Assessing Toxicokinetic Uncertainty and Variability in Risk Prioritization. (18th September 2019)

• Record Type: Journal Article
• Authors: Wambaugh, John F; Wetmore, Barbara A; Ring, Caroline L; Nicolas, Chantel I; Pearce, Robert G; Honda, Gregory S; Dinallo, Roger; Angus, Derek; Gilbert, Jon; Sierra, Teresa; Badrinarayanan, Akshay; Snodgrass, Bradley; Brockman, Adam; Strock, Chris; Setzer, R Woodrow; Thomas, Russell S
• Is Part Of: Toxicological sciences. Volume 172:Number 2(2019)
• Page Start: 235
• Page End: 251
• Publication Date: 2019-09-18
• Subjects: toxicokinetics -- high throughput -- Bayesian modeling -- uncertainty -- variability -- IVIVE; Toxicology -- Periodicals; Toxicology -- Periodicals; Toxicology; Periodicals; 615.9
• DOI: 10.1093/toxsci/kfz205
• Languages: English
• ISSNs: 1096-6080

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 ( f up ) and intrinsic hepatic clearance (Clint ). New experimental measurements of f up 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 f up 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 f up too low to measure from 44% to 9.1%. Uncertainty in f up 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.