A biomarker is any biological indicator that predicts or signals, with a high degree of reliability, some underlying biological state. The number of potential biomarker proteins, genes, metabolites, and other molecules has increased in recent years from a few dozen to perhaps several hundred. Many more will no doubt be discovered.
Fueled by the discovery of new biomarkers, personalized medicine will cause diagnostic and pharmaceutical companies to shift their thinking about new products, and eventually perhaps to adopt a radically new business model. All things being equal, the more personalized the treatment, the smaller the patient population and the less attractive the business opportunity. Which begs the question: Is the end approaching for the pharmaceutical blockbuster model?
A common misconception regarding personalized medicine is that it will end the blockbuster drug model as we know it. According to this reasoning, biomarker tests, by identifying and eliminating non-responding individuals from clinical trials and treatment, will necessarily shrink markets for many drugs, perhaps to below profitable levels.
While some observers have expressed mixed feelings about targeted or personalized therapies, regulators and the pharm/biotech industries have been doing their best to present the "glass half full" perspective, a position that Pacific Biometrics agrees with.
Along with its inevitable challenges, personalized medicine and drug-diagnostic combination products present vast opportunities. Novel, disease-specific biomarkers will greatly streamline drug discovery and clinical development. We are already seeing this in the form of gene and protein chips that screen patients for dozens (or thousands) of disease-relevant biomarkers. Considerable progress is being made in the area of metabolomics as well.
Rapid, high-throughput screening methods can identify drugs most likely to succeed for specific patient populations, enabling companies to out-license or drop projects that do not meet their financial objectives even before undertaking animal studies. During clinical trials, similar techniques can identify patients most likely to respond or who might be prone to serious adverse events, thus streamlining human testing by perhaps several years. To its credit, FDA's position thus far has been to support the use of biomarkers, in particular pharmacogenomics, and to encourage drug developers to submit such data.
Personalized medicine will create many opportunities for developing drugs that are effective in individuals who do not respond to traditional medicines. Such medications would probably qualify as "orphan" products on the basis of their limited patient base. Granted to drugs that treat diseases with fewer than 200,000 patients, orphan status provides extended market exclusivity, tax breaks, exemption from user fees, availability of grants to cover the cost of clinical trials, and other benefits.
The advent of personalized medicine will by no means be free of risk. There will be winners and losers, as well there should be. Drugs that are safer and more effective will move to the head of the class; those that are effective but carry a higher potential for serious side effects will be reserved for patients who do not respond to first-line therapies. And niche drugs, which may only be safe and effective in a very small number of patients, will be limited to those patients.
Using the safest, most effective medicines in the most appropriate patient populations is not just good medicine, it makes good macro-economic sense, and it is hoped good business sense as well. The penalty society pays for inappropriately prescribed drugs are huge: Adverse drug events are the fourth leading cause of death in the United States and cost the healthcare system $200 billion per year.
As the enabling technology for personalized or targeted therapies, biomarkers will continue to be a top priority for both academic and industrial biomedicine. While the scientific components of biomarkers—genomics, proteomics, metabolomics and diagnostic imaging—have deepened our understanding of the biology of disease and treatment, developing these methods into reliable diagnostic tools is an ongoing project.