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Toxicokinetic Triage for Environmental Chemicals
Citation:
Wambaugh, J., B. Wetmore, R. Pearce, C. Strope, R. Goldsmith, J. Sluka, A. Sedykh, A. Tropsha, S. Bosgra, I. Shah, R. Judson, R. Thomas, AND Woodrow Setzer. Toxicokinetic Triage for Environmental Chemicals. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 147(1):55-67, (2015).
Impact/Purpose:
For the thousands of man-made chemicals in the environment that currently have no TK data, we propose a framework for chemical TK triage, guided by confidence in HTTK model predictions.
Description:
Toxicokinetic (TK) models are essential for linking administered doses to blood and tissue concentrations. In vitro-to-in vivo extrapolation (IVIVE) methods have been developed to determine TK from limited in vitro measurements and chemical structure-based property predictions, providing a less resource–intensive alternative to traditional in vivo TK approaches. High throughput TK (HTTK) methods use IVIVE to estimate doses that produce steady-state plasma concentrations equivalent to those producing biological activity in in vitro screening studies (e.g., ToxCast). In this study, the domain of applicability and assumptions of HTTK approaches were evaluated using both in vivo data and simulation analysis. Based on in vivo data for 87 chemicals, specific properties (e.g., in vitro HTTK data, physico-chemical descriptors, chemical structure, and predicted transporter affinities) were identified that correlate with poor HTTK predictive ability. For 350 xenobiotics with literature HTTK data, we then differentiated those xenobiotics for which HTTK approaches are likely to be sufficient, from those that may require additional data. For 272 chemicals we also developed a HT physiologically-based TK (HTPBTK) model that requires somewhat greater information than a steady-state model, but allows non-steady state dynamics and can predict chemical concentration time-courses for a variety of exposure scenarios, tissues, and species. We used this HTPBTK model to show that the assumptions previously used for IVIVE are appropriate, except for highly bioaccumulative compounds. For the thousands of man-made chemicals in the environment that currently have no TK data, we propose a framework for chemical TK triage, guided by confidence in HTTK model predictions.
