is it time to revisit the current r&d model?

Int J Pharm Med 2007; 21 (5): 339-345CURRENT OPINION 1364-9027/07/0005-0339/$44.95/0

© 2007 Adis Data Information BV. All rights reserved.

Is it Time to Revisit the Current R&D Model?Damian O’Connell, Andrew Hopkins and David Roblin

Pfizer Global Research & Development, Sandwich Laboratories, Sandwich, England

The private biomedical research industry has brought significant benefits to patients and has been a majorAbstractfactor in the transformation of the course and treatment of disease over the past half century. It is estimated thatover 90% of the medicines in use today have been discovered or developed by the industry. Successful medicinesbring revenues to the companies who research and develop them through long-term at-risk investment; theensuing returns through medicine sales are a key element in sustaining a virtuous circle in the traditional drugresearch and development (R&D) model. However, late-stage attrition, along with increasing development costs,are now challenging companies and the current R&D model. As a consequence, biopharmaceutical companiesare under ever increasing pressure to develop new R&D models.

This article describes the current status of large pharma R&D and how it goes about developing new drugs. Itanalyses some of the current key industry strategic trends and themes that may govern whether the currentbusiness model succeeds and continues to be the engine house of delivery for new medicines for society, orwhether key changes are required to maximise R&D efficiency and to deliver regulatory approvable andmedically required new drugs.

Private biomedical research companies have been responsible whether the traditional model is still sustainable, and will besustainable for the next 50 years.for the development of at least 90% of the drugs we use today. The

Over the last decade, global R&D investment in the pharma-industry is one built on balancing risk; however, in an industryceutical and biotechnology sector has steadily increased but, at thewhere failure is more likely than success and the average researchsame time, fewer medicines have been successfully approved.and development (R&D) cycle is around 10 years, one can appre-Several factors have been cited as contributing to this productivityciate that, although high revenues are at stake, this long-term at-decline; these include not just regulatory and scientific factors, butrisk investment is not for the faint-hearted. Without a doubt, thealso environmental and organisational factors too (see table I).traditional drug development R&D model (illustrated in figure 1)Addressing these challenges by looking at alternative R&D mod-has been an enormous success for patients, clinicians, govern-els is needed, not only to maintain the long-term viability of anments and, of course, many pharmaceutical companies and theirindustry that contributes to job creation and economic growth but,shareholders. However, given recent challenges, it is unclearmore importantly, to ensure that researchers can continue to dis-cover and develop medicines to meet the patients’ and societies’needs. This challenge has been recognised and does not go unan-swered. Companies have merged or been acquired, alliances arecommon where risk can be shared and, increasingly, in the searchfor enhanced productivity, new R&D paradigms are being trialledas companies move away from conventional R&D processes andorganisational structures. The industry’s primary response to theproductivity crisis has been to boost R&D investment, with theaim of sustaining organic growth, and increase merger and acqui-sitions activity. This has allowed companies to exploit economiesof scale and, importantly, to build larger R&D drug portfolios

Discover and develop medicines

that make a difference to patients

Invest the money in discovering and developing drugs

Make money by being good at running

the business

Patients or payers pay for the medicines

because of the value they bring

Fig. 1. The traditional drug development research and development model.

340 O’Connell et al.

rate of introduction of new chemical entities to the pharmaceuticalmarket is currently lower than at any time since World War II.[1]

While new drug discovery techniques such as computer-aideddrug design, combinatorial chemistry and high throughput screen-ing have led to a few successes, to a large extent, massive invest-ment from most companies has failed to generate a single usefullead.[2] One senior executive has expressed the view that the newtechniques may be generating bigger haystacks as opposed tomore needles.[3] The largest companies are not generating enoughnovel drugs to sustain them, a fact that has driven the recent spateof mergers. Along with this, the costs per successful new moleculehave rocketed. Recent historical studies by Healey[4] clearly showthat the delay between chemical synthesis and successful market-ing was much shorter in the 1950s and 1960s than the mostoptimistic timescales predicted at present.

