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The Influence of Obesity on the Pharmacokinetics of Dioxin in Mice: An Assessment Using Classical and PBPK Modeling.

ABSTRACT: The effects of body fat mass on the elimination of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) was examined in mice. When male C57BL/6J mice are fed a high-fat, simple carbohydrate diet (HFD) for 13 weeks, they develop an obese phenotype. In contrast, A/J mice fed an HFD do not become obese. After 13 weeks on a normal diet (ND) or HFD, male C57BL/6J and A/J mice received a single dose by gavage of 0.1 or 5.0 µg of 2,3,7,8-tetrachloro[1,6-3H] dibenzo-p-dioxin per kg body weight. Using classical pharmacokinetics, the blood elimination half-life of TCDD was approximately 10 and 2 times longer in the C57BL/6J on the HFD compared with the mice on the ND at 0.1 and 5.0 μg/kg doses, respectively. The diet did not increase the blood half-life of TCDD in the A/J mice, which did not get obese. Using a physiologically based pharmacokinetic model for TCDD that incorporated experimentally derived percent body fat mass and tissue partition coefficients, as well as data on hepatic sequestration, did not provide accurate predictions to the data and could not explain the increase in half-life of TCDD in the HFD groups. This work demonstrates that obesity influences the half-life of TCDD, but other undetermined factors are involved in its elimination because the increase in body fat mass, decreases in cytochrome P4501A2, and altered partition coefficients could not completely explain the prolonged half-life.

SUBMITTER: Emond C

PROVIDER: S-EPMC6016688 | biostudies-other | 2018 Jul

REPOSITORIES: biostudies-other

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The Influence of Obesity on the Pharmacokinetics of Dioxin in Mice: An Assessment Using Classical and PBPK Modeling.

Emond Claude C DeVito Michael J MJ Diliberto Janet J JJ Birnbaum Linda S LS

Toxicological sciences : an official journal of the Society of Toxicology 20180701 1

The effects of body fat mass on the elimination of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) was examined in mice. When male C57BL/6J mice are fed a high-fat, simple carbohydrate diet (HFD) for 13 weeks, they develop an obese phenotype. In contrast, A/J mice fed an HFD do not become obese. After 13 weeks on a normal diet (ND) or HFD, male C57BL/6J and A/J mice received a single dose by gavage of 0.1 or 5.0 µg of 2,3,7,8-tetrachloro[1,6-3H] dibenzo-p-dioxin per kg body weight. Using classical ph ...[more]

PMID: 29596651

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Project description:PurposeInter-individual variability in clinical endpoints and occurrence of potentially severe adverse effects represent an enormous challenge in drug development at all phases of (pre-)clinical research. To ensure patient safety it is important to identify adverse events or critical subgroups within the population as early as possible. Hence, a comprehensive understanding of the processes governing pharmacokinetics and pharmacodynamics is of utmost importance. In this paper we combine Bayesian statistics with detailed mechanistic physiologically-based pharmacokinetic (PBPK) models. On the example of pravastatin we demonstrate that this combination provides a powerful tool to investigate inter-individual variability in groups of patients and to identify clinically relevant homogenous subgroups in an unsupervised approach. Since PBPK models allow the identification of physiological, drug-specific and genotype-specific knowledge separately, our approach supports knowledge-based extrapolation to other drugs or populations.MethodsPBPK models are based on generic distribution models and extensive collections of physiological parameters and allow a mechanistic investigation of drug distribution and drug action. To systematically account for parameter variability within patient populations, a Bayesian-PBPK approach is developed rigorously quantifying the probability of a parameter given the amount of information contained in the measured data. Since these parameter distributions are high-dimensional, a Markov chain Monte Carlo algorithm is used, where the physiological and drug-specific parameters are considered in separate blocks.ResultsConsidering pravastatin pharmacokinetics as an application example, Bayesian-PBPK is used to investigate inter-individual variability in a cohort of 10 patients. Correlation analyses infer structural information about the PBPK model. Moreover, homogeneous subpopulations are identified a posteriori by examining the parameter distributions, which can even be assigned to a polymorphism in the hepatic organ anion transporter OATP1B1.ConclusionsThe presented Bayesian-PBPK approach systematically characterizes inter-individual variability within a population by updating prior knowledge about physiological parameters with new experimental data. Moreover, clinically relevant homogeneous subpopulations can be mechanistically identified. The large scale PBPK model separates physiological and drug-specific knowledge which allows, in combination with Bayesian approaches, the iterative assessment of specific populations by integrating information from several drugs.

Dataset Information

The Influence of Obesity on the Pharmacokinetics of Dioxin in Mice: An Assessment Using Classical and PBPK Modeling.

Publications

The Influence of Obesity on the Pharmacokinetics of Dioxin in Mice: An Assessment Using Classical and PBPK Modeling.

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