Assessing Toxicokinetic Uncertainty and Variability in Risk Prioritization

Author:

Wambaugh John F1ORCID,Wetmore Barbara A2,Ring Caroline L134ORCID,Nicolas Chantel I135,Pearce Robert G13,Honda Gregory S13,Dinallo Roger6,Angus Derek6,Gilbert Jon6,Sierra Teresa6,Badrinarayanan Akshay6,Snodgrass Bradley6,Brockman Adam6,Strock Chris6,Setzer R Woodrow1,Thomas Russell S1ORCID

Affiliation:

1. National Center for Computational Toxicology

2. National Exposure Research Laboratory, Office of Research and Development, U.S. EPA, Research Triangle Park, North Carolina 27711

3. Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee 37831

4. ToxStrategies, Austin, TX 78759

5. Office of Pollution Prevention and Toxics, U.S. EPA, Washington, District of Columbia 20460

6. Cyprotex US, LLC, Watertown, Massachusetts 02472

Abstract

Abstract High(er) throughput toxicokinetics (HTTK) encompasses in vitro measures of key determinants of chemical toxicokinetics and reverse dosimetry approaches for in vitro-in vivo extrapolation (IVIVE). With HTTK, the bioactivity identified by any in vitro assay can be converted to human equivalent doses and compared with chemical intake estimates. Biological variability in HTTK has been previously considered, but the relative impact of measurement uncertainty has not. Bayesian methods were developed to provide chemical-specific uncertainty estimates for 2 in vitro toxicokinetic parameters: unbound fraction in plasma (fup) and intrinsic hepatic clearance (Clint). New experimental measurements of fup and Clint are reported for 418 and 467 chemicals, respectively. These data raise the HTTK chemical coverage of the ToxCast Phase I and II libraries to 57%. Although the standard protocol for Clint was followed, a revised protocol for fup measured unbound chemical at 10%, 30%, and 100% of physiologic plasma protein concentrations, allowing estimation of protein binding affinity. This protocol reduced the occurrence of chemicals with fup too low to measure from 44% to 9.1%. Uncertainty in fup was also reduced, with the median coefficient of variation dropping from 0.4 to 0.1. Monte Carlo simulation was used to propagate both measurement uncertainty and biological variability into IVIVE. The uncertainty propagation techniques used here also allow incorporation of other sources of uncertainty such as in silico predictors of HTTK parameters. These methods have the potential to inform risk-based prioritization based on the relationship between in vitro bioactivities and exposures.

Funder

Oak Ridge Institute for Science and Education

Publisher

Oxford University Press (OUP)

Subject

Toxicology

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