Modeling Exposure in the Tox21 in Vitro Bioassays

High-throughput in vitro bioassays are becoming increasingly important in the risk characterization of anthropogenic chemicals. Large databases gather nominal effect concentrations (C_nom) for diverse modes of action. However, the biologically effective concentration can substantially deviate due to differences in chemical partitioning. In this study, we modeled freely dissolved (C_free), cellular (C_cell), and membrane concentrations (C_mem) in the Tox21 GeneBLAzer bioassays for a set of neutral and ionogenic organic chemicals covering a large physicochemical space. Cells and medium constituents were experimentally characterized for their lipid and protein content, and partition constants were either collected from the literature or predicted by mechanistic models. The chemicals exhibited multifaceted partitioning to proteins and lipids with distribution ratios spanning over 8 orders of magnitude. Modeled C_free deviated over 5 orders of magnitude from C_nom and can be compared to in vivo effect data, environmental concentrations, and the unbound fraction in plasma, which is needed for the in vitro to in vivo extrapolation. C_cell was relatively constant for chemicals with membrane lipid-water distribution ratios of 1000 or higher and proportional to C_nom. Representing a sum parameter for exposure that integrates the entire dose from intracellular partitioning, C_cell is particularly suitable for the effect characterization of chemicals with multiple target sites and the calculation of their relative effect potencies. Effective membrane concentrations indicated that the specific effects of very hydrophobic chemicals in multiple bioassays are occurring at concentrations close to baseline toxicity. The equilibrium partitioning model including all relevant system parameters and a generic bioassay setup is attached as an excel workbook to this paper and can readily be applied to diverse in vitro bioassays.