QuantitativeIn Vitro-to-In VivoExtrapolation for Mixtures: A Case Study of Superfund Priority List Pesticides

Abstract

In vitro cell-based toxicity testing methods generate large amounts of data informative for risk-based evaluations. To allow extrapolation of the quantitative outputs from cell-based tests to the equivalent exposure levels in humans, reverse toxicokinetic (RTK) modeling is used to conduct in vitro-to-in vivo extrapolation (IVIVE) from in vitro effective concentrations to in vivo oral dose equivalents. IVIVE modeling approaches for individual chemicals are well-established; however, the potential implications of chemical-to-chemical interactions in mixture settings on IVIVE remains largely unexplored. We hypothesized that chemical co-exposures could modulate both protein binding efficiency and hepatocyte clearance of the chemicals in a mixture, which would in turn affect the quantitative IVIVE toxicokinetic parameters. To test this hypothesis, we used 20 pesticides from the Agency for Toxic Substances and Disease Registry (ATSDR) Substance Priority List, both individually and as equimolar mixtures, and investigated the concentration-dependent effects of chemical interactions on in vitro toxicokinetic parameters. Plasma protein binding efficiency was determined by using ultracentrifugation, and hepatocyte clearance was estimated in suspensions of cryopreserved primary human hepatocytes. We found that for single chemicals, the protein binding efficiencies were similar at different test concentrations. In a mixture, however, both protein binding efficiency and hepatocyte clearance were affected. When IVIVE was conducted using mixture-derived toxicokinetic data, more conservative estimates of Activity-to-Exposure Ratios (AERs) were produced as compared to using data from single chemical experiments. Because humans are exposed to mixtures of chemicals, this study is significant as it demonstrates the importance of incorporating mixture-derived parameters into IVIVE for in vitro bioactivity data in order to accurately prioritize risks and facilitate science-based decision-making.

Cumulative Risk Meets Inter-Individual Variability: Probabilistic Concentration Addition of Complex Mixture Exposures in a Population-Based Human In Vitro Model

“…Lymphoblastoid cells are useful because they are relatively easy to culture and demonstrate comparable results to iPSC-derived models, which are known as reliable human cell types for in silico studies; further, they can be used to study population variability as an alternative to iPSC-derived models. Further, the lymphoblast cell line model is promising for the quantification of inter-individual differences for risk assessment, which has largely been limited to using a default uncertainty factor of 3 or 10, despite its importance in dose–response assessment to protect the sensitive population for risk-based decision making [ 45 , 46 , 70 ]. Of importance in our study is that we used 42 ATSDR priority list chemicals that do not necessarily share the same mode of action.…”

“…Finally, it may be that our findings of possible greater-than-additive effects, in many cases, might reflect in vitro bioavailability in a mixture context, such as saturation of binding in the presence of a mixture [ 70 ]. Moreover, if protein binding is an issue, differences in protein content across different media types, as compared to human plasma, will make it challenging to extrapolate these data to in vivo.…”

“…Nonetheless, to assess the sensitivity of our results to saturation in bioavailability, we recalculated the individual-level CA truncating all PODs at the concentration corresponding to saturation ( Supplemental Figure S3 ), and found patterns nearly identical to our primary results in Figure 2 . It is possible that more sophisticated bioavailability calculations or measurements, including those in a mixture setting, would improve the performance of CA, as we have previously shown that plasma protein binding changes in a mixture setting compared to individual-chemical settings [ 70 ].…”

Evaluation of Metabolism of a Defined Pesticide Mixture through Multiple In Vitro Liver Models

“…Suspension assays using iHep were performed as previously detailed [ 34 ] with slight modification. In brief, pre-differentiated iHep were suspended in iHep maintenance media and adjusted to the cell concentration of 1 × 10 6 cells/mL.…”

IVIVE: Facilitating the Use of In Vitro Toxicity Data in Risk Assessment and Decision Making

“…Abdo and colleagues applied IVIVE to convert in vitro cytotoxic concentrations to OEDs for two pesticide mixtures with similar ranges of in vitro cytotoxicity and identified nominal differences in the margins of safety, suggesting the necessity of including IVIVE and potential human exposures in risk evaluation [ 162 ]. Valdiviezo and colleagues investigated the concentration-dependent effects of chemical interactions on toxicokinetic parameters using 20 pesticides (both individually and as equimolar mixtures) and observed that IVIVE using mixture-derived toxicokinetic data produced more conservative estimates of activity-to-exposure ratios as compared to using data from single chemical experiments [ 165 ].…”