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.
-
Cover Image
Cover Image
“Turning point” - This image captured at The Texas Medical Center for Innovation in Houston, Texas, USA represents the present ‘turning point’ for using artificial intelligence to predict clinical outcomes. Following recent innovation and novel applications, artificial intelligence methods are well-positioned to meaningfully assist in the clinical practice of medicine. Read more in the article by Pettit et al. (pp. 729–746) within this special artificial intelligence issue of Emerging topics in Life Sciences (volume 5, issue 6).
Artificial intelligence unifies knowledge and actions in drug repositioning
Zheng Yin, Stephen T. C. Wong; Artificial intelligence unifies knowledge and actions in drug repositioning. Emerg Top Life Sci 21 December 2021; 5 (6): 803–813. doi: https://doi.org/10.1042/ETLS20210223
Download citation file:
Sign in
Sign in to your personal account
Captcha Validation Error. Please try again.