A Revolution in R&D

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32 duce targets high in quality but low in quantity, perhaps just one to five for an average disease. That would produce at best a 25–30 percent chance of yielding a drug, given that chemistry and development remain far from fail-safe. For disease genetics to live up to its promise, it will need to improve those odds considerably. And to do that, it will have to call on a supplementary technique: pathway analysis. Disease-susceptibility genes, if identified through disease genetics, serve not only as targets themselves, but also as guides to additional targets. The genes form part of broader disease pathways, and these pathways contain other molecules that may serve as targets (perhaps 10 to 15 targets per pathway, according to experts). These new targets are identified by pathway analysis, often taking the form of the study of “simple” experimental systems, such as those of Drosophila melanogaster or C. elegans (a.k.a. fruitflies and worms). When studied in the laboratory, these systems disclose the genetic components of a given pathway. (Other approaches to pathway analysis include expression profiling of tissue samples and studies of protein-protein interaction.) Implementing pathway analysis will result in a lower cost per drug on average: it improves efficiency. Costs are reduced because pathway studies are relatively inexpensive and fewer human-derived targets are required—pathway analysis expands the pool of potential targets tenfold or more. As targets, they prove to be of high quality, moreover (in keeping with the disease-susceptibility gene that inspired their discovery), achieving good success rates in clinical trials. For although they themselves are not yet validated in humans or clearly implicated in the disease, they participate in a pathway that is. So pathway analysis should give human studies the requisite boost, with enough targets emerging to yield a drug more often than not. On the down side, there are the time and cost of additional animal research and the loss of some advantages in clinical trials. Adding pathway analysis, via genetic studies of Drosophila melanogaster, to indirect genome-wide association studies would result in a total savings of $425 million for each drug on average, regardless of the original human study approach, though it would add nearly two years of additional work (producing an additional $255 million of value per drug). The first one to do genetic studies takes a huge risk. If it works, you’ll see everyone running to join the crowd. —R&D executive, leading pharmaceutical company Implementing Disease Genetics The savings promised by disease genetics are enormous, and companies cannot ignore them. But they cannot ignore the risks either, and will need to exercise rigorous selectivity and discipline when it comes to pursuing specific disease genetics studies—which approaches to adopt, for instance, and which diseases to explore. Placing bets in this way is going to be nerve-racking enough. But companies face another difficult set of choices as well, in the various operational issues that need to be addressed. Placing Bets Some diseases have clear appeal as objects of genetic research: asthma, Alzheimer’s disease, and diabetes, for example, being complex diseases that afflict large populations and obviously contain heritable factors. They have already become competitive areas of study. Although opinion is still divided over the likely impact of disease genetics, substantial bets are being placed by various companies— emerging biotechs and established pharmaceutical companies alike. A few claim they are already seeing benefits from their investments: following its alliance with Roche, deCODE genetics claims to have succeeded in identifying a gene contributing to cerebrovascular disease; GlaxoSmithKline has announced finding genes associated with migraine, Type II diabetes, and psoriasis; and Genset, a French biotech company, is reported to have identified genes implicated in prostate cancer and schizophrenia. But all companies embarked on, or intent on, pursuing disease genetics must acknowledge that it is
