精密医学
计算机科学
人工智能
药物发现
药物开发
药品
疾病
数据科学
风险分析(工程)
个性化医疗
机器学习
医学
生物信息学
药理学
生物
病理
作者
Philippe Moingeon,Mélaine A. Kuenemann,Mickaël Guedj
标识
DOI:10.1016/j.drudis.2021.09.006
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.
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