One Size Does Not Fit All

Up to half of drug therapy is ineffective, according to recent statistics. This leaves patients’ diseases untreated, but also places them at risk for side effects and drug interactions. The reason for the unpredictability in the effectiveness of medication comes from a variety of factors: individual differences in enzymes that metabolize drugs, variations in drug transporters, ethnic differences, and environmental changes. For decades, the idea of personalized medicine — assessing and evaluating individual differences to tailor medicine and therapy regimens for the best results — has brought about new drugs and led to effective treatment of several diseases. However, now clinicians and researchers are returning to old drugs to optimize personalized therapy.

Researching and developing new drugs based on genetics is costly and time consuming. Reinvesting time and money in older drugs to improve the effectiveness and safety may produce more “bang for the buck” in the move towards personalized medicine. Research is increasingly focused on learning why existing drugs work better in some people than others. Genetic markers are offering clues to why patients respond well, or not, to cancer protocols, cardiovascular drugs, psychiatric medications, and kidney disease treatments, to name a few. Someday, perhaps drug companies will move away from continuously developing newer, costlier agents and focus on using the old drugs for new tricks.

Many new drugs come to market with accompanying diagnostic and genetic tests to establish safety and efficacy goals, but these are costly analyses. Simple tests, though, such as blood tests or cheek swabs, may be useful in determining if a patient will respond well to a commonly prescribed medication. These fast, relatively inexpensive tests could improve the overall cost-effectiveness of drug therapy.

The complex diseases that plague society are not the result of one gene or event, but, rather, a dynamic combination of factors. By evaluating individual genomes and studying the relationship to environmental factors, clinicians will learn how to identify susceptible groups of people and tailor disease prevention strategies and optimize treatment protocols. Physicians and pharmacists will be able to determine which patients will respond well to chemotherapy regimens, who will experience adverse drug reactions from a cholesterol drug, and who will have worsening asthma from an inhaled medication.

The advent of personalized medicine and the departure from the current one-size-fits-all health care model requires a paradigm shift for patients and providers. New standards will emerge for the management of genetic information and education will be paramount for clinicians and patients. There are still more questions than answers regarding personalized medicine and tailoring therapy to each individual, but, hopefully, personalized medicine will be a large piece of the future health care puzzle, allowing more preventive medicine and evidence-based treatment selection.

References

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Dean, C. (2009). Personalized Medicine: Boon or Budget-Buster? Annals of Pharmacotherapy, 43 (5), 958-962 DOI: 10.1345/aph.1L563

Leeder, J., & Spielberg, S. (2009). Personalized Medicine: Reality and Reality Checks Annals of Pharmacotherapy, 43 (5), 963-966 DOI: 10.1345/aph.1M065

Tan DS, Thomas GV, Garrett MD, et al. Biomarker-Driven Early Clinical Trials in Oncology: A Paradigm Shift in Drug Development. Cancer J. September/October 2009;15(5):406-420.

Rovin, B., McKinley, A., & Birmingham, D. (2009). Can We Personalize Treatment for Kidney Diseases? Clinical Journal of the American Society of Nephrology, 4 (10), 1670-1676 DOI: 10.2215/CJN.04140609

Wiechec, E., & Hansen, L. (2009). The effect of genetic variability on drug response in conventional breast cancer treatment European Journal of Pharmacology, 625 (1-3), 122-130 DOI: 10.1016/j.ejphar.2009.08.045

Campbell, D., & Levitt, P. (2008). Future of individualized psychiatric treatment Pharmacogenomics, 9 (5), 493-495 DOI: 10.2217/14622416.9.5.493