Comparative Analysis of Chemical Distribution Models for Quantitative In Vitro to In Vivo Extrapolation

Quantitative in vitro to in vivo extrapolation (QIVIVE) utilizes in vitro data to predict in vivo toxicity. However, there may be differences between reported nominal concentrations and the biologically effective free concentrations in media or cells. This study evaluated the performance of four in vitro mass balance models for predicting free media or cellular concentrations. Comparing model predictions to experimentally measured values for a wide range of chemicals and test systems, we found that predictions of media concentrations were more accurate than those for cells, and that the Armitage model had slightly better performance overall. Through sensitivity analyses, we found that chemical property-related parameters were most influential for media predictions, while cell-related parameters were also important for cellular predictions. Assessing the impact of these models on QIVIVE accuracy for a small dataset of 15 chemicals with both in vitro and regulatory in vivo points-of-departure, we found that incorporating in vitro and in vivo bioavailability resulted in at best modest improvements to in vitro-in vivo concordance. Based on these results, we conclude that a reasonable first-line approach for incorporating in vitro bioavailability into QIVIVE would be to use the Armitage model to predict media concentrations, while prioritizing accurate chemical property data as input parameters.