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Simulating toxicokinetic variability to identify susceptible and highly exposed populations

Journal of Exposure Science & Environmental Epidemiology volume 32, pages 855–863 (2022)Cite this article

Abstract

Background

Toxicokinetic (TK) data needed for chemical risk assessment are not available for most chemicals. To support a greater number of chemicals, the U.S. Environmental Protection Agency (EPA) created the open-source R package “httk” (High Throughput ToxicoKinetics). The “httk” package provides functions and data tables for simulation and statistical analysis of chemical TK, including a population variability simulator that uses biometrics data from the National Health and Nutrition Examination Survey (NHANES).

Objective

Here we modernize the “HTTK-Pop” population variability simulator based on the currently available data and literature. We provide explanations of the algorithms used by “httk” for variability simulation and uncertainty propagation.

Methods

We updated and revised the population variability simulator in the “httk” package with the most recent NHANES biometrics (up to the 2017–18 NHANES cohort). Model equations describing glomerular filtration rate (GFR) were revised to more accurately represent physiology and population variability. The model output from the updated “httk” package was compared with the current version.

Results

The revised population variability simulator in the “httk” package now provides refined, more relevant, and better justified estimations.

Significance

Fulfilling the U.S. EPA’s mission to provide open-source data and models for evaluations and applications by the broader scientific community, and continuously improving the accuracy of the “httk” package based on the currently available data and literature.

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Fig. 1: Overview of the key functions involved in Monte Carlo uncertainty and variability simulation in “httk”.
Fig. 2: Representation of “httk” PBTK model structure.
Fig. 3: Evaluation of PBTK GFR racial factor correction.
Fig. 4: Evaluation of PBTK GFR physiological model revision.
Fig. 5: Evaluation of physico-chemical properties update.
Fig. 6: Evaluation of NHANES biometrics update.

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Data availability

The data from this study are provided within the article and its Supplementary Files.

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Acknowledgements

The authors thank Drs. Xiaoqing Chang and Kristin Eccles for their helpful U.S. EPA internal reviews of the manuscript. We greatly appreciate Dr. Sarah Davidson-Fritz for support with software engineering for the “httk” R package. We thank Drs. Peter Egeghy and Risa Sayre for useful conversations. Although the manuscript was reviewed by the US EPA and approved for publication, it may not necessarily reflect official Agency policy. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.

Funding

The United States Environmental Protection Agency (EPA) through its Office of Research and Development (ORD) funded the research described here. This project was supported by appointments to the Internship/Research Participation Program at ORD and administered by the Oak Ridge Institute for Science and Education through an interagency agreement between the U.S. Department of Energy and U.S. EPA.

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Authors and Affiliations

  1. Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Research Triangle Park, NC, USA

    Miyuki Breen, John F. Wambaugh & Caroline L. Ring

  2. Oak Ridge Institute for Science and Education (ORISE) fellow at the Center for Public Health and Environmental Assessment, Research Triangle Park, NC, USA

    Amanda Bernstein

  3. Oak Ridge Institute for Science and Education (ORISE) fellow at the Center for Computational Toxicology and Exposure, Research Triangle Park, NC, USA

    Mark Sfeir

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  1. Miyuki Breen
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Contributions

Conceptualization, methodology, investigation, writing: MB, JFW, AB, MS, and CLR; software, data curation, validation, and formal analysis, project administration: MB, JFW, and CLR. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Caroline L. Ring.

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Breen, M., Wambaugh, J.F., Bernstein, A. et al. Simulating toxicokinetic variability to identify susceptible and highly exposed populations. J Expo Sci Environ Epidemiol 32, 855–863 (2022). https://doi.org/10.1038/s41370-022-00491-0

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