Uncertainties in pharmacokinetic modeling for perchloroethylene: II. Comparison of model predictions with data for a variety of different parameters

Applying Mode-of-Action and Pharmacokinetic Considerations in Contemporary Cancer Risk Assessments: An Example with Trichloroethylene

The guidelines for carcinogen risk assessment recently proposed by the U.S. Environmental Protection Agency (U.S. EPA) provide an increased opportunity for the consideration of pharmacokinetic and mechanistic data in the risk assessment process. However, the greater flexibility of the new guidelines can also make their actual implementation for a particular chemical highly problematic. To illuminate the process of performing a cancer risk assessment under the new guidelines, the rationale for a state-of-the-science risk assessment for trichloroethylene (TCE) is presented. For TCE, there is evidence of increased cell proliferation due to receptor interaction or cytotoxicity in every instance in which tumors are observed, and most tumors represent an increase in the incidence of a commonly observed, species-specific lesion. A physiologically based pharmacokinetic (PBPK) model was applied to estimate target tissue doses for the three principal animal tumors associated with TCE exposure: liver, lung, and kidney. The lowest points of departure (lower bound estimates of the exposure associated with 10% tumor incidence) for lifetime human exposure to TCE were obtained for mouse liver tumors, assuming a mode of action primarily involving the mitogenicity of the metabolite trichloroacetic acid (TCA). The associated linear unit risk estimates for mouse liver tumors are 1.5 x 10(-6) for lifetime exposure to 1 microg TCE per cubic meter in air and 0.4 x 10(-6) for lifetime exposure to 1 microg TCE per liter in drinking water. However, these risk estimates ignore the evidence that the human is likely to be much less responsive than the mouse to the carcinogenic effects of TCA in the liver and that the carcinogenic effects of TCE are unlikely to occur at low environmental exposures. Based on consideration of the most plausible carcinogenic modes of action of TCE, a margin-of-exposure (MOE) approach would appear to be more appropriate. Applying an MOE of 1000, environmental exposures below 66 microg TCE per cubic meter in air and 265 microg TCE per liter in drinking water are considered unlikely to present a carcinogenic hazard to human health.

Evaluation of Physiologically Based Pharmacokinetic Models in Risk Assessment: An Example with Perchloroethylene

One of the more problematic aspects of the application of physiologically based pharmacokinetic (PBPK) models in risk assessment is the question of whether the model has been adequately validated to provide confidence in the dose metrics calculated with it. A number of PBPK models have been developed for perchloroethylene (PCE), differing primarily in the parameters estimated for metabolism. All of the models provide reasonably accurate simulations of selected kinetic data for PCE in mice and humans and could thus be considered to be "validated" to some extent. However, quantitative estimates of PCE cancer risk are critically dependent on the prediction of the rate of metabolism at low environmental exposures. Recent data on the urinary excretion of trichloroacetic acid (TCA), the major metabolite of PCE, for human subjects exposed to lower concentrations than those used in previous studies, make it possible to compare the high- to low-dose extrapolation capability of the various published human models. The model of Gearhart et al., which is the only model to include a description of TCA kinetics, provided the closest predictions of the urinary excretion observed in these low-concentration exposures. Other models overestimated metabolite excretion in this study by 5- to 15-fold. A systematic discrepancy between model predictions and experimental data for the time course of the urinary excretion of TCA suggested a contribution from TCA formed by metabolism of PCE in the kidney and excreted directly into the urine. A modification of the model of Gearhart et al. to include metabolism of PCE to TCA in the kidney at 10% of the capacity of the liver, with direct excretion of the TCA formed in the kidney into the urine, markedly improved agreement with the experimental time-course data, without altering predictions of liver metabolism. This case study with PCE demonstrates the danger of relying on parent chemical kinetic data to validate a model that will be used for the prediction of metabolism.

The use of Markov chain Monte Carlo uncertainty analysis to support a Public Health Goal for perchloroethylene

The current Public Health Goal (PHG) for perchloroethylene (PCE) was derived using upper-bound estimates of fractional PCE metabolism in humans. These estimates were in part obtained from a published evaluation of the uncertainty and variability in human PCE metabolism conducted using a physiologically-based pharmacokinetic (PBPK) model in a Markov chain Monte Carlo (MCMC) analysis; however, the data used in that analysis were limited to post-exposure PCE blood and exhaled air concentrations from a single study. A more recent study [Volkel, W., Friedewald, M., Lederer, E., Pahler, A., Parker, J., Dekant, W., 1998. Biotransformation of perchloroethene: dose-dependent excretion of trichloroacetic acid, dichloroacetic acid, and N-acetyl-S-(trichlorovinyl)-l-cysteine in rats and humans after inhalation. Toxicol. Appl. Pharmacol. 153(1), 20-27.] provides data on blood concentrations of PCE and its major metabolite, trichloroacetic acid (TCA), and urinary excretion of TCA following exposure of human subjects to lower concentrations of PCE (10-40ppm) than in previous studies. In the present effort, a new MCMC analysis was performed that focused on data from this study along with two others [Fernandez, J., Guberan, E., Caperos, J., 1976. Experimental human exposures to tetrachloroethylene vapor and elimination in breath after inhalation. Am. Ind. Hyg. Assoc. J. 37, 143-150; Monster, A., Boersma, G., Steenweg, H., 1979. Kinetics of tetrachloroethylene in volunteers; influence of exposure concentration and work load. Int. Arch. Occup. Environ. Health 42, 303-309.] providing data on PCE blood concentrations and urinary excretion of TCA. To provide an accurate prediction of TCA kinetics, the PBPK model used here includes a description of the metabolism of PCE to TCA in both the liver and kidney. The resulting upper 95th percentile estimates of fraction of PCE metabolized by inhalation and oral routes were 2.1 and 5.2%, respectively, compared to 58 and 79% used in the derivation of the PHG.

