Drug Development Failure from Preclinical, Clinical, and Industrial Perspectives

Translation of promising drug candidates into approved therapies remains a major challenge in biomedical research. Despite advances in molecular biology, computational modeling, and clinical trial methodology, high failure rates persist across development pipelines. Many candidates fail due to weak target validation, limited predictive value of preclinical models, unfavorable pharmacokinetic properties, delayed toxicity detection, and suboptimal clinical trial design. These limitations are hindered by regulatory uncertainty, market competition, and financial restrictions. This review examines key factors contributing to translational failure from discovery to market authorization, with emphasis on early-stage evidence quality, drug disposition, human trial performance, and decision-making. It highlights strategies to improve development efficiency, human-relevant models, systems pharmacology, artificial intelligence-assisted screening, early PK/PD integration, adaptive trial designs, and translational biomarkers. Review emphasizes need for stronger collaboration, improved transparency, and cultural changes that promote reproducibility and rigorous validation. By integrating scientific, clinical, and economic perspectives, this review aims to provide novel insights to reduce avoidable failure and enhance the success of future therapeutic innovation.