Artificial intelligence-enhanced drug design and development: Toward a computational precision medicine

被引:41
作者
Moingeon, Philippe [1 ]
Kuenemann, Melaine [1 ]
Guedj, Mickael [1 ]
机构
[1] Servier, Res & Dev, 50 Rue Carnot, F-92284 Suresnes, France
关键词
Artificial Intelligence; Big data; Computational precision medicine; Disease model; Drug discovery & development; Machine learning; NEURAL-NETWORKS; SUCCESS; MODEL;
D O I
10.1016/j.drudis.2021.09.006
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
Artificial Intelligence (AI) relies upon a convergence of technologies with further synergies with life science technologies to capture the value of massive multi-modal data in the form of predictive models supporting decision-making. AI and machine learning (ML) enhance drug design and development by improving our understanding of disease heterogeneity, identifying dysregulated molecular pathways and therapeutic targets, designing and optimizing drug candidates, as well as evaluating in silico clinical efficacy. By providing an unprecedented level of knowledge on both patient specificities and drug candidate properties, AI is fostering the emergence of a computational precision medicine allowing the design of therapies or preventive measures tailored to the singularities of individual patients in terms of their physiology, disease features, and exposure to environmental risks.
引用
收藏
页码:215 / 222
页数:8
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