Research on the Application of Artificial Intelligence in Drug Discovery and Development
Authors: Zhang Wei, Li Na, Wang Fang, Chen Yu
Artificial intelligence (AI) is revolutionizing the field of drug discovery and development by enabling faster identification of potential drug candidates, optimizing clinical trial designs, and reducing costs. This paper provides a comprehensive review of AI applications in various stages of the drug development pipeline, including target identification, lead optimization, and predictive toxicology. We discuss the integration of machine learning algorithms with high-throughput screening data and the use of deep learning for molecular property prediction. Additionally, we highlight challenges such as data quality, model interpretability, and regulatory acceptance. Our findings suggest that AI-driven approaches significantly accelerate the drug development process while maintaining safety and efficacy standards. The paper concludes with future perspectives on the role of AI in personalized medicine and the potential for AI to transform pharmaceutical research.