Applications of Artificial Intelligence in Pharmaceutical Sciences: A Review

Artificial intelligence (AI) has emerged as a transformative technology in pharmaceutical sciences, providing innovative solutions to challenges associated with conventional drug research and development. Traditional pharmaceutical approaches are often time-consuming, costly, and associated with high attrition rates. The integration of AI-based tools, particularly machine learning (ML) and deep learning (DL) techniques, has enabled data-driven predictions, automation, and efficient handling of large and complex datasets. This review summarizes the fundamental concepts of artificial intelligence and discusses its applications across major pharmaceutical domains, including drug discovery, formulation development, pharmacokinetics and pharmacodynamics, clinical trials, and pharmacovigilance. Additionally, current challenges, ethical considerations, and regulatory issues related to AI adoption are highlighted. Future perspectives emphasize the role of explainable AI and personalized medicine. Overall, artificial intelligence is reshaping pharmaceutical research and holds significant promise for accelerating the development of safe and effective medicines .