Pharmacogenomics and the Brave New World of Personalized Medicine

FDA’s recent guidance on pharmacogenomics reduces manufacturers’ risks in evaluating genomic data. Will it spur development of more targeted therapies?

By Angelo De Palma, Ph.D., Contributing Editor

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Last December, the era of personalized medicine inched closer to reality when the U.S. Food and Drug Administration (FDA) approved Nitromed’s (Lexington, Mass.) Bidil, a combination therapy designed to treat heart failure in African Americans. This segment of the patient population doesn’t typically respond well to the angiotensin-converting enzyme (ACE) inhibitors that are usually prescribed to treat this condition.

Bidil’s approval has stimulated more discussion, and debate, about personalized medicine. Although some drug manufacturers may have mixed feelings about developing targeted drugs with small markets, those in favor of personalized medicine say that it will reduce the billions of dollars lost each year to adverse drug events — lost income and production, as well as higher disability and health care costs.

“Personalized medicine will not result in treating fewer patients,” says Felix Frueh, Ph.D., associate director for genomics at FDA’s Center for Drug Evaluation and Research (CDER; Bethesda, Md.). “If you take all costs into consideration — not just sales, but the cost of treating patients unnecessarily, or patients who suffer serious adverse events, the economics work out,” he says. He calls fears of fractionating existing drug markets “absurd,” chiding doomsayers for accepting a system that “treats” patients but provides no benefit.

“Adverse drug events are costly, Frueh points out. According to the Center for Education and Research on Therapeutics, adverse drug events cost the U.S. economy $136 billion per year. “Preventing just a small percentage of this loss will make a big improvement in healthcare economics.” (For more statistics, visit

Genomics may not have played a part in Bidil’s development, but it promises to drive the personalized therapies of the future. The idea: to treat disease based on the identification of biomarkers associated with the likelihood of a drug’s efficacy or potential toxicity.

Genotype vs. phenotype

The notion of treating groups of patients with the same overt disease is based on the now-recognized differences between genotype and phenotype. A century ago, “consumption” was considered a disease, but we now recognize it as comprising more than twenty distinct ailments (genotypes). Similarly today, it may be tempting to speak of “cancer” or “schizophrenia” as single diseases when they are merely “phenotypes” — overt physical manifestations — of what may be many different underlying diseases.

Pharmacogenomics, or the study of how a patient’s genetic makeup affects responses to drugs, is the sine qua non of personalized medicine. It is only in the last few years — thanks to whole-genome sequencing and rapid gene characterization — that practical pharmacogenomics has been possible. As recently as 1998, Hoechst (now Aventis) was forced to withdraw Seldane, an allergy drug with $600 million annual sales, due to serious cardiotoxicity in less than 0.5% of potential patients. These patients carried a genetic defect, which, in the presence of co-therapy with erythromycin, blocked Seldane metabolism.

Today, a simple genetic test might identify patients at risk for this serious drug interaction. Whether insurance companies would view such a test as cost-effective, a critical factor in the success of personalized treatments, is another story. It is likely that some reasonably significant fraction of the roughly 90% of drugs that fail in clinical testing might be approved, if only for small patient populations, if an appropriate genetic test were available to predict safety and efficacy.

That is exactly what happened when, around the same time as the Seldane incident, Genentech (South San Francisco, Calif.) noted that its breast cancer drug Herceptin only worked in one-fourth of patients — those whose tumors over-expressed the HER2 gene. Herceptin went on to become the poster child for personalized medicine and the model for rescuing failed compounds. GlaxoSmithKline (London) has followed Genentech’s lead by linking its Ziagen HIV treatment with a pharmacogenomic test that identifies the 5% or so of patients at risk for a severe hypersensitivity reaction to the drug. GSK also co-markets a test for an enzyme defect alongside its Purineetho pediatric leukemia drug to spot the one in 300 children at risk for drug-induced bone marrow toxicity.

End of the blockbuster?

Some observers believe that personalized medicine will end the blockbuster drug model as we know it. According to this reasoning, pharmacogenomic tests that uncover non-responders or those at risk for serious side effects can only cause potential patient populations to shrink. This “glass half-empty” argument ignores the dynamism of the pharmaceutical marketplace, where dozens — sometimes hundreds—of drugs compete in the major therapeutic categories. Leading products vie not only on glitz and marketing, but on the basis of clinical experience.

It’s commonly thought that drugs are effective in anywhere from 20% to 80% of those who take them. The typical hypertensive patient tries several medications before settling on one that works. In essence, this patient and his or her physician have performed a type of experiment, which, in most cases, reaches the same conclusion as a putative pharmacogenomic test.

Pharmacogenomic assays have the potential to eliminate much of the uncertainty and serendipity inherent in prescribing medications. There will, of course, be winners and losers. Pharmacogenomics will undoubtedly uncover a few patients who will not respond to any drug at all, a situation that is certain to engage medical ethicists. But the likelihood of important drug markets shrinking is almost nonexistent.

Getting the right medications into the right bodies is not only good medicine, it’s good business, says Brian Spear, Ph.D., director of genomic and proteomic technology at Abbott Laboratories (Abbott Park, Ill.). “The opportunities for developing drugs that work for non-responders are tremendous,” he believes. Spear debunks the notion that personalized medicine will fractionate drug markets by identifying non-responders to whom certain drugs should not be prescribed. Instead, he views the marketing opportunities as a more-than-half-full glass. He points out that, especially for competitive indications like cardiovascular and oncology, market shares are small but patient numbers are huge.

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