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December 29, 2010

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Genome research will lead to the right drug in right dose for patient

BACK in June 2000, when the draft human-genome sequence was announced, US President Bill Clinton proclaimed, "It will revolutionize the diagnosis, prevention, and treatment of most, if not all, human diseases."

A decade later, hope has given way to disappointment, reflected in headlines like "Gene Map Yields Few New Cures."

But pessimism about the potential of human-genome research to yield medical breakthroughs has arisen from unrealistic expectations. Indeed, while "silver bullets" that can cure our most feared diseases have not been found, progress in the area of gene-drug interactions, known as pharmacogenomics, has been extraordinary.

The ability to determine the principal genes that account for our variable response to prescription drugs has been advanced by a technique known as a genome-wide association study (GWAS).

The whole human genome has approximately six billion bases, but a window into its composition can be probed using approximately one million bases (0.01 percent of the genome) via a gene chip. The bases on the chip are selected because they are informative, tagging bins of the genome, like a post-code directory.

Using GWAS methodology, we have learned the biological basis for responses to many drugs - both their effectiveness and important side-effects.

Optimism

Examples of this progress in the past couple of years are plentiful, and include the statins, Plavix, interferon, warfarin, and the antibiotic flucloxacillin. The main side-effect of statins, which lower cholesterol in the blood, is severe muscle inflammation, and it can now be predicted with a simple genotype test, as can the response to Plavix, the second most commonly prescribed drug after statins.

Interferon, given for one year to patients with hepatitis C virus, costs around US$50,000 and makes all patients feel ill, but the drug works in only half the people treated. Genotype testing can determine if it will work for a patient and if not, then what other drug will be effective.

The list goes on.

To be sure, our predictive ability is far from complete. We know only common gene variants from the GWAS approach and most drugs have not even been studied yet, so there is a long way to go. Nevertheless, substantive and remarkable progress has been made, all in the last few years.

This has paved the way for next-generation pharmacies. Genotyping can now be accomplished in 20 minutes, and over time will get even faster.

To fill a prescription for a drug with a known pharmacogenomic profile, a customer can get rapid genotyping to determine appropriate dose, drug, or predilection for serious side-effects. Or even better, many people will submit a saliva sample to a consumer genomics company, which will analyze all of their pharmacogenomic data and perform an extensive panel of genotypes, updated every month, and store the data on their smart phones. For mail-order prescriptions, such genomic data would be a routine part of the customer database.

Misconceptions

In the United States, pharmacy benefit managers (PBM) handle prescriptions for almost all large employers and account for more than 200 million individuals. Two of the largest PBMs, Medco and CVS/Caremark, have announced plans to conduct large-scale genotyping for many drugs.

With US annual prescription drug expenditures totaling US$300 billion, there is certainly room to cut costs.

Unfortunately, the medical community is resisting the use of pharmacogenomic data in clinical practice, despite regulatory authorities' recommendations for many drugs.

The ultimate goal of pharmacogenomics is to provide the right drug, at the right dose, for the right individual, without any significant side-effects. Despite widespread misperceptions about the practical impact of genomic research, the science has hit its stride and points us toward individualized medicine. Next-generation pharmacies represent a promising step toward that goal.

(Eric J. Topol is professor of translational genomics at the Scripps Research Institute. Copyright: Project Syndicate, 2010. www.project-syndicate.org)




 

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