怀疑论
计算机科学
药物发现
工程伦理学
数据科学
工程类
生物信息学
认识论
生物
哲学
作者
Petra Schneider,W. Patrick Walters,Alleyn T. Plowright,Norman Sieroka,Jennifer Listgarten,Robert A. Goodnow,Jasmin Fisher,Johanna M. Jansen,José S. Duca,Thomas S. Rush,Matthias Zentgraf,John E. Hill,Elizabeth Krutoholow,Matthias Köhler,Jeff Blaney,Kimito Funatsu,Chris Luebkemann,Gisbert Schneider
标识
DOI:10.1038/s41573-019-0050-3
摘要
Artificial intelligence (AI) tools are increasingly being applied in drug discovery. While some protagonists point to vast opportunities potentially offered by such tools, others remain sceptical, waiting for a clear impact to be shown in drug discovery projects. The reality is probably somewhere in-between these extremes, yet it is clear that AI is providing new challenges not only for the scientists involved but also for the biopharma industry and its established processes for discovering and developing new medicines. This article presents the views of a diverse group of international experts on the ‘grand challenges’ in small-molecule drug discovery with AI and the approaches to address them. Artificial intelligence (AI) tools are increasingly being applied in drug discovery. This article presents the views of a group of international experts on the ‘grand challenges’ in small-molecule drug discovery with AI, including obtaining appropriate data sets, generating new hypotheses, optimizing in a multi-objective manner, reducing cycle times and changing the research culture.
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