Data Integration and Pharmacokinetic Model Testing for Selected PFAS

Physiological variation, sex-specific differences in per- and polyfluoroalkyl substances (PFAS) clearance, and disparate numerical fitting methodologies can result in large differences in reported among pharmacokinetic (PK) parameters, making cross-species extrapolation difficult. Using PFAS data from multiple sources, we present statistical methods for pooling these data to determine pharmacokinetic paramters for multiple PFAS. We also highlight the ability to test multiple hypotheses for PHAS pharmacokinetics based on the observed data for six PFAS: PFHxA, PFHxS, PFNA, PFDA, PFBS, and PFBA in rats. Using a hierarchical Bayesian approach, we generate distribution estimates of key PK parameters and compare model hypotheses to describe observed differences in PFAS pharmacokinetics.

Impact/Purpose

Using PFAS data from multiple sources, we present statistical methods for pooling these data to determine pharmacokinetic paramters for multiple PFAS. This presentation also highlights the ability to test multiple hypotheses for PHAS pharmacokinetics based on the observed data.

Citation

Zurlinden, T., P. Schlosser, D. Kapraun, M. Dzierlenga, A. Bernstein, AND V. Morozov. Data Integration and Pharmacokinetic Model Testing for Selected PFAS. Considerations of Development of DOD Exposure Limits for Current PFAS Compounds, NA, NC, July 21, 2022.