficacy early in the discovery process. Target-based drug discovery will build upon these foundations to deliver superior follower molecules employing the knowledge on the molecular interactions of the active molecules with the target. There has been a resurgence of the use of phenotypic drug discovery process in an effort to reverse the decline in discovery of new molecular entities coming through the drug discovery pipeline [ 34 , 44 , 45 ]. Table 1 gives a summary of the merits and demerits of either approach.

Repurposing and repositioning of existing drug molecules

Drugs that have been developed for a specific therapeutic application may in the course of their clinical use potentially reveal beneficial effects in other therapeutic areas outside the scope of their original indications. These molecules may, therefore, be evaluated for use in the new diseases areas without requiring structural modifications (drug repurposing) [ 46 ]. Alternatively, the drugs may require alteration of the primary molecular structure to accentuate a desirable side activity while diminishing the primary effect (drug repositioning) [ 47 ]. The two approaches have the potential to resuscitate/rescue previously abandoned molecules as well as expanding the therapeutic applications of drugs in current use. Examples of successful applications of drug repurposing and repositioning are given in Table 2 . They include the drug miltefosine which was developed in the 1980s as an antitumor agent but abandoned due to dose-limiting gastrointestinal side effects. The drug was refocused as an antileishmanial drug with significant success [ 49 ]. Other potential applications for its use as an anti-infective agent have been established with the latest, being its use in the treatment of granulomatous amoebic encephalitis [ 50 ].

Sildenafil is another classic example of successful drug repurposing. Although primarily researched for and originally launched into the market for treatment of pulmonary arterial hypertension secondary to patent ductus arteriosus, sildenafil and other phosphodiesterase type 5 inhibitors are best known for their repurposed clinical indication, namely the management of erectile dysfunction [ 51 , 52 ]. Similarly, drug repositioning was efficiently applied in the R&D of antidiabetic sulfonylureas from sulfonamide antibiotics where the hypoglycemic effect was enhanced while diminishing the antibacterial effect through systematic structural modifications [ 53 ]. The key advantage of drug repurposing and repositioning is the faster development time since the pharmacokinetics and toxicological data as well as other pertinent information regarding the molecules are already available with resultant huge economic savings [ 8 , 46 ]. Repurposing remains a viable approach to availing medicines for protozoan diseases and helminthic diseases [ 54 ]. Many experimental drugs that were abandoned due to development issues or efficacy shortfalls could be resuscitated through repurposing/repositioning [ 54 ]. Approaches to repurpose or reposition existing drugs include experimental screening and in silico approaches with the latter utilizing data of existing drugs to identify new molecule with the potential clinical application [ 47 ].

Collaborative research

By its nature, the corporate pharmaceutical industry is highly competitive with each company aspiring to dominate the race to launch new blockbuster molecules. It is an established industry fact that early market entrants reap more than those who launch follower molecules. Pioneer companies are able to establish strong brand recognition as well as patient and physician loyalty before competition enter the market [ 55 ]. Further, early entrants have sufficient time to perfect their product and set the market price. At any given time, the pharma companies are working to discover and develop molecules addressing similar or very closely related drug targets. Given the astronomical funding channeled into pharmaceutical R&D, these duplicated research efforts collectively end up utilizing resources that could better be invested in the R&D of other disease areas with unmet medical needs. A number of collaborative arrangements have been proposed and utilized for greater success of the pharma R&D. These include precompetitive research, pharma-academia collaboration, and public-private partnerships (PPP) models [ 56 ].

The precompetitive research entails collaboration among pharmaceutical companies, biotechnology companies, and the academic drug discovery units that would otherwise compete but are brought together by a common desire to conduct fundamental research that is facilitative of subsequent drug discovery and innovation. In essence, precompetitive research establishes scientific viability of pursuing a given therapeutic pathway prior to initiation of full-throttle drug discovery and development campaign. Some of the areas in which precompetitive research may be practiced include target identification and validation, sharing of compound libraries, and biomarker and assay development. There are numerous benefits deriving from precompetitive collaboration including reduced costs of research as companies share their resources and expertise, greater efficiency as companies focus on their core competencies thus furthering their excellence, and cross-fertilization of scientific ideas [ 57 ]. Precompetitive collaborations are modeled as virtual institutions with scheduled video conferences to monitor and evaluate the progress made. Once the objectives set upon are attained, companies can then venture into separate drug discovery projects [ 58 ]. Renown precompetitive collaborations include the Biomarkers Consortium, Innovative Medicine Initiative and TranSMART [ 59 ]. TransMART is an inter-organizational collaboration including government agencies, academia, and patient advocacy groups that serves as an open data warehouse arising from clinical trials and basic research [ 60 , 61 ]. In recognition of the potential gains that could accrue from precompetitive collaborations, the US-FDA developed guidelines for registration of drugs discovered through collaborative strategies in 2011 [ 62 ].

There exists a strong justification for pharma-academia collaboration. While the pharma industry has the financial muscle to fund drug discovery and development programs, the academia boasts of unrivaled proficiency in the conduct of basic research that delivers lead compounds, animal disease models, and putative drug targets [ 63 ]. The research capacities of academic institutions have been supported by the availability of tools for translational research, HTS, and chemical libraries. Notable pharma-academia collaborations include AstraZeneca-Columbia University, Pfizer-University of California at San Francisco, Monsanto-University of Washington, and the GlaxoSmithKline (GSK)-Harvard University, among others. The most successful partnerships have been in the area of infectious diseases with drug discoveries for malaria and meningitis A being made [ 64 ]. Novo-Nordisk has successfully employed these partnerships to maintain a competitive edge in the field of diabetes and cardiovascular medicine [ 65 ]. Other successful examples include the Scottish Translational Medicine Research Collaboration, the Dundee kinase consortium, structural genetics consortium, Single Nucleotide Polymorphism (SNP) consortium, and the Transcelerate consortium in the USA [ 66 ].

The PPP models play an important role in bringing new drugs to patients. The partnerships involve public institutions, pharmaceutical industries, and the academia. These partnerships help improve the productivity in the pharmaceutical industry while also aiding the development of drug discovery capabilities in academia from publicly funded research [ 67 ]. The World Health Organization-sponsored Special Programme for Research and Training in Tropical Diseases (WHO/TDR) is one of the most notable PPP globally credited with the discovery of several drugs for tropical diseases. They include chlorproguanil-dapsone combination (Lapdap®) with GSK; injectable artemether with Rhone Poulenc Rorer and injectable β-arteether with Artecef for malaria; eflornithine with Marion-Merrill Dow for human African trypanosomiasis; miltefosine with Zentaris; and liposomal amphotericin B with NeXstar for visceral leishmaniasis; ivermectin with Merck for onchocerciasis; and praziquantel with Bayer for schistosomiasis [ 68 , 69 ].

Under-served therapeutic fields

Strategic considerations are vital before a company commits to a drug discovery project. Among the key considerations is the economic viability of a potential drug molecule upon market entry. For sustainable pharma R&D, any drug development candidate must have an acceptable return on investment to ensure the discovery company remains a viable going concern and is able to fund other drugs in the research pipeline. As such majority of the pharmaceutical R&D efforts are inclined to the therapeutic areas with vast economic potential such as oncology, immunotherapy, endocrinology, neurology, and cardiovascular fields where the probability of recouping the huge capital investment is more certain [ 41 ]. Therapeutic areas that offer negligible financial benefits such NTDs and rare diseases do not attract much attention and therefore the opportunities for novel discoveries largely remain unexplored [ 70 ]. Rare diseases are genetic disorders that afflict a small patient population and thus offer little economic promise. The NTDs, on the other hand, are vector-borne diseases that afflict billions of people in resource-poor countries. However, these populations have low purchasing power and as such, the pharma companies may not recoup their investments let alone enjoy profitability [ 71 ].

The NTDs and rare diseases therapeutic areas present potential avenues of discovering novel drug targets that can then be exploited in other more profitable disease areas where they can be of huge economic value. National agencies have incentivized pharma R&D in these areas by providing tax breaks, accelerated reviews, and extended patent exclusivity [ 72 ]. Investments in orphan drugs can serve as a solid platform for new molecules providing a safety net for companies, thus reducing the impact caused by patent expirations on blockbuster medicines [ 73 ]. The rate at which antibiotic resistance is developing outstrips the rate of their development thereby resulting in a decline in the options available for treating infectious diseases. This is also a fertile avenue for pharmaceutical companies to explore [ 74 ].

Outsourcing strategies

The term outsourcing refers to the industrial practice of contracting out services that were previously performed in-house or to access additional capabilities. Outsourcing of certain activities in the drug discovery and development presents an opportunity to enhance the efficiency of the entire process. The outsourcing industry has expanded significantly with the largest growth being registered in China and India where several contract research organizations (CROs) are domiciled supported by cheaper labor, lower land rates, and an increasingly expanding infrastructure [ 75 ]. Some of the activities amenable to outsourcing include target identification and validation, development of disease models, lead discovery and optimization, pre-formulation studies and specific phases or entire clinical trials [ 76 ]. This approach allows pharmaceutical companies to focus on their core competencies while delegating specific activities to the more highly specialized CROs.

Since the contracted firms are specialists in their core areas, outsourcing results in faster development and significant economic savings. Research has indicated that clinical trials that are carried out by CROs have higher success rates compared to those executed by pharmaceutical companies [ 77 ]. Successful outsourced drug discovery and development projects result in cost reduction, increased operational efficiency, and optimization of resource allocation [ 78 ]. Full benefits are only realized when competent partners are selected and the careful implementation of the project followed [ 79 ]. Adequate control measures must be instituted to ensure that the contracted organizations follow the established code of ethics while conducting the trials [ 8 ].

Pharmaceutical modeling and artificial intelligence

Modeling entails the use of in silico simulations to predict diverse attributes of a drug molecule including pharmacokinetics and pharmacodynamics profiles [ 80 ] . Advances in computing power have enabled development of software that allows simulation of the drug-receptor binding processes, a subset of computer-aided drug design (CADD) also referred to as virtual screening, with tremendous benefits to drug discovery efficiency. First, CADD facilitates generation of focused screens that are then validated in vitro. Second, the CADD is well positioned to guide the lead optimization process thus providing valuable information to the medicinal chemistry team aspiring to enhance the lead molecules receptor affinity or optimize drug metabolism and pharmacokinetics (DMPK) properties including absorption, distribution, metabolism, excretion, and the potential for toxicity (ADMET). Third, the CADD facilitates rational drug design either by “growing” starting molecules one functional group at a time (de novo drug design) on the target site or by piecing together fragments into novel molecules (fragment-based drug design) [ 81 ]. Two screening approaches, namely ligand-based virtual screening and target-based virtual screening, have been used in CADD to filter out the compounds that are unlikely to be successful in the development pipeline due to poor physicochemical properties and/or intolerable toxicological profile while identifying those likely to have the activity of interest.

In ligand-based virtual screening, structural features of known compounds are used to construct computer models that are used to predict the properties of other compounds not included in the training data set. The data sets are then used to generate quantitative-structure activity relationship (QSAR) models correlating structural features and the physicochemical properties of a homologous series to the observed biological activity. The chemical structure of known compounds is reduced to a set of molecular descriptors that are used to generate a mathematical model that is used to predict the properties of the test compounds. Molecular descriptors with the highest activity are chosen for the model [ 82 ]. Target-based virtual screening entails computer models that test the docking properties of test compounds against the three-dimensional structure of the target (X-ray crystal structure or homology model) [ 83 , 84 , 85 ]. Each of the test compounds is optimally positioned on the binding site and assigned a score based on the binding affinity. Top scoring compounds are synthesized and tested in vitro [ 86 ]. Application of these models can enhance the efficiency of drug discovery projects by providing focused screens that can have better chances of succeeding downstream. Problematic molecules are also identified earlier in the drug discovery process thus avoiding expensive late-stage failures. Integration of ligand-based and target-based virtual screening yields better results [ 32 , 87 ].

Modeling and simulation have also been employed in various areas of the clinical drug development process [ 88 ]. The modeling process is founded on mathematical polynomials generated from empirical data for real-life patients. Key areas that may be modeled include bio-simulation to inform planning, implementation, and evaluation of clinical trial designs with the goal of optimizing the efficiency, quality, and cost effectiveness of the trials. Pharmacodynamic and pharmacokinetic models are used to predict optimal dosage levels in the various phases of clinical trials as well as in special populations including pediatrics, geriatrics, pregnant women, and others with constrained physiological conditions that will impact on drug disposition. The application of modeling improves the effectiveness of clinical trials with enormous cost and time saving [ 89 , 90 ]. Successful application of computer-based drug design is exemplified by several drugs in clinical use including nelfinavir, imatinib, zanamivir, saquinavir, and norfloxacin [ 91 ].

Artificial intelligence (AI) is increasingly being applied in the drug design and development. This has been possible due to the availability of large chemical and biological databases that are prerequisites for development of accurate predictive models. Scientists contend that AI has the capacity to revolutionize the drug discovery process enabling the screening of billions of potential molecules for hit identification, prioritization of proposed alternatives, and validation of biological targets. It can further guide lead optimization and inform the design and implementation of clinical trials in the latter stages of drug development. Consequently, strategic implementation of AI could enormously supplement the R&D efforts to avail novel, effective, and safe drugs to alleviate human suffering due to unmet clinical needs [ 92 ]. Generative deep learning networks can propose completely new molecules that exhibit the desired physical and biological properties which can be instrumental in the discovery of drugs for complex disease conditions. They may also be in the optimization of existing molecules. AI is also applied in the multi-objective optimization of lead molecules through the application of machine learning allowing identification of compounds that exhibit a healthy balance of the requisite set of physicochemical, biological, and pharmacokinetic characteristics [ 93 ]. Examples of software used in pharmaceutical modeling and AI-guided drug discovery are listed in Table 3 .

The ever-increasing costs of drug discovery projects have not translated into increased efficiency in delivering new medicines. On the contrary, fewer drugs are transiting through the drug development pipeline than ever before. The observed productivity decline is majorly attributable to the overreliance of the industry on high technology platforms, stringent drug registration and approval requirements for new medicines, and the exhaustion of the obvious and easy-to-reach drug targets necessitating exploration of more complex biological systems.

Scientific advancements allow the application of advanced molecular techniques that include genomics and lately proteomics in identification and validation of drug targets. Carefully executed target identification and validation will reduce the attrition rates attributable to poor efficacy that currently accounts for more than 50% of drug failures. The complementarity of phenotypic and target-based drug discovery approaches would enable discovery of first-in-class molecules while also delivering safer, more efficacious and potent best-in-class follower molecules.

Collaborative strategies, such as precompetitive research and public-private partnerships, have positively impacted efficiency in drug discovery. Expansion of research activities into the underserved therapeutic areas covering rare and neglected diseases would offer a safeguard for companies whose blockbuster drugs are teetering on the patent cliff. Advances in computing technologies will also facilitate selection of focused screens with better success rates downstream. Pharmaceutical modeling and AI are expected to continue contributing significantly to improved efficiency in drug discovery and development in the years to come. Carefully executed outsourcing strategies allow companies to focus on their core competencies while delegating other development activities to expertise offered by the CROs, a strategy that accelerates the discovery process while reducing overhead costs.

Availability of data and materials

Data and materials are available upon request.

Abbreviations

Absorption, distribution, metabolism, elimination, and toxicity

• Artificial intelligence

Acquired immune deficiency syndrome

Computer-aided drug design

Contract Research Organization

Drug metabolism and pharmacokinetics

Deoxyribonucleic acid

United States Food and Drug Administration

G protein-coupled receptors

GlaxoSmithKline

High throughput screening

Mass spectrometry

Public-private partnerships

Quantitative-structure activity relationship

Research and development

Ribonucleic acid

RNA interference

Small interfering RNA

Special Programme for Research and Training in Tropical Diseases

World Health Organization

Drews J (2000) Drug discovery: a historical perspective. Science 287:1960–1964 https://doi.org/10.1126/science.287.5460.1960

Article   CAS   PubMed   Google Scholar  

Rotella DP (2016) The critical role of organic chemistry in drug discovery. ACS Chem Neurosci 7:1315–1316 https://doi.org/10.1021/acschemneuro.6b00280

Gaynes R (2017) The discovery of penicillin—new insights after more than 75 years of clinical use. Emerg Infect Dis 23:849–853 https://doi.org/10.3201/eid2305.161556

Article   PubMed Central   Google Scholar  

Pammolli F, Magazzini L, Riccaboni M (2011) The productivity crisis in pharmaceutical R&D. Nat Rev Drug Discov 10:428–438 https://doi.org/10.1038/nrd3405

Petrova E et al (2014) Innovation in the pharmaceutical industry: the process of drug discovery and development. Springer, New York, pp 19–81

Google Scholar  

Naci H, Carter AW, Mossialos E (2015) Why the drug development pipeline is not delivering better medicines. BMJ:h5542 https://doi.org/10.1136/bmj.h5542

Lipinski CA (2000) Drug-like properties and the causes of poor solubility and poor permeability. J Pharmacol Toxicol Methods 44:235–249. https://doi.org/10.1016/S1056-8719 (00)00107-6

Paul SM, Mytelka DS, Dunwiddie CT et al (2010) How to improve R&D productivity: the pharmaceutical industry’s grand challenge. Nat Rev Drug Discov 9:203–214 https://doi.org/10.1038/nrd3078

Cummings JL, Morstorf T, Zhong K (2014) Alzheimer’s disease drug-development pipeline: few candidates, frequent failures. Alzheimers Res Ther 6:37 https://doi.org/10.1186/alzrt269

Article   PubMed   PubMed Central   Google Scholar  

Ridley RG (2002) Medical need, scientific opportunity and the drive for antimalarial drugs. Nature 415:686–693 https://doi.org/10.1038/415686a

Hughes J, Rees S, Kalindjian S, Philpott K (2011) Principles of early drug discovery: principles of early drug discovery. Br J Pharmacol 162:1239–1249 https://doi.org/10.1111/j.1476-5381.2010.01127.x

Article   CAS   PubMed   PubMed Central   Google Scholar  

Wallis G, BASC (1999) The genetic basis of human disease. The Biochemical Society, London

King R, Rotter J, Motulksy A (2002) The genetic basis of common diseases, 2nd ed

WHO | Genes and human disease. In: WHO. https://www.who.int/genomics/public/geneticdiseases/en/index2.html . Accessed 31 Jan 2019

Hopkins AL, Groom CR (2002) The druggable genome. Nat Rev Drug Discov 1:727–730 https://doi.org/10.1038/nrd892

Dixon SJ, Stockwell BR (2009) Identifying druggable disease-modifying gene products. Curr Opin Chem Biol 13:549–555 https://doi.org/10.1016/j.cbpa.2009.08.003

Chris Finan (2017) The druggable genome and support for target identification and validation in drug development. Sci Transl Med 9:eaag1166. https://doi.org/10.1126/scitranslmed.aag1166

Harrison RK (2016) Phase II and phase III failures: 2013–2015. Nat Rev Drug Discov 15:817–818 https://doi.org/10.1038/nrd.2016.184

Hopkins AL (2008) Network pharmacology: the next paradigm in drug discovery. Nat Chem Biol 4:682–690 https://doi.org/10.1038/nchembio.118

Capdeville R, Buchdunger E, Zimmermann J, Matter A (2002) Glivec (STI571, imatinib), a rationally developed, targeted anticancer drug. Nat Rev Drug Discov 1:493–502 https://doi.org/10.1038/nrd839

Cobleigh MA et al (1999) Multinational study of the efficacy and safety of humanized anti-HER2 monoclonal antibody in women who have HER2-overexpressing metastatic breast cancer that has progressed after chemotherapy for metastatic disease. J Clin Oncol 17:2639–2639 https://doi.org/10.1200/JCO.1999.17.9.2639

Garman KS, Nevins JR, Potti A (2007) Genomic strategies for personalized cancer therapy. Hum Mol Genet 16:R226–R232 https://doi.org/10.1093/hmg/ddm184

Lussier YA, Chen JL (2011) The emergence of genome-based drug repositioning. Sci Transl Med 3:96ps35-96ps35. https://doi.org/10.1126/scitranslmed.3001512

Plenge RM, Scolnick EM, Altshuler D (2013) Validating therapeutic targets through human genetics. Nat Rev Drug Discov 12:581–594 https://doi.org/10.1038/nrd4051

Lindsay MA (2003) Target discovery. Nat Rev Drug Discov 2:831–838 https://doi.org/10.1038/nrd1202

Penrod NM, Cowper-Sal-lari R, Moore JH (2011) Systems genetics for drug target discovery. Trends Pharmacol Sci 32:623–630 https://doi.org/10.1016/j.tips.2011.07.002

Bleicher KH, Böhm H-J, Müller K, Alanine AI (2003) Hit and lead generation: beyond high-throughput screening: a guide to drug discovery. Nat Rev Drug Discov 2:369–378 https://doi.org/10.1038/nrd1086

Dimitri Semizarov, Eric Blomme (2008) Genomics in drug discovery and development | Wiley. In: Wiley.com. https://www.wiley.com/en-us/Genomics+in+Drug+Discovery+and+Development-p-9780470096048 . Accessed 19 Mar 2020

