Hisham A. El-Masri

Development of a human physiologically based pharmacokinetic (PBPK) model for inorganic arsenic and its mono- and di-methylated metabolites

A physiologically-based pharmacokinetic (PBPK) model was developed to estimate levels of arsenic and its metabolites in human tissues and urine after oral exposure to arsenate (AsV), arsenite (AsIII) or organoarsenical pesticides. The model consists of interconnected individual PBPK models for inorganic arsenic (AsV and AsIII), monomethylarsenic acid (MMAV), and, dimethylarsenic acid (DMAV). Reduction of MMAV and DMAV to their respective trivalent forms also occurs in the lung, liver, and kidney including excretion in urine. Each submodel was constructed using flow limited compartments describing the mass balance of the chemicals in GI tract (lumen and tissue), lung, liver, kidney, muscle, skin, heart, and brain. The choice of tissues was based on physiochemical properties of the arsenicals (solubility), exposure routes, target tissues, and sites for metabolism. Metabolism of inorganic arsenic in liver was described as a series of reduction and oxidative methylation steps incorporating the inhibitory influence of metabolites on methylation. The inhibitory effects of AsIII on the methylation of MMAIII to DMA, and MMAIII on the methylation of AsIII to MMA were modeled as noncompetitive. To avoid the uncertainty inherent in estimation of many parameters from limited human data, a priori independent parameter estimates were derived using data from diverse experimental systems with priority given to data derived using human cells and tissues. This allowed the limited data for human excretion of arsenicals in urine to be used to estimate only parameters that were most sensitive to this type of data. Recently published urinary excretion data, not previously used in model development, are also used to evaluate model predictions.

Exploration of an interaction threshold for the joint toxicity of trichloroethylene and 1,1-dichloroethylene: utilization of a PBPK model

Physiologically based pharmacokinetic (PBPK) modeling and gas uptake experiments were utilized to verify the competitive inhibition mechanism of interaction between trichloroethylene (TCE) and 1,1-dichloroethylene (DCE) and to investigate the presence of an interaction threshold between the two chemicals. Initially, gas uptake experiments were conducted on Fischer 344 rats where the initial concentrations of both DCE and TCE were 2000∶0, 0∶2000, 2000∶2000, 1000∶0, 1000∶1000, and 500∶500 ppm, respectively. When the different modes of inhibition interactions (competitive, uncompetitive and noncompetitive) were employed in the PBPK model, the model description of the competitive inhibition interaction provided the best description of the declining concentrations in the gas uptake chamber. Furthermore, to predict the range at which the interaction threshold would be found, the PBPK model included a mathematical description of the percentage of enzyme sites occupied by either chemical in the presence or the absence of the other. By comparing the percentage of occupied sites by one chemical, in the presence of the other, to those sites occupied in the absence of the latter, the PBPK model predicted a range of concentrations (100 ppm or less) of either chemical where the competitive inhibition interaction would not be observed. Consequently, gas uptake experiments were designed where the initial concentration was selected at 2000 ppm for one chemical while the other chemical was set at 100 in one experiment and 50 ppm in another. Under these conditions, the best simulation to the concentration depletion curves in the gas uptake system of the chemical in the higher concentration was obtained when the PBPK model was run under the assumption of no-interaction. This substantiated the model predictions of the presence of observable interaction only at concentrations higher than 100 ppm.

Physiologically based pharmacokinetic/pharmacodynamic modeling of chemical mixtures and possible applications in risk assessment

Human exposure to chemicals, be it environmental or occupational, is rarely, if ever, limited to a single chemical. Therefore, it is essential that we consider multiple chemical effects and interactions in our risk assessment process. However, with the almost infinitely large number of chemical mixtures in the environment, systematic studies of the toxicology of these chemical mixtures with conventional methodologies and approaches are impossible because of the immense resources and unrealistically long durations required. Thus, the development of predictive and alternative toxicology method is imperative. In order to have a reasonable chance to deal with the complex issue of toxicology of chemical mixtures, we believe that the following concepts must be considered: (1) the exploitation of recent advances in computational technology; (2) the utilization of mathematical/statistical modeling; (3) coupling computer modeling with very focused, mechanistically based, and short-term toxicology studies. Our approach is, therefore, the utilization of physiologically based pharmacokinetic/pharmacodynamic (PB-PK/PD) modeling, coupled with very focused, model-directed toxicology experiments as well as other statistical/mathematical modeling such as isobolographic analysis and response surface methodology. Tissue dosimetry at the pharmacokinetic and pharmacodynamic levels is achievable with simple and complex, but chemically defined, mixtures. Our long-term goal is to formulate innovative risk assessment methodologies for chemical mixtures. In this presentation, one of our specific research projects is described: PB-PK/PD modeling of toxicologic interactions between Kepone and carbon tetrachloride (CCl4) and the coupling of Monte Carlo simulation for the prediction of acute toxicity.

