Pharmacogenomics-driven precision pharmacy: Mechanisms, challenges, and translational advances
TL;DR
The integration of artificial intelligence and machine learning approaches for pharmacogenomic prediction, the emergence of polygenic risk scores, and the role of multi-omics integration in refining therapeutic decision-making are examined.
Abstract
Pharmacogenomics represents a transformative paradigm in clinical pharmacology, offering the promise of individualized drug therapy based on genetic profiles. This comprehensive review examines the mechanisms underlying pharmacogenomic variability, the current state of clinical implementation, and the translational advances driving precision pharmacy practice. We systematically discuss the role of pharmacokinetic genes, including cytochrome P450 enzymes (CYP2D6, CYP2C19, CYP2C9, CYP3A4/5), thiopurine S-methyltransferase (TPMT), and solute carrier organic anion transporter family member 1B1 (SLCO1B1), as well as pharmacodynamic targets such as vitamin K epoxide reductase complex subunit 1 (VKORC1) and adrenoceptor beta 1 (ADRB1). Human leukocyte antigen (HLA) genes and their association with severe adverse drug reactions are also critically evaluated. The review further explores the evidence base supporting clinical pharmacogenomic implementation, including guidelines from the Clinical Pharmacogenetics Implementation Consortium (CPIC), the Dutch Pharmacogenetics Working Group (DPWG), and major implementation initiatives such as the IGNITE network and the PREPARE study. We examine the integration of artificial intelligence and machine learning approaches for pharmacogenomic prediction, the emergence of polygenic risk scores, and the role of multi-omics integration in refining therapeutic decision-making. Challenges, including economic barriers, regulatory considerations, health equity concerns, and healthcare system integration, are thoroughly discussed. Finally, we outline future directions for the field, emphasizing the need for global diversification of pharmacogenomic data, enhanced clinical decision support systems, and policy frameworks that facilitate equitable access to precision pharmacy services.