2023, Volume 27, Issue 8
Engineering >> 2023, Volume 27, Issue 8 doi: 10.1016/j.eng.2023.01.014
Artificial Intelligence in Pharmaceutical Sciences
a College of Pharmaceutical Sciences & The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310058, China
b Shanghai Key Laboratory of New Drug Design, East China University of Science and Technology, Shanghai 200237, China
c Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba–Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou 330110, China
d Innovation Center for AI and Drug Discovery, East China Normal University, Shanghai 200062, China
e Lingang Laboratory, Shanghai 200031, China
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Abstract
Drug discovery and development affects various aspects of human health and dramatically impacts the pharmaceutical market. However, investments in a new drug often go unrewarded due to the long and complex process of drug research and development (R&D). With the advancement of experimental technology and computer hardware, artificial intelligence (AI) has recently emerged as a leading tool in analyzing abundant and high-dimensional data. Explosive growth in the size of biomedical data provides advantages in applying AI in all stages of drug R&D. Driven by big data in biomedicine, AI has led to a revolution in drug R&D, due to its ability to discover new drugs more efficiently and at lower cost. This review begins with a brief overview of common AI models in the field of drug discovery; then, it summarizes and discusses in depth their specific applications in various stages of drug R&D, such as target discovery, drug discovery and design, preclinical research, automated drug synthesis, and influences in the pharmaceutical market. Finally, the major limitations of AI in drug R&D are fully discussed and possible solutions are proposed.
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