Abstract

This study demonstrates the utility of an updated mass balance model for predicting the distribution of organic chemicals in in vitro test systems (IV-MBM EQP v2.0) and evaluates its performance with empirical data. The IV-MBM EQP v2.0 tool was parameterized and applied to four independent data sets with measured ratios of bulk medium or freely-dissolved to initial nominal concentrations (e.g., C24/C0 where C24 is the measured concentration after 24 h of exposure and C0 is the initial nominal concentration). Model performance varied depending on the data set, chemical properties (e.g., “volatiles” vs. “non-volatiles”, neutral vs. ionizable organics), and model assumptions but overall is deemed acceptable. For example, the r2 was greater than 0.8 and the mean absolute error (MAE) in the predictions was less than a factor of two for most neutral organics included. Model performance was not as good for the ionizable organic chemicals included but the r2 was still greater than 0.7 and the MAE less than a factor of three. The IV-MBM EQP v2.0 model was subsequently applied to several hundred chemicals on Canada’s Domestic Substances List (DSL) with nominal effects data (AC50s) reported for two in vitro assays. We report the frequency of chemicals with AC50s corresponding to predicted cell membrane concentrations in the baseline toxicity range (i.e., >20–60 mM) and tabulate the number of chemicals with “volatility issues” (majority of chemical in headspace) and “solubility issues” (freely-dissolved concentration greater than water solubility after distribution). In addition, the predicted “equivalent EQP blood concentrations” (i.e., blood concentration at equilibrium with predicted cellular concentration) were compared to the AC50s as a function of hydrophobicity (log octanol-water partition or distribution ratio). The predicted equivalent EQP blood concentrations exceed the AC50 by up to a factor of 100 depending on hydrophobicity and assay conditions. The implications of using AC50s as direct surrogates for human blood concentrations when estimating the oral equivalent doses using a toxicokinetic model (i.e., reverse dosimetry) are then briefly discussed.

Highlights

  • To address the fact that experimental dose confirmation is not always feasible, various researchers have developed and applied mass balance models to simulate the distribution of organic chemicals in in vitro test systems [17,18,19,20,21,22,23,24]

  • Casey et al found that the predictive performance of their extrapolation approaches was significantly improved by adjusting in vitro bioactivity data using the cellular Enrichment Factor (EF, ratio of predicted cell concentration to nominal medium concentration) generated by the in vitro distribution model described by Armitage et al [18]

  • Availability and suitability, any of the other in vitro distribution models published in the literature could be considered

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Summary

Introduction

The ToxCast program (https://www.epa.gov/chemical-research/toxicity-forecasting) has generated in vitro data for thousands of chemicals across hundreds of different assays and assay endpoints [1,2]. A major challenge with the interpretation and application of in vitro toxicity test data is the typical practice of using nominal (administered) bulk medium concentrations to report the dose associated with responses instead of more directly relevant metrics such as the freely-dissolved or cellular concentration [3,4,5,6,7,8,9,10,11,12,13,14,15].

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