1. Application of Machine Learning Methods for the Development of Antidiabetic Drugs
- Author
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Liu Xiujuan, Xiaosheng Qu, Sooranna Dev, Minjie Li, Bing Niu, Zhao Juanjuan, Pengcheng Xu, Xiaobo Ji, and Wencong Lu
- Subjects
Pharmacology ,Drug ,Dipeptidyl-Peptidase IV Inhibitors ,Dpp iv inhibitors ,business.industry ,Computer science ,media_common.quotation_subject ,Machine learning ,computer.software_genre ,Machine Learning ,Diabetes Mellitus, Type 2 ,Drug development ,Blueprint ,Drug Discovery ,Humans ,Hypoglycemic Agents ,Artificial intelligence ,business ,computer ,media_common - Abstract
Diabetes is a chronic non-communicable disease caused by several different routes, which has attracted increasing attention. In order to speed up the development of new selective drugs, machine learning (ML) technology has been applied in the process of diabetes drug development and opens up a new blueprint for drug design. This review provides a comprehensive portrayal of the application of ML in antidiabetic drug use.
- Published
- 2022