Chanda SK, Caldwell JS (2003) Fulfilling the promise: drug discovery in the post-genomic era. Drug Discov Today 8:168–174. https://doi.org/10.1016/S1359-6446 (02)02595-3

Jain KK (2002) Proteomics-based anticancer drug discovery and development. Technol Cancer Res Treat 1:231–236 https://doi.org/10.1177/153303460200100403

Jain KK (2004) Applications of proteomics technologies for drug discovery. In: Hondermarck H (ed) Proteomics: Biomedical and Pharmaceutical Applications. Kluwer Academic Publishers, Dordrecht, pp 201–227

Chapter   Google Scholar  

Moffat JG, Vincent F, Lee JA et al (2017) Opportunities and challenges in phenotypic drug discovery: an industry perspective. Nat Rev Drug Discov 16:531–543 https://doi.org/10.1038/nrd.2017.111

Wagner BK (2016) The resurgence of phenotypic screening in drug discovery and development. Expert Opin Drug Discovery 11:121–125 https://doi.org/10.1517/17460441.2016.1122589

Article   Google Scholar  

Zheng W, Thorne N, McKew JC (2013) Phenotypic screens as a renewed approach for drug discovery. Drug Discov Today 18:1067–1073 https://doi.org/10.1016/j.drudis.2013.07.001

Ban TA (2006) The role of serendipity in drug discovery. Clin Res 8:10

Samsdodd F (2005) Target-based drug discovery: is something wrong? Drug Discov Today 10:139–147. https://doi.org/10.1016/S1359-6446 (04)03316-1

Kotz J (2012) Phenotypic screening, take two. Sci-Bus Exch 5:380–380 https://doi.org/10.1038/scibx.2012.380

Swinney DC (2013) Phenotypic vs. target-based drug discovery for first-in-class medicines. Clin Pharmacol Ther 93:299–301 https://doi.org/10.1038/clpt.2012.236

Eder J, Sedrani R, Wiesmann C (2014) The discovery of first-in-class drugs: origins and evolution. Nat Rev Drug Discov 13:577–587 https://doi.org/10.1038/nrd4336

Khachaturian ZS (2002) Models and modeling systems in Alzheimer disease drug discovery. Alzheimer Dis Assoc Disord 16

Norris, Diana Pankevich, Miriam Davis, Bruce Altevogt (2014) Improving and accelerating therapeutic development for nervous system disorders: workshop summary. National Academies Press (US), Washington (DC)

Swinney DC, Anthony J (2011) How were new medicines discovered? Nat Rev Drug Discov 10:507–519 https://doi.org/10.1038/nrd3480

Croston GE (2017) The utility of target-based discovery. Expert Opin Drug Discovery 12:427–429 https://doi.org/10.1080/17460441.2017.1308351

Comley J (2015) Phenotypic drug discovery: striving towards the highest level of biological relevance. https://www.ddw-online.com/ . Accessed 28 Jan 2019

Sams-Dodd F (2006) Drug discovery: selecting the optimal approach. Drug Discov Today 11:465–472 https://doi.org/10.1016/j.drudis.2006.03.015

Pushpakom S, Iorio F, Eyers PA et al (2018) Drug repurposing: progress, challenges and recommendations. Nat Rev Drug Discov 18:41–58 https://doi.org/10.1038/nrd.2018.168

Article   PubMed   CAS   Google Scholar  

Cha Y, Erez T, Reynolds IJ et al (2018) Drug repurposing from the perspective of pharmaceutical companies: drug repurposing in pharmaceutical companies. Br J Pharmacol 175:168–180 https://doi.org/10.1111/bph.13798

Ashburn TT, Thor KB (2004) Drug repositioning: identifying and developing new uses for existing drugs. Nat Rev Drug Discov 3:673–683 https://doi.org/10.1038/nrd1468

Charlton RL, Rossi-Bergmann B, Denny PW, Steel PG (2018) Repurposing as a strategy for the discovery of new anti-leishmanials: the-state-of-the-art. Parasitology 145:219–236 https://doi.org/10.1017/S0031182017000993

Article   PubMed   Google Scholar  

Sindermann H, Engel J (2006) Development of miltefosine as an oral treatment for leishmaniasis. Trans R Soc Trop Med Hyg 100:S17–S20 https://doi.org/10.1016/j.trstmh.2006.02.010

Board on Health Sciences Policy (2014) Drug repurposing and repositioning: workshop summary. National Academies Press (US)

White JR (2014) A brief history of the development of diabetes medications. Diabetes Spectr 27:82–86 https://doi.org/10.2337/diaspect.27.2.82

Sola D, Rossi L, Schianca GPC et al (2015) State of the art paper sulfonylureas and their use in clinical practice. Arch Med Sci 4:840–848 https://doi.org/10.5114/aoms.2015.53304

Article   CAS   Google Scholar  

Andrews KT, Fisher G, Skinner-Adams TS (2014) Drug repurposing and human parasitic protozoan diseases. Int J Parasitol Drugs Drug Resist 4:95–111 https://doi.org/10.1016/j.ijpddr.2014.02.002

Cha M, Yu F (2018) Pharma’s first-to-market advantage | McKinsey. https://www.mckinsey.com/industries/pharmaceuticals-and-medical-products/our-insights/pharmas-first-to-market-advantage . Accessed 29 Jan 2019

Munos BH, Chin WW (2011) How to revive breakthrough innovation in the pharmaceutical industry. Sci Transl Med 3:89cm16-89cm16. https://doi.org/10.1126/scitranslmed.3002273

Yildirim O, Gottwald M, Schüler P, Michel MC (2016) Opportunities and challenges for drug development: public–private partnerships, adaptive designs and big data. Front Pharmacol 7. https://doi.org/10.3389/fphar.2016.00461

Medicine (US) (2010) Types of pre-competitive collaborations. National Academies Press (US)

Gastfriend E, Lee B (2015) Pre-competitive collaboration in pharma. 19

Athey BD, Braxenthaler M, Haas M, Guo Y. tranSMART: An Open Source and Community-Driven Informatics and Data Sharing Platform for Clinical and Translational Research. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3814495/#__ffn_sectitle .

Schumacher A, et al (2014) A collaborative approach to develop a multi-omics data analytics platform for translational research. https://reader.elsevier.com/reader/sd/pii/S2212066114000350?token=086E8A7B05341EE1C0A558241BF007678C6B310508BD3F97DFD1DEC923B28DE719E0E0DB2B82F6936FC9E544E850DE7F .

Fridlyand J, Simon RM, Walrath JC et al (2013) Considerations for the successful co-development of targeted cancer therapies and companion diagnostics. Nat Rev Drug Discov 12:743–755 https://doi.org/10.1038/nrd4101

Palmer M, Chaguturu R (2017) Academia–pharma partnerships for novel drug discovery: essential or nice to have? Expert Opin Drug Discovery 12:537–540 https://doi.org/10.1080/17460441.2017.1318124

Cui L, Su X (2009) Discovery, mechanisms of action and combination therapy of artemisinin. Expert Rev Anti-Infect Ther 7:999–1013 https://doi.org/10.1586/eri.09.68

Stilz HU, Bregenholt S (2018) Successful pharmaceutical innovation: In: Frølund L, Riedel MF (eds) Strategic Industry-University Partnerships. Elsevier, pp 39–57

Gill D (2014) Re-inventing clinical trials through TransCelerate. Nat Rev Drug Discov 13:787–788 https://doi.org/10.1038/nrd4437

Tralau-Stewart CJ, Wyatt CA, Kleyn DE, Ayad A (2009) Drug discovery: new models for industry–academic partnerships. Drug Discov Today 14:95–101 https://doi.org/10.1016/j.drudis.2008.10.003

Nwaka S, Ridley RG (2003) Virtual drug discovery and development for neglected diseases through public–private partnerships. Nat Rev Drug Discov 2:919–928 https://doi.org/10.1038/nrd1230

Balaña-Fouce R, Pérez Pertejo MY, Domínguez-Asenjo B et al (2019) Walking a tightrope: drug discovery in visceral leishmaniasis. Drug Discov Today 24:1209–1216 https://doi.org/10.1016/j.drudis.2019.03.007

Hong-Bo Weng et al (2018) Innovation in neglected tropical disease drug discovery and development. 7:

Hunter J (2011) Challenges for pharmaceutical industry: new partnerships for sustainable human health. Philos Trans R Soc A Math Phys Eng Sci 369:1817–1825 https://doi.org/10.1098/rsta.2010.0377

Volmar C-H, Wahlestedt C, Brothers SP (2017) Orphan diseases: state of the drug discovery art. Wien Med Wochenschr 167:197–204 https://doi.org/10.1007/s10354-015-0423-0

Sharma A, Jacob A, Tandon M, Kumar D (2010) Orphan drug: development trends and strategies. J Pharm Bioallied Sci 2:290–299 https://doi.org/10.4103/0975-7406.72128

Projan SJ (2003) Why is big pharma getting out of antibacterial drug discovery? Curr Opin Microbiol 6:427–430 https://doi.org/10.1016/j.mib.2003.08.003

Subramaniam S, Dugar S (2012) Outsourcing drug discovery to India and China: from surviving to thriving. Drug Discov Today 17:1055–1058 https://doi.org/10.1016/j.drudis.2012.04.005

Piachaud BS (2002) Outsourcing in the pharmaceutical manufacturing process: an examination of the CRO experience. Technovation 22:81–90. https://doi.org/10.1016/S0166-4972 (01)00081-5

Kaitin KI (2010) Deconstructing the drug development process: the new face of innovation. Clin Pharmacol Ther 87:356–361 https://doi.org/10.1038/clpt.2009.293

Shuchman M (2007) Commercializing clinical trials — risks and benefits of the CRO boom. N Engl J Med 357:1365–1368 https://doi.org/10.1056/NEJMp078176

Klopack TG (2000) Balancing the risks and the benefits. Drug Discov Today 5:157–160. https://doi.org/10.1016/S1359-6446 (00)01469-0

Klebe G (2006) Virtual ligand screening: strategies, perspectives and limitations. Drug Discov Today 11:580–594 https://doi.org/10.1016/j.drudis.2006.05.012

Song CM, Lim SJ, Tong JC (2009) Recent advances in computer-aided drug design. Brief Bioinform 10:579–591 https://doi.org/10.1093/bib/bbp023

Roy K, Kar S, Das RN (2015) Understanding the basics of QSAR for applications in pharmaceutical sciences and risk assessment, 1st ed. Academic Press

Agah S, Faham S, Vaidehi N, Klein-Seetharaman J (2012) Membrane protein structure and dynamics: methods and protocols, 1st ed. Humana Press

Lyne PD (2002) Structure-based virtual screening: an overview. Drug Discov Today 7:1047–1055. https://doi.org/10.1016/S1359-6446 (02)02483-2

Cole JC, Korb O, Olsson TSG, Liebeschuetz J (2011) The basis for target-based virtual screening: protein structures. In: Virtual Screening. pp 87–114

Lindahl ER, Kukol A (2008) Molecular modeling of proteins, 1st ed. Humana Press

Wiggers HJ, Rocha JR, Cheleski J, Montanari CA (2011) Integration of ligand- and target-based virtual screening for the discovery of cruzain inhibitors. Mol Inform 30:565–578 https://doi.org/10.1002/minf.201000146

Stockmann C, Barrett J, Roberts J, Sherwin C (2015) Use of modeling and simulation in the design and conduct of pediatric clinical trials and the optimization of individualized dosing regimens. CPT Pharmacometrics Syst Pharmacol 4:630–640 https://doi.org/10.1002/psp4.12038

Girard P, Cucherat M, Guez D et al (2004) Clinical trial simulation in drug development. Thérapie 59:297–304 https://doi.org/10.2515/therapie:2004057

Office of the Commissioner (2018) About science & research at FDA - how simulation can transform regulatory pathways. Accessed 1 Feb 2019

Prieto-Martínez FD, López-López E, Eurídice Juárez-Mercado K, Medina-Franco JL (2019) Computational drug design methods—current and future perspectives. In: In Silico Drug Design. Elsevier, pp 19–44

Chan HCS, Shan H, Dahoun T et al (2019) Advancing drug discovery via artificial intelligence. Trends Pharmacol Sci 40:592–604 https://doi.org/10.1016/j.tips.2019.06.004

Schneider P, Walters WP, Plowright AT et al (2019) Rethinking drug design in the artificial intelligence era. Nat Rev Drug Discov https://doi.org/10.1038/s41573-019-0050-3

Download references

Acknowledgements

The authors are grateful to the University of Nairobi for providing infrastructural support by way of online resources required for this review.

There was no funding for this manuscript.

Author information

Authors and affiliations.

Department of Pharmaceutics and Pharmacy Practice, School of Pharmacy, University of Nairobi, P.O. Box 19676-00202, Nairobi, Kenya

Geoffrey Kabue Kiriiri & Alex Njoroge Mwangi

Department of Pharmaceutical Chemistry, School of Pharmacy, University of Nairobi, P.O. Box 19676-00202, Nairobi, Kenya

Peter Mbugua Njogu

You can also search for this author in PubMed   Google Scholar

Contributions

GK conceived and wrote the first draft; PN and AN reviewed all drafts and gave additional input to improve the scientific rigor required. The authors read and approved the final draft for publication.

Corresponding author

Correspondence to Geoffrey Kabue Kiriiri .

Ethics declarations

Ethics approval and consent to participate.

Not applicable.

Consent for publication

Competing interests.

There are no competing interests to declare for all authors.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Kiriiri, G.K., Njogu, P.M. & Mwangi, A.N. Exploring different approaches to improve the success of drug discovery and development projects: a review. Futur J Pharm Sci 6 , 27 (2020). https://doi.org/10.1186/s43094-020-00047-9

Download citation

Received : 14 November 2019

Accepted : 10 June 2020

Published : 23 June 2020

DOI : https://doi.org/10.1186/s43094-020-00047-9

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Target-based screening
• Repositioning
• Repurposing

• Review article
• Open access
• Published: 29 June 2022

Practices of patient engagement in drug development: a systematic scoping review

• Olga Zvonareva   ORCID: orcid.org/0000-0001-5548-7491 1 ,
• Constanța Craveț 1 &
• Dawn P. Richards 2  

Research Involvement and Engagement volume  8 , Article number:  29 ( 2022 ) Cite this article

5205 Accesses

10 Citations

10 Altmetric

Metrics details

During the past decade, patient engagement (PE) has attracted significant attention in the field of drug development. Readiness to accept the central importance of patients’ knowledge and contributions has become evident. This study aimed to synthesize evidence on the current state of PE in drug development: what is actually being done and how.

A systematic scoping review was conducted based on a PRISMA-informed protocol. Search was performed in PubMed, EMBASE and Web of Science, covering the period between 2011 and 2021. For analysis of extracted data, we developed a framework for analyzing PE in Drug Development. The Framework distinguishes a number of different PE types that take place at different stages of drug development and are characterized by the different degrees of power patients have in the process. It allowed us to assess depth and intensity of PE initiatives included in this review.

Most included PE initiatives took place at the stage of designing studies (40 in total). At this stage drug development goals are already set, but the mode of reaching them has not yet been fully determined. PE initiatives on the finetuning details stage followed (16 in total). The finetuning details stage covers the last parts of the drug development trajectory, when only relatively minor issues are still open for patients’ contributions. The least numerous were PE initiatives on the stage of setting up R&D program (13 in total). This stage refers to the early steps in drug development where PE has the potential to make the most impact on shaping the subsequent process. In terms of intensity of engagement, most PE initiatives included in this review align with consultation and involvement types, 26 and 30 initiatives, respectively. Partnership was less frequent in the published accounts of PE (13 initiatives).

Conclusions

This review delineated a contemporary landscape of PE in drug development. Although attention to PE in drug development is relatively recent, a wide range of PE practices has already been initiated. The results indicate the necessity of distinguishing between different types of PE in order to understand consequences of choices regarding depth and intensity of PE.

Plain English summary

This article summarizes what is publicly found in scientific papers about patient engagement in drug development initiatives between 2011 and 2021. It also introduces a new Framework to use to look at these patient engagement efforts. The Framework breaks these efforts down based on the depth of patient engagement in the drug development process and different degrees of influence or power patients have or intensity of engagement. In terms of depth of patient engagement in the process of drug development, most patient engagement initiatives described efforts involved in designing studies where goals were already set. Next were patient engagement efforts related to finetuning details where patients could make minor contributions. The fewest efforts were found related to setting up a research and development program where patients potentially could make significant impact. In terms of intensity of patient engagement, most initiatives aligned with consultation and involvement intensities, and few examples aligned with the highest intensity of patient engagement that was considered partnership. While patient engagement in drug development is becoming more common, the approaches to doing so vary widely. We have developed a new Framework to help characterize these efforts related to patient influence in the process as well as depth of their engagement.

Peer Review reports

During the past decade, attitudes towards patient engagement (PE) in drug development have changed significantly. Until recently, it was typical for regulators, industry, and academic researchers to think of patients mostly as clinical trial participants with their contribution limited to data provision. This view contrasted with those existing in other health-related spheres, such as healthcare priority-setting and services delivery, where patient and public engagement has been increasingly practiced for about thirty years [ 1 , 2 ]. However, readiness to reconsider the role of patients, and acknowledge the central importance of their lived knowledge and contributions, is now becoming more evident in the drug development field as well [ 3 ].

Different stakeholders have articulated a range of expectations in connection to PE. Many of these expectations arise in the context of concerns over declining productivity of contemporary drug development. Drug development enterprise participants often mention rising costs, administrative delays, inefficiencies, and high failure rates among obstacles that, together, beset the progress [ 4 , 5 ]. PE, consequently, is framed as a potential answer to these obstacles. By putting unmet health needs first, using outcomes relevant for patients, and designing trials to be more convenient for participation, drug developers expect to decrease the chances of costly late-stage failures and address wide-spread problems with recruitment and retention in clinical trials [ 6 , 7 ].

Hand-in-hand with the expectations of improved productivity of the pharmaceutical industry, naturally emerge expectations of better quality and more relevant drugs [ 8 ]. Full consideration of patients’ priorities, experiences, and circumstances during the drug development process may deliver better solutions, as patients know best about what makes a meaningful difference to them. PE brings the question ‘what is needed?’ on a par with the question ‘what is possible?’, the latter question being a more traditional one for pharmaceutical innovating [ 9 ]. Furthermore, improvements in the regulatory process are also expected. During thematic forums, in officials’ statements, and in dedicated publications, PE is discussed as holding a promise to make the regulatory reviews more responsive to the patients and even to speed up drug approval. For example, it is anticipated that if a company relies on patient preferences when defining endpoints to be used in clinical trials, its case would be clearer and more convincing for the regulators [ 10 ].

Finally, the rising interest and declared commitment to PE introduces the possibility of democratizing drug development. Explicit discussions of drug development democratization have been limited. More pragmatic expectations outlined above feature more frequently in PE advocates’ statements. Yet, recognition of the patients’ right to shape treatment options available to them is implicitly present in the notion of PE itself. For a long time, decisions regarding problems to address, profiles of drugs to develop, and modes of assessing candidate drugs have been made by a restricted group of stakeholders. This group has consisted mostly of those involved with the industry and, to a lesser extent, regulation and academic research. However, the consequences of these decisions are so far-reaching, affecting the health and lives of so many people, that opening drug development up for wider participation appears to be imperative.

With discussions about PE in drug development intensifying, we witness the emergence of regulatory initiatives aimed at facilitating PE, as well as efforts to develop guidance for undertaking PE in practice [ 11 , 12 ]. Scholarly attention has turned to exploring attitudes to PE among various stakeholders, ascertaining effects of particular PE instances, and developing tools for evaluating PE [ 13 , 14 , 15 ]. What has remained relatively less studied is the overall landscape of PE in drug development over the course of the recent decade: what is actually being done, where, and by whom. The study reported here aims to address this gap. Adding to the reviews that focused on specific fields, such as antimicrobial drug development [ 16 ], and on specific stages, such as preclinical laboratory research [ 17 ], this article offers a more general review of PE in drug development.

Since PE may take different forms and can be initiated at different stages of the drug development process, we developed a conceptual framework that reflects this diversity. This article draws on this new framework, described in the next section, to provide a meaningful snapshot of the contemporary state of PE in drug development. After describing the framework, we outline methods employed to conduct this review, followed by presentation of the results. The results section begins with a general picture of PE in drug development: when accounts of PE initiatives included in this review were published, where these initiatives were conducted, and by whom. Further, we delineate how the identified PE initiatives map into the different types of PE proposed by our framework and provide detailed descriptions of each type with illustrative examples.

Framework for analyzing patient engagement in drug development

Existing definitions of PE vary considerably. Much of the conceptual work of defining PE has been done in the field of health care. For instance, Carman et al. [ 18 ] defined PE in health care as ‘patients, families, their representatives, and health professionals working in active partnership at various levels across the health care system—direct care, organizational design and governance, and policy-making—to improve health and health care’ (p. 224). To add complexity, some authors prefer to use the term involvement and/or also include public alongside patients, as for example Tritter [ 19 ] who defined patient and public involvement as ‘[w]ays in which patients can draw on their experience and members of the public can apply their priorities to the evaluation, development, organization and delivery of health services’ (p. 276).

