The growing field of pharmacogenomics—the study of how genes affect an individual’s response to drugs—holds transformative potential for the personalization of healthcare. By enabling clinicians to tailor drug therapies based on a patient’s genetic profile, pharmacogenomics reduces the risk of adverse drug reactions, enhances therapeutic efficacy, and improves clinical outcomes. However, widespread integration of pharmacogenomics into healthcare systems poses substantial cost, logistical, and policy challenges that demand thorough economic evaluation. This paper conducts a comprehensive cost-benefit analysis of pharmacogenomics integration, drawing on real-world case studies, health economic models, and clinical trial data across oncology, cardiology, psychiatry, and infectious disease domains. It considers both direct costs—such as genetic testing, IT infrastructure, training, and laboratory setup—and indirect costs including workflow disruptions and regulatory compliance. The benefits are measured in terms of reduced hospitalization rates, decreased polypharmacy, improved medication adherence, and long-term public health gains. The analysis reveals that while upfront investments are considerable, the long-term benefits of personalized drug therapy often offset initial costs, particularly in high-risk or high-cost patient populations. Cost-effectiveness is maximized when pharmacogenomics is implemented as part of clinical decision support tools integrated into electronic health records. Additionally, we explore policy incentives, payer reimbursement models, and ethical considerations for equitable access. Our findings highlight that with strategic implementation and stakeholder alignment, pharmacogenomics can deliver substantial economic and clinical returns, reinforcing its value as a cornerstone of next-generation healthcare delivery.