| Literature DB >> 34881780 |
Zheng Yin1, Stephen T C Wong1.
Abstract
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.Entities:
Keywords: artificial intelligence; computational biology; deep learning; drug repositioning; systems medicine
Mesh:
Year: 2021 PMID: 34881780 PMCID: PMC8923082 DOI: 10.1042/ETLS20210223
Source DB: PubMed Journal: Emerg Top Life Sci ISSN: 2397-8554