药物开发
药品
药物代谢
排泄
计算机科学
药物发现
机器学习
人工智能
数据科学
药理学
生物信息学
医学
生物
内科学
作者
Thi Tuyet Van Tran,Hilal Tayara,Kil To Chong
出处
期刊:Pharmaceutics
[Multidisciplinary Digital Publishing Institute]
日期:2023-04-17
卷期号:15 (4): 1260-1260
被引量:98
标识
DOI:10.3390/pharmaceutics15041260
摘要
Drug metabolism and excretion play crucial roles in determining the efficacy and safety of drug candidates, and predicting these processes is an essential part of drug discovery and development. In recent years, artificial intelligence (AI) has emerged as a powerful tool for predicting drug metabolism and excretion, offering the potential to speed up drug development and improve clinical success rates. This review highlights recent advances in AI-based drug metabolism and excretion prediction, including deep learning and machine learning algorithms. We provide a list of public data sources and free prediction tools for the research community. We also discuss the challenges associated with the development of AI models for drug metabolism and excretion prediction and explore future perspectives in the field. We hope this will be a helpful resource for anyone who is researching in silico drug metabolism, excretion, and pharmacokinetic properties.
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