Physiologically Based Pharmacokinetic Model Use in Risk Assessment—Why Being Published Is Not Enough

A panel of experts in physiologically based pharmacokinetic (PBPK) modeling and relevant quantitative methods was convened to describe and discuss model evaluation criteria, issues, and choices that arise in model application and computational tools for improving model quality for use in human health risk assessments (HHRAs). Although publication of a PBPK model in a peer-reviewed journal is a mark of good science, subsequent evaluation of published models and the supporting computer code is necessary for their consideration for use in HHRAs. Standardized model evaluation criteria and a thorough and efficient review process can reduce the number of review and revision iterations and hence the time needed to prepare a model for application. Efficient and consistent review also allows for rapid identification of needed model modifications to address HHRA-specific issues. This manuscript reports on the workshop where a process and criteria that were created for PBPK model review were discussed along with other issues related to model review and application in HHRA. Other issues include (1) model code availability, portability, and validity; (2) probabilistic (e.g., population-based) PBPK models and critical choices in parameter values to fully characterize population variability; and (3) approaches to integrating PBPK model outputs with other HHRA tools, including benchmark dose modeling. Two specific case study examples are provided to illustrate challenges that were encountered during the review and application process. By considering the frequent challenges encountered in the review and application of PBPK models during the model development phase, scientists may be better able to prepare their models for use in HHRAs.

Integrated Approaches for the Analysis of Toxicologic Interactions of Chemical Mixtures

Although an overwhelmingly large portion of the resources in toxicologic research is devoted to single chemical studies, the toxicology of chemical mixtures, not single chemicals, is the real issue regarding health effects of environmental and/or occupational exposure to chemicals. The relative lack of activities in the area of toxicology of chemical mixtures does not suggest ignorance of the importance of the issue by the toxicology community. Instead, it is a reflection of the difficulty, complexity, and controversy surrounding this area of research. Until recently, much of the literature on the toxicology of chemical mixtures has been either very focused on certain specific interaction studies or slanted toward broad-based, relatively vague theoretical deliberation. The typical interaction study involved binary mixtures at relatively high dose levels with acute toxicities as endpoints. Although the theoretical papers have been valuable contributions, little is available on actual, practical experimental approaches toward a systematic solution of this immensely complex area of research. We present here a broad discussion on the important issues of the toxicology of chemical mixtures. First, we provide some background information with respect to the problem and significance of toxicology of chemical mixtures in relation to some of the real life issues. Second, we review and compare the existing experimental approaches relevant to toxicologic interactions of chemical mixtures. Third, we propose three integrated approaches that involve the combination of physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) modeling with: (1) Monte Carlo simulation, (2) median effect principle (MEP), and (3) response surface methodology (RSM). These modeling approaches, coupled with very focused mechanistically based toxicology studies, could be the basis for solving the problems of toxicology and risk assessment of chemical mixtures.

Physiologically based pharmacokinetic/pharmacodynamic modeling of the toxicologic interaction between carbon tetrachloride and Kepone

