Advances in the Application of Deep Learning in Drug Development

Recently, artificial intelligence (AI) represented by deep learning (DL) has been deeply integrated with various fields of medical and pharmaceutical sciences. DL has been applied to drug research and development with significant progress in the prediction of protein structure and function, drug target, pharmacokinetic properties, drug safety and efficacy, and drug interactions, with improved efficiency of drug research and development and reduced costs and risks of preclinical and clinical trials. This review summarizes the specific applications of various methods of DL in the whole process of drug research and development, with an analysis of the application characteristics of different DL methods in drug research and development. Finally, some problems and prospects of DL in drug research and development are presented so as to provide reference for ideas and methods in further research.