The Influence of Big (Clinical) Data and Genomics on Precision Medicine and Drug Development
Year: 2017
Type: article
Abstract: 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 genetic makeup, 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 existing medications. 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 precision medicine.
DOI: 10.1002/cpt.951
Institutions: Vanderbilt University Medical Center, Vanderbilt University
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: green
Awards: Integrated, Individualized, Intelligent Prescribing (I3P), Improving Prediction of Drug Action, Data and Research Support Center , VGER, the Vanderbilt Genome-Electronic Records Project, Beyond PheWAS: Recognition of Phenotype Patterns for Discovery and Translation, Exploring Statin Pleiotropic Effects within a Very Large EHR Cohort
OpenAlex ID: W2770336014