Recent progresses in the exploration of machine learning methods as in-silico ADME prediction tools.

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作者： L,Tao ^[1] ; P,Zhang ^[2] ; C,Qin ^[2] ; S Y,Chen ^[2] ; C,Zhang ^[2] ; Z,Chen ^[3] ; F,Zhu ^[4] ; S Y,Yang ^[5] ; Y Q,Wei ^[5] ; Y Z,Chen ^[6]

作者单位： State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, West China Medical School, Sichuan University, Chengdu 610041, China; Bioinformatics and Drug Design Group, Department of Pharmacy, Center for Computational Science and Engineering, National University of Singapore, Singapore 117543, Singapore. ^[1] Bioinformatics and Drug Design Group, Department of Pharmacy, Center for Computational Science and Engineering, National University of Singapore, Singapore 117543, Singapore. ^[2] Zhejiang Key Laboratory of Gastro-intestinal Pathophysiology, Zhejiang Hospital of Traditional Chinese Medicine, Zhejiang Chinese Medical University, No. 54 Youdian Road, Hangzhou 310006, China. ^[3] Innovative Drug Research Centre and College of Chemistry and Chemical Engineering, Chongqing University, Chongqing, China. ^[4] State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, West China Medical School, Sichuan University, Chengdu 610041, China. ^[5] Bioinformatics and Drug Design Group, Department of Pharmacy, Center for Computational Science and Engineering, National University of Singapore, Singapore 117543, Singapore. Electronic address: phacyz@nus.edu.sg. ^[6]

关键词 ADME Absorption Distribution Drug discovery Excretion Machine learning Metabolism Molecular descriptors QSAR

主题词计算机模拟(Computer Simulation);人类(Humans);模型, 生物学(Models, Biological);药用制剂(Pharmaceutical Preparations);药代动力学(Pharmacokinetics)

DOI 10.1016/j.addr.2015.03.014

PMID 26037068

发布时间 2015-07-03

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