Pharmacogenomics (a.k.a. pharmacogenetics or PGx) is the science of how genes impact an individual’s response to medications. Benefits of pharmacogenetics can range from helping clinicians target medications to improve patient outcomes to enhancing efficiency of pre-market clinical trials for new drug entities.
**Various medication classes such as antidepressants, antipsychotics, analgesics, and oncologics can be ineffective for 20-75% of treated patients.**
Compelling biological and clinical evidence suggests that genetic differences may explain an estimated 20-95% of the variability in medication effects, such as unpredictable response or serious adverse drug reactions (ADRs). Testing for clinical relevant genetic variations may offer clinicians an objective tool to help better predict medication response for their patients.
Pain and mental health medications were among the top 5 most expensive medications in 2012. Psychiatric, pain, and cardiovascular medications are among the most frequently cited in ADRs.
Many factors, including diet, lifestyle, and age contribute to inter-patient variability in medication response. However, genetics remains one of the most compelling targets to evaluate in clinical practice because of the relative ease of measuring and quantifying its impact on patient response. As such, genetic testing may provide a more consistent barometer for predicting medication response among patients compared to other clinical factors and it is also relatively easy to implement in clinical practice.
Patients with variant (or non-normal) phenotypes can experience significant differences in their response to certain medications compared to the reference (or normal) phenotype.
More than 1 in 4 primary care patients take at least one medication associated with ADRs and known to be metabolized by genetically variable enzymes.
For patients receiving cardiovascular, CNS, or analgesic medications, the emergence of ADRs or therapeutic failure can be particularly problematic because they can lead to additional costly treatments, hospitalization, or even mortality.
Multiple cases of frequency data are especially relevant to clinicians because they suggest that substantially more patients exhibit genetic variations when examined across multiple genes than expected from frequency distributions within a single gene and may therefore benefit from PGx.
One important consideration is clinician awareness and preparedness to interpret and apply genetic test results to manage their patients. Another important stepping stone to routine implementation is achieving consensus among stakeholders regarding the relevant criteria, definitions, and validation models used to assess genetic tests for clinical value.
For clinicians weighing the decision to incorporate PGx into patient management, the decision may be ultimately guided by clinical relevance. In the post-genomic era of the last decade, the rate of published pharmacogenomics research has accelerated almost exponentially each year. Nonetheless, it remains challenging for clinicians to distinguish between PGx targets with actionable information that can be implemented immediately in patient care from investigational tests that may presently offer only preliminary value. As the clinical evidence mounts for specific gene-drug pairs, some clinical experts question whether we are shortchanging patient care by waiting for proof-of-value using potentially inadequate models of utility.
One potential driver of health care costs in patients with genetic variations is the pharmacy costs associated with ineffective medications. Preliminary studies demonstrate that PGx may improve clinical outcomes and adherence for diabetes therapy, statin use, and depression. Given the association between genetic variations and these drivers of non-adherence, optimizing medication therapy using PGx may improve adherence by reducing the risk of side effects or therapeutic failures.
The FDA has approved drug labeling that provides dosing and administration guidance for over 120 medications according to pharmacogenomic information. Over 120 medications carry pharmacogenomics information in their FDA product label including codeine, Risperdal, Abilify, Paxil, Strattera, and Ultram.
The clinical literature continues to expand for new and emerging genetic targets and these data are likely to improve the precision of pharmacogenomics testing in predicting patient outcomes. These novel biomarkers include genes that encode transport proteins involved in cellular influx and efflux of drugs as well as cell surface receptors that interact with receptors to produce a therapeutic effect. Epigenetic biomarkers, which can alter protein expression of DNA variations, represent a novel and intensely researched area that may soon be translated from the research arena into clinical practice.