Open AccessArtificial intelligence unifies knowledge and actions in drug repositioning
Author(s) -
Zhimin Yin,
Stephen T.C. Wong
Publication year - 2021
Publication title -
emerging topics in life sciences
Language(s) - English
Resource type - Journals
eISSN - 2397-8562
pISSN - 2397-8554
DOI - 10.1042/etls20210223
Subject(s) - drug repositioning , drug , drug discovery , computer science , artificial intelligence , medicine , risk analysis (engineering) , pharmacology , bioinformatics , biology
Drug repositioning aims to reuse existing drugs, shelved drugs, or drug candidates that failed clinical trials for other medical indications. Its attraction is sprung from the reduction in risk associated with safety testing of new medications and the time to get a known drug into the clinics. Artificial Intelligence (AI) has been recently pursued to speed up drug repositioning and discovery. The essence of AI in drug repositioning is to unify the knowledge and actions, i.e. incorporating real-world and experimental data to map out the best way forward to identify effective therapeutics against a disease. In this review, we share positive expectations for the evolution of AI and drug repositioning and summarize the role of AI in several methods of drug repositioning.