期刊
CLINICAL PHARMACOLOGY & THERAPEUTICS
卷 103, 期 3, 页码 409-418出版社
WILEY
DOI: 10.1002/cpt.951
关键词
-
资金
- National Institutes of Health (NIH) [R01 LM010685, P50 GM115305, U01 HG008672, U01 HG007253, R01 HL133786, U2C OD023196]
Drug development continues to be costly and slow, with medications failing due to lack of efficacy or presence of toxicity. The promise of pharmacogenomic discovery includes tailoring therapeutics based on an individual's geneticmakeup, rational drug development, and repurposing medications. Rapid growth of large research cohorts, linked to electronic health record (EHR) data, fuels discovery of new genetic variants predicting drug action, supports Mendelian randomization experiments to show drug efficacy, and suggests new indications for existingmedications. New biomedical informatics and machine-learning approaches advance the ability to interpret clinical information, enabling identification of complex phenotypes and subpopulations of patients. We review the recent history of use of big data from EHR-based cohorts and biobanks supporting these activities. Future studies using EHR data, other information sources, and new methods will promote a foundation for discovery to more rapidly advance precisionmedicine.
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