Examining underlying assumptions when translating in vitro bioassay results to in vivo conditions

摘要

In vitro testing is creating information that can be used to improve mechanistic understanding of toxicity pathways and for chemical assessments. The data can be used for hazard-based prioritization or they can be combined with exposure data for risk-based prioritization. Chemical potency comparisons require a consistent exposure metric ("x-axis") corresponding to the observed response ("y-axis"). Translating chemical concentrations from one system under specific conditions to a different system with different conditions requires consistent metrics and units. For example, the corroboration of in vitro data with in vivo data and comparisons of exposure and hazard concentrations for risk estimation require consideration of various sub-phase volumes and their sorptive capacities as well as chemical property information, e.g. partition coefficients. The freely dissolved concentration (Cfree; nmol/L) has been proposed as a relevant metric to translate concentrations across and within systems (e.g., blood-tissues). The objectives of this study were to examine commonly applied assumptions (e.g., Cblood, in vivo = Cnominal, in vitro) and alternative assumptions when translating in vitro bioassay results to in vivo conditions. Mass balance models and equilibrium partitioning theory were used to examine assumptions for translating in vitro test assay data to in vivo systems. A series of representative in vitro bioassay conditions are simulated with a suite of neutral hypothetical chemicals capturing a relevant range of partitioning properties (e.g. octanol-water partition coefficient, Kow). The first in vitro system (1) represents a cell-free assay. The second in vitro system (2) represents a cell-based test in which no serum is present during the test assay and the third in vitro system (3) represents a cell-based test in which 10% serum is present during the test assay. Differences in Cfree and Cblood / Cnom are relatively small for lower Kow chemicals (log Kow < 2) independent of the assay. However, as Kow increases, Cfree decreases. All else being equal, i.e., the magnitude of response in the assay for Cnom is the same for all chemicals, the higher Kow chemicals appear to be more potent than the lower Kow chemicals because they elicit the same response at lower Cfree. The difference in Cfree can be as much as 4-5 orders of magnitude lower. Extending the translation to Cblood and comparing against Cnom, the opposite interpretation would be made, i.e., the hydrophobic chemicals appear to be "less potent" because the concentration in blood required to elicit the same response in vitro (i.e., Cnom) is higher.