- The Washington Times - Sunday, August 23, 2009


Two drug companies that jointly market a prominent cancer drug recently changed the labeling to discourage the drug’s use in colon-cancer patients who have certain gene mutations, following clinical studies that showed the drug is not effective in those patients.

This represents a significant improvement in cancer chemotherapy, both because the drug itself, Erbitux, is expensive — costing $8,000 to $10,000 a month — and because patients can be offered effective alternative therapy without losing time trying and abandoning ineffective treatments.

This is the wave of the future in medicine. Drug therapy for a variety of conditions has begun to shift from a one-size-fits-all approach to a more personalized one. Patients are matched to the best drug for their genetic makeup or the exact subcategory of their disease, better enabling doctors to avoid prescribing a drug (or wrong dosage) that might cause serious side effects in certain populations. In other words, even among patients who apparently have the same disease and symptoms, the treatment for each one would be determined by various predictive or prognostic tests.

Paradoxically, this approach could be a boon to patients but detrimental to drug companies’ bottom line.

Personalized drug therapy uses biological indicators, or “biomarkers,” to suggest how patients should be treated and to estimate the likelihood the intervention will be effective. This concept is not new. It has been known for decades that people genetically deficient in an enzyme called glucose-6-phosphate dehydrogenase (G6PD) can experience a severe and precipitous anemia if they consume fava beans or are exposed to certain drugs.

Similarly, various ethnic groups and individuals have widely varying abilities to clear drugs from the bloodstream because of differences in the levels and effectiveness of the enzymes that metabolize, or degrade, drugs. This is important because low metabolizers clear certain drugs slowly and have higher blood concentrations for longer periods than high metabolizers; thus, the former might be prone to overdose and the latter to insufficient levels of the drug. The phenomenon is known to occur with various drug classes, including psychotropic drugs and blood thinners.

Prognostic biomarkers already are making a difference in cancer therapy, as in the Erbitux example above. Because the drug works only against tumors containing the normal version of a gene called KRAS, if mutations of KRAS are present, Erbitux is ineffective. Such mutations explain about 30 percent to 40 percent of cases in which patients fail to respond to Erbitux and a similar drug, Vectibix, and a recent study suggests that mutations in another gene, called BRAF, could account for another 12 percent. This information will reduce sharply the number of cancer patients who are subjected unnecessarily to the side effects (and expense) of drugs that won’t work.

Improving the efficacy and reducing the side effects of drug therapy will be a boon to doctors, patients and insurance companies, to be sure, but because of other forces that pull in opposite directions, the benefits to drug companies will be less certain.

The presence of biomarkers will enable drug companies to perform smaller, better-targeted clinical studies to demonstrate efficacy. The reason is related to the “statistical power” of clinical studies: In any kind of experiment, a fundamental principle is that the greater the number of subjects or iterations, the more reliable the conclusions. In a clinical trial that compares two interventions — say, a drug versus a placebo — the likelihood of a cure or response (or side effect) is expressed as a range that represents a so-called margin of error, such as 20 percent to 50 percent. The larger the sample size, the smaller the margin of error and the greater the confidence in the results of the study. Small studies generally have large uncertainties in results unless the effect of the intervention is profound. That is where biomarkers come in: They can help design clinical studies that will show a high relative treatment difference between the drug and whatever it is being compared to — often a placebo, but sometimes another treatment.

The other side of the coin is that when drugs ultimately are approved under these circumstances, the indications (uses) in the labeling may be more restricted — that is, more narrowly circumscribed — which would reduce the size of the patient population for whom the drug is intended.

For example, a drug broadly approved for arthritis — joint inflammation that may be caused by dozens of different disease processes — likely would be more widely marketed than one approved to treat only the arthritis that accompanies psoriasis or gout.

In reality, however, the situation is more complex than just these two opposing influences. Even if smaller, better-targeted clinical trials offer clear evidence of efficacy, escalating risk-aversion at the Federal Drug Administration will cause regulators to demand far larger studies to provide safety data.

Increasingly defensive about accusations that drugs and vaccines are inadequately tested for safety, safety-obsessed regulators in recent years have required massive, hugely expensive and time-consuming clinical trials designed to detect even very rare side effects.

A vaccine against rotavirus (a common, sometimes fatal gastrointestinal infection in children) was tested in more than 72,000 children (and another 40,000-plus in post-marketing studies) and a vaccine to prevent human papilloma infection and cervical cancer was tested in almost 30,000 young women. The size of these trials is absurd.

Thus, the short-term impact of personalized medicine might be positive at the patient’s bedside, but vast clinical trials to demonstrate the safety of new drugs will impose huge development costs that may never be recovered by the manufacturers. Historically, only about 3 in 10 approved drugs recoup their development costs.

This dichotomy augurs poorly for the next generation of drugs needed by an aging population — and for the health of America’s pharmaceutical industry. If society at large is to derive maximum benefit from personalized medicine, regulators will need to adopt more reasoned and reasonable policies.

Henry I. Miller, a physician and fellow at the Stanford University’s Hoover Institution and the Competitive Enterprise Institute, was an official at the Food and Drug Administration from 1979 to 1994. He is the author of “To America’s Health: A Proposal to Reform the FDA.”



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