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.

Transfer of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) and polychlorinated biphenyls (PCBs) from oral exposure into cow’s milk – part II: toxicokinetic predictive models for risk assessment

“…soil, grass, gelatine capsule) but also on the concentration itself as shown for pigs in Savvateeva et. al (2020) (16) . From eqns.…”

Transfer of Per- and Polyfluoroalkyl Substances (PFAS) from Feed into the Eggs of Laying Hens. Part 2: Toxicokinetic Results Including the Role of Precursors

“…By plotting a time series of the yolk concentration for each quantified PFAS before modeling (see the plot of experimental data, the symbols in Figure ) on a semi-log- y plot, the apparent quasi-linear behavior during the depuration phase (days 25–67) is a mathematical signature of a single-exponential decay behavior. This is in turn equivalent to a one-compartment model, which physiologically means that no significant amount of the quantified PFAS seems to be distributed to a slower or kinetically separated second compartment (the way it happens with, e.g., polychlorinated biphenyls or PCDD/Fs).…”

Current Approaches and Techniques in Physiologically Based Pharmacokinetic (PBPK) Modelling of Nanomaterials

“…An approach for the estimation of adipose/blood partition coefficients through QSAR for 67 environmental chemicals, which was also used for gap filling of the logP (adipose/blood) data for 513 chemicals from the US EPA, was reported by Jean et al [ 143 ]. Quantitative property-property relationships (QPPRs) have been applied to the high-throughput prediction of internal dose of inhaled organic chemicals in PBPK models [ 144 ], while physiologically based toxicokinetic (PBTK) model parameters have been calculated by Sarigiannis et al [ 145 ] and Savvateeva et al [ 146 ]. Research specific to parameters of nanomaterial PBPK models is less common but increasing—a method combining an artificial intelligence-based cell simulation and a calibrated fluorescence assay that quantifies rate constant for biological interactions between NMs and individual cells is proposed by Price and Gesquiere [ 147 ].…”