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精品文章:Artificial intelligence in drug design

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发表于 2018-8-9 14:36:36 | 显示全部楼层 |阅读模式
2018-Artificial intelligence in drug design

Thanks to the fast improvement of the computing power and the rapid development of the computational chemistry and biology,
the computer-aided drug design techniques have been successfully applied in almost every stage of the drug discovery and
development pipeline to speed up the process of research and reduce the cost and risk related to preclinical and clinical trials.
Owing to the development of machine learning theory and the accumulation of pharmacological data, the artificial intelligence
(AI) technology, as a powerful data mining tool, has cut a figure in various fields of the drug design, such as virtual screening,
activity scoring, quantitative structure-activity relationship (QSAR) analysis, de novo drug design, and in silico evaluation of
absorption, distribution, metabolism, excretion and toxicity (ADME/T) properties. Although it is still challenging to provide a
physical explanation of the AI-based models, it indeed has been acting as a great power to help manipulating the drug discovery
through the versatile frameworks. Recently, due to the strong generalization ability and powerful feature extraction capability,
deep learning methods have been employed in predicting the molecular properties as well as generating the desired molecules,
which will further promote the application of AI technologies in the field of drug design.





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