Physiologically based toxicokinetic models and in silico predicted partition coefficients to estimate tetrachlorodibenzo-p-dioxin transfer from feed into growing pigs

Abstract

Tetrachlorodibenzo- p -dioxin (TCDD) is a ubiquitous, toxic, persistent and bioaccumulative organic pollutant. TCDD can potentially enter the food chain through contaminated food of animal origin as a consequence of feed contamination. Prediction of the TCDD transfer from feed into animal products is thus important for human health risk assessment. Here, we develop several physiologically based toxicokinetic (PBTK) models of TCDD transfer from contaminated feed into growing pigs ( Sus scrofa ) exposed to doses ranging from 24.52 to 3269.25 ng of TCDD. We test the consequences of explicit dose-dependent absorption (DDA) versus the indirect effects of a self-induced liver metabolism (SIM). The DDA and SIM models showed similar fit to experimental data, although currently it is not possible to unequivocally make statement on a mechanistic preference. The performance of both toxicokinetic models was successfully evaluated using the 1999 Belgian case of contaminated fats for feeding. In combination with toxicokinetic models of other dioxin congeners, they can be used to formulate maximum allowance levels of dioxins in feedstuffs for pigs. Additionally, the implementation of in silico-predicted partition coefficients was explored as a useful alternative to predict TCDD tissue distribution in low-dose scenarios without recurring to animal experiments.

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