PERSONALIZED MEDICINE AND PHARMACOGENOMICS: EXPLORING GENETIC DETERMINANTS OF DRUG RESPONSE VARIABILITY: A SYSTEMATIC REVIEW

Abstract

Pharmacogenomics has emerged as a key driver of personalized medicine, explaining interindividual variability in drug efficacy, toxicity, and dosing requirements. Despite advances in genetic testing, the translation of pharmacogenomic evidence into clinical practice remains inconsistent.

Objective

This systematic review aimed to synthesize empirical evidence on pharmacogenomic determinants of drug response variability, highlighting clinical implications across therapeutic areas including cardiology, oncology, psychiatry, neurology, and infectious diseases.

Methods

The review adhered to PRISMA 2020 guidelines. Eligible studies included cross-sectional, case-control, retrospective, and prospective cohort designs published between 2000 and 2024. Databases searched included PubMed, Scopus, Web of Science, and Embase. Extracted data encompassed study design, population, genetic markers, drug class, outcomes, and statistical associations. Quality appraisal was performed using the Newcastle–Ottawa Scale and Joanna Briggs Institute tools.

Results

A total of 10 peer-reviewed studies met inclusion criteria. Findings highlighted strong associations between genetic polymorphisms and drug outcomes. Warfarin-related studies demonstrated the influence of VKORC1 and CYP2C9 variants on anticoagulation stability and dosing. Oncology research identified transporter and enzyme polymorphisms linked to docetaxel toxicity, while psychiatric pharmacogenomics implicated HSD11B1 polymorphisms in antidepressant outcomes and suicide risk. Neurological and infectious disease studies further demonstrated the role of pharmacogenomic variability in antiepileptic efficacy and risk of drug-induced liver injury. However, evidence for some markers, such as TPMT in vasculitis, showed limited predictive value.

Conclusion

Pharmacogenomics significantly advances the promise of personalized medicine by identifying genetic predictors of drug efficacy and adverse reactions. However, variability in study quality, population diversity, and biomarker validation limits universal applicability. Future research should prioritize large-scale, multi-ethnic cohorts, integration of novel biomarkers, and implementation science approaches to ensure equitable global adoption of pharmacogenomic testing.