Combinations of single gene predictors with AI-driven polygenic precision therapies in cardiovascular diseases

Pharmacogenomics (PGx) is transforming how we treat cardiovascular disease (CVD) by enabling us to select and dose drugs based on our genetic profiles. The pharmacokinetics and pharmacodynamics of commonly prescribed cardiovascular drugs are greatly affected by gene-drug interactions, which improve the therapeutic outcome and reduce adverse drug reactions. This narrative review will summarize evidence on the clinical use of pharmacogenomics (PGx) in cardiology published between 2020 and 2025. The pharmacogenes that have been proved to be clinically useful in the genotype-guided therapy include CYP2C19, SLCO1B1, VKORC1, and CYP2D6. An example is that the use of CYP2C19-guided antiplatelet therapy following percutaneous coronary intervention has been linked to a lower risk of major adverse cardiovascular events (MACE). Similarly, SLCO1B1 genotyping can be used to prevent statin-induced myopathy, with VKORC1 and CYP2C9 variant used to warfarin dosing to reduce the risk of bleeding. Emerging technologies such as polygenic risk scores (PRS) and machine learning (ML) are expanding PGx by capturing multi‑gene contributions to drug response. In this critical review, validated gene-drug interactions are critically evaluated, and a translational roadmap is outlined to implement PGx in the cardiovascular practice to achieve precision medicine and to improve patient-specific outcomes.