Transforming Pharmacovigilance With Pharmacogenomics: Toward Personalized Risk Management

Pharmacovigilance is a critical component of medication safety. Despite rigorous evaluation of new drugs during clinical trials, some adverse effects might only be identified once pharmaceuticals are used by a larger population for a longer duration. Adverse drug reactions cause negative healthcare outcomes and in severe cases, may lead to hospital admissions, delayed hospital discharges, or deaths. Adverse event reports submitted to pharmacovigilance programs by healthcare professionals and consumers are a key source of information regarding previously unrecognized detrimental effects. Pharmacogenetic markers that indicate how particular genes impact an individual's response to medication can help explain some idiosyncratic adverse reactions. Incorporating pharmacogenomic guidance in prescribing is proven to decrease the incidence of adverse reactions and improve clinical outcomes. However, this information is not yet routinely included in incident reports. In this era of precision medicine, when prescribing can be tailored to the individual, pharmacogenomic test results yield valuable data that can enhance both individual and population health. Furthermore, advanced artificial intelligence (AI) and machine learning (ML) methods facilitate analysis of complex genetic data, revealing insights not previously available. This white paper outlines current pharmacovigilance and pharmacogenomic practices and recommends that pharmacovigilance programs include pharmacogenomics as a crucial data point in their investigations.