Application of Machine Learning Methods for the Development of Antidiabetic Drugs
| Autor: | Liu Xiujuan, Xiaosheng Qu, Sooranna Dev, Minjie Li, Bing Niu, Zhao Juanjuan, Pengcheng Xu, Xiaobo Ji, Wencong Lu |
|---|---|
| Rok vydání: | 2022 |
| Předmět: |
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 |
| Zdroj: | Current Pharmaceutical Design. 28:260-271 |
| ISSN: | 1381-6128 |
| DOI: | 10.2174/1381612827666210622104428 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|