Race in Precision Medicine: From Social Categories to Genomic Equity

Race remains embedded in clinical risk algorithms and therapeutic recommendations despite its limitations as a proxy for biological variation. As a sociopolitical construct, race captures aspects of social experience and structural inequality but does not reliably reflect an individual's genetic ancestry or pharmacogenomic profile. This distinction is increasingly important in genetically admixed populations, where broad racial and ethnic classifications can obscure substantial variation in allele frequencies, genetic architecture, and treatment response. Pharmacogenomics offers a more direct approach to individualized prescribing by identifying clinically actionable genetic variants that influence drug metabolism, transport, efficacy, and toxicity. However, realizing its potential requires addressing persistent gaps in the representation of diverse populations in genomic research, including the underrepresentation of non-European ancestry populations and insufficient resolution of variation within broad population categories. Genetic ancestry, subpopulation-level analyses, and individual genotypes can improve the characterization of genetic variation when appropriately matched to the research or clinical question. Yet genomic approaches alone cannot eliminate health disparities and may exacerbate inequities if testing, interpretation, and evidence-based interventions remain inaccessible to underserved populations. Advancing genomic equity therefore requires representative research, equitable access to pharmacogenomic services, responsible data governance, and meaningful community engagement. A precision-medicine framework should move beyond race as a biological proxy while retaining race and ethnicity as relevant variables for examining structural inequities and monitoring disparities in health outcomes.