Development of an integrated multi-species and multi-dose route PBPK model for volatile methyl siloxanes – D4 and D5

AbstractThere are currently seven published physiologically based pharmacokinetic (PBPK) models describing aspects of the pharmacokinetics of octamethylcyclotetrasiloxane (D4) and decamethylcyclopentasiloxane (D5) for various exposure routes in rat and human. Each model addressed the biological and physico-chemical properties of D4 and D5 (highly lipophilic coupled with low blood: air partition coefficient and high liver clearance) that result in unique kinetic behaviors as well differences between D4 and D5. However, the proliferation of these models resulted in challenges for various risk assessment applications when needing to determine the optimum model for estimating dose metrics. To enhance the utility of these PBPK models for risk assessment, we integrated the suite of structures into one coherent model capable of simulating the entire set of existing data equally well as older more limited scope models. In this paper, we describe the steps required to develop this integrated model, the choice of physiological, partitioning and biochemical parameters for the model, and the concordance of the model behavior across key data sets. This integrated model is sufficiently robust to derive relevant dose metrics following individual or combined dermal and inhalation exposures of workers, consumer or the general population to D4 and D5 for route-to-route, interspecies and high to low dose extrapolations for risk assessment

Physiologically Based Pharmacokinetic (PBPK) Modeling of Interstrain Variability in Trichloroethylene Metabolism in the Mouse

Background: Quantitative estimation of toxicokinetic variability in the human population is a persistent challenge in risk assessment of environmental chemicals. Traditionally, interindividual differences in the population are accounted for by default assumptions or, in rare cases, are based on human toxicokinetic data

The Contribution of Peroxisome Proliferator-Activated Receptor Alpha to the Relationship Between Toxicokinetics and Toxicodynamics of Trichloroethylene

Exposure to the ubiquitous environmental contaminant trichloroethylene (TCE) is associated with cancer and non-cancer toxicity in both humans and rodents. Peroxisome proliferator-activated receptor-alpha (PPARα) is thought to be playing a role in liver toxicity in rodents through activation of the receptor by the TCE metabolite trichloroacetic acid (TCA). However, most studies using genetically altered mice have not assessed the potential for PPARα to alter TCE toxicokinetics, which may lead to differences in TCA internal doses and hence confound inferences as to the role of PPARα in TCE toxicity. To address this gap, male and female wild type (129S1/SvImJ), Pparα-null, and humanized PPARα (hPPARα) mice were exposed intragastrically to 400 mg/kg TCE in single-dose (2, 5 and 12 h) and repeat-dose (5 days/week, 4 weeks) studies. Interestingly, following either a single- or repeat-dose exposure to TCE, levels of TCA in liver and kidney were lower in Pparα-null and hPPARα mice as compared with those in wild type mice. Levels of trichloroethanol (TCOH) were similar in all strains. TCE-exposed male mice consistently had higher levels of TCA and TCOH in all tissues compared with females. Additionally, in both single- and repeat-dose studies, a similar degree of induction of PPARα-responsive genes was observed in liver and kidney of hPPARα and wild type mice, despite the difference in hepatic and renal TCA levels. Additional sex- and strain-dependent effects were observed in the liver, including hepatocyte proliferation and oxidative stress, which were not dependent on TCA or TCOH levels. These data demonstrate that PPARα status affects the levels of the putative PPARα agonist TCA following TCE exposure. Therefore, interpretations of studies using Pparα-null and hPPARα mice need to consider the potential contribution of genotype-dependent toxicokinetics to observed differences in toxicity, rather than attributing such differences only to receptor-mediated toxicodynamic effects

Evaluating Pharmacokinetic and Pharmacodynamic Interactions with Computational Models in Supporting Cumulative Risk Assessment

Simultaneous or sequential exposure to multiple chemicals may cause interactions in the pharmacokinetics (PK) and/or pharmacodynamics (PD) of the individual chemicals. Such interactions can cause modification of the internal or target dose/response of one chemical in the mixture by other chemical(s), resulting in a change in the toxicity from that predicted from the summation of the effects of the single chemicals using dose additivity. In such cases, conducting quantitative cumulative risk assessment for chemicals present as a mixture is difficult. The uncertainties that arise from PK interactions can be addressed by developing physiologically based pharmacokinetic (PBPK) models to describe the disposition of chemical mixtures. Further, PK models can be developed to describe mechanisms of action and tissue responses. In this article, PBPK/PD modeling efforts conducted to investigate chemical interactions at the PK and PD levels are reviewed to demonstrate the use of this predictive modeling framework in assessing health risks associated with exposures to complex chemical mixtures

Physiologically Based Pharmacokinetic (PBPK) Modeling of Interstrain Variability in Trichloroethylene Metabolism in the Mouse

Background: Quantitative estimation of toxicokinetic variability in the human population is a persistent challenge in risk assessment of environmental chemicals. Traditionally, interindividual differences in the population are accounted for by default assumptions or, in rare cases, are based on human toxicokinetic data. Objectives: We evaluated the utility of genetically diverse mouse strains for estimating toxicokinetic population variability for risk assessment, using trichloroethylene (TCE) metabolism as a case study. Methods: We used data on oxidative and glutathione conjugation metabolism of TCE in 16 inbred and 1 hybrid mouse strains to calibrate and extend existing physiologically based pharmacokinetic (PBPK) models. We added one-compartment models for glutathione metabolites and a two-compartment model for dichloroacetic acid (DCA). We used a Bayesian population analysis of interstrain variability to quantify variability in TCE metabolism. Results: Concentration–time profiles for TCE metabolism to oxidative and glutathione conjugation metabolites varied across strains. Median predictions for the metabolic flux through oxidation were less variable (5-fold range) than that through glutathione conjugation (10-fold range). For oxidative metabolites, median predictions of trichloroacetic acid production were less variable (2-fold range) than DCA production (5-fold range), although the uncertainty bounds for DCA exceeded the predicted variability. Conclusions: Population PBPK modeling of genetically diverse mouse strains can provide useful quantitative estimates of toxicokinetic population variability. When extrapolated to lower doses more relevant to environmental exposures, mouse population-derived variability estimates for TCE metabolism closely matched population variability estimates previously derived from human toxicokinetic studies with TCE, highlighting the utility of mouse interstrain metabolism studies for addressing toxicokinetic variability. Citation: Chiu WA, Campbell JL Jr, Clewell HJ III, Zhou YH, Wright FA, Guyton KZ, Rusyn I. 2014. Physiologically based pharmacokinetic (PBPK) modeling of interstrain variability in trichloroethylene metabolism in the mouse. Environ Health Perspect 122:456–463; http://dx.doi.org/10.1289/ehp.130762