Literature on PE in drug development has offered less conceptual input. Rather, it generally tends to emphasize partnership with patients and inclusion of patients’ voice across the entire cycle of medicines development. Several insights from the literature on PE in health care are particularly relevant for further conceptualizing PE in drug development. First, those who are engaged may be patients, but may also be caregivers and the general public [ 20 ]. Second, engagement may take place at different stages or levels of an activity in question. In the field of health care such levels could be, for example, direct care, organizational design and governance, and policy making [ 18 ]. Third, engagement may take different forms that can be positioned on a continuum from lower to higher degrees of patients’ power or influence and decision-making authority [ 21 ].

Taking account of these insights and, in particular, drawing on visualizations of engagement continuums by Carman et al. [ 18 ] and Spectrum of Public Participation by International Association for Public Participation [ 22 ], we developed a framework for analyzing PE in drug development (Fig. 1 ).

The first dimension of the Framework concerns the intensity of engagement. Here, different types of engagement are understood as forming a continuum. On the left side of the continuum, patients’ roles are less active and their participation in shaping agendas and decision-making is limited. On the right side of the continuum, patients are active partners in shaping agendas and making decisions and may have more power and responsibility than other stakeholders. This continuum can be broken down into a number of tentatively discreet types. The continuum in this Framework begins from consultation , which is understood as asking patients for their views to inform decisions in the drug development process, but without any obligation to act on these views. Then follows involvement , which is a dialogue or interaction with patients with a degree of mutual influence and accountability. Further, the continuum moves to partnership —active, ongoing and equal collaboration between drug developers and patients, both groups broadly conceived. Finally, the fourth type is patient leadership , when drug development is driven by patients who decide who else and when to invite.

Since the continuum spans from low to high intensity of engagement, it may be tempting to conclude that the higher the intensity the better. This conclusion could be valid in many situations, but in others lower intensity engagement may be appropriate either due to the nature of an issue at hand, type of a question to answer, or particularities of the situation itself. At the same time, it should be noted that movement from lower to higher intensity of engagement is associated with movement from one-off PE instances to more sustained and continuous collaboration. Partnerships, for instance, are more likely to be ongoing than consultations which tend to be arranged as isolated exercises. Therefore, it is possible to think of an engagement ecosystem where different types of engagement are practiced in connection to different purposes and issues and one-off PE instances take place alongside longer-term commitments.

The second dimension of the Framework focuses on the depth of engagement. Depth of engagement here is understood as being related to the drug development stage at which engagement is initiated. We distinguish three stages positioned from later stage to earlier stage engagement. The first stage is finetuning details , when patients engage in the drug development at the late stages, after all core decisions are already taken and only minor implementation issues are to be decided upon, for example, checking wording in trial informed consent forms or dissemination materials. The second stage is designing studies , when patients engage in the drug development process mid-way, when the mode of reaching the drug development goals has already been decided upon. Finally, the third stage is setting up research and development (R&D) programs , when patients engage in the drug development process (almost) from the beginning, at the point of delineating unmet needs and setting up the research agenda. Correspondingly, the earlier engagement takes place the more impact on drug development can be expected.

The Framework has empty cells. This is because the kinds of PE that would fit these cells are illogical and/or hard to conceive in practice. Partnership and, especially, patient leadership require initiation at the earlier stages of drug development because initiation at the later stages would mean that the most fundamental decisions have already been made. Consequently, patients would not be able to play a role of equal collaborators or leaders, implied by partnership and patient leadership types of engagement. For example, when a partnership with patients is sought to co-develop trial information materials or dissemination tools, it can be doubted whether such an initiative represents a partnership because patients participate in making decisions of comparatively minor importance in the overall drug development scheme. At the same time, initiation at the earlier stages does not preclude patients from subsequently engaging in activities falling under the finetuning details stage.

Study design

This systematic scoping review was conducted according to a protocol developed prior to the literature search. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guided the reporting [ 23 ]. The review is termed systematic because of the systematic search and extraction of data; it is termed scoping because it aims at mapping PE initiatives and does not involve quality appraisal of the included articles. Definitions of types of PE employed in this study follow the framework for analyzing Patient Engagement in Drug Development, described above.

Data sources and search strategy

An electronic search strategy was developed by a trained search strategist and adapted for the following databases: EMBASE, PubMed and Web of Science. The search strategy included a combination of medical subject headings (MeSH) terms such as ‘patient participation’ and ‘drug development’ and words/phrases related to patient engagement at different stages of drug development (see Additional file 1 : for summary of search strategies). Search terms were derived from a prior background literature search, tested and updated based on the test results and taking into account suggestions by the databases’ search engines. Other similar relevant terms were found in the literature or suggested by the databases’ search engines. The search specifically focused on the “patient” as a “research partner” engaged in shaping drug research and development. Background literature search indicated that the terms “consumer” or “public” participation, while prominent in many fields, were rarely used specifically in the field of drug development. This terminological particularity emerged during the initial shaping of the field of PE in drug development and reflects wording choices made by widely read authors. Scholars who cited their works subsequently tended to adhere to these choices. Therefore, the terms “consumer” and “public” participation were excluded due to their different theoretical and contextual meaning.

The search of the three databases was conducted on the 14th of April 2021. Furthermore, reference lists of the included studies were manually reviewed to ensure comprehensiveness. References were exported to a reference management software program (Zotero) and saved into the project library within Zotero.

Eligibility criteria

We included peer-reviewed publications that reported initiatives to engage adult patients in any form of activities during any of the stages of drug research and development. All original publications were eligible if the initiatives reported implied some degree of an impact on drug development practice and provided sufficient detail on the process of PE. Thus, publications that reported studies of patients’ perspectives on aspects of drug development with no clear route to use these perspectives in shaping practice were excluded along with the publications which gave only minor details on how exactly PE was done. Only articles in English published between 2011 and 2021 were considered. The choice of a period is because PE in drug development is a relatively recent phenomenon. Background literature search suggests that widespread interest to PE has emerged during this decade. We did not include unpublished data or abstract-only articles. All commentaries and editorials were excluded, as well as reviews after their reference lists were manually checked.

Study selection

Following the step of de-duplication, CC screened titles and abstracts of identified articles. As the screening was performed by a single team member, it introduced possibility of omissions. Articles that appeared to engage patients in drug development were retained and uploaded to Zotero (see Additional File 2 : for a Flow Diagram of identified, screened and eligible publications). Then two reviewers, CC and OZ, independently screened retained articles based on the full text. Screened articles were classified by the reviewers into three categories: ‘Relevant’, ‘Possibly Relevant’, and ‘Irrelevant’. The resulting classifications were compared, differences discussed and reconciled, and the category ‘Possibly Relevant’ sorted into ‘Relevant’ and ‘Irrelevant’ categories. Articles agreed upon to belong to the category ‘Relevant’ were deemed eligible for further data extraction and analysis. All excluded articles were kept in a separate folder within the project Zotero library and reasons for exclusion were documented in an Excel spreadsheet for ease of monitoring and reporting.

Data extraction

A data extraction form was developed to facilitate a systematic and transparent examination of included publications. The form was piloted and refined to ensure suitability for reaching the objectives of the review. The extracted characteristics were grouped in four clusters (see Additional file 3 : Data extraction spreadsheet). The first cluster focused on the publication itself and included authors, their affiliations, and year of publication. The second cluster focused on the drug development activity where PE was implemented and included country, funding source, disease area, aim, study design, drug being developed, and population. The latter characteristic, population, was relevant for clinical trials primarily. The third cluster focused on PE and included data on who is engaged, how PE was initiated, PE methods, depth of engagement and intensity of engagement. Depth and intensity of engagement were judged based on the Framework for Analyzing Patient Engagement in Drug Development. Reasons for classifying instances of PE as belonging to a particular type were documented in the data extraction form. The fourth cluster included PE outcomes and, where reported, strengths and limitations of specific PE initiatives.

Data extraction began with both reviewers, CC and OZ, randomly selecting five articles found eligible for this review and independently extracting data from them according to the described standardized form. Afterwards, the extraction results were compared and any uncertainties regarding the extraction process were clarified. Further, CC proceeded to extract the data from remaining studies and OZ randomly checked data extraction for 25% of the included publications.

Data analysis

The Framework for Analyzing Patient Engagement in Drug Development guided data analysis. It allowed to, first, organize included publications into groups according to depth and intensity of PE activities reported. Further, we examined methods and aims of PE activities within each group and compared the identified characteristics within and between the groups, producing a narrative synthesis of the data. Identified patterns enabled us to develop a map of the overall landscape of PE over the course of the recent decade and also to further specify the Framework employed in this review. We also developed case descriptions based on selected examples of different types of PE to illustrate similarities and differences between them.

Quality assessment

Formal quality assessment criteria were not used in this review. Because the overall aim of this review was to characterize the landscape of PE in drug development in terms of PE types employed, we only ensured that included publications provided sufficient details on who was engaged, how, and for which purpose. The full list of included publications can be found in Additional File 4 .

PE in drug development: when, where, why and who

In total, 69 publications were included. Most of the articles on PE in drug development included in this review were published in 2016–2019 (see Fig.  2 and Table 1 ). The rise in published accounts of PE by 2016 may have been stimulated by increasing attention of regulators and others to patients’ perspectives in the context of drug development and evaluation. For example, in 2012 the U.S. Food and Drug Administration (FDA) launched its Patient-Focused Drug Development (PFDD) initiative to understand patients’ experiences in specific disease areas and their views on currently available treatments [ 24 ]. In the European Union, 2012 became the year The European Patients’ Academy on Therapeutic Innovation (EUPATI) was launched by the Innovative Medicines Initiative, which is a public–private partnership [ 25 ]. A sharp decline in publications reporting on PE following 2019 can, arguably, be attributed to the COVID-19 pandemic, which made the publishing process more lengthy, complicated implementation of PE in practice, and could also have temporarily changed the priorities of drug developers, shifting attention away from PE.

Number of publications per year (2011–2021)

The geographical distribution of PE activities reported in the articles included in this review is highly uneven (see Fig.  3 , Table 1 ). Most of the reported activities took place in the U.S. (47). The U.K. and Germany are the two countries that follow the U.S. but with significantly less instances of PE, 18 and 13, respectively. Australia, Canada, Italy, and Poland account for 6 to 7 PE activities each. Notably, no PE in drug development was reported in countries in Africa, except for 1 instance in South Africa, and very little reported in countries in Asia and South America. Near absence of the countries that constitute what has been termed the Global South on the map of PE in drug development is surprising. Given a wealth of existing publications that report on efforts to make clinical trials more adapted and responsive to local perspectives in these settings [ 26 , 27 ], some contribution into PE in drug development could well be expected. However, while expansion of clinical trial conduct into lower-income locations has been accompanied by efforts to engage local communities into trial planning and oversight, our review found little published evidence of PE in drug development.

Geographical distribution of PE activities

There appear to be at least two complementary explanations for this picture. First, there is a tendency in academic publications to speak of community engagement when it comes to lower-income locations and of patient engagement or patient and public engagement when it comes to higher-income locations. While engagement initiatives may well configure communities as consisting of people who share a particular diagnosis, in practice community engagement usually concerns individuals who inhabit a particular place. Thus, engagement initiatives in the Global South tend to avoid engaging patients as such but rather focus more generally on local communities where clinical trials are conducted.

Second, clinical trials are undertaken not only in the context of drug development, but also for the purposes of testing public health interventions and non-pharmaceutical treatments. It is possible that engagement initiatives in lower-income locations tend to be associated with non-pharmaceutical trials, while pharmaceutical trials designed elsewhere are highly standardized by the time they land in these locations and have little space left for PE. Furthermore, PE at the stages of setting up R&D programs and designing studies that precede trial conduct, may be logistically challenging to conduct outside of higher-income locations, such as the U.S., where most drug development projects are currently initiated. Also, PE in lower-income locations may be further deprioritized since large pharmaceutical companies—the main players in the drug development arena, have devoted limited attention to developing drugs for diseases affecting the global poor, who disproportionately reside in these lower-income locations.

This latter point is illustrated by an overview of disease areas in which PE activities took place (see Table 2 ). Most PE initiatives reported in the articles included in this review took place within the context of developing drugs for non-communicable diseases. The cluster of infectious and parasitic diseases that take a heavy toll on populations residing in lower-income locations is represented by only 7 instances of PE in drug development for HIV/AIDS, Hepatitis C Virus, and COVID-19 pneumonia. This is not to suggest that drugs for non-communicable diseases are not relevant for people residing outside of the high-income countries. Rather we are highlighting that PE appears to occur more often when drugs are developed for non-communicable diseases compared to when drugs are developed for communicable diseases, perhaps, in part due to less drug development efforts devoted to communicable diseases more generally.

It was not always easy to clearly discern the initiators of PE in drug development. One relevant indication is a source of funding. From the information provided in the included publications we gathered that 3 initiatives were funded by charities, 3 initiatives by consortiums of public and private organizations, 23 initiatives by the pharmaceutical industry, and 42 initiatives by academic research funders and other public bodies. This latter group is rather diverse and includes such funders as the U.S. National Institutes of Health, universities, and various national research programs. There are situations when those who are initiating PE are different from those who are funding it. In cases of pharmaceutical companies, the funder and initiator are usually one entity. But in other cases, arrangements can be more complicated. For example, PE funded by an academic research funder could be conceived and initiated by a hospital, research association or a collaborative network that may include diverse actors such as patient advocacy organizations, state agencies, businesses, and others.

A trend noted in the process of analysis was a lack of financial involvement of industry at the stage of finetuning details in included publications. PE initiatives at this stage were funded and initiated by non-industry organizations, possibly due to their inability to reach earlier stages of drug development that tend to be carried out by industry. It is also possible that these initiatives were simply not reported by industry in the academic journals. The composition of organizations active at other stages is mixed.

Diversity of PE activities: an overview

Among all PE initiatives described in the articles included in this review (see Table 3 ) most numerous are the ones taking place at the stage of designing studies (40 in total). At this stage drug development goals are already set, but the mode of reaching them has not yet been (fully) determined. In the PE initiatives classified in this review as belonging to this stage, patients were involved in deciding upon outcomes to consider, recommended amendments in trial design and organization primarily to improve enrollment and retention, contributed to development of tools for trial oversight, evaluated reporting process, and brought attention to ethical issues such as access to a drug being evaluated.

Following PE initiatives in the designing studies stage, are initiatives on the finetuning details stage (16 in total). The finetuning details stage covers the last parts of the drug development trajectory, when only relatively minor issues are still open for patients to contribute to. Here patients played roles in informing patient recruitment strategies and evaluating and contributing to the development of information and education materials, informed consent forms, and such tools as decision aids.

Finally, the least numerous were PE initiatives on the stage of setting up R&D program (13 in total). This stage refers to the early steps in drug development where PE has the potential to make the most impact on shaping the subsequent process. In the initiatives that fell under this category patients participated in defining research agendas and priorities, choosing specific directions of inquiry to pursue and identifying barriers, provided insight into preferred outcomes and drug characteristics in terms of balance between risks and benefits, and contributed to designing drug development programs.

In terms of intensity of engagement, most PE initiatives included in this review align with consultation and involvement types, 26 and 30 initiatives, respectively. Both of these types imply a certain degree of preliminary framing by drug developers. That is, patients are invited to answer pre-formulated questions, discuss pre-formulated issues, and/or contribute to reaching pre-formulated goals. However, during a consultation drug developers and patients are at greater distance from each other and assume more clearly defined roles of those who ask questions and those who answer them. Involvement implies a more diverse spectrum of interactions and closer relations between the parties.

Partnership offers patients more opportunities to shape the space and conditions of their engagement. Parties are on a more equal footing and much less differentiation is apparent between those who engage and those who are engaged. This type of PE was less frequent in the published accounts of PE (13 initiatives), which could stem from a variety of reasons, including organizational complexity of setting up a partnership, uncertainty and resource requirements of this PE type, and simple underreporting in academic journals. The latter reason is very likely to partly account for zero initiatives of the patient leadership type included in this review. There are patient organizations that fund research related to the conditions of their focus. It is likely some of them also lead drug development efforts of their disease areas of interest but choose not to invest resources into writing articles about this experience for academic journals.

PE at the stage of setting up an R&D program

At the stage of setting up an R&D program, the fewest initiatives followed the format of consultation (2 initiatives). It appears to be more typical for early-stage PE to involve more multidirectional communication and longer-term contacts than the consultation format allows. When the consultation format is selected, it is conceived as collecting data from the patients to inform drug development strategy and product design. Such data collection can be aided by digital technologies and online platforms, as an example demonstrates from an industry early drug development project for chronic obstructive pulmonary disease (COPD) [ 28 ]. In this example the company set up three studies. The first was a social media listening study—an analysis of online conversations in open-access platforms among patients with COPD conducted in the patients’ own words and without influence of researchers. The second was an online bulletin board exercise, where twenty COPD patients answered predefined questions derived from the previous study. Patients provided their answers asynchronously, in the course of two weeks within a moderated, closed online community platform, similar to a private chat room. The third was a patient preference study, where findings from the two previous studies were quantitatively evaluated via an online survey among patients with COPD. The authors of the publication where these studies were presented suggest that ‘collectively these patient insights and preferences will help assemble hypothetical treatment profiles with specific characteristics and also aid in selecting clinical outcome assessments beyond conventional end points in the COPD drug development program’ (p. 22).

Involvement and partnership are almost equally present at the stage of setting up R&D programs, 5 and 6 initiatives, respectively. Involvement practices tend to differ from pure consultations by a greater degree of dialogue and a possibility for patients to exert influence beyond simply allowing their experiences and preferences to be collected as data. An interesting example illustrating this point is an initiative by a regulatory agency [ 29 ]. On the one hand, the initiative did concern eliciting individual patient preferences, in this case, with regards to treatments for advanced melanoma and multiple myeloma. On the other hand, the instrument for eliciting preferences was developed in cooperation with two patient organizations, in which patients provided feedback on the technical aspects, content, and methodology, and the publication reporting on the process was written together by regulators and patients. The resulting patient preference elicitation methodology, applied at the stages preceding regulatory review early enough to ensure correspondence between a drug's characteristics and patients’ perspectives, may produce evidence to be included in marketing authorization applications. According to the authors of the publication, such information could provide support for ‘a claim of a favorable benefit–risk and inform the regulators’ decisions in situations where the balance of benefits and risks is not self-evident’ (p. 551).

Finally, partnership as a type of PE in drug development takes place in a more sustained manner. Conditions of partnership are not as pre-set as in the case of involvement and, especially, consultation, and what exactly the partnership is going to focus its activities on is defined jointly. An article, included in this review, describes an example of a partnership initiated by a pharmaceutical company, where the Patient Advocate Advisory Council (PAAC) was established [ 30 ]. The PAAC worked with the company representatives to design and execute a program whereby patients join clinical development teams. In parallel with developing a framework for patients and clinical development teams to work together, the PAAC conducted a pilot where, under a confidentiality agreement, a cancer patient advisor engaged with one of the clinical development teams, meeting key members of the team and providing feedback on the protocol and development program. While initiated by a pharmaceutical company, relationships between the PAAC and the company can be considered a partnership because PAAC members had a space to define different elements of the program themselves and try them out. A result of this partnership was characterized positively: it was agreed to expand the pilot to reach other development programs within the company and initiate engagement between patient advisors and development programs ‘even earlier than was possible with the pilot study. … despite the risk that therapy development programs in the earliest stages may not advance to later development’ (p. 350).

PE at the stage of designing studies

Consultation initiatives were common at the stage of designing studies (16 initiatives). Those involved in designing studies formulate questions they would like to have information on and seek answers to these questions from the patients. Seeking answers in the cases of consultation may take a variety of forms, mostly quite restrictive. For example, a group of trialists from an academic hospital and with some industry affiliations developed a financial assistance program for cancer clinical trial participants to improve trial enrollment and retention [ 31 ]. Patients contributed to evaluation of this program by reporting their financial concerns and barriers to participation via survey. As a result of this evaluation the financial assistance program was considered effective and suitable for being implemented as a part of future trials. Another example, similarly illustrative of the boundaries pre-set for the patient input in the consultation format, is a formative study conducted by a non-profit organization to improve recruitment in its trials [ 32 ]. In this initiative people living with HIV/AIDS (PLWHA) diagnosed with cancer and invited to participate in a trial were offered to complete a survey about factors influencing their decision-making regarding trial participation and asked for recommendations about how to improve the organization’s trial accrual. Further, as typical for the consultation format, it was up to those asking questions, in this case trialists, to decide what to do with the input received. Thus, authors of the study that reported the initiative, concluded: ‘These suggestions present opportunities to the [organization] and its participating sites to consider ways to improve the appeal and experience of clinical trial participation and streamline the accrual process’ (p. 6).

