Advances in Artificial Intelligence for Drug Discovery and Development: A Review of Current Trends and Applications - E.Bharath; T.S.Thilagavathi; D.Jeeva; S.Anbazhagan; S.A.Vadivel (Asian Journal of Pharmaceutical Research and Development, 2025)
The rapid advancement of Artificial Intelligence (AI) has revolutionized drug discovery and development, reshaping the pharmaceutical landscape with its computational power and data-driven approaches. AI-driven methodologies, including deep learning, machine learning, and neural networks, have significantly expedited target identification, lead optimization, and drug repurposing, thereby reducing both time and cost associated with traditional drug development. Virtual screening, molecular docking, and predictive modelling have enabled more precise drug-target interactions, enhancing therapeutic efficacy and minimizing potential adverse effects. Moreover, AI's integration into chemical synthesis, polypharmacology, and biomarker discovery has expanded its applications in personalized medicine. This review explores the latest trends and applications of AI in drug discovery, emphasizing its role in optimizing drug design, predicting novel therapeutics, and improving preclinical and clinical trial success rates. While AI has demonstrated remarkable potential, challenges such as data bias, interpretability, and regulatory concerns remain critical barriers to its full-scale implementation. Addressing these challenges will be essential to unlocking AI’s transformative capabilities in revolutionizing modern drug development.