Development of a System for Postmarketing Population Pharmacokinetic and Pharmacodynamic Studies Using Real‐World Data From Electronic Health Records
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.
Citing Literature
Number of times cited according to CrossRef: 2
- Richard W. Peck, Pratik Shah, Spiros Vamvakas, Piet H. Graaf, Data Science in Clinical Pharmacology and Drug Development for Improving Health Outcomes in Patients, Clinical Pharmacology & Therapeutics, 10.1002/cpt.1803, 107, 4, (683-686), (2020).
- Shin J. Liau, Samanta Lalic, Janet K. Sluggett, Matteo Cesari, Graziano Onder, Davide L. Vetrano, Lucas Morin, Sirpa Hartikainen, Aleksi Hamina, Kristina Johnell, Edwin C.K. Tan, Renuka Visvanathan, J. Simon Bell, Medication Management in Frail Older People: Consensus Principles for Clinical Practice, Research, and Education, Journal of the American Medical Directors Association, 10.1016/j.jamda.2020.05.004, (2020).