Abstract Carbon tetrachloride (CCl4) lethality in Sprague-Dawley rats is greatly amplified by pretreatment of Kepone (decachlorooctahydro-1,3,2-metheno-2H-cyclobuta[cd]pentalen-2-one). The increase in lethality was attributed to the obstruction of liver regenerative processes. These processes are essential for restoring the liver to its full functional capacity following injury by CCl4. Based on the available mechanistic information on Kepone/CCl4 interaction, a physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) model was constructed where the following effects of Kepone on CCl4 toxicity are incorporated: (1) inhibition of mitosis; (2) reduction of repair mechanism of hepatocellular injury; (3) suppression of phagocytosis. The PBPK/PD model provided computer simulation consistent with previously published time-course results of hepatotoxicity (i.e., pyknotic, injured and mitotic cells) of CCl4 with or without Kepone. As a further verification of this model, the computer simulations were also consistent with exhalation kinetic data for rats injected with different intraperitoneal (i.p.) doses of CCl4 in our laboratory. Subsequently, the PBPK/PD model, coupled with Monte Carlo simulation, was used to predict lethalities of rats treated with CCl4 alone and CCl4 in combination with Kepone. The experimental lethality studies performed in our laboratories were as follows: Sprague-Dawley rats were given either control diet or diet containing 10 ppm Kepone for 15 days. On day 16, rats in the Kepone treated group were given i.p. doses of 0, 10, 50, and 100 μl/kg CCl4 (n=9) while control rats were exposed to 0, 100, 1000, 3000, and 6000 μl/kg CCl4 (n=9). Lethality was observed at the 1000 (1/9), 3000 (4/9), and 6000 (8/9) μl/kg doses for the control group and at the 50 (4/9) and 100 (8/9) μl/kg for the treated group. Based on Monte Carlo simulation, which was used to run electronically 1000 lethality experiments for each dosing situation, the LD50 estimates for CCl4 toxicity with and without Kepone pretreatment were 47 and 2890 μl/kg, respectively. Monte Carlo simulation coupled with the PBPK/PD model produced lethality rates which were not significantly different from the observed mortality, with the exception of CCl4 at very high doses (e.g., 6000 μl/kg, p=0.014). Deviation at very high doses of the predicted mortality from the observed may be attributed to extrahepatic systemic toxicities of CCl4, or solvent effects on tissues at high concentrations, which were not presently included in the model. Our modeling and experimental results verified the earlier findings of Mehendale (1990) for the 67-fold amplification of CCl4 lethality in the presence of Kepone. However, much of this amplification of CCl4 lethality with Kepone pretreatment was probably due to pharmacokinetic factors, because when target tissue dose (i.e., model estimated amount of CCl4 metabolites) was used to evaluate lethality, this amplification was reduced to 4-fold.

A Physiologically based Pharmacokinetic Model for Intravenous and Ingested Dimethylarsinic Acid in Mice

A physiologically based pharmacokinetic (PBPK) model for the organoarsenical dimethylarsinic acid (DMA(V)) was developed in mice. The model was calibrated using tissue time course data from multiple tissues in mice administered DMA(V) intravenously. The final model structure was based on diffusion limitation kinetics. In general, PBPK models use the assumption of blood flow-limited transport into tissues. This assumption has historically worked for small lipophilic organic solvents. However, the conditions under which flow-limited kinetics occurs and how to distinguish when flow-limited versus diffusion-limited transport is more appropriate, have been rarely evaluated. One important goal of this modeling effort was to systematically evaluate descriptions of flow-limited compared with diffusion-limited tissue distribution for DMA(V), using the relatively extensive pharmacokinetic data available in mice. The diffusion-limited model consistently provided an improved fit over flow-limited simulations when compared with tissue time course iv experimental data. After model calibration, an independent data set obtained by oral gavage of DMA(V), was used to further test model structure. Sensitivity analysis of the two PBPK model structures showed the importance of early time course data collection, and the impact of diffusion for kidney time course data description. In summary, this modeling effort suggests the importance of availability of organ specific time course data sets necessary for the discernment of PBPK modeling structure, motivated by knowledge of biology, and providing necessary feedback between experimental design and biological modelers.

Development of multi-route physiologically-based pharmacokinetic models for ethanol in the adult, pregnant, and neonatal rat

Biofuel blends of 10% ethanol (EtOH) and gasoline are common in the USA, and higher EtOH concentrations are being considered (15–85%). Currently, no physiologically-based pharmacokinetic (PBPK) models are available to describe the kinetics of EtOH-based biofuels. PBPK models were developed to describe life-stage differences in the kinetics of EtOH alone in adult, pregnant, and neonatal rats for inhalation, oral, and intravenous routes of exposure, using data available in the open literature. Whereas ample data exist from gavage and intravenous routes of exposure, kinetic data from inhalation exposures are limited, particularly at concentrations producing blood and target tissue concentrations associated with developmental neurotoxicity. Compared to available data, the three models reported in this paper accurately predicted the kinetics of EtOH, including the absorption, peak concentration, and clearance across multiple datasets. In general, model predictions for adult and pregnant animals matched inhalation and intravenous datasets better than gavage data. The adult model was initially better able to predict the time-course of blood concentrations than was the neonatal model. However, after accounting for age-related changes in gastric uptake using the calibrated neonate model, simulations consistently reproduced the early kinetic behavior in blood. This work provides comprehensive multi-route life-stage models of EtOH pharmacokinetics and represents a first step in development of models for use with gasoline-EtOH blends, with additional potential applicability in investigation of the pharmacokinetics of EtOH abuse, addiction, and toxicity.