still a scientifically risky endeavor. As they construct their customized portfolio of bets, they will have to keep reviewing not just their internal capabilities but also the degree of risk they are prepared to accept. Putting Disease Genetics into Operation If companies do opt to participate in disease genetics, they may still choose to maintain some distance by outsourcing the activity or licensing in the results. Those that decide to launch a major disease genetics program in-house will confront a number of significant challenges as they put the program into operation. Take the problem of obtaining the required samples, for instance. From whom should samples be collected? And how are samples to be stored? The use of human tissue raises ethical considerations as well. What constitutes consent? How can privacy be protected? Who “owns” the tissue material? And who should profit from it? (Several companies, such as Genomics Collaborative and the not-forprofit First Genetic Trust, are emerging to address these conundrums.) And, of course, there are major organizational questions. What are the implications for human resources and labor relations? For big pharmaceutical companies, new capabilities will be demanded, and new skills will have to be acquired—statistical geneticists, for instance, and experts on pathway genetic studies. And other capabilities may suddenly be less in demand—perhaps even obsolete. We will discuss implementation issues such as these in more detail in the final chapter of this report. Pharmacogenetics Just as some genetic variations among individuals may influence their susceptibility to diseases, so others may influence their responsiveness to drug treatments for those diseases. It is the goal of pharmacogenetics to seek out and characterize some of these latter variations. The savings that pharmaceutical companies might hope to harvest are considerable, though nothing like as high as those that disease genetics stands to achieve in ideal circumstances. The Potential The impact of pharmacogenetics on R&D productivity will derive from the increased flexibility it introduces into clinical development. Currently, drug-development policy is dominated by a binary scenario in its later stages: either shepherd a compound through its clinical trials and out to market, or abandon it as unmarketable if it stumbles in the trials. Pharmacogenetics provides a more nuanced scenario, with an expanded range of possible outcomes, by allowing the exclusion of patients genetically predisposed to respond poorly to the drug. Two particular benefits emerge: “standard” clinical trials can now be streamlined; and “failing” compounds can now be salvaged. (See Exhibit 7.) The streamlining of trials would apply only to compounds destined to proceed successfully through the clinical trial process anyway. That path can now be made smoother. The trials can be designed more subtly. They can be smaller and quicker than before, now that it is possible to preselect promising patients—that is, patients whose genetic makeup is likely to maximize the drug’s efficacy and minimize its side effects. So, patients lacking the drug-susceptible variation of the target gene EXHIBIT 7 PHARMACOGENETICS EXPANDS DEVELOPMENT CHOICES Proportion of patients showing poor or no response High Low SOURCE: BCG analysis. Current options Abandon drug before market Continue clinical trials to market Options available with pharmacogenetics Continue trials safely by excluding at-risk patients Optimize clinical trials, making them smaller and shorter 33
Page 1 and 2: A Revolution in R&D HOW GENOMICS AN
Page 3 and 4: A Revolution in R&D HOW GENOMICS AN
Page 5 and 6: Table of Contents ABOUT THE AUTHORS
Page 7 and 8: Foreword To meet growth targets, ph
Page 9 and 10: cogenetics). The productivity gains
Page 11: Introduction Throughout the pharmac
Page 14 and 15: 12 The Opportunities What is the im
Page 16 and 17: 14 and generally helping to optimiz
Page 18 and 19: 16 Cellomics are well positioned to
Page 20 and 21: 18 trials, if the company were able
Page 22 and 23: 20 almost to that of more familiar
Page 24 and 25: 22 UPSTART START-UPS—THE COMPETIT
Page 26 and 27: 24 Chapter 2: The Impact of Genetic
Page 28 and 29: 26 genetics-based form of pharmacog
Page 30 and 31: 28 DISEASE GENETICS—VARIOUS APPRO
Page 32 and 33: 30 Efficiency improvements in targe
Page 36 and 37: 34 would be excluded from the trial
Page 38 and 39: 36 Given these technological limita
Page 40 and 41: 38 Side-effect-based pharmacogeneti
Page 42 and 43: 40 moves, along with the relative s
Page 44 and 45: 42 POTENTIAL SAVINGS—FROM THEORET
Page 46 and 47: 44 ogy—to discover new drugs. Bro
Page 48 and 49: 46 INDUSTRY CHANGES The genomics la
Page 50 and 51: 48 Selecting Technologies According
Page 52 and 53: 50 tions, interfaces, and so on. Th
Page 54 and 55: 52 CASE STUDY: REDISCOVERING DISCOV
Page 56 and 57: 54 other—often literally—on col
Page 58 and 59: 56 The formidable operational and o
Page 61 and 62: Methodology The many diverse studie
Page 63 and 64: The Boston Consulting Group publish

A Revolution in R&D

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