Similar to consultation, involvement at the stage of designing studies constitutes a common type of PE (17 initiatives). One of the primary differences between the two types is the degree of mutual influence. During a consultation, patients rarely have an opportunity to go beyond the framework that predefines their role, questions posed, and the format answers should follow. In the case of involvement, the degree of freedom patients have to shape their input is higher. An example to illustrate this point comes from a study of tocilizumab for treatment of COVID-19 pneumonia conducted by an academic consortium [ 33 ]. While PE was not originally foreseen, a single-arm design of this trial was a result of a media campaign for giving a drug to all participating patients, instead of dividing them into experimental and control groups and giving a drug only to those in the experimental group. The campaign was spearheaded by physicians with support and under pressure from patients and led to a significant change in the study design in an attempt by investigators to strike the balance between scientific considerations and demands from physicians and patients. This situation suggests that involvement may not only be architectured by those designing studies but may well be uninvited, that is initiated by patients and their allies. Descriptions of invited involvement are more numerous in the publications included in this review. But in the cases of invited involvement at the stage of designing studies, patients’ influence is still broader than in the cases of consultation. This difference is noticeable in the PE initiatives that involve development of patient-reported outcomes (PROs)—tools for measuring outcomes that matter to patients [ 34 ]. Since these tools are meant to reflect patients’ perspectives, PE is necessary for PRO development. For example, creation of a novel PRO to evaluate therapy that is being developed for pantothenate kinase-associated neurodegeneration included interviews with professionals, patient advocates, and caregivers to inform the first version of the PRO [ 35 ]. This version was then piloted, finalized after patients who participated in piloting and primary caregivers provided their feedback on the first version during interviews, and used in a phase III trial.

Partnership as a form of PE at the stage of designing studies is seen less often (7 initiatives) and includes more prolonged engagement than consultation and involvement. Not only does it take time to set up a partnership, but the process of engagement itself in this case is inevitably lengthier because it is less scripted, more unpredictable, and cannot be limited to an isolated instance of feedback provision. For example, in an effort to facilitate clinical trials for facioscapulohumeral muscular dystrophy (FSHD) treatments, FSHD researchers initiated a series of meetings with industry and patients [ 36 ]. These meetings allowed identifying gaps in clinical trial readiness. In order to address these gaps, on the basis of FSHD Clinical Trial Research Network a study was developed to identify novel clinical outcome assessments and refine eligibility criteria for future clinical trials. The protocol for this study was informed by discussions between FSHD researchers, industry and patients and included provisions for ‘continuing dialogue throughout the course of the study’ (p.3). Continuing dialogue beyond development of the protocol itself was meant to ‘address specific aims or difficulties encountered in running the proposed study; for example, defining what would be clinically meaningful to people with FSHD, addressing concerns related to participating in clinical studies, and issues with recruitment and retention’ (p. 4). In this and other instances of partnership more prolonged engagement is likely to produce more transparency and, consequently, trust: remaining in touch with a particular project, patients also see what happened to their input.

PE at the stage of finetuning details

PE at the stage of finetuning details focuses mostly on trial information materials and recruitment strategies. The analytical framework employed in this review distinguishes two types of PE at this stage: consultation (8 initiatives) and involvement (8 initiatives). The framework does not foresee the possibility of a partnership at this stage, because for a PE initiative to be a partnership it needs to be sufficiently prolonged for establishment of collaborative relationships and sufficiently deep to exert an impact beyond relatively minor aspects. This is not to suggest that partnerships cannot be concerned with information materials and recruitment strategies. Partnerships may well extend to include these items but are unlikely to focus exclusively on them.

Examples of PE at the stage of finetuning details found in the reviewed literature are quite similar and, indeed, do not resemble a partnership. Patients are invited to test information materials and tools and are asked about their experiences and expectations with regards to trial participation to facilitate recruitment and retention in trials. Consultation and involvement at this stage can be differentiated by looking at how pre-structured the patients’ input is. Consultation is more restrictive in this regard than involvement. For example, one consultation initiative carried out by an academic group aimed to test seven different strategies for recruitment of cancer patients and their caregivers in a randomized controlled trial [ 37 ]. After patients and their caregivers were contacted and invited to participate in this initiative, using seven strategies being tested, recruitment outcomes were compared. This initiative concluded that opt-out recruitment techniques are the most effective, yielding the highest number of participants, and should be used in future trial recruitment. This example illustrates how consultation initiatives at the stage of finetuning details channel patient input narrowly, not leaving opportunities for an unforeseen, patient-initiated feedback. In this case, patients and their caregivers could only indicate whether they would agree to participate in a study being contacted via a particular strategy.

Involvement at the stage of finetuning details is not drastically different from consultation, in part due to this stage itself limiting the scope of PE possibilities. When patients are involved, though, they have somewhat more space to articulate their views. For example, one involvement initiative by an academic group aimed to identify patients’ physical and psychosocial experiences of an investigational long-acting injectable pre-exposure prophylaxis (PrEP) product to aid in the development of patient and provider education materials [ 38 ]. Here patients were asked to rate their pain during and after injection on a five-point scale. This request is a closed one, similar to the request to make a choice whether or not to agree to study participation in the previous example. But the involvement example also included interviews with open-ended questions, where patients could direct a conversation and bring up issues investigators had not considered.

Discussion and conclusion

This review delineated a contemporary landscape of PE in drug development. Although attention to PE in drug development is a relatively recent phenomena, a wide range of PE practices has already been initiated. These practices take place at varying stages of drug development and are characterized by different intensity of engagement. Using our novel Framework for analyzing PE in drug development, we were able to show that most reported PE initiatives took the form of consultation and involvement and occur at the stage of designing studies. Instances of partnership are fewer. Notable is the absence of reports about the patient leadership initiatives in the available academic literature .

The results indicate the necessity of distinguishing between different types of PE in drug development. While emergent scholarship and guidance documents tend to speak of PE in drug development as a relatively homogenous group of activities, this review indicates that in practice PE takes a wide variety of forms. Attention to this variety allows to elicit distinct positions accorded to or assumed by patients within engagement initiatives and different assumptions regarding the value and content of patients’ input embedded in the setup of specific PE practices. Importantly, distinguishing between different types of PE in drug development makes visible the consequences of choices regarding depth and intensity of PE. These consequences concern the impact patients are actually able to make on the drug development and the degree to which aspirations to take the patients’ voices seriously have been realized. Recognizing differences between PE types does not mean an obligation to strive for uniformly early and intense engagement in all situations. Rather, such recognition could facilitate building a PE ecosystem where different types of PE co-exist complementing each other.

The reported rise in diverse PE initiatives has been taking place against the backdrop of extensively articulated expectations regarding the capacity of patients’ input to cure drug development of its present-day maladies responsible for declining productivity. While evaluation of the PE outcomes was not the purpose of this review, it is hard to avoid discussing, however briefly, the significance of hopes pinned on PE in drug development for the future of PE. While being very far-reaching, expectations proposed by the existing literature are rather pragmatic: with patients’ input drug developers would be developing more relevant products, face less late-stage failures, experience less difficulties with trial recruitment and retention, and even have their products approved faster. These pragmatic expectations are, to a large extent, reflected in the empirical reports of PE initiatives included in this review. Not all reports provided information on the outcomes of PE, but those that did, focused on pragmatic outcomes such as satisfaction of patients with trial participation or improved relevance of end points.

These pragmatic outcomes are, without any doubt, of paramount importance. However, as mentioned in the introduction to this article, improving productivity is not the only rationale for PE in drug development. Of at least equal importance is the democratization rationale. Democratization rationale entails that since drug development priorities and practices affect lives and wellbeing of (almost) everyone, decisions in this domain must be opened up for wider participation. Yet, there is little explicit mention of democratization in the literature on PE in drug development and the reviewed empirical reports of PE initiatives do not evaluate the outcomes from this point of view. We argue that for PE to facilitate meaningful change in drug development, it is important to take the issue of democratization seriously and avoid attaching exclusively pragmatic significance to patients’ participation. Otherwise, in the absence of aspirations to democratization, PE in drug development risks devolving into a technical exercise, devoid of its hoped-for transformative powers.

Limitations

Results of this review cannot be taken as a direct representation of the state of PE in drug development. We mapped PE in drug development based on the accounts published in academic journals between 2011 and 2021 in English. Conference abstracts were not included because details they provide about PE initiatives tend to be insufficient for the purposes of this review; also, the dispersed body of grey literature remained untouched. Thus, instances of PE described in the venues other than academic journals and in languages other than English are not included in this review, impacting the picture obtained. Further, it is conceivable that many instances of PE, especially the ones conducted by the corporate actors, remain unpublished and, therefore, not reflected in this review. Diverse terminology used in the recent scholarship on PE may have resulted in relevant initiatives escaping our attention. Finally, this review focused on engagement of adult patients. Therefore, important initiatives to engage pediatric populations in drug development and possible efforts to engage more general public are not included.

In view of these limitations, it is important to further study the landscape of PE in drug development in its entirety. Recently the broader scholarship on public participation has moved from studying individual cases of participation to considering more holistically how diverse forms of participation interrelate in wider systems. By joining this “systemic turn”, studies of PE in drug development would make the next step towards understanding multiple collectives and spaces of PE and their interactions with broader political landscapes.

Availability of data and materials

Original articles are available through their respective publishers, some as open access.

Abbreviations

Excerpta Medica Database

European Patients’ Academy on Therapeutic Innovation

Food and Drug Administration

Medical subject headings

• Patient engagement

Patient-Focused Drug Development

Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols

Research and development

Crawford MJ. Systematic review of involving patients in the planning and development of health care. BMJ. 2002;325(7375):1263–1263.

Article   PubMed   PubMed Central   Google Scholar  

Bolsewicz Alderman K, Hipgrave D, Jimenez-Soto E. Public engagement in health priority setting in low- and middle-income countries: current trends and considerations for policy. PLoS Med. 2013;10(8):e1001495.

Lowe MM, Blaser DA, Cone L, Arcona S, Ko J, Sasane R, et al. Increasing patient involvement in drug development, vol 19, value in health. 360 park Ave South, New York, NY 10010-1710 USA: Elsevier Science Inc; 2016. p. 869–78.

Getz K. Reflections on the evolution of patient engagement in drug development. Pharm Med. 2019;33(3):179–85.

Article   Google Scholar  

Yanni AJ, Fine J. Evolution of drug development: integrating the patient perspective into early research. Ther Innov Regul Sci. 2018;52(1):89–93.

Article   PubMed   Google Scholar  

Pushparajah DS. Making patient engagement a reality. Patient. 2018;11(1):1–8.

Hoos A, Anderson J, Boutin M, Dewulf L, Geissler J, Johnston G, et al. Partnering with patients in the development and lifecycle of medicines: a call for action. Ther Innov Regul Sci. 2015;49(6):929–39.

Geissler J, Ryll B, di Priolo SL, Uhlenhopp M. Improving patient involvement in medicines research and development: a practical roadmap. Ther Innov Regul Sci. 2017;51(5):612–9.

Lacombe D, O’Morain C, Casadei B, Hill K, Mateus E, Lories R, et al. Moving forward from drug-centred to patient-centred research: a white paper initiated by EORTC and developed together with the BioMed Alliance members. Eur Respir J. 2019;53(2):1801870.

Hansen MB, Nørgaard LS, Hallgreen CE. How and why to involve patients in drug development: perspectives from the pharmaceutical industry, regulatory authorities, and patient organizations. Ther Innov Regul Sci. 2020;54(3):577–85.

Feldman D, Kruger P, Delbecque L, Duenas A, Bernard-Poenaru O, Wollenschneider S, et al. Co-creation of practical “how-to guides” for patient engagement in key phases of medicines development—from theory to implementation. Res Involv Engagem. 2021;7(1):57.

Mavris M, Furia Helms A, Bere N. Engaging patients in medicines regulation: a tale of two agencies. Nat Rev Drug Discov. 2019;18(12):885–6.

Article   CAS   PubMed   Google Scholar  

Faulkner SD, Sayuri Ii S, Pakarinen C, Somers F, Jose Vicente Edo M, Prieto Remon L, et al. Understanding multi-stakeholder needs, preferences and expectations to define effective practices and processes of patient engagement in medicine development: a mixed-methods study. Health Expect. 2021;24(2):601–16.

Vat LE, Finlay T, Jan Schuitmaker-Warnaar T, Fahy N, Robinson P, Boudes M, et al. Evaluating the “return on patient engagement initiatives” in medicines research and development: a literature review. Health Expect. 2020;23(1):5–18.

Vat LE, Finlay T, Robinson P, Barbareschi G, Boudes M, Diaz Ponce AM, et al. Evaluation of patient engagement in medicine development: a multi-stakeholder framework with metrics. Health Expect. 2021;24(2):491–506.

Evans D, Bird E, Gibson A, Grier S, Chin TL, Stoddart M, et al. Extent, quality and impact of patient and public involvement in antimicrobial drug development research: a systematic review. Health Expect. 2018;21(1):75–81.

Fox G, Fergusson DA, Daham Z, Youssef M, Foster M, Poole E, et al. Patient engagement in preclinical laboratory research: a scoping review. EBioMedicine. 2021;70:103484.

Carman KL, Dardess P, Maurer M, Sofaer S, Adams K, Bechtel C, et al. Patient and family engagement: a framework for understanding the elements and developing interventions and policies. Health Aff. 2013;32(2):223–31.

Tritter JQ. Revolution or evolution: the challenges of conceptualizing patient and public involvement in a consumerist world. Health Expect. 2009;12(3):275–87.

Gibson A, Britten N, Lynch J. Theoretical directions for an emancipatory concept of patient and public involvement. Health (London). 2012;16(5):531–47.

Oliver SR, Rees RW, Clarke-Jones L, Milne R, Oakley AR, Gabbay J, et al. A multidimensional conceptual framework for analysing public involvement in health services research. Health Expect. 2008;11(1):72–84.

International Association for Public Participation (IAP2). Spectrum of Public Participation [Internet]. 2018 [cited 2021 Oct 29]. https://cdn.ymaws.com/www.iap2.org/resource/resmgr/pillars/Spectrum_8.5x11_Print.pdf

Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;29:n71.

Perfetto EM, Burke L, Oehrlein EM, Epstein RS. Patient-focused drug development a new direction for collaboration. Med Care. 2015;53(1):9–17.

Chakradhar S. Training on trials: patients taught the language of drug development. Nat Med. 2015;21(3):209–10.

Marsh V, Kamuya D, Rowa Y, Gikonyo C, Molyneux S. Beginning community engagement at a busy biomedical research programme: experiences from the KEMRI CGMRC-Wellcome Trust Research Programme, Kilifi, Kenya. Soc Sci Med. 2008;67(5):721–33.

Reynolds L, Sariola S. The ethics and politics of community engagement in global health research. Crit Public Health. 2018;28(3):257–68.

Patalano F, Gutzwiller FS, Shah B, Kumari C, Cook NS. Gathering structured patient insight to drive the PRO strategy in COPD: patient-centric drug development from theory to practice. Adv Ther. 2020;37(1):17–26.

Postmus D, Mavris M, Hillege HL, Salmonson T, Ryll B, Plate A, et al. Incorporating patient preferences into drug development and regulatory decision making: results from a quantitative pilot study with cancer patients, carers, and regulators. Clin Pharmacol Ther. 2016;99(5):548–54.

Selig W, Banks I, Davis A, DeCotiis G, Hohman R, Schlager L. Incorporating patient advocates in oncology clinical development: lessons learned from a novel pilot program. Ther Innov Regul Sci. 2019;53(3):349–53.

Nipp RD, Lee H, Powell E, Birrer NE, Poles E, Finkelstein D, et al. Financial burden of cancer clinical trial participation and the impact of a cancer care equity program. Oncologist. 2016;21(4):467–74.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Burkhalter JE, Aboulafia DM, Botello-Harbaum M, Lee JY. Participant characteristics and clinical trial decision-making factors in AIDS malignancy consortium treatment trials for HIV-infected persons with cancer (AMC #S006). HIV Clin Trials. 2018;19(6):235–41.

Chiodini P, Arenare L, Piccirillo MC, Perrone F, Gallo C. A phase 2, open label, multicenter, single arm study of tocilizumab on the efficacy and tolerability of tocilizumab in the treatment of patients with COVID-19 pneumonia (TOCIVID-19 trial): Statistical analysis plan, vol 20, contemporary clinical trials communications. 525 B Street, Ste 1900, San Diego, CA 92101-4495 USA: Elsevier INC; 2020.

Makrinioti H, Bush A, Griffiths C. What are patient-reported outcomes and why they are important: improving studies of preschool wheeze. Arch Dis Child Educ Pract Ed. 2020;105(3):185–8.

Klopstock T, Escolar ML, Marshall RD, Perez-Dueñas B, Tuller S, Videnovic A, et al. The FOsmetpantotenate Replacement Therapy (FORT) randomized, double-blind, Placebo-controlled pivotal trial: Study design and development methodology of a novel primary efficacy outcome in patients with pantothenate kinase-associated neurodegeneration. Clin Trials. 2019;16(4):410–8.

LoRusso S, Johnson NE, McDermott MP, Eichinger K, Butterfield RJ, Carraro E, et al. Clinical trial readiness to solve barriers to drug development in FSHD (ReSolve): protocol of a large, international, multi-center prospective study. BMC Neurol. 2019;19(1):224.

Sygna K, Johansen S, Ruland CM. Recruitment challenges in clinical research including cancer patients and their caregivers. A randomized controlled trial study and lessons learned, vol. 16, Trials. Campus, 4 Crinan St, London N1 9XW, England: BMC; 2015.

Meyers K, Rodriguez K, Brill AL, Wu Y, La Mar M, Dunbar D, et al. Lessons for patient education around long-acting injectable PrEP: findings from a mixed-method study of phase II trial participants. AIDS Behav. 2018;22(4):1209–16.

Download references

Acknowledgements

We would like to thank the organizers and participants of the Patient Engagement Open Forum and the team members of the project ‘InPart’.

Authors’ information

OZ is Assistant Professor in Maastricht University. Her research focuses on public engagement in health and biomedical knowledge production. CC is Research Assistant at Health, Ethics and Society Department, Maastricht University. DPR is the Founder of Five02 Labs, Inc, and lives with rheumatoid arthritis and osteoarthritis. Five02 Labs, Inc. provides services to researchers and organizations related to patient and public engagement.

This research has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 948073).

Author information

Authors and affiliations.

Department of Health, Ethics and Society, Maastricht University, Minderbroedersberg 4-6, 6211 LK, Maastricht, The Netherlands

Olga Zvonareva & Constanța Craveț

Five02 Labs, Inc., Toronto, ON, Canada

Dawn P. Richards

You can also search for this author in PubMed   Google Scholar

Contributions

All authors participated in the research and were actively involved in preparing the manuscript . OZ conceptualized the initial manuscript, contributed to the study design, and produced the first version of the manuscript; CC developed the study design, collected and analyzed data, and contributed to writing of the manuscript; DPR contributed to the design, theoretical framing of the study, and analysis; provided content and feedback on manuscript drafts, and contributed to writing up and revising the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Olga Zvonareva .

Ethics declarations

Ethics approval and consent to participate.

Not applicable.

Consent for publication

Competing interests.

The authors declare that they have no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1..

Summary of search strategies.

Additional file 2.

Flow Diagram of identified, screened and eligible publications.

Additional file 3.

Data extraction spreadsheet.

Additional file 4.

Full list of included articles.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Zvonareva, O., Craveț, C. & Richards, D.P. Practices of patient engagement in drug development: a systematic scoping review. Res Involv Engagem 8 , 29 (2022). https://doi.org/10.1186/s40900-022-00364-8

Download citation

Received : 17 November 2021

Accepted : 18 June 2022

Published : 29 June 2022

DOI : https://doi.org/10.1186/s40900-022-00364-8

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Patient participation
• Drug development
• Systematic scoping review

Research Involvement and Engagement

ISSN: 2056-7529

• General enquiries: [email protected]

Switch language:

How technology could transform drug research in 2022

Pharmaceutical Technology takes a look at some of the tech innovations set to impact drug discovery and development in 2022.

• Share on Linkedin
• Share on Facebook

When we think of new technologies in medicine, we tend to conjure images of futuristic AI computers , 3D-printed organs , and robot surgeons. The ambitious and lesser-explored methods currently being applied in drug discovery and development, however, could prove to be just as exciting.

A GlobalData survey this year revealed that over 70% of pharma industry respondents anticipate drug development will be the area most impacted by the implementation of smart technologies. As the year draws to a close, Pharmaceutical Technology takes a look at some of the technological innovations and approaches that could transform drug research in 2022.

Go deeper with GlobalData

Chemotherapy in Pharmaceuticals: Platinum-based cancer drug composi...

Future of pharma - looking ahead to 2023, premium insights.

The gold standard of business intelligence.

Find out more

Related Company Profiles

Astrazeneca plc, fujitsu ltd, nvidia corp, oxford nanopore technologies plc, harnessing ai with supercomputing.

Supercomputers are vastly superior to general-purpose computers in terms of speed and performance, and are particularly valuable when it comes to performing scientific and data-intensive tasks. It makes sense, then, that researchers are looking to apply supercomputing to the exhaustive process of drug discovery and design.

