Applications of Artificial Intelligence and Pharmacogenomics in Cardiovascular and Cancer Treatment

Review Article

Abstract

The convergence of Artificial Intelligence (AI) and pharmacogenomics marks a pivotal advancement in precision medicine, particularly in cardiovascular and oncological therapeutics. Modern healthcare has evolved beyond conventional treatment approaches, embracing individualized therapeutic strategies based on genetic profiles, environmental factors, and lifestyle considerations. AI technologies enhance diagnostic precision, accelerate drug development pipelines, and optimize clinical decision-making through complex data interpretation. Pharmacogenomic investigations reveal crucial insights into patient-specific drug responses, enabling the development of genetically tailored therapeutic regimens. The synergy between AI and pharmacogenomics has demonstrated remarkable progress across multiple medical domains. Notable applications include identifying single nucleotide polymorphism markers in metabolic disorders, optimizing antiplatelet therapy in peripheral arterial disease, and predicting chemotherapy resistance patterns. In oncology, machine learning models have revolutionized breast cancer treatment protocols, while deep learning applications combined with neuroimaging data have enhanced the prediction of antidepressant efficacy in psychiatric conditions. Clinical pharmacists serve as essential intermediaries, bridging technological innovations with practical healthcare delivery through genetic interpretation, medication management, and patient education. While this technological integration faces implementation challenges, its potential to transform healthcare delivery remains unprecedented. The successful implementation of these innovations requires expanded accessibility, robust ethical guidelines, and enhanced interdisciplinary collaboration, ultimately leading to more precise, effective, and equitable healthcare delivery.