Pharmacogenomics and Rare Diseases: Optimizing Therapeutics with Artificial Intelligence

Rare diseases, despite their low individual prevalence, collectively affect millions worldwide and present significant challenges in drug development due to small patient populations, genetic heterogeneity, and lack of surrogate biomarkers. Pharmacogenomics integrates genetic information into clinical decision-making to optimize drug therapy and minimize adverse reactions, holding transformative potential for rare disease treatment. The application of pharmacogenomics in rare diseases is particularly promising given the genetic basis of many of these conditions and the need for precision medicine approaches. However, clinical implementation remains unequal globally due to regulatory disparities, lack of diversity in genetic research, limited healthcare infrastructure, and insufficient clinician education. Artificial intelligence and computational approaches can enhance genetic analysis, disease prediction, and therapeutic optimization. AI tools have shown effectiveness in genetic-phenotypic analysis, facilitating rare disease diagnoses and identifying causative variants. The synergy between pharmacogenomics and AI offers opportunities to overcome challenges in rare disease drug development and advance precision medicine. This review examines the role of pharmacogenomics in rare disease therapeutics, current challenges, and the potential of AI-driven computational approaches for personalized treatment.