The current decline in productivity in the output of pharmaceu-tical research has resulted in a questioning of some of the basicassumptions that have ruled drug discovery for over two de-cades.[5] For the past 20 years the dominant paradigm in drugdiscovery has been the genetic reductionism of ‘one drug-onetarget’. The modus operandi of the genetic reductionist approachto drug discovery has been a focus on the discovery of singledisease genes, which are then isolated as recombinant proteins andsubjected to high-throughput screening against massive librariesof synthetic compounds. Significant investment has been made intarget identification and target validation before any screening orchemical leads are identified. The genetic reduction approach hasproved most successful in diseases where there is a strong correla-tion with a monogenetic change. For example, the protective effect

Table I. Key factors implicated in declining research and development(R&D) productivity

Environmental

High-profile failures postmarketing

Attrition in late stage trials

Continued reliance by a majority of major pharmaceutical companies onblockbuster drugs with the accompanying corporate view thatblockbusters are ‘made’ – not ‘discovered’

Reimbursement and cost pressures

Increasing encroachment by generics

Regulatory

Increasing pressure to better predict and assess product safety

Increasing compliance and postmarketing scrutiny

Scientific

Evolving scientific tools and methods increasing number of putative drugtargets requiring more proficient target validation

Failure across the industry to capture scientific learning effectively

Science not consistently driving decision making in the R&D process

Unacceptable record of current predictive modelling, and commonly usedendpoints in discovery and clinical studies

Increasing molecule complexity creating challenges relative to theoptimal formulation

Organisational

Expensive, lengthy and risky drug development process

Rigid phased decision-making

R&D activities being ‘black boxes’ to management, who assumethroughput and productivity cannot be measured or predicted with anydegree of accuracy

Talent not deployed effectively

Declining job satisfaction of the functionally inactive CCR5Δ32 mutation against HIV-1 M-tropic infection[6] led to the discovery of the anti-HIV CCR5

through mergers and acquisitions. However, the fact that produc- antagonist, maraviroc.[7] The discovery of imatinib is anothertivity continues to decline after a decade of growth in company successful example of where an understanding of the role of thesizes and R&D investment demonstrates the shortcomings of a mutate BCR-ABL kinase in chronic myeloid leukaemia led tostrategy that seeks size for the sake of size alone and indeed such development of an efficacious drug.[8]

‘diseconomies’ of scale are now leading to such ‘corrective’ trends Despite these successes, critics have identified several difficul-as the downsizing of sales workforces, off-shoring and outsourc- ties with the genetic reductionist approach to drug discovery,ing. where it has been argued that the dominance of the paradigm may

This article describes the current status of large pharmaceutical have contributed to decline in productivity of pharmaceuticalR&D and analyses some of the key strategic trends and themes research over the past decade.[9,10] The first difficulty with thethat will, over the next 5 years, govern whether this business biological-driven approach to target validation has been the highmodel succeeds and continues to be the engine house of delivery attrition rate due to the lack of drug-like chemical matter for manyfor new medicines for society. targets with good biological rationale, despite intensive screening

efforts by many companies. The observation that many screeningcampaigns against many targets failed to translate into discovery1. Drug Discoverychemical matter has lead to the a priori assessment of the potential

Novel medicines can derive from either developing new chemi- to discover a drug against the target.[11] The ‘druggability’ conceptcal entities or discovering new indications for known drugs. The argues that the inherent physico-chemical-topology properties of a

© 2007 Adis Data Information BV. All rights reserved. Int J Pharm Med 2007; 21 (5)

Revisiting the Current R&D Model 341

binding site on a biological target determine the complementary tant therapeutic strategy, systematic approaches to the identifica-physico-chemical properties of its ligands.[12] Large-scale analysis tion of novel drug combinations have been proposed.[23] Thirdly,of protein structure binding sites and proteins with known drug- the advent of large-scale, integrated chemogenomics knowledgelike ligands has revealed a small proportion of proteins expressed bases enable the systematic search across integrated structureby the human genome that are likely to bind to drug-like com- activity data for compounds that are observed or predicted to bindpounds.[13] The predicted scarcity of druggable targets has been to multiple targets.[16,24,25]

illustrated by the high failure rate of many biological-driven drug Advances in our understanding are providing insight into drugdiscovery projects.[14]

discovery leading to an increasing number of strategic options inTo improve the chance of successful drug discovery, chemoge- the search for new medicines. No doubt a significant amount of

