Citation:

Saunders, L. AND J. Nichols. Models Used to Predict Chemical Bioaccumulation in Fish from in Vitro Biotransformation Rates Require Accurate Estimates of Blood–Water Partitioning and Chemical Volume of Distribution. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, 42(1):33-45, (2023). https://doi.org/10.1002/etc.5503

Impact/Purpose:

In vitro biotransformation rates for fish may be extrapolated to the intact animal as a means of refining modeled bioaccumulation predictions for fish.  The accuracy of such extrapolations depends, in turn, on the accuracy of several extrapolation factors including estimated chemical blood-water partitioning (Pbw) and apparently volume of distribution (VD).  Empirical and composition-based algorithms for the prediction of Pbw and VD have been provided by several authors.  Currently, however, there is no consensus on which binding algorithms provide the best predictions.  The purpose of this paper was to show how different binding algorithms translate to differences in predicted Pbw and VD values, and by extension modeled bioconcentration factors (BCFs) for fish.  These different modeled BCFs are important because, depending on which binding algorithms are used, it is possible to reach different conclusions on whether a chemical does/does not exceed regulatory criteria for bioaccumulation assessment.  Concluding sections identify specific research needed to develop a preferred approach to the prediction of Pbw and VD values for fish.      

Description:

Methods for extrapolating measured in vitro intrinsic clearance to a whole-body biotransformation rate constant (kB) have been developed to support modeled bioaccumulation assessments for fish. The inclusion of extrapolated kB values into existing bioaccumulation models improves the prediction of chemical bioconcentration factors (BCFs), but there remains a tendency for these methods to overestimate BCFs relative to measured values. Therefore, a need exists to evaluate the extrapolation procedure to assess potential sources of error in predicted kB values. Here we examine how three different approaches (empirically-based, composition-based, and poly parameter linear free energy relationships [ppLFERs]) used to predict chemical partitioning in vitro (liver S9 system; KS9W), in blood (KBW), and in whole fish tissues (KFW) impact the prediction of a hepatic clearance binding term (fU) and a fish’s apparent volume of distribution (VD), both of which factor into the calculation of kB and the BCF. Each approach yielded different KS9W, KBW, and KFW values, but resulted in fU values that are of similar magnitude and remain relatively constant at log KOW >4. This is because KBW and KS9W values predicted by any given approach exhibit a similar dependence on log KOW (i.e., regression slope), which results in a cancelation of “errors” when fU is calculated. In contrast, differences in KBW values predicted by the three approaches translate to differences in VD, and by extension kB and the BCF, which become most apparent at log KOW >6. There is a need to collect KBW and VD data for hydrophobic chemicals in fish that can be used to evaluate and improve existing partitioning prediction approaches in extrapolation models for fish.

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