AI-Driven Transformation in Drug Discovery and Translational Medicine: Innovations, Challenges, and Future Directions

Introduction: Artificial Intelligence (AI) is increasingly transforming the field of drug discovery and development. By integrating advanced computational approaches such as machine learning (ML) and deep learning (DL), AI is improving the efficiency of drug design, screening, and clinical research. This review explores the role of AI in different stages of drug development and highlights its significance in translational medicine. Materials and Methods: A systematic literature review was conducted using major scientific databases including PubMed and Scopus. Keywords such as “artificial intelligence,” “drug discovery,” “machine learning,” “clinical trials,” and “translational medicine” were used for the search. Peer-reviewed articles published between 2015 and 2025 were included. The selected studies were analyzed and categorized according to different phases of drug discovery, including molecular modelling, preclinical testing, clinical trials, and personalized medicine. Results: The findings indicate that AI significantly reduces the time and cost of drug development while improving predictive accuracy. AI techniques support molecular modeling, virtual screening, drug repurposing, biomarker discovery, and clinical trial optimization. In translational medicine, AI also contributes to personalized treatment strategies through the analysis of genomic and clinical data. However, challenges remain, including data quality issues, model interpretability, ethical concerns, and the need for appropriate regulatory frameworks. Conclusion: AI has the potential to revolutionize drug discovery and translational medicine by accelerating research, improving prediction accuracy, and enabling personalized therapies. Despite existing challenges, continued advancements in AI technologies and collaborative efforts among researchers, clinicians, and regulatory bodies will further enhance its application in healthcare and pharmaceutical innovation.