Evaluation and Optimization of Pharmacokinetic Models for to Extrapolation of Estrogenic Activity for Environmental Chemicals.

BACKGROUND

To effectively incorporate data into regulatory use, confidence must be established in the quantitative extrapolation of activity to relevant end points in animals or humans.

OBJECTIVE

Our goal was to evaluate and optimize to extrapolation (IVIVE) approaches using in vitro estrogen receptor (ER) activity to predict estrogenic effects measured in rodent uterotrophic studies.

METHODS

We evaluated three pharmacokinetic (PK) models with varying complexities to extrapolate to dosimetry for a group of 29 ER agonists, using data from validated [U.S. Environmental Protection Agency (U.S. EPA) ToxCast™ ER model] and (uterotrophic) methods. activity values were adjusted using mass-balance equations to estimate intracellular exposure via an enrichment factor (EF), and steady-state model calculations were adjusted using fraction of unbound chemical in the plasma ([Formula: see text]) to approximate bioavailability. Accuracy of each model-adjustment combination was assessed by comparing model predictions with lowest effect levels (LELs) from guideline uterotrophic studies.

RESULTS

We found little difference in model predictive performance based on complexity or route-specific modifications. Simple adjustments, applied to account for intracellular exposure (EF) or chemical bioavailability ([Formula: see text]), resulted in significant improvements in the predictive performance of all models.

CONCLUSION

Computational IVIVE approaches accurately estimate chemical exposure levels that elicit positive responses in the rodent uterotrophic bioassay. The simplest model had the best overall performance for predicting both oral (PPK_EF) and injection (PPK_[Formula: see text]) LELs from guideline uterotrophic studies, is freely available, and can be parameterized entirely using freely available tools. https://doi.org/10.1289/EHP1655.