This year, US tech company NVIDIA launched Cambridge-1 , the UK’s most powerful supercomputer, to help British healthcare researchers solve some of the industry’s most urgent healthcare challenges. Along with the launch of Cambridge-1, NVIDIA also announced a series of collaborations with the pharma behemoths AstraZeneca and GlaxoSmithKline, and institutions like Guy’s and St Thomas’ NHS Foundation Trust, King’s College London and Oxford Nanopore Technologies .

The Cambridge-1 supercomputer has the potential to significantly accelerate and optimise every stage of drug research. NVIDIA is collaborating with AstraZeneca to build a transformer-based generative AI model for chemical structures, which will allow researchers to leverage massive datasets using self-supervised training methods and enable faster drug discovery.

GSK’s own research has a steadfast focus on  genetically validated targets, which are twice as likely to become approved therapies and now make up more than 70% of the company’s drugs pipeline. NVIDIA has partnered up with GSK and its AI team to unlock vast quantities of genetic and clinical data and help the company to develop more effective drugs and vaccines, faster.

How well do you really know your competitors?

Access the most comprehensive Company Profiles on the market, powered by GlobalData. Save hours of research. Gain competitive edge.

Your download email will arrive shortly

Not ready to buy yet? Download a free sample

We are confident about the unique quality of our Company Profiles. However, we want you to make the most beneficial decision for your business, so we offer a free sample that you can download by submitting the below form

NVIDIA’s vice president of healthcare Kimberly Powell shared with Pharmaceutical Technology the company’s top three predictions for supercomputing in pharma:

• AI accelerates million-times drug discovery : “ Molecular simulations help to model target and drug interactions completely in silico. The breakthroughs of AlphaFold and RoseTTAFold that created a thousand-fold explosion of known protein structures, and AI that can generate a thousand more potential chemical compounds has increased the opportunity to discover drugs by a million times. ”
• Multimodal AI : “There are over ten thousand diseases without a therapy. Multiple sources of health data need to be used, whether it is to discover drugs or treat patients. In order to leverage the world’s largest data sources, multimodal AI will bring us to that new frontier in discovering disease pathways, as well as personalising the treatment and prognosis of patients.”
• AI 2.0 with federated learning : “To help application developers industrialise their AI technology and expand the application’s business benefit, AI must be trained and validated on data that resides outside the possession of their group, institution and geography. Federated learning is key to enable such collaboration to build and validate robust AI models without sharing sensitive data. Federated learning will be an essential capability to facilitate the continuous learning and evaluation of AI.”

While Cambridge-1 may be the most powerful supercomputer in the UK, Japan is home to the world’s fastest. Fugaku, jointly developed by research institute RIKEN and tech company Fujitsu , aims to tackle a range of pressing scientific and social issues. For healthcare, this means drug discovery through functional control of biomolecular systems, and integrated computational life science to aid the development of personalised and preventive medicine.

Despite only officially launching earlier this year, Fugaku has already proved valuable in identifying medicines that can be repurposed to fight Covid-19, narrowing over 2000 potential drug candidates down to just a few dozen. The Covid-19 research project employing Fugaku’s supercomputing capabilities to uncover potential therapies will run until March next year.

Gene writing

Gene editing – the insertion, deletion, modification, or replacement of DNA in a genome – is a promising and relatively new approach to treat genetic disorders. Newer still is the concept of gene writing to tackle inherited disease.

Pioneered by Massachusetts-based Tessera Therapeutics , the technique involves writing therapeutic messages directly into the genome to correct disease-causing genetic errors – and the company says the technology has the potential to target virtually any inherited disorder at its source.

Gene writing is based on using mobile genetic elements (MGEs), a type of genetic material that can be inserted into specific locations within a genome, using DNA or RNA templates.

Tessera only launched in 2020, but has already caught the attention of investors and researchers alike; the company raised an impressive $230m in Series B financing early this year, and last month announced an R&D collaboration with the Cystic Fibrosis Foundation.

Tessera’s co-founder and chief innovation officer Jacob Rubens said the company plans to continue to advance it gene writing technology in the next year.  “By delivering our therapeutics with RNA and lipid nanoparticle technologies, we believe it may be possible to revolutionise healthcare by making genetic medicines widely available for many diseases in diverse geographies.”

Spanish biotech Integra Therapeutics, founded last year, has also thrown its hat into the gene writing ring. Just this month, the company secured €4.5m funding towards the next-generation gene writing tools that it’s developing to make advanced therapies safer and more effective. The funds will also allow the company to carry out preclinical validation using in vivo and ex vivo models, and manage its patent portfolio in 2022 and the year after.

Integra CEO Avencia Sánchez-Mejías told Pharmaceutical Technology the company’s focus for next year is developing “a really strong proof of concept and a final prototype”.

Quantum computing

Applying computational methods to drug discovery is nothing new, but the use of ultra-efficient quantum computers to reveal previously unknown compounds has only recently emerged as an area of promise.

While classical computers rely on “bits” that are either on or off, quantum computers use “qubits”, which can either be on or off, or both – known as superposition. This property of superposition allows quantum computers to drastically accelerate and optimise testing and predictions, making the technology especially promising for drug discovery efforts.

Australian-German Quantum Brilliance is one company on a mission to make quantum-powered drug discovery a reality. Founded in 2019, the start-up is developing diamond quantum accelerators that can simulate interactions between multiple molecules for in silico drug discovery and design.

“Our goal for 2022 is to demonstrate the concept and value of distributed quantum computing (QC) for computational chemistry as part of our software stack,” says Quantum Brilliance’s chief scientific officer Marcus Doherty.

While QC is still in its infancy, Doherty says, industry players have acknowledged its potential to revolutionise medical research – and the spate of deals made between QC groups and major drug companies this year is proof that the pharma industry isn’t waiting to get involved.

In January, Boehringer Ingelheim entered a collaboration with Google Quantum AI to apply quantum methods to drug design and in silico modelling. A month later, pharma giant Roche announced a deal with Cambridge Quantum Computing to accelerate the development of early-stage Alzheimer’s disease drugs.

More recently, in November, digital QC company SEEQC announced that its UK-based team had been awarded a £6.85m grant from the country’s government agency Innovate UK. With the funding, SEEQC will build and deliver a full-stack quantum computer to be used for drug development by German multinational Merck KgaA.

“The demonstration of quantum utility – defined as a quantum system outperforming classical processors of comparable size, weight and power in similar environments – could become valuable for the discovery of new materials and new medicines,” Doherty says.

To know more about pharma & healthcare forecasts and trends that are likely to make an impact in 2022, catch more of our coverage here;

Mapping the RNA therapeutics R&D landscape in 2022

2022 forecast: decentralised trials to reach new heights with 28% jump

2022 forecast: diabetes, cardiovascular, respiratory trial activity set to rebound

Revealed: emerging healthcare industry investment themes to watch in 2022

Revealed: countries with the most hospital project completions in 2022

Free Whitepaper

Precision medicine: streamlining treatments and drug development.

By downloading this case study, you acknowledge that GlobalData may share your information with Scotland and that your personal data will be used as described in their Privacy Policy

Sign up for our daily news round-up!

Give your business an edge with our leading industry insights.

More Relevant

ESCMID 2024: Drug resistance in fungi – a growing issue

Addex stock tanks after lead drug flops in phase ii epilepsy trial, fda approves x4 pharmaceuticals' whim syndrome drug, pharmalink partners with recall results on safety of drugs, sign up to the newsletter: in brief, your corporate email address, i would also like to subscribe to:.

Pharma Technology Focus : Pharmaceutical Technology Focus (monthly)

Thematic Take (monthly)

I consent to Verdict Media Limited collecting my details provided via this form in accordance with Privacy Policy

Thank you for subscribing

View all newsletters from across the GlobalData Media network.

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Review Article
• Published: October 2004

A guide to drug discovery

The role of the medicinal chemist in drug discovery — then and now

• Joseph G. Lombardino 1 &
• John A. Lowe III 2  

Nature Reviews Drug Discovery volume  3 ,  pages 853–862 ( 2004 ) Cite this article

70k Accesses

236 Citations

21 Altmetric

Metrics details

Medicinal chemists paly a crucial role in the drug discovery process through the selection and synthesis of compounds that establish structure–activity relationships and achieve efficacy and safety in preclinical animal testing

Many aspects of the medicinal chemist's role have changed since the early era of drug discovery when animal testing and small, informal project teams dominated the process.

Combinatorial chemistry, high-throughput screening and molecularly defined targets that allow structure-based drug design have changed the chemist's role in the modern era.

In vitro screens for pharmacokinetic properties, the focus on synthesizing drug-like compounds, and in vitro toxicity screens are important new developments that aid the medicinal chemist's job today.

Suggestions for improving the drug discovery process include more in vivo testing earlier in the drug discovery process, allowing medicinal chemists to champion their drug candidate during its development; and passing on the tacit knowledge of experienced medicinal chemists to their younger colleagues.

The role of the medicinal chemist in drug discovery has undergone major changes in the past 25 years, mainly because of the introduction of technologies such as combinatorial chemistry and structure-based drug design. As medicinal chemists with more than 50 years of combined experience spanning the past four decades, we discuss this changing role using examples from our own and others' experience. This historical perspective could provide insights in to how to improve the current model for drug discovery by helping the medicinal chemist regain the creative role that contributed to past successes.

Similar content being viewed by others

Causal machine learning for predicting treatment outcomes

Highly accurate protein structure prediction with AlphaFold

Refining the impact of genetic evidence on clinical success

Medicinal chemists prepare and/or select appropriate compounds for biological evaluation that, if found to be active, could serve as LEAD COMPOUNDS . They then evaluate the STRUCTURE–ACTIVITY RELATIONSHIPS (SARs) of analogous compounds with regard to their in vitro and in vivo efficacy and safety. Today, medicinal chemists who are engaged in drug discovery are part of interdisciplinary teams, and must therefore understand not only the field of organic chemistry, but also a range of other disciplines to anticipate problems and interpret developments to help move the project forward.

As highlighted in this article, the role of the medicinal chemist has changed significantly in the past 25 years. In the early era ('then') of drug discovery (1950 to about 1980), medicinal chemists relied primarily on data from in vivo testing. In the more recent ('now') period (about 1980 to the present), the development of new technologies, such as high-throughput in vitro screening, large compound libraries, COMBINATORIAL TECHNOLOGY , defined molecular targets and structure-based drug design, has changed that earlier and relatively simple landscape. Although these new technologies present many opportunities to the medicinal chemist, the multitude of new safety requirements that have arisen has also brought unanticipated hurdles for the task of translating in vitro activity to in vivo activity. Simultaneously, the knowledge base that supports drug research has expanded considerably, increasing the challenge for chemists to understand their fields of expertise. The demonstration of adequate clinical safety and efficacy in humans has also become more complex, and ever-increasing amounts of data are now required by regulatory agencies. In fact, despite the use of many new technologies, and the growing resources and funding for drug research, the number of launches of new medicines in the form of NEW MOLECULAR ENTITIES (NMEs) has been generally decreasing for more than a decade. Clearly, the difficulty and complexity of drug research has increased in the past two decades. It is our aim with this article to discuss how these changes have influenced the role of medicinal chemists and to suggest ways to help them to contribute more effectively to the drug discovery process.

The process of drug discovery

Inventing and developing a new medicine is a long, complex, costly and highly risky process that has few peers in the commercial world. Research and development (R&D) for most of the medicines available today has required 12–24 years for a single new medicine, from starting a project to the launch of a drug product ( Fig. 1 ). In addition, many expensive, long-term research projects completely fail to produce a marketable medicine. The cost for this overall process has escalated sharply to up to an estimated US $1.4 billion for a single new drug 1 . All of the funds to support this research usually come from the income of the private pharmaceutical company that sponsors the work. In the research ('R'; discovery) phase, only a fraction of the scientific hypotheses that form the basis for a project actually yield a drug candidate for development. In the drug development ('D') phase, experience has shown that only approximately 1 out of 15–25 drug candidates survives the detailed safety and efficacy testing (in animals and humans) required for it to become a marketed product. And for the few drug candidates that successfully become marketed products, some will not recover their costs of development in the competitive marketplace, and only approximately one in three will become a major commercial product. Clearly, this is a high-stakes, long-term and risky activity, but the potential benefits to the millions of patients with serious diseases provide a constant motivating force. At virtually every phase — from project initiation to discovery, development and planning for marketing for a new drug — the modern medicinal chemist can have a role.

The drug discovery process begins with the identification of a medical need, including a judgement on the adequacy of existing therapies (if there are any). From this analysis, together with an appraisal of the current knowledge about the target disease, will come hypotheses on how to possibly improve therapy — that is, what efficacy, safety or mechanistically novel improvements will advance the method of drug treatment for patients with the target disease? On the basis of these hypotheses, specific objectives will be set for the project. Then, testing selected chemicals in appropriate biological tests can begin. Key subsequent steps in the process include detecting relevant biological activity (a 'hit') for a structurally novel compound in vitro , then finding a related compound with in vivo activity in an appropriate animal model, followed by maximizing this activity through the preparation of analogous structures, and finally selecting one compound as the drug development candidate. This drug candidate then undergoes toxicological testing in animals, as required by law. If the compound passes all these tests, all the accumulated research data are assembled and submitted as an Investigational New Drug Application (IND) to the Food and Drug Administration (FDA) in the United States (or comparable agency in other countries) before clinical trials are initiated. In the clinic, there is sequential evaluation in normal human volunteers of toleration (Phase I), efficacy and dose range in patients (Phase II), followed by widespread trials in thousands of appropriate patients to develop a broad database of efficacy and safety. For the few (4–7%) drug candidates that survive this series of development trials, a New Drug Application (NDA) that contains all the accumulated research data is filed for thorough review by the experts at the FDA. Only with their approval can the new drug be offered to doctors and their patients to treat the disease for which it was designed.

The role of the medicinal chemist

The modern medicinal chemist, although part of a team, has a particularly crucial role in the early phases of drug discovery. The chemist, trained to prepare new chemicals and with an acquired knowledge of the target disease and of competitive drug therapies, has an important part in framing the hypothesis for the new drug project, which then sets the objectives for the project. The chemist also helps to decide which existing chemicals to screen for a lead compound and which screening hits need to be re-synthesized for biological evaluation. Purification and proper characterization of the new chemicals is also the responsibility of the chemist. When an in vitro ' HIT ' is identified, the chemist decides on what analogous compounds should be obtained or synthesized to explore the SARs for the structural family of compounds in an effort to maximize the desired activity. Developing in vivo activity for the hit compound in an appropriate animal model is also mainly the responsibility of the chemist. This can often be one of the most difficult steps to accomplish because several factors, such as absorbability, distribution in vivo , rate of metabolism and rate of excretion (ADME), all present hurdles for the chemist to solve in the design and preparation of new, analogous chemicals for testing. The goal at this stage is to maximize efficacy while minimizing side effects in an animal model.

For the medicinal chemist to address all the challenges outlined above, several skills are required. These include a thorough knowledge of modern organic chemistry and medicinal chemistry, an understanding of the biology that relates to the target disease, an understanding of the pharmacological tests used in the project and sufficient knowledge of the factors that influence ADME characteristics of chemicals in vivo . Furthermore, they should also have an understanding of clinical medicine that pertains to the target disease; knowledge of the regulatory requirements for related drugs; a current knowledge of competitive therapies, both in the market and under development by competitors; a thorough knowledge of the literature that is relevant to the target disease; familiarity with the many newer technologies available to facilitate drug discovery; and an entrepreneurial attitude in behaving as an innovator and inventor. Finally — and of crucial importance to the timely success of the project — the chemist must show superior interpersonal skills throughout the life of the project to interact effectively with colleagues from other disciplines to achieve project goals.

The medicinal chemist — then and now

Then (1950s–1980s). About 25–45 years ago, a medicinal chemist's tasks differed in some ways from those of a chemist today; an example of a successful project from this era (the development of the anti-inflammatory agent piroxicam (Feldene; Pfizer)) is highlighted in Box 1 . At that time, the medicinal chemist and a pharmacologist counterpart were the main drivers of the research programme: compounds were designed and individually synthesized by the chemist in gram quantities to accommodate the need for testing in whole animals by the pharmacologist. Given the limited synthetic methodology available, these syntheses were often time-consuming and, even with one or two technical assistants working in the laboratory, the output from one chemistry laboratory was limited to an average of one to three compounds per week. Commercially available starting materials were often limited. The chemist had only a few tools (for example, infrared and ultraviolet spectroscopy, and column chromatography) to assist with compound characterization and purification. Outsourcing was rare; all tasks, including bulk syntheses, toxicological testing and analogue synthesis, were done in-house. The creativity and intuition of the medicinal chemist was pivotal to the success of the programme, although given the limited number of compounds produced, serendipity had a large role as well.

Projects generally used in vivo models for primary screening, as little was known about the detailed biological mechanisms involved in most diseases. In vitro testing against a key enzyme or specific receptor involved in the disease process was usually not possible; as discussed in Box 2 (which describes the discovery of the antipsychotic ziprasidone (Geodon; Pfizer)), in vitro receptor-based pharmacology only became common in the 1980s and 1990s. In addition, compound collections for exploratory biological screening were limited. The data generated from the test models were compiled, analysed and displayed by hand in the form of charts and graphs. Similarly, searching the literature for relevant information involved the handling of bound volumes taken individually from the library shelves.

Small companies tend to rely on informal communication and timelines, and this was often the case in the smaller pharmaceutical industry 'then'. For the medicinal chemist, the benefit of this informality was ready access to colleagues in other disciplines to evaluate a compound that the chemist was interested in. The disadvantage came once a chemist's compound was selected for further development. The chemist, who would probably have moved on to another project, usually heard little or nothing about the drug candidate until the (often) bad news came back that the candidate had failed some key test. Keeping abreast of the progress of the drug candidate required the same proactive, informal action that the chemist had used previously to periodically contact the appropriate scientists in other disciplines to get some news about the drug candidate. To address these issues, most organizations in the 1980s established interdisciplinary matrix teams for each drug candidate to facilitate information exchange and joint planning between departments, such as chemistry, biology, pharmaceutics, toxicology, PHARMACOKINETICS , clinical medicine and regulatory affairs, all of which have important roles in drug development.

Overall, the process of drug discovery 'then' was slower and operated from a relatively smaller knowledge base. Several factors combined to slow the process: there was less known about diseases, there were fewer available compounds to screen, there were no computerized technologies for handling information and data, there was a need to manually search the literature, there was a need to individually prepare gram quantities of each new compound for testing, and chemists rarely received information from other disciplines about their development candidates. On the other hand, once a lead was identified in the primary in vivo test model, many of the pharmacokinetic (ADME) problems were mainly in hand or could be rapidly addressed, thereby expediting the selection of a drug candidate to study in the clinic.

Now (1980s–present). Despite some differences from the earlier era of drug discovery described above, medicinal chemists today face many of the same tasks and challenges that they did 40 years ago. So, the chemist still selects the appropriate structural series of compounds to follow and pursues the SARs to identify suitable drug candidates for advancement to safety and clinical testing. But today's chemist has a much wider range of tools to help overcome the numerous hurdles in the drug discovery process. These new tools include advances in synthetic, analytical and purification technology, such as transition-metal-catalysed carbon–carbon bond-forming reactions, high-field NMR and preparative high-performance liquid chromatography (HPLC), as well as computer-assisted literature and data retrieval and analysis. The recent trend towards outsourcing many routine, tedious aspects of the drug discovery process has freed today's chemist to spend more time on new compound design. In addition, two powerful technologies have put numbers on the chemist's side: combinatorial chemistry (combichem) and high-throughput screening (HTS). Combichem allows chemists to generate rational, focused libraries of compounds that define SARs in a fraction of the time that was required 'then'. Depending on where they work, chemists can design, synthesize and purify libraries themselves, or hand over the final synthesis steps to a group of chemists designated for this purpose. This group might also make lead-compound libraries that target specific receptor or enzyme families to provide better quality leads that are suitable for library follow up. The development of HTS of large sample collections, including the designed libraries, has produced marked decreases in the personnel, time and money required to identify compounds that hit a specific biological target, although many companies are struggling to triage the large number of screening hits to viable lead compounds that can support a successful drug discovery project. In this struggle, costs can escalate significantly as the generation of large amounts of data is not the same as generating viable, quality leads. Finally, new graphics software, such as Excel and Spotfire 2 , can facilitate the retrieval and analysis of the mountain of data generated from screening compound libraries in a large panel of in vitro assays.

The molecular genetics revolution 3 has driven the development of another key ingredient in today's drug discovery model: the use of molecularly defined biological targets, such as enzymes, receptors and transporters. The desire for defined molecular targets for drug discovery, in contrast to the clinically based animal-model approach used in the early era of drug discovery discussed above, derives from several factors. One is the advantage of a known mechanism of action over a 'black-box' (that is, unknown) mechanism obtained from animal-model testing that could produce unanticipated toxicity during drug development. Another is the use of structure-based drug design, which allows the chemist to design new compounds by directly visualizing the interaction of a lead compound with the target protein through X-ray crystallographic analysis, but which is only possible with a molecularly defined target protein 4 . A recent example from the new era of drug discovery described in Box 3 (the kinase inhibitor imatinib mesylate (Gleevec; Novartis)) illustrates these advantages, which are now so well established that retreat to the black-box models of yesteryear is no longer feasible.

