Introduction: Cardiovascular diseases (CVDs) are the leading cause of morbidity and mortality worldwide. Variability in drug response among patients is a significant challenge in CVD management, often influenced by genetic and pharmacogenetic factors. Personalized medicine offers a promising approach to optimize treatment efficacy and minimize adverse effects by tailoring therapies based on individual genetic profiles.
Methods: This study analyzed genetic polymorphisms associated with drug metabolism, efficacy, and safety in CVD treatment. A systematic review of pharmacogenetic data was conducted, focusing on key cardiovascular drugs such as statins, beta-blockers, and antiplatelet agents. Clinical trials assessing the impact of genetic testing on treatment outcomes were also evaluated. Additionally, computational tools were employed to model gene-drug interactions and predict patient-specific responses.
Results: Findings reveal that polymorphisms in genes such as CYP2C19, SLCO1B1, and VKORC1 significantly influence drug efficacy and toxicity. For instance, variations in CYP2C19 affect clopidogrel metabolism, leading to variability in antiplatelet response, while SLCO1B1 variants are linked to statin-induced myopathy. Incorporating pharmacogenetic testing into clinical practice improved therapeutic outcomes by guiding drug selection and dosage adjustments. Personalized strategies were particularly effective in reducing adverse drug reactions and achieving optimal lipid control and blood pressure management.
Conclusion: Genetic and pharmacogenetic factors play a pivotal role in the variability of drug responses in CVD management. Integrating genetic testing into routine clinical workflows can enhance the precision of treatment regimens, improving patient outcomes and reducing healthcare costs. Future research should focus on expanding genetic databases, developing cost-effective testing methods, and implementing personalized approaches on a broader scale.