期刊
NATURE MACHINE INTELLIGENCE
卷 3, 期 1, 页码 68-+出版社
NATURE PORTFOLIO
DOI: 10.1038/s42256-020-00276-w
关键词
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资金
- National Center for Advancing Translational Research of the National Institutes of Health [UL1TR002733]
Drug repurposing is an effective strategy to discover new uses for existing drugs by analyzing real-world data, offering new possibilities for disease treatment.
Drug repurposing is an effective strategy to identify new uses for existing drugs, providing the quickest possible transition from bench to bedside. Real-world data, such as electronic health records and insurance claims, provide information on large cohorts of users for many drugs. Here we present an efficient and easily customized framework for generating and testing multiple candidates for drug repurposing using a retrospective analysis of real-world data. Building upon well-established causal inference and deep learning methods, our framework emulates randomized clinical trials for drugs present in a large-scale medical claims database. We demonstrate our framework on a coronary artery disease cohort of millions of patients. We successfully identify drugs and drug combinations that substantially improve the coronary artery disease outcomes but haven't been indicated for treating coronary artery disease, paving the way for drug repurposing.
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