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Toxicol Sci. 2015 Sep;147(1):55-67. doi: 10.1093/toxsci/kfv118. Epub 2015 Jun 16.

Toxicokinetic Triage for Environmental Chemicals.

Author information

*National Center for Computational Toxicology and
The Hamner Institutes for Health Sciences, Research Triangle Park, North Carolina 27709-2137;
*National Center for Computational Toxicology and.
*National Center for Computational Toxicology and Oak Ridge Institute for Science and Education Grantee P.O. Box 117, Oak Ridge, Tennessee 37831-0117, United States;
National Exposure Research Laboratory, Office of Research and Development, US EPA, Research Triangle Park, North Carolina 27711;
Biocomplexity Institute, Indiana University, Bloomington, Indiana 47405-7105;
Department of Chemical Biology and Medicinal Chemistry, University of North Carolina, Chapel Hill, North Carolina 27955-7568; and.
The Netherlands Organisation for Applied Scientific Research (TNO), 3700 AJ Zeist, The Netherlands.


Toxicokinetic (TK) models link administered doses to plasma, blood, and tissue concentrations. High-throughput TK (HTTK) performs in vitro to in vivo extrapolation to predict TK from rapid in vitro measurements and chemical structure-based properties. A significant toxicological application of HTTK has been "reverse dosimetry," in which bioactive concentrations from in vitro screening studies are converted into in vivo doses (mg/kg BW/day). These doses are predicted to produce steady-state plasma concentrations that are equivalent to in vitro bioactive concentrations. In this study, we evaluate the impact of the approximations and assumptions necessary for reverse dosimetry and develop methods to determine whether HTTK tools are appropriate or may lead to false conclusions for a particular chemical. Based on literature in vivo data for 87 chemicals, we identified specific properties (eg, in vitro HTTK data, physico-chemical descriptors, and predicted transporter affinities) that correlate with poor HTTK predictive ability. For 271 chemicals we developed a generic HT physiologically based TK (HTPBTK) model that predicts non-steady-state chemical concentration time-courses for a variety of exposure scenarios. We used this HTPBTK model to find that assumptions previously used for reverse dosimetry are usually appropriate, except most notably for highly bioaccumulative compounds. For the thousands of man-made chemicals in the environment that currently have no TK data, we propose a 4-element framework for chemical TK triage that can group chemicals into 7 different categories associated with varying levels of confidence in HTTK predictions. For 349 chemicals with literature HTTK data, we differentiated those chemicals for which HTTK approaches are likely to be sufficient, from those that may require additional data.


IVIVE; environmental chemicals; high throughput; toxicokinetics

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