Recent changes — medicinal chemistry today

New techniques for addressing pharmacokinetic issues. The emphasis on in vitro screening of compounds against molecularly defined targets, although rapid and specific, has additional consequences for today's medicinal chemist. As the primary screen used to guide SAR studies, in vitro data do not help chemists to overcome the pharmacokinetic liabilities of their compounds. On the other hand, relying on in vivo animal models for the evaluation of pharmacokinetic performance suffers from a potentially serious drawback: differences between absorption and metabolism of drugs in humans and rats (a common test species) can lead to the development of drugs that work only in rats and not in humans. To help overcome this limitation, in vitro screens have been developed that are predictive of human pharmacokinetic performance, for example, by measuring a compound's degradation by preparations of human microsomes or hepatocytes or by recombinant human CYTOCHROME P450 ENZYMES . In addition to assessing metabolic stability, P450 assays can determine whether a compound is likely to interfere with the metabolism of other drugs that a patient is taking by virtue of inhibiting the P450 enzyme required for their elimination. Permeability and transporter assays have also been developed to characterize drug uptake into or efflux from the target organ(s) (for a review of the P-glycoprotein (Pgp) transporter in drug development, see Ref. 5 ). So, today's chemist has a complex array of in vitro SAR patterns to discern and interpret to plan the preparation of compounds for follow up (for a review of the screening data typically used in the drug discovery process, see Ref. 6 ). Selected compounds must also be profiled in vivo to assess how well the in vitro data predict in vivo performance. Further in vivo testing is then required to show that the compound attains levels at the target organ commensurate with achieving the desired biological effect that is proposed to result from the in vitro activity.

Final testing might involve a disease-relevant animal model, although these data must be interpreted cautiously owing to several limitations. For example, many diseases, such as stroke , atherosclerosis and Alzheimer's disease , do not have clinically effective drugs that can validate a disease-progression-relevant animal model. Also, older models are based on drugs that work by certain mechanisms, and might not fairly assess drugs that are developed against a new mechanism. As such, the disease-relevant animal model is only one of many assays used to evaluate new compounds and, coming later in the testing sequence, has less impact on decisions made by today's chemists.

Synthesis of 'drug-like' compounds. Another strategy to overcome pharmacokinetic liabilities is the prediction and synthesis of compounds with ' DRUG-LIKE ' properties. Highly lipophilic, high-molecular-mass compounds tend to have more potent in vitro binding activity, by virtue of excluding water from the enzyme or receptor surface and thereby picking up additional hydrophobic interactions. But these compounds are usually not drug-like because of their low water solubility, and they generally fail in further development because of poor pharmacokinetics and oral BIOAVAILABILITY . Lipinski et al . 7 formulated the 'rule-of-five' to predict drug-likeness, which consists of four important properties, each related to the number 5 (molecular mass <500 Da; calculated LOGP <5; hydrogen-bond donors <5; and hydrogen-bond acceptors <10). The rule is based on data in the literature for a large number of compounds, including all known drugs, that correlate physical properties with oral bioavailability. Support for the rule as a predictor of drug-likeness comes from observing weaknesses in the development pipelines of major pharmaceutical companies owing to failure to adhere to the rule-of-five 8 . Computational calculations routinely predict rule-of-five properties for prospective compounds in a chemist's SAR plans to guide compound selection, although this guidance comes at the cost of adding complexity to an already complex set of in vitro data.

Use of in vitro toxicity screens to reduce attrition. Completing the in vitro screens that the chemist uses to select the next compound to synthesize are the toxicity screens that weed out compounds predicted to fail for safety reasons. The Ames test, and related in vitro tests for mutagenicity and carcinogenicity, has a long history, but recent additions to this list include the hERG channel, a cardiac potassium ion channel involved in cardiac repolarization following ventricle contraction during the heartbeat 9 . Drugs that bind to and inhibit the hERG channel can cause prolongation of the QT interval of the electrocardiogram, leading to loss of a synchronous heartbeat and eventually ventricular fibrillation, and even death. The danger posed by a drug that inhibits the hERG channel was illustrated by the deaths of patients taking the allergic rhinitis drug astemizole (Hismanal; Janssen), which led to its abrupt withdrawal from the market 10 . In the aftermath of this and other incidents of fatal complications from hERG-blocking drugs, the FDA is formulating guidelines to address the issue. Most pharmaceutical companies now have hERG screening in place to afford chemists an indication of the therapeutic index of their compounds for this end point 11 .

Box 4 summarizes the various criteria that today's chemist must follow to develop a successful drug candidate. A recent literature example that illustrates many of the new techniques and testing hurdles for today's medicinal chemist — a series of farnesyl transferase inhibitors — is given in Box 5 .

Final thoughts on the drug discovery process

The role of a champion in drug discovery. As a scientist involved at the very earliest stages of drug discovery, including the setting of project objectives, the medicinal chemist with leadership qualities has the opportunity to act as a champion for the drug candidate throughout the long R&D process. Championing a drug candidate was often a key factor in a successful drug project 'then' and was facilitated by the smaller project teams typical of this earlier era. For example, key publications concerning a new drug often had just two authors, the chemist and the biologist, who were essentially the drug champions. There is a multitude of commercially successful drugs today that survived a dark period during development only because a champion worked to keep the drug alive by finding answers to problems (see examples provided in Ref. 12 ).

To act as a champion for a drug candidate, a chemist with current knowledge of all aspects of the drug programme must take an enduring, pervasive interest in all aspects of the development process, especially in helping to solve those seemingly intractable challenges that inevitably arise during the long path to regulatory approval. Without a champion, a drug candidate can lose momentum and stall irreversibly during the years leading to regulatory approval. This is truer today than ever, because the process has become so much more complicated. And yet the contribution of a medicinal chemist can seem diluted by the presence of scientists from the many other disciplines that make up a typical drug discovery programme today, disciplines which have risen significantly in importance in recent years. In addition to the increased number of contributing scientific sub-specialities today, the high cost and increased complexity of drug R&D today 1 can dwarf any one scientist's contribution.

Suggestions for improving the drug discovery process. Recent data indicate that productivity has not kept pace with increasing resource allocation to the drug discovery process. We would like to suggest three ways to improve the current model for new drug discovery that would help the medicinal chemist to be more productive. The first stems from the current heavy reliance on in vitro screening for driving SARs early in a programme, at the risk of finding poor pharmacokinetics and oral bioavailability later on. Coordinating animal testing with in vitro testing early in the drug discovery process to pre-screen lead series in vivo , and then correlating in vitro pharmacokinetics screens with in vivo data as soon as possible, might provide a firmer footing for the chemist to overcome any deficiencies in pharmacokinetics. Such testing might also help to identify lead compounds on the basis of their promising in vivo activity or pharmacokinetic properties that would have been rejected on the basis of in vitro testing alone.

The second suggestion is based on the need to have a committed drug champion to bring background information and a historical perspective (sometimes termed 'institutional memory'), and to suggest solutions to the myriad issues that arise throughout a drug's development. By appointing a small, permanent committee, which includes the medicinal chemist from the discovery team, to be involved with the entire drug development programme through to drug registration (and to work alongside the interdisciplinary matrix development teams), there would always be someone available to provide informed judgments on the basis of their medicinal chemistry background and experience on the project to help keep the drug on track during the many years required for its successful development.

Finally, as many of the most experienced chemists in the pharmaceutical industry reach retirement age, there remains the challenge of how to pass on their learning to the next generation. They possess tacit knowledge (that is, residing in the mind of the experienced scientist but not yet communicated to others) of the drug discovery experience that needs to be recognized, captured and then passed on to the young scientists (as outlined in Ref. 13 ). Companies that accomplish this, by, for example, holding in-house workshops on drug design and lecture series on medicinal chemistry, will help to teach the next generation of scientists the art of successful drug discovery.

The changing landscape of the pharmaceutical industry. Some basic questions about the new technologies and procedures now used for drug research, compared with the dwindling supply of new drugs approved in recent years, have been raised in recent news articles 14 , 15 , 16 , 17 . For example, has the introduction of major changes in the drug discovery process caused the obvious drop in new drug output? Is this drop temporary, to last only until the new technologies begin to yield some products? Have the changes produced a decrease in output by stifling the creativity of the scientists (including the medicinal chemists) involved in drug discovery? Has the role of serendipity, so important to drug discovery in the past, been supplanted by robots? What has happened to the role of the medicinal chemist's intuition and creativity in producing quality drugs? How many of today's most successful drugs could have been made through the limited chemical pathways offered by combichem techniques? Making millions of new chemicals robotically does not, apparently, lead to more new drugs.

An important perspective on this discussion comes from a recent account 17 of the key differences in the pharmaceutical industry experienced by a father–son pair of medicinal chemists, Leo Sternbach ('then', about 40–50 years ago, when he invented chlordiazepoxide (Librium; Hoffman-La Roche) and diazepam (Valium; Hoffman-La Roche)) and his son, Daniel ('now', currently a medicinal chemist at GlaxoSmithKline). By their account, the role of the medicinal chemist has changed considerably from that of a highly autonomous, independent inventor 'then' to a significant player in a large team that is increasingly influenced by the business units 'now'.

In our opinion, whatever the merits of the business decisions that led to this change, the role of serendipity, chemical intuition and creativity in thoughtfully selecting a chemical target to synthesize in order to discover the best-quality drugs has not diminished. There must always be an opportunity in research for the useful chance observation by a prepared mind. There are many examples of 'back burner' (that is, unauthorized) projects that have yielded important new drugs. Although the new technologies that have accelerated the process of drug discovery provide some undoubted benefits, the human factor remains an integral part of success in this endeavour. It is our hope that the accounts of successful drug discoveries presented here will serve as a reminder of the chemists whose decisions actually led to these success stories.

Today, the rapidly expanding knowledge base concerning diseases, their causes, symptoms and their effects on the human body holds great promise for the discovery of important new medicines. Sequencing the human genome also offers the opportunity for finding many more novel and selective therapies. Such discoveries will probably come from teams of scientists, including medicinal chemists, whose careers are devoted to this one task. The enormous cost of this task will be borne mainly by those pharmaceutical companies that can successfully generate the required research funds from the sale of their existing drugs.

Medicinal chemists today live in exciting times. They are key participants in the effort to produce more selective, more effective and safer medicines to treat the diseases of mankind. Their work can have a beneficial effect on millions of suffering patients — surely an important motivating factor for any scientist.

Box 1 | Discovery of piroxicam (1962–1980)

The project that produced the novel anti-arthritic and anti-inflammatory agent piroxicam (Feldene; Pfizer) began in 1962 and led to the product launching into key European markets in 1980. A detailed history of this 18-year process, including the failures and setbacks along the way, has been described elsewhere 12 , 18 , so only a brief outline will be given here.

The original research team assigned to produce a new anti-inflammatory agent at Pfizer consisted of just two people — a medicinal chemist and a pharmacologist. Both were new to the area of inflammation research and had to educate themselves on all aspects of this therapeutic area. Several therapies for treating the symptoms of arthritis were already available or in development at other companies. These therapies included aspirin, indomethacin, diclofenac, ibuprofen and others. The medicinal chemist noted that all of these agents were from one chemical class — the carboxylic acids. Members of this chemical class were known to be rapidly metabolized and excreted, therefore necessitating multiple daily dosing (three to six times a day) of these drugs to maintain control of the pain and swelling of arthritis. These multiple daily doses were a feature that patients found to be undesirable and led to poor compliance. Furthermore, high daily doses (up to 16 g of aspirin) were required for some of these relatively non-potent agents, therefore placing a heavy load on the gastrointestinal tract, liver and kidneys, and consequently increasing the potential for toxicity.

In the early period of the project that eventually produced piroxicam, a set of project objectives were gradually developed that guided the project in the succeeding years. These objectives were to:

seek a structurally novel compound with acidic properties, but not a carboxylic acid.

seek a highly potent anti-inflammatory agent in animal models that was predictive of clinical activity and to use as controls the drugs known to be efficacious in humans.

identify an active agent that resists metabolism that would produce a long plasma half-life in animals and in humans, and consequently lead to reduced frequency of dosing in humans.

seek a very safe agent that arthritic patients could use over long periods of time to treat their chronic disease.

These stringent objectives placed formidable hurdles in the pathway to success and prolonged the time required to successfully achieve the goal.

The synthesis of gram quantities of compounds designed by the chemist then began, all of which were thought to have the potential to fulfill the project objectives. The acidity (p K a ) of each structure was measured and the serum half-life in dogs was determined for selected analogues to guide the synthesis programme. Using in vivo animal models of inflammation (this was before prostaglandins were known to be involved in inflammation), several families of compounds were found and partially developed ( a–d ), but each failed during a 5-year period (reviewed in Ref. 12 ) before the first 'oxicam' shown in panel e (CP-14304) was synthesized (see figure). The synthesis of this particular compound was a 'back burner' probe based on the intuition of the chemist. The introduction of a carboxamide function into the molecule proved to be a key factor in increasing anti-inflammatory activity and for increasing acidity. Structure–activity relationships (SARs) for several hundred analogous oxicam structures produced improved activity and safety, and, eventually, through a series of three development candidates (see figure parts c and e ), led to piroxicam as the agent that best met the project objectives. Extensive clinical trials confirmed the efficacy and safety of the new drug, leading to approvals and launches into major European markets in 1980, 18 years after the project was started. The drug provided around-the-clock symptom control for arthritis patients with just one 20-mg dose per day, leading to widespread acceptance by patients and making Feldene one of the most successful drugs in the 1980s. After 1992, major protective patents expired and generic brands of piroxicam dominated the market.

Box 2 | Discovery of ziprasidone (1984–2001)

Ziprasidone (Geodon; Pfizer) was launched in 2001 for the treatment of schizophrenia, a debilitating mental disease characterized by delusions, social withdrawal, suicidal behaviour and cognitive decline. The project that led to the discovery of ziprasidone relied primarily on disease-relevant animal models as had piroxicam ( Box 1 ), but, in addition, in vitro receptor-binding assays helped to find an agent that would lead to a significant advance over the already-available treatment.

The disease-relevant animal models for the ziprasidone discovery programme go back to the 1950s and the discovery of the first drug for schizophrenia (chlorpromazine), an anti-allergy drug that was serendipitously found to produce a calming effect in psychotic patients 19 . Paul Janssen, who had set up a medical research laboratory in 1953, studied the potential for discovering new antipsychotic drugs based on chlorpromazine by using it as a control drug in animal models designed to predict clinical activity. The models that Janssen developed relied on the ability of chlorpromazine to block the locomotor effects of stimulants such as amphetamine and apomorphine. Testing new agents that mimicked this activity of chlorpromazine led to his discovery of the first-generation antipsychotic drug haloperidol 20 . These models were still being used in the 1980s and therefore contributed to the discovery of ziprasidone.

As a supplementary approach to in vivo animal models as the primary screen, in vitro receptor-based pharmacology emerged in the 1980s and 1990s and came to dominate the field of antipsychotic drug research. This was based on the finding that agents such as haloperidol are effective antipsychotic drugs at the mechanistic level by virtue of their blockade of dopamine type 2 (D 2 ) receptors. In addition, clozapine — the first 'atypical' antipsychotic drug (so-called because it lacks the undesirable motor side effects of haloperidol and chlorpromazine, known as extrapyramidal symptoms (EPS)) — binds to both D 2 and 5-hydroxytryptamine type 2 (5-HT 2 ) receptors. The 5-HT 2 receptor for the neurotransmitter serotonin is thought to afford protection from EPSs that are caused by excessive D 2 -receptor blockade 21 , and this hypothesis initiated a search for an agent with a favourable (>10-fold) ratio of D 2 - to 5-HT 2 -receptor blockade 22 .

The search for ziprasidone began by considering the structure of naphthylpiperazine (compound 1 in the figure). Compound 1 was reported to be a potent ligand for serotonin receptors, including the 5-HT 2 receptor 23 . Combining compound 1 with the structure of dopamine, the natural ligand for the D 2 receptor, and then substituting the catechol with an oxindole as a surrogate produced the combined D 2 and 5-HT 2 antagonist compound 2 (see figure). Compound 2 seemed to be the perfect antipsychotic agent, at least in rats 24 . Further testing in monkeys, however, was disappointing, and attention switched to a new series derived from the 1,2-benzisothiazole group, which proved to have even more potent D 2 -receptor blockade while adding potent 5-HT 2 -receptor blockade that afforded the desired D 2 /5-HT 2 ratio 25 . Fine-tuning of the structure–activity relationship in this new series led from the prototype compound 3 to compound 4 (ziprasidone; see figure) 26 . Finally, the discovery programme confirmed the validity of the D 2 /5-HT 2 hypothesis using disease-relevant animal-model testing, which demonstrated efficacy without EPS liability. Following the 5-year-long discovery phase, another 9 years of clinical testing and 3 years to address regulatory requirements were needed before approval of ziprasidone was given by the FDA. Extensive clinical testing validated the discovery approach, and today hundreds of thousands of patient-days of use have demonstrated the efficacy and safety of ziprasidone as it continues to help patients afflicted with this lifelong, devastating disease.

Box 3 | Discovery of imatinib mesylate

An illustration of the role of a defined molecular target coupled with structure-based drug design in drug discovery comes from the story of imatinib mesylate (Gleevec; Novartis), a selective tyrosine kinase inhibitor approved for the treatment of CHRONIC MYELOGENOUS LEUKAEMIA . The discovery of the oncogenes in the 1970s promised to aid the discovery of oncological drugs with reduced toxicity. In contrast to the cancer drugs in use then, which nonspecifically inhibited DNA synthesis and cell division, an oncogene inhibitor should be selectively toxic to cancer cells. Zimmerman and the Novartis group chose the tyrosine kinase BCR–ABL — which is created by a reciprocal chromosomal translocation that produces the BCR–ABL gene — as their target, as it is found only in leukaemic cells 27 . Inhibiting this molecularly defined target therefore reduces toxicity and maximizes the desired therapeutic effect. They chose compound 1 (see figure), an inhibitor of protein kinase C, as the starting point for the medicinal chemistry programme. Addition of the amide and methyl groups to the phenyl ring (see figure, compound 2) added the potency and selectivity needed for BCR–ABL inhibition, and addition of the piperazinylmethyl group (to generate imatinib, compound 3) was required for water solubility and oral bioavailability. Here is where the second advantage of a defined molecular target provides a crucial insight: when the X-ray crystal structure of imatinib bound to BCR–ABL was solved, it was found that the piperazine ring made significant contacts with the enzyme and was not just providing improved water solubility 28 . More importantly, these X-ray structure data provide insight into how mutations in the BCR–ABL gene produce an imatinib-resistant form of the enzyme, which offers the potential for designing new drugs to overcome this resistance.

Box 4 | In vitro tests: 'now' and 'then'

The following is a typical battery of tests for a modern drug discovery programme 'today'; those marked with an asterisk were also in use 'then'.

In vitro target

Selectivity assays

In vitro absorption, distribution, metabolism and elimination (ADME)

Microsomal stability

Hepatocyte stability

P450 substrate

P450 inhibitor

Permeability

Transporter efflux (for example, P-glycoprotein)

Protein binding

Physical properties

Rule-of-five

In silico ADME

* Secondary (behavioural, chronic)

* Ames test

Micronucleus test

hERG half-maximal inhibitory concentration (IC 50 )

P450 induction

Broad screening

* Others (depending on project)

Box 5 | Farnesyl transferase inhibitors

As one of the oncogenes characterized in the 1970s, RAS has been the target of numerous drug discovery efforts. Compounds that inhibit the enzyme farnesyl transferase (FTase) prevent the mutant form of RAS from causing tumour formation. A group at Merck has published extensively 29 on their FTase inhibitor programme, and examples from this programme are shown in the figure.

The table in the figure shows data for a set of compounds illustrating the criteria that the Merck group used to evaluate their compounds 30 . Compound 1 shows potent in vitro activity for the primary endpoint, farnesyl transferase (FTase) inhibition (IC 50 values are shown), as well as selectivity against geranyl geranyl transferase type I (GGTase), required for cell viability (IC 50 values are shown). Even though it shows good oral bioavailability (F) — 81% — it inhibits the hERG channel (the inflection point for binding to the hERG channel by radioligand displacement assay (hERG IP) = 440 nM) and causes QT PROLONGATION in the dog at a dose that is unacceptable. Macrocyclization to give compound 2 overcomes the problem with inhibition of hERG while maintaining in vitro potency, selectivity and oral bioavailability. In addition, X-ray crystal structure data of compound 2 bound to FTase explain how the enzyme accommodates this structural change and aids in further drug design. Increasing flexibility by saturating one of the rings of the naphthyl core in compound 2 to produce compound 3 and compound 4 considerably increases in vitro potency. Compound 3, however, is unfortunately very potent at hERG (80 nM), whereas compound 4 is cleared rapidly (rate of plasma clearance in the dog (CLp) = 7.3 ml per min per kg). So, even though it is the least potent compound in the set, compound 2 is the best choice for further structure–activity relationship development, primarily because of its pharmacokinetics and safety margin. This example illustrates why today's chemist more often prefers to begin with compounds that possess better pharmacokinetic and selectivity properties, and then to proceed to optimize potency for the primary in vitro end point. (Func 1, cell-based radiotracer assay for FTase inhibition; Func 2, cell-based assay for inhibition of FTase substrate derivatization, given in the absence and presence of human serum; N/A, not available; P450, IC 50 value for inhibition of human P450 3A4.)

