Precision Prescribing with Pharmacogenetics can Prevent Adverse Drug Reactions (ADRs)

Every one of us responds to medications in different ways as we have a unique genetic code, distinct lifestyles and unique environmental factors surrounding us. Because of this, the type and severity of side effects for the same medication and same dose vary. For some people, adverse drug reactions can be minor but for other individuals, they can be serious or fatal. Precision prescribing software with pharmacogenetics can be used to predict and prevent adverse drug reactions, optimize drug dose, and ultimately improve patient safety.

The increasing prevalence of adverse drug reactions (ADRs) ^1,2 constitutes a substantial burden for healthcare providers due to the additional costs associated with hospitalizations, prolongation of hospital stays, clinical investigations, and prescription cascades ³. It is now clear that a significant portion of ADRs, as well as therapeutic failures, are caused by genetically based inter-individual differences in drug absorption, excretion or metabolism ⁴. Pharmacogenetics is an effective method of reducing ADRs as shown by high-level evidence from systematic reviews and guidelines ^5–7.

A study in hospitalized adults quantified the burden of adverse drug reactions (ADR) in Singapore and found that almost a third of ADRs detected in the study were caused by at least one drug with pharmacogenetic evidence for adverse events ⁸. The most notable case was warfarin and bleeding and/or supratherapeutic INR, for which there is very strong pharmacogenetic-based evidence in two genes (CYP2C9 and VKORC1). This is in line with previous clinical trials showing that pharmacogenetic-based dosing significantly reduced the risk of ADRs and major bleeding compared to conventional dosing ⁹.

The results of Chan et al.’s study suggest that a large percentage of ADRs could be predicted or avoided using pharmacogenetic testing. In fact, previous research revealed that pre-emptive pharmacogenetic testing of multiple genes represents an efficient approach to improve treatment decision making and patient safety ¹⁰.

About GenXys

GenXys provides the world’s most comprehensive precision prescribing software to solve healthcare’s most pressing challenges. Our precision prescribing software & pharmacogenetic solutions prevent adverse drug reactions, the 4th largest killer in the US, and personalize drug selection to dramatically increase drug efficacy. Powering every prescription with our proven software improves medication safety, efficacy and healthcare costs.

1. Patel, H. et al. Trends in hospital admissions for adverse drug reactions in England: analysis of national hospital episode statistics 1998-2005. BMC Clin. Pharmacol. 7, 9 (2007).
2. Bourgeois, F. T., Shannon, M. W., Valim, C. & Mandl, K. D. Adverse drug events in the outpatient setting: an 11-year national analysis. Pharmacoepidemiol. Drug Saf. 19, 901–910 (2010).
3. Sultana, J., Cutroneo, P. & Trifirò, G. Clinical and economic burden of adverse drug reactions. J. Pharmacol. Pharmacother. 4, S73 (2013).
4. Verbeurgt, P., Mamiya, T. & Oesterheld, J. How common are drug and gene interactions? Prevalence in a sample of 1143 patients with CYP2C9, CYP2C19 and CYP2D6 genotyping. Pharmacogenomics 15, 655–665 (2014).
5. Phillips, K. A., Veenstra, D. L., Oren, E., Lee, J. K. & Sadee, W. Potential role of pharmacogenomics in reducing adverse drug reactions: a systematic review. JAMA 286, 2270–2279 (2001).
6. Swen, J. J. et al. Pharmacogenetics: From Bench to Byte— An Update of Guidelines. Clinical Pharmacology & Therapeutics 89, 662–673 (2011).
7. Cargnin, S., Jommi, C., Canonico, P. L., Genazzani, A. A. & Terrazzino, S. Diagnostic accuracy of HLA-B*57:01 screening for the prediction of abacavir hypersensitivity and clinical utility of the test: a meta-analytic review. Pharmacogenomics 15, 963–976 (2014).
8. Chan, S. L., Ang, X., Sani, L. L., Ng, H. Y., Winther, M. D., Liu, J. J., Brunham, L. R., and Chan, A. (2016) Prevalence and characteristics of adverse drug reactions at admission to hospital: a prospective observational study. Br J Clin Pharmacol, doi: 10.1111/bcp.13081.
9. Shi C, Yan W, Wang G, Wang F, Li Q, Lin N. Pharmacogenetics-based versus conventional dosing of warfarin: a meta-analysis of randomized controlled trials. PLoS One 2015; 10: e0144511.
10. Schildcrout JS, Denny JC, Bowton E, Gregg W, Pulley JM, Basford MA, et al. Optimizing drug outcomes through pharmacogenetics: a case for preemptive genotyping. Clin Pharmacol Ther 2012; 92: 235–242.