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National Library of Medicine Informatics Lecture Series: Use of Clinical Big Data to Inform Precision Medicine

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Air date: Wednesday, November 4, 2015, 2:00:00 PM
Time displayed is Eastern Time, Washington DC Local
Views: Total views: 362 (130 Live, 232 On-demand)
Category: Special
Runtime: 01:02:26
Description: Abstract: Precision medicine offers the promise of improved diagnosis and more effective, patient-specific therapies. Typically, clinical research studies have been pursued by enrolling a cohort of willing participants in a town or region, and obtaining information and tissue samples from them. At Vanderbilt, Dr. Denny and his team have linked phenotypic information from de-identified electronic health records (EHRs) to a DNA repository of nearly 200,000 samples, creating a ‘virtual’ cohort. This approach allows study of genomic basis of disease and drug response using real-world clinical data. Finding the right information in the EHR can be challenging, but the combination of billing data, laboratory data, medication exposures, and natural language processing has enabled efficient study of genomic and pharmacogenomic phenotypes. The Vanderbilt research team has put many of these discovered pharmacogenomic characteristics into practice through clinical decision support. The EHR also enables the inverse experiment – starting with a genotype and discovering all the phenotypes with which it is associated – a phenome-wide association study (PheWAS). PheWAS requires a densely-phenotyped population such as found in the EHR. Dr. Denny’s research team has used PheWAS to replicate more than 300 genotype-phenotype associations, characterize pleiotropy, and discover new associations. They have also used PheWAS to identify characteristics within disease subtypes.
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NLM Title: Use of clinical big data to inform precision medicine / Joshua Denny.
Author: Denny, Joshua Charles.
National Library of Medicine (U.S.),
Publisher:
Abstract: (CIT): Precision medicine offers the promise of improved diagnosis and more effective, patient-specific therapies. Typically, clinical research studies have been pursued by enrolling a cohort of willing participants in a town or region, and obtaining information and tissue samples from them. At Vanderbilt, Dr. Denny and his team have linked phenotypic information from de-identified electronic health records (EHRs) to a DNA repository of nearly 200,000 samples, creating a "virtual" cohort. This approach allows study of genomic basis of disease and drug response using real-world clinical data. Finding the right information in the EHR can be challenging, but the combination of billing data, laboratory data, medication exposures, and natural language processing has enabled efficient study of genomic and pharmacogenomic phenotypes. The Vanderbilt research team has put many of these discovered pharmacogenomic characteristics into practice through clinical decision support. The EHR also enables the inverse experiment - starting with a genotype and discovering all the phenotypes with which it is associated - a phenome-wide association study (PheWAS). PheWAS requires a densely-phenotyped population such as found in the EHR. Dr. Denny's research team has used PheWAS to replicate more than 300 genotype-phenotype associations, characterize pleiotropy, and discover new associations. They have also used PheWAS to identify characteristics within disease subtypes.
Subjects: Biomedical Research
Datasets as Topic
Precision Medicine
Publication Types: Lecture
Webcast
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NLM Classification: WB 102
NLM ID: 101673091
CIT Live ID: 17452
Permanent link: https://videocast.nih.gov/watch=17452