A Revolution in R&D

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36 Given these technological limitations, we estimate that less than 15 percent of drugs will be amenable to the application of pharmacogenetics. Desirability—Market Economics As already mentioned, there are circumstances in which a company might have an incentive to shun pharmacogenetics entirely. After all, by excluding patients from trials, you are in effect giving the drug a restricted label when trying to market it. Gauging the likely effect of a restricted label involves some complex analysis. For a start, you need to consider two distinct groups of patients: those who take a prescription for the full course of treatment (which could last many years, or even the remaining lifetime for those suffering from chronic diseases), and those who embark on a prescription but then discontinue it for reasons of inefficacy or side effects. The pharmacogenetics test would shrink these two potential patient groups in different ways. From the former, it would eliminate the “placebo responders.” From the latter, it would eliminate some of the nonresponders and negative responders. Market fragmentation has happened in many industries—the marketing group can’t put their heads in the sand. We have to figure out what to do about pharmacogenetics. —Genetics director, leading biotech company Since pharmacogenetics seems to be chipping away at a drug’s market base, why pursue it in the first place? The answer may lie, in part, in competitive dynamics and game theory: companies may have to embrace pharmacogenetics because their competitors are doing so. Merck & Co., for example, according to a recent Wall Street Journal article, is busy developing capabilities to reproduce pharmacogenetic analyses conducted by its competitors, if only to disprove any claims that a rival drug might be superior to its own. But the compensatory advantages can be more positive, too—the potential for market upside, once again: price premium, share shift, and new patients. What a company has to judge, before adopting pharmacogenetics for any drug in development, is the likely breakeven point—the point at which a price premium or increased market share begins to offset the volume loss. Our model assumes a modest market premium of 20 percent, and calculates the breakeven point in various scenarios, based on four different approaches to pharmacogenetics. (See sidebar, “Pharmacogenetics—Four Applications,” and Exhibit 10.) Efficacy-based pharmacogenetics can reduce trial costs considerably. But the market dynamics could then cast a cloud over that economic picture. If the restricted label, by disqualifying placebo responders and some nonresponders and negative responders, translates into an overall revenue loss of just 2 percent, that cancels out the savings achieved in the clinical trials. EXHIBIT 10 PHARMACOGENETICS’ VALUE DEPENDS ON MARKET DYNAMICS Patients lacking good response (%) 1 100 80 60 40 20 0 Conduct normal trials Abandon drug 100 SOURCES: Industry interviews; BCG analysis. Pharmacogenetics can optimize clinical trials 200 Pharmacogenetics trials make drug viable 300 Revenue increase required from market premium (%) 1Example based on a scenario in Nature Biotechnology, vol. 18, May 2000 of ApoE4 efficacy in tacrine response; assumes response rate of 41 percent among patients with the SNP versus 20 percent among those without it; also assumes 50 percent of nonresponders discontinue.
PHARMACOGENETICS—FOUR APPLICATIONS To evaluate pharmacogenetics properly, companies need to take an especially close look at the market dynamics. These dynamics vary according to how pharmacogenetics is used. We have identified four such applications (each associated with a different category of patient responding to a given drug). The first three are used to exclude patients from trials; the fourth is used to expand the potential market for the drug. First, efficacy prediction identifies patients who will show no real or significant response to the drug— perhaps because they metabolize the drug in an unusual way, or have an unusual form or combination of susceptibility genes. A typical drug produces this negligible response in about a third of patients, but sometimes the proportion is far higher. For example, Cognex (tacrine), the first drug for Alzheimer’s, is inefficacious in more than 50 percent of patients. The varying response is associated with differing versions of the ApoE gene, and is therefore readily predictable by a pharmacogenetic test. Second, common-side-effect prediction identifies patients likely to experience familiar side effects, as a result of metabolic difficulties caused by wellknown enzymes. A test can screen out negative responders—“slow acetylators,” for instance. The acetylation polymorphism in the NAT2 gene is one of the commonest genetic variations in drug metabolism; it has the effect of reducing the enzyme’s lifespan and thus reducing the effective amount of the enzyme in cells at any one time. This polymorphism is present in more than 50 percent of Caucasians, who are thus at greater risk of drug toxicity. Knowledge of this polymorphism could save a drug in clinical trials that would otherwise be abandoned. Third, very-rare-side-effect prediction identifies patients at risk for unconventional side effects, but comes into play only after the drug is on the market. Unlike most of the common side effects, which are associated with metabolic pathways and usually emerge in preclinical studies, these rare side effects tend to be provoked by nonmetabolic genes, and to be overlooked at first. They cannot easily be predicted, since there are too many possible sources (modifications of the target or of the disease pathway, or unrelated pathways), and they may occur too rarely to show up in clinical trials. A case in point is Lotronex, a drug for irritable bowel syndrome, now withdrawn from the market. Only after its market launch, and 450,000 prescriptions, did its severe side effect (bowel impaction) become apparent. About one in 6,500 patients was affected—a frequency far too rare for a standard clinical trial to detect beforehand. (A typical trial involves about 5,000 patients: for this side effect to have been manifest in a statistically significant way, a trial of nearly 100,000 patients would have been needed.) Pharmacogenetics could in certain cases come to the rescue of such compromised drugs, by belatedly devising a screening test. Finally, market expansion identifies patients who are currently unsuited to the drug but potentially responsive to it. Since fine-tuning of dosages or formulation can often reduce side effects and occasionally improve efficacy, pharmacogenetics could reassess and upgrade many of the supposedly ineligible patients. The market for the drug might expand considerably as a result. Take the case of cyclophosphamide, a chemotherapy drug, which works only when metabolized by the enzymes CYP3A4 and CYP3A5. Some patients appear underresponsive to it: a genetic variation suppresses the activity of the enzymes, thereby decreasing the amount of active drug in the bloodstream. The best course is not to discontinue the drug, but to compensate by taking a higher dosage. A pharmacogenetic test could identify the appropriate patients prior to treatment, and their consumption of the drug, instead of declining to zero, would actually increase. 37
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 34 and 35: 32 duce targets high in quality but
Page 36 and 37: 34 would be excluded from the trial
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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