nomics has emerged as a chemocentric approach to genomics that investment has been required by industry and academia to under-emphasises a focus on targets and gene families where there is a stand how to operate in the information-rich post-genomics worldhigher probability for finding chemical leads.[15] The large-scale but progress, both scientific and strategic, is now being made.integration of historical pharmacology screening is enabling the However, the challenge of predicting clinical efficacy from labora-comprehensive identification of biologically active chemical tory models is still one of the greatest bottlenecks in drug discov-space as a rich source of knowledge for lead discovery.[16]

ery.The second challenge to the single gene paradigm of drug

discovery has arisen from the emerging appreciation of the robust-2. Traditional Drug Development Modelsness of biological systems.[17] For many of the complex diseases

with multiple aetiologies, it is unlikely that there is a single geneticThe use of traditional sequential phases of drug development iscause. The increasing number of failures of phase II compounds in

changing. In a model where success can be predicted, it makesrecent years due to a lack of efficacy may be a result of moresense for companies to invest at risk beyond a projects keyselective, single target compounds entering the clinic.[18] Large-decision point in order that progression is unimpeded and revenuescale gene knock-out studies in mice and several other modelfrom sales returned early and patent in-market are extended. In theorganisms have revealed that biological systems are robust topost-genomic world where target opportunities abound and wheremany single gene deletions, with surprisingly few genes seen towe are faced with the challenge of showing ever clearer differenti-have a dramatic effect on phenotype.[19] Biological systems oftenation between new compounds and existing medicines, the phar-have alternative compensatory signalling routes to bypass themaceutical industry has moved to explore biological mechanismsinhibition of individual nodes, which often result in robust pheno-that are incompletely understood and where failure or attrition,types.particularly in phase II trials, is more common than success (figureNetwork biology predicts that modulating multiple proteins2).simultaneously is often required to modify robust phenotypes.[20]

Systematic experiments with dual knock-outs in yeast have shown Clinical development decisions centre on one pivotal question:that, while the deletion of two genes in isolation may show no what shall we invest and where shall we invest it? The accuracy ofeffect, the simultaneous deletion of two genes can lead to ‘synthet- these decisions bears directly on the success of new treatments foric lethality’.[21] The combination of gene-deletion observations of disease and the resultant return on investment (ROI) made by thephenotypic robustness and network biology theory indicate that in company. To maximise ROI, it is necessary to channel resourcesseveral instances exquisitely selective compounds may exhibit a into the rapid development and registration of candidate drugslower than desired efficacy for the treatment of disease. Thus, with the best potential for success. This means that there has to becompounds that selectively act on two or more targets of interest an incentive to terminate ineffective drugs and targets early.could increase the confidence-in-rationale or range of efficacy. Furthermore, we have to provide a disincentive to make incorrect

‘go’ decisions; these decisions can be identified by failure of theIn order to perturb a biological network rather that an individualcompound later in the development cycle and may be a moretarget (node), several new strategies are emerging. First, chemicalaccurate performance measure at each stage of the developmentbiologists have re-introduced the use of cell-based screening ofprocess than the current benchmarking system. Hence, the per-compounds that perturb phenotype rather than individual recombi-formance of preclinical decision-makers could be measured not bynant targets.[22] Secondly, combination therapies, the use of two orthe number of compounds they pass to clinical pharmacology, butmore agents to improve efficacy, has risen in importance in severalby the percentage of those compounds that fail in phase I and/orareas of medicine and fits well with the new network paradigm ofphase IIa trials.drug discovery. In recognition of drug combinations as an impor-



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(a) (b)

Fig. 2. Phase II survival rates from the (a) KMR Group[26] and (b) CMR International.[27]

A further rationale for this phase II focus is that animal models with the resultant decrease in clinical trial size and, thus, a moreof efficacy typically do not translate well to patient outcomes with rapid patient accrual and increasingly efficient data collection.the result that, increasingly, phase II studies have become large Meanwhile, the effective and increased use of translationaland long with consequent operational complexity and expense. In medicine and biomarker approaches is seeing success. There iscontrast, safety-related phase II failures have decreased signifi- evidence of proof-of-pharmacology driving critical ‘go/no-go’cantly and, by and large, compounds do not fail in phase II for decisions in drug development.[28]

commercial reasons. This leads to the inescapable reality for Such a strategy also leads to smaller initial patient trials withpharmaceutical companies that it is all about demonstrating une- limited patient numbers (e.g. 10–20 patients per dose, small place-quivocal efficacy earlier and more efficiently in patients; hence, bo arms) analogous to phase I. Initial patient studies can employmore and more companies are now adapting a ‘fast-to-patient’ conventional and/or biomarker endpoints and include elements ofstrategy to the majority of projects as a response (table II). crossover designs, dose escalation and research formulations. This

has a consequent reduction in costs and is usually significantly3. Clinical Trial Designs faster than conventional phase II paradigms.

