From Molecules to Medicine: AI-Driven Translational Science

Abstract

Fundamental laboratory discoveries and their application in clinical practice is connected by translational science. The growing synergy between translational science, AI, computational tools, and medicinal chemistry has brought a paradigm shift in drug discovery and development. Medicinal chemistry forms the molecular basis for the rational design and optimization of drug candidates, while computational strategies and AI-based tools enhance target identification, lead refinement, and the prediction of pharmacokinetic and safety characteristics. This review examines the contribution of AI-driven computational medicinal chemistry to translational science, highlighting its role in shortening development timelines, increasing success rates, and supporting personalized and precision medicine. Recent innovations, existing challenges, and future prospects for integrating AI with experimental and clinical workflows are also discussed, emphasizing their relevance to next-generation healthcare.