Advancing Drug Discovery via Artificial Intelligence

被引：336

作者：

Chan, H. C. Stephen ^{[1
,2
]}

Shan, Hanbin ^{[3
]}

Dahoun, Thamani ^{[2
,4
]}

Vogel, Horst ^{[2
,4
]}

Yuan, Shuguang ^{[1
,2
,4
]}

机构：

[1] Chinese Acad Sci, Res Ctr Comp Aided Drug Discovery, Shenzhen Inst Adv Technol, Shenzhen 518055, Peoples R China

[2] AlphaMol Sci Ltd, CH-4123 Allschwil, Switzerland

[3] Shanghai Inst Pharmaceut Ind, Shanghai 200040, Peoples R China

[4] Ecole Polytech Fed Lausanne, Inst Chem Sci & Engn ISIC, CH-1015 Lausanne, Switzerland

来源：

TRENDS IN PHARMACOLOGICAL SCIENCES | 2019年 / 40卷 / 08期

关键词：

MATCHED MOLECULAR PAIRS; DEEP NEURAL-NETWORKS; PHYSICAL-PROPERTIES; AUTOMATED SYNTHESIS; YIELD PREDICTION; MACHINE; COMPUTER; DESIGN; DOCKING; BINDING;

D O I：

10.1016/j.tips.2019.06.004

中图分类号：

R9 [药学];

学科分类号：

1007 ;

摘要：

Drug discovery and development are among the most important translational science activities that contribute to human health and wellbeing. However, the development of a new drug is a very complex, expensive, and long process which typically costs 2.6 billion USD and takes 12 years on average. How to decrease the costs and speed up new drug discovery has become a challenging and urgent question in industry. Artificial intelligence (AI) combined with new experimental technologies is expected to make the hunt for new pharmaceuticals quicker, cheaper, and more effective. We discuss here emerging applications of AI to improve the drug discovery process.

引用

页码：592 / 604

页数：13

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