Therefore, with this increasing focus on phase II studies it is notCompanies are realising that in this scenario it is more prudentsurprising that industry attention to experimental/translationalto invest to a key decision-point only, and only invest further ifmedicine has markedly increased over the last few years. Centralsuccessful. Consequently, we see the more frequent dovetailing ofto the pursuit of a translational medicine strategy in early drugphase I and proof-of-concept stages of drug development by usingdevelopment is the mantra that every first phase II trial must be aBayesian adaptive trial designs. This approach focuses early on avalid test of the drug target. To achieve this aim, it is fundamentalprobabilistic rather than a deterministic approach in clinical trials

Table II. Themes emerging as pharma research and development (R&D) imperatives

Strategic imperative Tactical response

Build earlier and improved human medical Get to patients as soon as feasibleinsights Consider (where appropriate) novel material sparing paradigms for early decision making

(microdosing, eIND)

Translational medicine for target selection/validation, insightful exploratory development trials anddecision criteria

Pharmacodynamic biomarkers to reduce clinical pharmacology risk; better efficacy biomarkers/models

Increase confidence in decisions

Match investment with risk to avoid high Building in earlier optimisation in an effort to reduce late-stage attritioncosts of attrition Development strategies that match investment to risk profiles

Increase productivity through improved phase II survival

Speed up learning Increase speed of development; faster validation

Project learnings and experiences better used for decision making

Reduce activity and infrastructural costs; outsourcing or off-shoring noncritical activities

eIND = exploratory investigational new drug application.



Monitoredrelease

Sequential, phased, 'go/no-go' decision making

Compoundfocus

Sciencefocus

Discovery Phase I

ConfirmLearn

Fullrelease

Confirmingtrials

In humanIn vitro

In vitro

Proof-of-Concept

a

b

Phase II Phase III LaunchPostmarketingsurveillance

Postmarketingsurveillance

Pharmaceutical development

Fig. 3. Comparison of the (a) current and (b) ‘learn and confirm’ paradigms of drug discovery and development.

that drug developers understand the required level of pharmaco- of-concept and the intelligent use of biomarkers throughout thelogical activity from preclinical work and can translate this activi- process. Integral to this type of development paradigm is thety to humans as a go/no go decision criteria for proof-of-mecha- requirement to greatly increase the biological evidence around anynism (POM); that is, the compound safely expresses adequate project and to look more closely at how individual differencespharmacology in phase I. Only if POM is achieved should the next affect response to drugs.studies in phase II commence. These phase II studies and their

In the ‘learn’ phase, the predominant emphasis is to dramatical-results speak to the validity of the drug target and enable data-

ly increase the amount of learning about the science/moleculardriven programme decisions, which can predict late phase success.

basis of diseases, and technologies for their interdiction. TheDose selection remains one of the major determinants of the ‘learn’ phase runs from basic research through to proof-of-concept

efficiency of the overall drug development process, impacting – with an incremental increase in the knowledge (‘learning’) aboutcommercial success through its implications on pricing and other

a given target/disease using a subset of the human population, in aproduct factors such as safety and efficacy. Repeating a large

controlled environment. Any particular team can be working si-phase II dose-response study can take a year or longer, and can

multaneously on thousands of compounds and dozens of therapeu-easily cost $US5–15 million. However, this cost is dwarfed by the

tic targets throughout the learn phase (figure 3).opportunity cost of 6 months or more of lost exclusivity for an

In the ‘confirm’ phase the focus of development activities is toultimately successful compound. Selection of the best dose or doseconfirm understanding of the science by rapidly testing a productrange results in the optimal therapeutic ratio and, hence, the best(or a select few products) that have been shown to have a potential-efficacy and safety profile possible for the candidate compound.