Application of PBPK modeling in support of the derivation of toxicity reference values for 1,1,1-trichloroethane.

PBPK modeling has been increasingly applied in chemical risk assessment for dose, route, and species extrapolation. The use of PBPK modeling was explored in deriving toxicity reference values for 1,1,1-trichloroethane (1,1,1-TCE). This effort involved a 5-step process: (i) reconstruction of several published PBPK models for 1,1,1-TCE in the rat and human; (ii) selection of appropriate pharmacokinetic datasets for model comparison; (iii) determination of the most suitable PBPK model for supporting reference value derivation; (iv) PBPK model simulation of two critical studies to estimate internal dose metrics; and (v) calculation of internal dose metrics for human exposure scenarios for reference value derivation. The published model by Reitz et al. [Reitz, R.H., McDougal, J.N., Himmelstein, M.W., Nolan, R.J., Schumann, A.M., 1988. Physiologically based pharmacokinetic modeling with methylchloroform: implications for interspecies, high dose/low dose, and dose route extrapolations. Toxicol. Appl. Pharmacol. 95, 185-199] was judged the most suitable. This model has liver, fat, and rapidly and slowly perfused compartments, contains a saturable process for 1,1,1-TCE hepatic metabolism, and accommodates multiple exposure pathways in three species. Data from a human volunteer study involving acute inhalation exposure [Mackay, C.J., Campbell, L., Samuel, A.M., Alderman, K.J., Idzikowski, C., Wilson, H.K., Gompertz, D., 1987. Behavioral changes during exposure to 1,1,1-trichloroethane: time-course and relationship to blood solvent levels. Am. J. Ind. Med. 11, 223-239] and a chronic rat inhalation study [Quast, J.F., Calhoun, L.L., Frauson, L.E., 1988. 1,1,1-Trichloroethane formulation: a chronic inhalation toxicity and oncogenicity study in Fischer 344 rats and B6C3F1 mice. Fundam. Appl. Toxicol. 11, 611-625] were selected to simulate appropriate internal dosimetry data from which to derive reference value points of departure. Duration, route, and species extrapolations were performed based on internal dose metrics.

A Workflow to Investigate Exposure and Pharmacokinetic Influences on High-Throughput in Vitro Chemical Screening Based on Adverse Outcome Pathways

Background Adverse outcome pathways (AOPs) link adverse effects in individuals or populations to a molecular initiating event (MIE) that can be quantified using in vitro methods. Practical application of AOPs in chemical-specific risk assessment requires incorporation of knowledge on exposure, along with absorption, distribution, metabolism, and excretion (ADME) properties of chemicals. Objectives We developed a conceptual workflow to examine exposure and ADME properties in relation to an MIE. The utility of this workflow was evaluated using a previously established AOP, acetylcholinesterase (AChE) inhibition. Methods Thirty chemicals found to inhibit human AChE in the ToxCast™ assay were examined with respect to their exposure, absorption potential, and ability to cross the blood–brain barrier (BBB). Structures of active chemicals were compared against structures of 1,029 inactive chemicals to detect possible parent compounds that might have active metabolites. Results Application of the workflow screened 10 “low-priority” chemicals of 30 active chemicals. Fifty-two of the 1,029 inactive chemicals exhibited a similarity threshold of ≥ 75% with their nearest active neighbors. Of these 52 compounds, 30 were excluded due to poor absorption or distribution. The remaining 22 compounds may inhibit AChE in vivo either directly or as a result of metabolic activation. Conclusions The incorporation of exposure and ADME properties into the conceptual workflow eliminated 10 “low-priority” chemicals that may otherwise have undergone additional, resource-consuming analyses. Our workflow also increased confidence in interpretation of in vitro results by identifying possible “false negatives.” Citation Phillips MB, Leonard JA, Grulke CM, Chang DT, Edwards SW, Brooks R, Goldsmith MR, El-Masri H, Tan YM. 2016. A workflow to investigate exposure and pharmacokinetic influences on high-throughput in vitro chemical screening based on adverse outcome pathways. Environ Health Perspect 124:53–60; http://dx.doi.org/10.1289/ehp.1409450