R&D execs paint bleak picture of industry productivity: $1.4 bil. per NME. The Pink Sheet 6 (18 August 2003).

Demesmaeker, M. in Proc. 13th European Symp. Quantitative Structure-Activity Relationships: Rational Approaches to Drug Design (eds Hoeltje, H.-D. & Sippl, W.) 506–511 (Prous Science, Barcelona, 2000).

Google Scholar  

Chanda, S. K. & Caldwell, J. S. Fulfilling the promise: drug discovery in the post-genomic era. Drug Discov. Today 8 , 168–174 (2003).

Article   CAS   Google Scholar  

Reich, S. H. & Webber, S. E. Structure-based drug design (SBDD): every structure tells a story. Perspect. Drug Discov. Design 1 , 371–390 (1993).

Lin, J. H. & Yamazaki, M. Role of P-glycoprotein in pharmacokinetics: clinical implications. Clin. Pharmacokinet. 42 , 59–98 (2003).

Lin, J. et al. The role of absorption, distribution, metabolism, excretion and toxicity in drug discovery. Curr. Top. Med. Chem. 3 , 1125–1154 (2003). An excellent summary of the screening paradigm used in big pharma to evaluate new compounds for suitability as development candidates.

Article   Google Scholar  

Lipinski, C. A., Lombardo, F., Dominy, B. W. & Feeney, P. J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Del. Rev. 46 , 3–26 (2001). A classic paper that outlines the use of physical properties to predict 'drug-likeness', used by most pharmaceutical companies to guide drug design.

Lipinski, C. A. Drug-like properties and the causes of poor solubility and poor permeability. J. Pharmacol. Toxicol. Methods 44 , 235–249 (2000).

Tseng, G. -N. IKr: The hERG channel. J. Mol. Cell. Cardiol. 33 , 835–849 (2001).

Taglialatela, M. et al. Cardiac ion channels and antihistamines: possible mechanisms of cardiotoxicity. Clin. Exp. Allergy 29 (Suppl. 3), 182–189 (1999).

Redfern, W. S. et al. Relationships between preclinical cardiac electrophysiology, clinical QT interval prolongation and torsade de pointes for a broad range of drugs: evidence for a provisional safety margin in drug development. Cardiovasc. Res. 58 , 32–45 (2003).

Wiseman, E. H. & Lombardino, J. G. in Chronicles of Drug Discovery Ch. 8 (eds Bindra, J. S. & Lednicer, D.) 173–200 (J. Wiley and Sons, Inc., New York, 1982). An account of the discovery of the novel anti-inflammatory drug piroxicam.

Sapienza, A. M. & Lombardino, J. G. Recognizing, appreciating, and capturing tacit knowledge of R & D scientists. Drug Dev. Res. 57 , 51–57 (2002).

Mullen, R. Priming the pipeline. Chem. Eng. News 82 , 23–42 (2004).

Landers, P. Drug industry's big push into technology falls short. The Wall Street Journal A1 (24 February 2004).

Big Trouble for Big Pharma. The Economist 14 (16 December 2003).

Flynn, J. In two generations, drug research sees a big shift. The Wall Street Journal A1 (11 February 2004). An account of the careers of Leo Sternbach, inventor of Valium, and his son, Daniel, contrasting their experiences in drug discovery.

Lombardino, J. G. & Wiseman, E. H. Nonsteroidal Antiinflammatory Drugs — Mechanisms and Clinical Use Ch. 26 (eds Lewis, A. & Furst, D.) 487–506 (Marcel Dekker Inc., New York, 1987).

Delay, J., Deniker, P., Green, A. & Mordret, M. Excitor-motor syndromes provoked by ataratics. Presse Medicale (1893–1971), 65 , 1771–1774 (1957).

CAS   PubMed   Google Scholar  

Granger, B. The discovery of haloperidol. Encephale , 25 , 59–66 (1999).

Hippius, H. A historical perspective of clozapine. J. Clin. Psychiatry 60 (Suppl. 12), 22–23 (1999). An account of the development history of the first atypical antipsychotic drug clozapine.

PubMed   Google Scholar  

Pere, J. J. Clinical psychopharmacology: the example of clozapine (Leponex). Encephale 21 (Spec. No. 3), 9–12 (1999).

Glennon, R. A., Slusher, R. M., Lyon, R. A., Titeler, M. & McKenney, J. D. 5-HT1 and 5-HT2: binding characteristics of some quipazine analogs. J. Med. Chem. 29 , 2375–2380 (1986).

Lowe, J. A. et al. 1-naphthylpiperazine derivatives as potential atypical antipsychotic agents. J. Med. Chem. 34 , 1860–1866 (1991).

Lowe, J. A. Atypical antipsychotics based on the D2/5-HT2 ratio hypothesis. Curr. Med. Chem. 1 , 50–60 (1994).

CAS   Google Scholar  

Howard, H. R. et al.. 3-benzisothiazolylpiperazine derivatives as potential atypical antipsychotic agents. J. Med. Chem. 39 , 143–148 (1996). An account of the discovery of the atypical antipsychotic drug ziprasidone.

Capdeville, R., Buchdunger, E., Zimmermann, J. & Matter, A. Glivec (STI571, imatinib), a rationally developed, targeted anticancer drug. Nature Rev. Drug Discov. 1 , 493–502 (2002). An account of the design and discovery of the anticancer drug imatinib mesylate (Gleevec; Novartis).

Schindler, T. Structural mechanism for STI-571 inhibition of abelson tyrosine kinase. Science 289 , 1938–1942 (2000).

Bell, I. M. et al. 3-aminopyrrolidinones farnesyltransferase inhibitors: design of macrocyclic compounds with improved pharmacokinetics and excellent cell potency. J. Med. Chem. 45 , 2388–2409 (2002). An account of a recent programme to discover novel anticancer agents that inhibit farnesyl transferase. Some of these data come from reference 30.

Bell, I. M. et al. Design and biological activity of ( S )-4-(5-{[1-(3-Chlorobenzyl)-2-oxopyrrolidin-3-ylamino]methyl}imidazol-1-ylmethyl)benzonitrile, a 3-aminopyrrolidinone farnesyltransferase inhibitor with excellent cell potency. J. Med. Chem. 44 , 2933–2949 (2001).

Download references

Author information

Authors and affiliations.

13 Laurel Hill Drive, Niantic, 06357, Connecticut, USA

Joseph G. Lombardino

Pfizer Global Research and Development, Pfizer Inc., MS 8220-4118, Eastern Point Road, Groton, 06340, Connecticut, USA

John A. Lowe III

You can also search for this author in PubMed   Google Scholar

Corresponding authors

Correspondence to Joseph G. Lombardino or John A. Lowe III .

Ethics declarations

Competing interests.

The authors declare no competing financial interests.

Related links

Alzheimer's disease

A chemical structure or series of structures that show activity and selectivity in a pharmacological or biochemically relevant screen.

The correlation of structural features with the activity of compounds in a given assay.

Synthetic technologies to generate compound libraries rather than single compounds.

(NME). A medication containing an active ingredient that has not been previously approved for marketing in the United States in any form.

A biologically active compound that exceeds a certain activity threshold in a given assay.

The study of the absorption, distribution, metabolism, excretion and interactions of a drug.

Members of the cytochrome P450 superfamily of haem proteins have a key role in the metabolism of drugs, and so understanding the roles of these enzymes is important for issues such as drug bioavailability and drug–drug interactions.

A haematological cancer characterized by excessive proliferation of cells of the myeloid lineage.

Sharing certain characteristics with other molecules that act as drugs. The set of characteristics — such as size, shape and solubility in water and organic solvents — varies depending on who is evaluating the molecules.

The fraction or percentage of an administered drug or other substance that becomes available in plasma or to the target tissue after administration.

The octanol/water partition coefficient is the ratio of the solubility of a compound in octanol to its solubility in water (also known as K ow ). The logarithm of this partition coefficient is called log P. It provides an estimate of the ability of the compound to pass through a cell membrane.

Human ether-a-go-go-related gene, the gene that encodes the α-subunit of the I Kr channel, a major determinant of human cardiac repolarization.

The QT interval is a measure of the total time of ventricular depolarization and repolarization. In recent years, several drugs have been withdrawn from the market because of unexpected reports of sudden cardiac death associated with prolongation of the QT interval. Blockade of the hERG channel has been linked to this effect.

Rights and permissions

Reprints and permissions

About this article

Cite this article.

Lombardino, J., Lowe, J. The role of the medicinal chemist in drug discovery — then and now. Nat Rev Drug Discov 3 , 853–862 (2004). https://doi.org/10.1038/nrd1523

Download citation

Issue Date : October 2004

DOI : https://doi.org/10.1038/nrd1523

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

This article is cited by

In-silico and in-vitro study reveals ziprasidone as a potential aromatase inhibitor against breast carcinoma.

• Ankita Sahu
• Shaban Ahmad
• Saurabh Verma

Scientific Reports (2023)

Predicting phytochemical diversity of medicinal and aromatic plants (MAPs) across eco-climatic zones and elevation in Uttarakhand using Generalized Additive Model

• Deepti Tiwari
• Pushpa Kewlani
• Veena Pande

Exploring the Potential of Compounds Isolated from Laranthus micranthus for the Treatment of Benign Prostatic Hyperplasia: Comprehensive Studies on Spectroscopic, Reactivity, and Biological Activity

• Richard U. Ukpanukpong
• Adindu E. Azubuike
• Hitler Louis

Chemistry Africa (2023)

Integrated data-driven and experimental approaches to accelerate lead optimization targeting SARS-CoV-2 main protease

• Rohith Anand Varikoti
• Katherine J. Schultz
• Neeraj Kumar

Journal of Computer-Aided Molecular Design (2023)

Arbuscular mycorrhizal fungi and production of secondary metabolites in medicinal plants

• YanYan Zhao
• Annalisa Cartabia
• Stéphane Declerck

Mycorrhiza (2022)

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

• Skip to main content

Achieve a Master's Degree In Drug Development & Product Management

Giving You New Career Opportunities and Advancement

The Application Period for the 2024 Cohort Is Now Open!

Deadline: july 17, 2024.

Apply Today

Average salary for life science employees in the U.S.

Skaggs School of Pharmacy ranking in the U.S.

Alumni that have reported career advancement since 2019

Ranked Top 5 in U.S.

Skaggs School of Pharmacy Was Ranked Among Top 5 Nationally for NIH Awards in 2022

Next Online Information Session

Join us for a live, 1-hour session to learn more about the program:

Thursday, May 30, 2024 12:00 pm PST

Register Today

Why Wait? Advance Your Career

Do you have a scientific, pharmaceutical, biotech, medical, business management, or legal background? Are you looking for career opportunities and advancement? You have found it.

Is this degree right for you?

Achieving a Master of Science in Drug Development and Product Management gives you the specialized skill set required for careers and advancement in the pharmaceutical, biotech, and other life science industries. This program is designed for working professionals who want to build new skills and advance their careers.

From Coursework to Career

Graduates who choose clinical positions in the pharmaceutical and biotechnology industries can expect to provide clinical support and scientific input to multi-functional drug product teams. They may also be involved with study design, protocol concepts, preparation, statistical analysis plans, and reporting.

Marketing professionals in the pharmaceutical and biotechnology industries contribute to the strategic direction and execution of brand strategies and are responsible for brand-level development including market analysis, strategic planning, and brand management. These individuals might also manage marketing materials to establish product branding and messaging, develop and implement product education, publication, and other promotional activities to communicate product positioning and lifecycle development of products to customers. 

Business Development

Individuals who work in business development are responsible for creating strategic plans to enter and expand new business opportunities. Business development strategies include prospecting, prioritizing opportunities, evaluating, conducting diligence, transacting and implementing business and collaboration opportunities. They maintain contacts and relationships related to external opportunities consistent with their company's strategies and goals for portfolio management.

Regulatory Science

Regulatory science professionals are responsible for various activities related to regulatory affairs, including the preparation and submission of regulatory documents, correspondence with regulatory agencies, tracking, filing, and writing regulatory standard operating procedures. They will also provide regulatory support to cross-functional teams.

Entrepreneurship

Those who plan on being entrepreneurs who have identified an unmet medical need in the life science industry will learn how to create a business plan and raise capital. Entrepreneurs are excited by the challenges that come with starting new companies.

Marketing professionals in the pharmaceutical and biotechnology industries contribute to the strategic direction and execution of brand strategies and are responsible for brand-level development including market analysis, strategic planning, and brand management. These individuals might also manage marketing materials to establish product branding and messaging, develop and implement product education, publication, and other promotional activities to communicate product positioning and lifecycle development of products to customers.

A Master's Degree Designed for Working Professionals

Evening Classes for Busy Professionals

Complete Your Degree in 3 Quarters

Learn from UCSD Faculty and Industry Professionals

Since the DDPM program is highly related to the pharmaceutical industry, all the knowledge I learned from the courses is beneficial on the job search. Read more

- Bobbi Hsieh , Clinical Trial Manager

These courses connected science to industry and business, which greatly interested me. Read more

- Maria Jarama Ruiz , Product Manager

I appreciated the small class sizes because it helped me to make meaningful connections with my professors, guest lecturers and classmates. Read more

- Chelsea Friedman , Graduate Research Assistant

Featured Events

Next online information session:, there are currently no upcoming events, please sign up for our mailing list to get updates, privacy overview.

Dawn Lam Marketing Manager CTK Biotech Class of 2019

Why did you choose to attend the Master in Drug Development and Product Management (DDPM)?

I was attracted to the Master in DDPM for its comprehensive drug development and commercialization curriculum. I used to work for a pharma company but only knew a small part of drug development; therefore, I wanted to learn and understand the whole process. My other goal was to explore different career paths in the biotech/pharma industry, and I knew this program would provide me with that opportunity.

What skills and proficiencies did you gain from this program and how did it benefit your career?

The marketing and entrepreneurship/IP courses allowed me to apply the knowledge on the job immediately. I used the course materials to prep for my job interviews and received great feedback on my experience in this area. The group projects taught me to be collaborative, innovative, and adaptive, which is essential for a managerial position.

Can you describe networking experiences that were initiated by the program?

The networking opportunities that I got from the program were valuable. I got the chance to meet a VP of my previous company during one of the lectures. I connected with him in person, and he offered to create an internship for me and be my mentor.

What did you like best about the program?

I thoroughly enjoyed every aspect of the program. The knowledge I gained was the most current information, which made me a competitive candidate in the workforce. In addition to the coursework, the guest lecturers and professors are experts and well connected in their fields, making the new program more credible.

If you could give an incoming DDPM student one piece of advice, what would it be?

I would suggest getting involved with professional organizations to expand your network. If you are looking for a new job or transition into a new field, it is best to be proactive and reach out to your academic and professional network to let them know your career goals.

Jeremy Ballack Senior Manager, Commercial Operations bluebird bio, Inc. Class of 2020

After spending ~7yrs in Regulatory and Marketing roles within Pharma post-undergrad, I recognized a gap in my insight of the medical function. I wanted to be exposed to clinical trial design, manufacturing and pharmacology. To gain this, I needed to work towards a goal I’d been neglecting in fear for some time, returning to school.

The DDPM program was thoughtfully crafted for working professionals who yearn to pursue something greater in their careers, in their lives even. I applied because I trusted that UCSD’s Skaggs School of Pharmacy professors would be best equipped to elevate a new breed of continuing students, even if their academic background was not initially in the sciences. As a humanities undergrad with some pharmaceutical work experience, I believed the posted DDPM curriculum was specific enough to glean worthwhile, practical learnings. So, I pursued this cohort wholeheartedly. And then, it changed my life.

Time management, relationship building, navigating group project dynamic, aural and oral presentation skills. Recognizing that it takes an empathetic village with a shared goal to accomplish anything, no matter the task, is a reassuring lesson in accepting that none of us are ever truly alone. These ‘soft skills’ are profound in the work setting, helping us all to connect with the human side of corporate work, so often deeply robotic and capitalist in foundation.

I do not recall attending any networking events, if offered, other than briefly meeting guest lecturers post-class. I default to other alum’s answers to this question, as I don’t have a substantive perspective or recollection.

My peers. The international student cohort brought a wealth of perspective and personality to the classroom every week. Our group chats were helpful to keep track of class responsibilities throughout each semester. The acquaintanceships, both personal and professional, made during the quick 1.5yr program are my fondest gifts.

Believe in your capability and capacity. Know you belong everywhere and anywhere, even when you feel darkest. Be proactive with planning your work schedule. Speak up for yourself, because healthy boundaries are important. & Keep pushing!

Amanda Vogel Sr. Associate, Biomarker Operational Specialist Pfizer Inc Class of 2021

Why did you choose to attend the Master in Drug Development and Product Management (DDPM) Program?

Before the program, the majority of my experience and knowledge was limited to diagnostic laboratory work. I had just transitioned into a project management position at a Pharmaceutical company and I felt that I needed to expand my knowledge of the pharma world. I was excited when I discovered this program and saw that I would have the opportunity to learn about drug development, clinical trials and product marketing. I decided to attend this graduate program not only to help me excel in my current position but to also help myself in advancing my career.

Not only did this program help me understand the bigger picture of my new position at work but it also opened my eyes to potential avenues along my career path. In addition, I gained insight on business plans, financial statements, and how to interpret clinical trial protocols and ICER reports.

The program introduced us to experts in different areas of the pharmaceutical world which allowed us to ask questions and gain knowledge of career paths we may not have known about before.

I appreciated that it was a more intimate class size in comparison to undergraduate classes. I also really liked the broad range of topics that we learned about from PK/PD, reverse engineering a drug, regulatory agencies, marketing and entrepreneurship .

You get what you put into it. Make sure you take advantage of the wealth of knowledge and experience that all the professors have and ask questions.

Keira Kim Medical Writing Manager Jazz Pharmaceuticals Class of 2022

I had been working as a medical writer in pharma for 10+ years and wanted to expand my knowledge and opportunities. I was confident in the UCSD faculty and their network of industry professionals to help me attain my goals of increasing my knowledge of the development, management, and commercialization of new drugs and increasing my perspective of key stakeholders, especially upper management.

The greatest gains were in presentation skills, interpersonal communication, and strategic thinking. Learning how to think and plan strategically has helped me grow as a leader and has changed my approach to project management resulting in greater successes. My increased understanding of drug development/commercialization and growth in strategic perspective combined with my medical writing/management skills will be beneficial when working with and leading cross-functional teams.

Can you describe networking experiences that were initiated by the program? All the professors and guest speakers provided their contact info and invited us to reach out to them with any questions, which is a tremendous resource. I also greatly appreciated the career guidance provided by my mentor and the support of my classmates.

The mastery of the professors combined with the varied professional experiences of the students and their willingness to share created a rich learning environment.

Be proactive by coordinating with your team early and asking your professors for clarity or guidance when needed; school is the safest place to learn, not work.

Chelsea Friedman Graduate Research Assistant UT Austin – DiGiovanni Lab Class of 2019

Tell us a little bit about the work that you are currently doing.

I’m a first year Translational Science PhD student working in the DiGiovanni lab. My dissertation project has not been fully decided yet, but I’m really interested in personalized medicine and my research will revolve around elucidating the mechanisms of cancer and seeing how modulating the underlying pathways impacts disease state.

Why did you decide to get this MAS degree?

I had been working in the biotech/pharma industry for a few years and knew I wanted to continue my education. My undergraduate degree was in Molecular & Cell Biology and I thought it would be beneficial to get a Master’s degree in a slightly different discipline. I was intrigued by the objectives and curriculum of the program and thought it could open up new opportunities for me. The fact that this program was designed for students who were working full time so I didn’t have to put my career on pause was definitely a factor in my decision to apply.

I appreciated the small class sizes because it helped me to make meaningful connections with my professors, guest lecturers and classmates. My cohort had a very diverse group of students with different professional backgrounds and it was really interesting to hear their perspectives on various issues. Working in the pharmaceutical industry while attending this program was an added bonus because it gave me the opportunity to see the concepts taught in class be applied in a real world setting.

What skills are you using that you learned in the program?

Project management skills, interpersonal skills, risk management… the list goes on! I’ve honestly drawn upon something I learned from every course while I was still working in industry.

How did you (or do you plan to) leverage the program to further your career?

