| Literature DB >> 31957870 |
Leena Choi1, Cole Beck1, Elizabeth McNeer1, Hannah L Weeks1, Michael L Williams1, Nathan T James1, Xinnan Niu2, Bassel W Abou-Khalil3, Kelly A Birdwell4, Dan M Roden2,4,5, C Michael Stein4,5, Cosmin A Bejan2, Joshua C Denny2,4, Sara L Van Driest4,6.
Abstract
Postmarketing population pharmacokinetic (PK) and pharmacodynamic (PD) studies can be useful to capture patient characteristics affecting PK or PD in real-world settings. These studies require longitudinally measured dose, outcomes, and covariates in large numbers of patients; however, prospective data collection is cost-prohibitive. Electronic health records (EHRs) can be an excellent source for such data, but there are challenges, including accurate ascertainment of drug dose. We developed a standardized system to prepare datasets from EHRs for population PK/PD studies. Our system handles a variety of tasks involving data extraction from clinical text using a natural language processing algorithm, data processing, and data building. Applying this system, we performed a fentanyl population PK analysis, resulting in comparable parameter estimates to a prior study. This new system makes the EHR data extraction and preparation process more efficient and accurate and provides a powerful tool to facilitate postmarketing population PK/PD studies using information available in EHRs.Entities:
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Year: 2020 PMID: 31957870 PMCID: PMC7093250 DOI: 10.1002/cpt.1787
Source DB: PubMed Journal: Clin Pharmacol Ther ISSN: 0009-9236 Impact factor: 6.875