Dynamic Mass Balance Modeling for Chemical Distribution Over Time in In Vitro Systems With Repeated Dosing - Bloch, Sherri; Arnot, Jon A.; Kramer, Nynke I.; Armitage, James M.; Verner, Marc-André (Frontiers in Toxicology, 2022)
As toxicologists and risk assessors move away from animal testing and more toward using in vitro models and biological modeling, it is necessary to produce tools to quantify the chemical distribution within the in vitro environment prior to extrapolating in vitro concentrations to human equivalent doses. Although models predicting chemical distribution in vitro have been developed, very little has been done for repeated dosing scenarios, which are common in prolonged experiments where the medium needs to be refreshed. Failure to account for repeated dosing may lead to inaccurate estimations of exposure and introduce bias into subsequent in vitro to in vivo extrapolations. Our objectives were to develop a dynamic mass balance model for repeated dosing in in vitro systems; to evaluate model accuracy against experimental data; and to perform illustrative simulations to assess the impact of repeated doses on predicted cellular concentrations. A novel dynamic in vitro partitioning mass balance model (IV-MBM DP v1.0) was created based on the well-established fugacity approach. We parameterized and applied the dynamic mass balance model to single dose and repeat dosing scenarios, and evaluated the predicted medium and cellular concentrations against available empirical data. We also simulated repeated dosing scenarios for organic chemicals with a range of partitioning properties and compared the in vitro distributions over time. In single dose scenarios, for which only medium concentrations were available, simulated concentrations predicted measured concentrations with coefficients of determination (R2) of 0.85-0.89, mean average error within a factor of two and model bias of nearly one. Repeat dose scenario simulations displayed model bias < 2 within the cell lysate, and ~1.5-3 in the medium. The concordance between simulated and available experimental data supports the predictive capacity of the IV-MBM DP v1.0 tool, but further evaluation as empirical data becomes available is warranted, especially for cellular concentrations.