While I was attending this program I was working at a small pharmaceutical company that was starting a phase 2 clinical trial. Because of this program, I was offered the role of the unblinded representative for a phase 2 clinical trial they were initiating. I impressed them enough on that trial to be offered the role again for a clinical trial investigating a potential treatment for COVID-19. Now I have some clinical trial management experience under my belt, which could open up other opportunities for me in the future. Through this program, I gained valuable insight into the complexities of drug development, FDA regulations and post marketing challenges and I can’t wait to finish my PhD and get back into industry to put it all to good use!

What would you like to tell someone who is considering the program?

Take advantage of all that this program has to offer! You get out what you put in, and time management is a key piece in being successful in this program. It’s hard work but it’s totally worth it!

Bobbi Hsieh Associate Clinical Trial Manager Fate Therapeutics Class of 2020

My responsibilities are to oversee clinical trial operations, including site management, initiation and qualification, patient recruitment, the timeline of the study, etc. My job’s primary goal is to ensure that clinical trials can be implemented smoothly and successfully at different clinical sites. With that, high-quality data must be collected and used to support new drug approval.

Why did you decide to get this M.S. degree?

Previously, I didn’t have any work experience in the U.S. industry. DDPM is an efficient one-year program that would give me a comprehensive understanding of the pharmaceutical industry and the drug development process in the U.S. In addition, I was interested in the business side of the industry, which is a large part of the DDPM curriculum.

There are many guest lecturers from pharma and biotech companies that provided us with professional insights and practical knowledge. That knowledge is what the industry needs. Also, the case studies and the questions from the business class are superb. They really gave me a chance to think about the industry from different perspectives.

I appreciate that I learned the concept of clinical trial design and about FDA regulations. They were extremely helpful for me in understanding the rationale of trial design and clinical strategy, which are very important when collaborating and communicating with different departments. In addition, the program improves your presentation skills by requiring more than 20 presentations throughout the year, which I found to be very useful.

How did you leverage the program to get a new job?

Since the DDPM program is highly related to the biopharmaceutical industry, all the knowledge I gained from the courses was beneficial on the job search. Students are given a general understanding of the role of different departments, which is very helpful in interviews. In addition, some of the faculty are DDPM career mentors, and their advice is truly useful. The guest lecturers are also open to providing insight and expanding your professional network.

If you are interested in the pharmaceutical industry and would like to have a big picture of the whole process of drug development, from research to commercialization, DDPM is an amazing program for you to explore.

María Jarama Ruiz Assistant Product Manager CTK Biotech Class of 2020

Tell us a little bit about the work that you are currently doing. 

In my current role, I maintain and track databases, design projects, and manage engineering change requests. I also acquire standards, clinical specimens, and competitor products, and generate experiment protocols, data analysis, and reports.

Why did you decide to get this MAS degree? 

I applied to the master’s degree because of the courses it had. These courses connected science to industry and business, which greatly interested me. I also decided to do the MS because of the job opportunities that are made available to students. I have an undergraduate degree in biotechnology, so I knew I could have applied to biotech companies before getting this degree. However, I wasn’t sure if a pharmaceutical company would hire me without understanding the drug development process, so I entered the degree seeking to expand my knowledge. Thanks to this master’s degree, I was able to move away from the bench and obtain a position as a Product Manager.

I liked how much I learned in the marketing course. It opened my mind. I never thought I was going to like marketing, and it turned out to be my favorite course and the direction in which I would like to take my career in the future. While doing the case studies, I noticed how much I learned after doing 2 or 3. I rapidly noticed how my writing skills improved. I also learned that it is important to say what you think even though you may not know if that is the correct answer. I also liked the idea of creating my startup, which I hopeI can do one day.

What skills are you using that you learned in the program? 

Project management, product management, communication skills, organization skills, time management, working in a cultural environment, hard work.

How did you leverage the program to get a new job? 

Thanks to the help UCSD provided, my resume changed from something that was overlooked to a resume that got me a lot of interviews and eventually a job.

  What would you like to tell someone who is considering the program?

I would say that with hard work and motivation, anything is possible. It can be stressful and time consuming, but once you are done with it, the knowledge and the experience you get with the master is worth it. Something important to take from the master’s is that it prepares you to break into the industry. When they told me to read their SOPs during my first day of work, I realized that if it hadn’t been for the master’s degree, I wouldn’t have been able to understand half of what they had on it. Furthermore, with the master’s, you get used to being on the spot almost every week. The presentations prepare you to speak in front of people, which happens every day at work. Overall, I really recommend this master’s degree.

Cecilia Tran Project Manager Argonaut Manufacturing Services Class of 2019

I provide overall program management at a strategic and tactical level to 15-plus diagnostic, life science, medical device, and drug product companies.  Among these programs, 7 of them are COVID-19 products.

Why did you decide to get this MS degree?   

I decided to get this degree for my professional development. My undergrad was a BA in International Studies. I was pre-med, but that didn’t translate into the job offers that I was looking for. I wanted to further develop my career in the biotech/pharma world, but I needed to equip myself with more knowledge and an official MS stamp to “validate” my background and core competencies on paper.

What did you like best about the program?  

There were so many amazing things about this program. The interaction and learning from industry leaders was incredibly interesting and useful. The real-world case studies also helped us better understand the complexities of drug development. The professors from the School of Pharmacy were very effective in teaching us the pharmacology behind drug products. Overall, the degree has a very well-rounded curriculum that prepares you for all aspects of the industry.

What skills are you using that you learned in the program?  

Project management, time management, a comprehensive product life cycle management, and most importantly, people/team management.

How did you leverage the program to further your career?  

I added highlights of my class projects and learning points to all my cover letters. Depending on the job description, I highlighted key aspects of what I had learned. I made sure to advertise those key points during phone interviews and in-person interviews. Most hiring managers I interviewed with were impressed and expressed interest in the program.

What would you like to tell someone who is considering the program?  

I love that the program is tailored for working professionals who want to further develop their career in product management. I love that I got to learn real-world case studies from leading professionals of the industry and learn from some of the best professors at a world-class institution. Last but not least, the best thing was learning from my fellow classmates who came from all different areas of the industry. This network that I formed is truly amazing; not just for my professional growth, but for my personal growth as well.

Gaia Canevari Commercial Haematology Graduate Bristol Myers Squibb Class of 2020

This role is a 2-year graduate programme that focuses on the commercial aspects of the pharmaceutical industry. I will be working on market research, market access, business planning and analytics, building and implementing marketing plans and strategy. It is in the Haematology business unit, and I will have the chance to work on the launch of several drugs.

This master’s degree was the perfect integration of my scientific background (having an undergraduate degree in biochemistry) and the commercial part of product management that I was keen to explore. My ambition is to be a successful product manager in a big multinational pharmaceutical company and this master’s degree has been the perfect opportunity to give me the basis to start my career in this field. The courses looked very appealing and everything I had hoped to learn, and even more, was included in the syllabus.

What did you like best about the program? 

I loved the fact that the programme is built in such a way to get the bigger picture of the entire drug development process. It includes all the steps from the early research and discovery to the commercialisation, post-launch and declining phases of a product. On top of the scientific and more technical contents of the entire process, I really liked the fact that the programme also involves the regulatory, pharmacoeconomic, marketing, business and law aspects (and others!) of the industry. This gave me a very solid view of the drug development process and all of its important features.

We were often asked to work in teams during the programme, which is something I enjoyed a lot as the cohort was very diverse with everyone having a unique background. I learned a lot from my classmates, and I know that working in a team is one of the strongest skills I can have for my career.

The programme gave me all the features that this new role was asking for. During the interviews, I spoke a lot about the course content, especially about the Marketing and Pharmacoeconomics courses, as well as the Business Development and the Clinical Trials courses. They were impressed by how comprehensive the programme was, and I felt confident in talking about more technical and deeper details with them.

What would you like to tell someone who is considering the program? 

I would definitely recommend this programme. The faculty is great, and you will get a lot of external lecturers who give you many opportunities to network. UCSD is one of the top institutions of the world, and the programme will leave you with great knowledge and a way of thinking that will 100% be essential for your career.

• Skip to main content
• Skip to FDA Search
• Skip to in this section menu
• Skip to footer links

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you're on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

U.S. Food and Drug Administration

•   Search
•   Menu
• Science & Research
• Science and Research Special Topics
• Advancing Regulatory Science

CERSI Collaborative Research Projects

The CERSIs conduct cutting-edge regulatory science research with high public health impact aimed at development of new tools, standards, and approaches to assess the safety, efficacy, quality and performance of FDA-regulated products. Many of these research projects are conducted in collaboration with FDA.

The CERSIs promote innovation in regulatory science predominantly through cutting-edge scientific research that supports FDA's regulatory science needs. They may also provide regulatory science information sharing opportunities, such as lectures, workshops, courses, scholar awards, fellowships, and competitions. We aim for the collaborative activities to target one or more of the focus areas in the Regulatory Science Framework .

CERSI Collaborative Research Projects Filters

Clear Filters

A shortcut for drug discovery

Novel method predicts on a large scale how small molecules interact with proteins.

For most human proteins, there are no small molecules known to bind them chemically (so called "ligands"). Ligands frequently represent important starting points for drug development but this knowledge gap critically hampers the development of novel medicines. Researchers at CeMM, in a collaboration with Pfizer, have now leveraged and scaled a method to measure the binding activity of hundreds of small molecules against thousands of human proteins. This large-scale study revealed tens of thousands of ligand-protein interactions that can now be explored for the development of chemical tools and therapeutics. Moreover, powered by machine learning and artificial intelligence, it allows unbiased predictions of how small molecules interact with all proteins present in living human cells. These groundbreaking results have been published in the journal Science , and all generated data and models are freely available for the scientific community.

The majority of all drugs are small molecules that influence the activity of proteins. These small molecules -- if well understood -- are also invaluable tools to characterize the behavior of proteins and to do basic biological research. Given these essential roles, it is surprising that for more than 80 percent of all proteins, no small-molecule binders have been identified so far. This hinders the development of novel drugs and therapeutic strategies, but likewise prevents novel biological insights into health and disease.

To close this gap, researchers at CeMM in collaboration with Pfizer have expanded and scaled an experimental platform that enables them to measure how hundreds of small molecules with various chemical structures interact with all expressed proteins in living cells. This yielded a rich catalog of tens of thousands of ligand-protein interactions than can now be further optimized to represent starting points for further therapeutic development. In their study, the team led by CeMM PI Georg Winter has exemplified this by developing small-molecule binders of cellular transporters, components of the cellular degradation machinery and to understudied proteins involved in cellular signal transduction. Moreover, taking advantage of the large dataset, machine learning and artificial intelligence models were developed that can predict how additional small molecules interact with proteins expressed in living human cells.

"We were amazed to see how artificial intelligence and machine learning can elevate our understanding of small-molecule behavior in human cells. We hope that our catalog of small molecule-protein interactions and the associated artificial intelligence models can now provide a shortcut in drug discovery approaches," says Georg Winter. To maximize the potential impact and usefulness for the scientific community, all data and models are made freely available through a web application. "This was an outstanding partnership between industry and academia. We are delighted to present the results which were obtained through three years of close collaboration and teamwork between the groups. It's been a great project," says Dr Patrick Verhoest, Vice President and Head of Medicine Design at Pfizer.

• Lung Cancer
• Human Biology
• Pharmacology
• Organic Chemistry
• Nature of Water
• Biochemistry
• Protein microarray
• Protein structure

Story Source:

Materials provided by CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences . Note: Content may be edited for style and length.

Journal Reference :

• Fabian Offensperger, Gary Tin, Miquel Duran-Frigola, Elisa Hahn, Sarah Dobner, Christopher W. am Ende, Joseph W. Strohbach, Andrea Rukavina, Vincenth Brennsteiner, Kevin Ogilvie, Nara Marella, Katharina Kladnik, Rodolfo Ciuffa, Jaimeen D. Majmudar, S. Denise Field, Ariel Bensimon, Luca Ferrari, Evandro Ferrada, Amanda Ng, Zhechun Zhang, Gianluca Degliesposti, Andras Boeszoermenyi, Sascha Martens, Robert Stanton, André C. Müller, J. Thomas Hannich, David Hepworth, Giulio Superti-Furga, Stefan Kubicek, Monica Schenone, Georg E. Winter. Large-scale chemoproteomics expedites ligand discovery and predicts ligand behavior in cells . Science , 2024; 384 (6694) DOI: 10.1126/science.adk5864

Cite This Page :

Explore More

• Emergence of Animals: Magnetic Field Collapse
• Ice Shelves Crack from Weight of Meltwater Lakes
• Countries' Plans to Remove CO2 Not Enough
• Toward Robots With Human-Level Touch Sensitivity
• 'Doubling' in Origin of Cancer Cells
• New Catalyst for Using Captured Carbon
• Random Robots Are More Reliable
• Significant Discovery in Teleportation Research
• Orangutan Treats Wound With Pain-Relieving Plant
• 75,000-Year-Old Neanderthal from Burial Cave

Trending Topics

Strange & offbeat.

AI-Driven Drug Discovery by Pfizer and Austrian Institute Set to Transform Healthcare

P fizer, the top pharmaceutical firm, and the Research Center for Molecular Medicine of the Austrian Academy of Sciences (CeMM) have developed an AI-driven drug discovery method The novel approach, which was a result of the ground-breaking effort, can potentially escalate the period during which the active substance with the therapeutic potential is identified, the most prominent progress being accomplished in the field of pharmaceutical research.

AI-Powered Drug Discovery Unveiled

in The Science Journal, through a team of CeMM researchers, an AI machine-learning platform was designed to display the binding preferences of hundreds of small molecules to thousands of diverse human proteins. This innovative platform creates rich data on a small molecule–protein interactions to maintain the database, which presents a key starting point in expediting drug research.

There is a gap in drug development information about how small molecules interact with human proteins. This relationship has not been widely researched. Although small molecules are one key component of drug development, only a minute part of human proteins, also known as ligands, make it therapeutically and scientifically difficult to advance innovation and fundamental understanding.

Unprecedented Scale and Impact

The scientists adopted a chemical proteomics strategy by using about 407 different small molecule fragment ligands to target areas of human proteins. By employing this approach, they managed to detect almost 47.7K precise protein-ligand interactions, which pertain to 2,600 various proteins. Interestingly, almost 90% of the forming proteins have no known ligands, which is surely a great merit of the joint work.

This study has academic meaning and larger implications for translating into the treatment of protein targets with the synthesis of ligand analogs. Moreover, big data has been instrumental in creating computer learning structures that can predict the behavior of small molecules in biological systems. This has greatly benefited scientific research.

Open access and collaborative endeavors

Central to the ethos of this collaboration is the commitment to open science. All models and data generated through this endeavor are freely available to researchers worldwide, fostering collaboration and driving collective progress in drug discovery. Scientists can access and explore the wealth of information generated by CeMM and Pfizer through a user-friendly web application, empowering further innovation and discovery.

The collaboration between Pfizer and CeMM represents a paradigm shift in drug discovery. It harnesses the power of AI and machine learning to accelerate the identification of potential therapeutics. This pioneering research promises to revolutionize the pharmaceutical industry and advance human health by bridging the gap in understanding small molecule-protein interactions.

As the pharmaceutical landscape evolves, collaborations between industry leaders and academic institutions will play an increasingly pivotal role in driving innovation and addressing unmet medical needs. The groundbreaking research unveiled by Pfizer and CeMM underscores the transformative potential of such partnerships, setting the stage for a new drug discovery and development era.

By leveraging cutting-edge technologies and fostering a culture of openness and collaboration, the path toward novel therapeutics becomes not just conceivable but achievable. With the tools and insights provided by this collaboration, the scientific community stands poised to unlock new frontiers in medicine and improve the lives of millions worldwide.

News sourced from Science

Together we are beating cancer

About cancer

Cancer types

• Breast cancer
• Bowel cancer
• Lung cancer
• Prostate cancer

Cancers in general

• Clinical trials

Causes of cancer

Coping with cancer

• Managing symptoms and side effects
• Mental health and cancer
• Money and travel
• Death and dying
• Cancer Chat forum

Health Professionals

• Cancer Statistics
• Cancer Screening
• Learning and Support
• NICE suspected cancer referral guidelines

Get involved

• Make a donation

By cancer type

• Leave a legacy gift
• Donate in Memory

Find an event

• Race for Life
• Charity runs
• Charity walks
• Search events
• Relay For Life
• Volunteer in our shops
• Help at an event
• Help us raise money
• Campaign for us

Do your own fundraising

• Fundraising ideas
• Get a fundraising pack
• Return fundraising money
• Fundraise by cancer type
• Set up a Cancer Research UK Giving Page
• Find a shop or superstore
• Become a partner
• Cancer Research UK for Children & Young People
• Our We Are campaign

Our research

• Brain tumours
• Skin cancer
• All cancer types

By cancer topic

• New treatments
• Cancer biology
• Cancer drugs
• All cancer subjects
• All locations

By Researcher

• Professor Duncan Baird
• Professor Fran Balkwill
• Professor Andrew Biankin
• See all researchers
• Our achievements timeline
• Our research strategy
• Involving animals in research

Funding for researchers

Research opportunities

• For discovery researchers
• For clinical researchers
• For population researchers
• In drug discovery & development
• In early detection & diagnosis
• For students & postdocs

Our funding schemes

• Career Development Fellowship
• Discovery Programme Awards
• Clinical Trial Award
• Biology to Prevention Award
• View all schemes and deadlines

Applying for funding

• Start your application online
• How to make a successful application
• Funding committees
• Successful applicant case studies

How we deliver research

• Our research infrastructure
• Events and conferences
• Our research partnerships
• Facts & figures about our funding
• Develop your research career
• Recently funded awards
• Manage your research grant
• Notify us of new publications

Find a shop

• Volunteer in a shop
• Donate goods to a shop
• Our superstores

Shop online

• Wedding favours
• Cancer Care
• Flower Shop

Our eBay store

• Shoes and boots
• Bags and purses
• We beat cancer
• We fundraise
• We develop policy
• Our global role

Our organisation

• Our strategy
• Our Trustees
• CEO and Executive Board
• How we spend your money
• Early careers

Cancer news

• Cancer News
• For Researchers
• For Supporters
• Press office
• Publications
• Update your contact preferences

ABOUT CANCER

GET INVOLVED

NEWS & RESOURCES

FUNDING & RESEARCH

You are here

Drug Development Project

About this scheme, how to apply to this scheme, key information.

We consider applicants that:

• Have a novel cancer agent needing preclinical and/or clinical development
• Have supporting in vivo efficacy data
• Are based at a UK academic institution or;
• Are a pharmaceutical or biotech company (UK or international)
• Have already been in touch with our Centre for Drug Development  to discuss the suitability of their proposal

All technology areas are considered, including small molecule, biological and other therapeutics.

Examples of eligible projects include those requiring:

• Preclinical development, including biomarkers, assays, and formulation development prior to a phase 1 trial
• Phase 1 trials, including phase 1a and 1b, first-in-human and first-in-class
• Combinations of unregistered and registered agents
• Early phase 2 proof of principle trials
• Studies on unlicensed agents in active commercial development that are off the company’s critical path or repurposed novel agents

Drug Development Projects are not external grant funding awards. Approved projects are sponsored and managed by our Centre for Drug Development (CDD) , and a project team is allocated to work in partnership with you.

The CDD manage the project for as long as necessary to support preclinical and early clinical development of the novel agent. This includes:

• Managed preclinical and clinical development
• Management of regulatory documents and communication with relevant authorities throughout the trial
• Protocol design and trial management
• Oversight of trial safety and clinical data
• Treatment of patients in a UK-wide network of clinical centres with world-leading scientific investigators and expertise in early clinical trials

New Agents Committee

Before making your application

• You must discuss the suitability of your proposal with the Centre for Drug Development
• Please email [email protected]

Overview of the application process

Applications follow a two-stage process:

• Confidential, informal discussions with the Centre for Drug Development to establish eligibility and suitability
• Formal application and review by the New Agents Committee

Confidential discussion

Email us to request a discussion. If required, we will set up a Confidential Disclosure Agreement to protect your data.

Please include a short project outline. For us to conduct an internal review to determine suitability under this scheme, we typically require the following information (if available):

• Project background and stage of development
• Agent manufacture information and physicochemical properties
• Target and scientific rationale, including mechanism of action
• In vitro and in vivo data including efficacy, toxicology and PK/PD
• Data or hypothesis-driven rationale for proof of mechanism biomarker and proof of principle/efficacy biomarker
• Summary of preclinical or clinical studies proposed
• The criteria that would constitute a successful study
• IP position
• Next steps in development
• Agent’s USP or competitive advantage over other similar agents in development

Key considerations we look for in projects at this stage include:

• Strength of scientific rationale
• Adequacy of preclinical data package
• Potential application in patients

We will provide feedback on your proposal and advise if it is ready for a formal application and review.

Formal applications

• You must submit a data package through our online Grants Management System .
• New Agents Committee: you will be invited to attend the meeting or join online to give a brief overview and address any questions from Committee members. The Committee will consider your application.
• You will receive the NAC's decision and feedback within 4 weeks.

All NAC proposals and panel meetings are confidential.

Start your application

Cancer Research UK contact details