Often, the difference between a ‘best-in-class’ and a ‘me-too’ ly successful profile in a broader human population (e.g. includingprofile can hinge on a small safety or efficacy advantage observed provisional filings). The ‘confirm’ phase runs from proof-of-at optimal doses, which may disappear if doses that are too high or concept through to postmarketing surveillance to confirm thetoo low are employed. science on human populations living in the real world. Trials are

designed with the view that dozens of targets based on the sameA number of companies (e.g. Novartis, Wyeth) have shifted toscience are in the ‘learn’ phase, and trial design must confirm thethe ‘learn and confirm’ model of drug discovery and developmentunderlying sciences, as well as prove the safety and efficacy of the(figure 3). This new model puts an emphasis on investment

strategy up to phase II stage with particular focus on early proof- tested compound(s).



New adaptive trial designs with frequent futility testing and re- clinical trials currently fail to meet their recruitment deadlines.[30]

sample sizing are increasingly driving down development costs For this reason improved patient recruitment presents one of theand providing clearer results largest opportunities to eliminate delays in clinical trials, thereby

making it possible to reduce the time to market. Corporate4. External Collaborations processes must be realigned to enable the best access to patients

and prospective participants, as well as utilising them in subse-Competition drives the pharmaceutical industry and its success. quent trials. Such processes should leverage standardisation to

However, there is increasing agreement that companies can do drive and expedite the entire development process, from the devel-more in a pre-competitive manner, both between themselves but opment of clinical trial protocols to the development of clinicalalso with regulators, clinicians, academics and other stakeholders. data presentations. The move towards outsourcing of operationsThis concept is now well recognised across the world in consorti- and the additional flexibility this provides is a key ingredient toum activity such as the National Institutes of Health (NIH) Bi- creating a nimble and adaptive company.omarker Consortium, the Pharmaceutical Research and Manufac-

The culture of organisations is also key. Pharma is a highlyturers of America (PhRMA) Biomarker Consortium, Genetic

regulated industry; some would argue the most regulated industry.Association Information Network, European Framework Pro-

In addition, as companies have grown there has been a drive togramme 6 Projects AddNeuroMed & PredTox as well as with the

make cost savings through standardisation. With both these pres-roll out in the US and Europe of the Critical Path and Innovative

sures comes an inexorable production of processes. Yet every drugMedicines Initiatives, respectively.[29]

development team has different challenges and one team’s ‘bestThese collaborations allow bottlenecks in R&D to be tackled practice’ process can become obsolete within months and be a

where information is held across the stakeholder group, the risk of hindrance for another team with different problems. As the milita-investing in a solution is too great for one company, or a solution is ry have learnt and other industry’s practice processes should beenabling to all stakeholders operating in a given area. These can replaced by specifications of success and suitably qualified exper-range from biomarkers of disease to epidemiological databases, ienced personnel (SQEPs) as operators. Knowing what successwhich give a thorough understanding of disease, disease progres- looks like means SQEPs can do what is right in moving potentialsion and its modification by therapy. This information allows new medicines through the complicated R&D process’ in a timelyrationale trial design; the refinement of populations and endpoints and economic manner.[31]

to allow clinical trials to more often give clear unequivocal results.Increasingly, the approval of new medicines by regulators does 6. Conclusion

not mean access to new medicines for patients. Health technologyassessment agencies (HTA) are becoming increasingly prevalent Pharma faces many challenges, it has an awareness of theseworldwide. Through the 1990s the industry and regulatory agen- challenges and in it has a richness of resources in an improvingcies spent time learning how to work together to allow a facile understanding of disease processes and the technologies at hand toassessment of benefit-risk based on a regulatory dossier. The be successful. We await clear signs of an improvement in produc-challenge now is to engender a discourse with HTA to help ensure tivity. There is unlikely to be a single approach that will bethat sufficient evidence is created that the HTA can use to make successful for all companies/issues, each problem is unique andaccess decisions for their patients. Industry and HTA need to has its own solution. This is an important lesson for industry toengage in an early understanding of what such information might learn.be and to allow this to be designed into the clinical programme asearly as possible. No one, especially the patient, benefits from an Acknowledgementsimpasse at the access stage.

The authors are all employees of Pfizer Inc. and own stock options in thecompany. The views in this article are the personal views of the authors and5. Operational Issuesshould not be construed as those of Pfizer.

No sources of funding were used to assist in the preparation of this review.Operational issues also play an important role in drug R&D.For example, patient recruitment consumes 27% of the cost ofdevelopment, which amounts to an annual figure of $US5.9 billion References

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is it time to revisit the current r&d model?

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