Pharmacogenomics and Personalized Drug Therapy: Advances in Genetic Variants, Drug Response Prediction, and Precision Medicine

The study of individual drug response due to genetic variation, known as Pharmacogenomics (PGx), has transitioned from a research concept to become a key component of precision medicine in the clinic. New advances in genetic research have led to the identification of variants of cytochrome P450 metabolising enzymes (such as CYP2D6, CYP2C19, CYP2C9) and drug transporters (SLCO1B1), and human leukocyte antigen (HLA) genes, which account for much of the inter-individual differences in efficacy and toxicity of commonly used drug classes including antiplatelets, anticoagulants, antidepressants, statins, and chemotherapeutic drugs. This review collates recent literature (2020-2025) on three interwoven themes: (i) clinically actionable genetic variants and guidance for their use in consortia, such as the Clinical Pharmacogenetics Implementation Consortium (CPIC); (ii) the progression of drug response prediction, from rule-based algorithms through regression-based dosing models to novel machine learning and deep learning approaches incorporating multi-omics data; and (iii) the implementation of precision medicine, such as embedding clinical decision support in electronic health records (EHRs), establishing preemptive testing programmes, and the ongoing challenges of ancestral diversity, cost-effectiveness, and workforce education. We include a summary table of representative drug-gene pairs, a methodological comparison table, and an implementation efforts table, along with four figures visualising the PGx prescribing workflow, cytochrome P450 metabolizer phenotypes, an artificial intelligence approach to the prediction pipeline, and global disparities in pharmacogenomic representation. We believe the scientific and regulatory foundation for pharmacogenomic informed prescribing is developing, but translating it into routine use worldwide remains an unfinished agenda that will require coordinated clinical, informatics, and policy action.