Pharmacogenomics-Guided Drug Dose Adjustment in Personalized Medicine: A Systematic Literature Review
TL;DR
Overall, pharmacogenomic-guided dose adjustment is a promising strategy to support safer and more precise pharmacotherapy, although broader implementation requires standardized guidelines, prospective validation, population-specific evidence, and integration into routine healthcare systems.
Abstract
Pharmacogenomics-guided drug dose adjustment is an important approach in personalized medicine because genetic polymorphisms can influence drug metabolism, therapeutic response, dose requirements, and the risk of adverse drug reactions. This systematic literature review synthesized recent evidence on pharmacogenomics-guided dose adjustment, clinically relevant pharmacogenomic biomarkers, and emerging technologies supporting precision medicine. Literature searches were conducted in Scopus and PubMed for studies published between January 2021 and May 2026. Eligible studies were selected using predefined PICOS criteria and synthesized narratively because of heterogeneity in study design, therapeutic area, biomarkers, and reported outcomes. A total of 23 studies were included in the qualitative synthesis. The evidence covered various therapeutic areas, including infectious diseases, neurology, psychiatry, oncology, cardiovascular medicine, and transplantation. Pharmacogenomic-guided dosing was most clearly supported for clinically established gene–drug pairs, including CYP2C9/VKORC1–warfarin, CYP2C19-related therapies, DPYD–fluoropyrimidines, SLCO1B1–statins, CYP2B6–efavirenz, and selected CYP3A5-related immunosuppressant therapies. Other biomarkers, such as ABCB1, APOE, GABRG2, UGT genes, and receptor-related polymorphisms, were associated with treatment response or drug disposition but still require stronger clinical validation for routine dose-adjustment recommendations. Emerging technologies, including clinical decision support systems, model-informed precision dosing, population pharmacokinetic modeling, bioinformatics, artificial intelligence, and machine learning, may strengthen biomarker interpretation and individualized dose optimization. Overall, pharmacogenomic-guided dose adjustment is a promising strategy to support safer and more precise pharmacotherapy, although broader implementation requires standardized guidelines, prospective validation, population-specific evidence, and integration into routine healthcare systems.