Framework for evaluation of physiologically-based pharmacokinetic models for use in safety or risk assessment

Proposed applications of increasingly sophisticated biologically-based computational models, such as physiologically-based pharmacokinetic models, raise the issue of how to evaluate whether the models are adequate for proposed uses, including safety or risk assessment. A six-step process for model evaluation is described. It relies on multidisciplinary expertise to address the biological, toxicological, mathematical, statistical, and risk assessment aspects of the modeling and its application. The first step is to have a clear definition of the purpose(s) of the model in the particular assessment; this provides critical perspectives on all subsequent steps. The second step is to evaluate the biological characterization described by the model structure based on the intended uses of the model and available information on the compound being modeled or related compounds. The next two steps review the mathematical equations used to describe the biology and their implementation in an appropriate computer program. At this point, the values selected for the model parameters (i.e., model calibration) must be evaluated. Thus, the fifth step is a combination of evaluating the model parameterization and calibration against data and evaluating the uncertainty in the model outputs. The final step is to evaluate specialized analyses that were done using the model, such as modeling of population distributions of parameters leading to population estimates for model outcomes or inclusion of early pharmacodynamic events. The process also helps to define the kinds of documentation that would be needed for a model to facilitate its evaluation and implementation.

Incorporating pharmacokinetic differences between children and adults in assessing children's risks to environmental toxicants

Children's risks from environmental toxicant exposure can be affected by pharmacokinetic factors that affect the internal dose of parent chemical or active metabolite. There are numerous physiologic differences between neonates and adults that affect pharmacokinetics including size of lipid, and tissue compartments, organ blood flows, protein binding capacity, and immature function of renal and hepatic systems. These factors combine to decrease the clearance of many therapeutic drugs, which can also be expected to occur with environmental toxicants in neonates. The net effect may be greater or lesser internal dose of active toxicant depending upon how the agent is distributed, metabolized, and eliminated. Child/adult pharmacokinetic differences decrease with increasing postnatal age, but these factors should still be considered in any children's age group, birth through adolescence, for which there is toxicant exposure. Physiologically based pharmacokinetic (PBPK) models can simulate the absorption, distribution, metabolism, and excretion of xenobiotics in both children and adults, allowing for a direct comparison of internal dose and risk across age groups. This review provides special focus on the development of hepatic cytochrome P-450 enzymes (CYPs) in early life and how this information, along with many factors unique to children, can be applied to PBPK models for this receptor population. This review describes a case study involving the development of neonatal PBPK models for the CYP1A2 substrates caffeine and theophylline. These models were calibrated with pharmacokinetic data in neonates and used to help understand key metabolic differences between neonates and adults across these two drugs.

Physiologically based pharmacokinetic (PBPK) modeling of caffeine and theophylline in neonates and adults: implications for assessing children's risks from environmental agents

Children's risks can differ from those in adults for numerous reasons, one being differences in the pharmacokinetic handling of chemicals. Immature metabolism and a variety of other factors in neonates can affect chemical disposition and clearance. These factors can be incorporated into physiologically based pharmacokinetic (PBPK) models that simulate the fate of environmental toxicants in both children and adults. PBPK models are most informative when supported by empirical data, but typically pediatric pharmacokinetic data for toxicants are not available. In contrast, pharmacokinetic data in children are readily available for therapeutic drugs. The current analysis utilizes data for caffeine and theophylline, closely related xanthines that are both cytochrome P-450 (CYP) 1A2 substrates, in developing PBPK models for neonates and adults. Model development involved scale-up of in vitro metabolic parameters to whole liver and adjusting metabolic function for the ontological pattern of CYP1A2 and other CYPs. Model runs were able to simulate the large differences in half-life and clearance between neonates and adults. Further, the models were able to reproduce the faster metabolic clearance of theophylline relative to caffeine in neonates. This differential between xanthines was found to be due primarily to an extra metabolic pathway available to theophylline, back-methylation to caffeine, that is not available to caffeine itself. This pathway is not observed in adults exemplifying the importance of secondary or novel routes of metabolism in the immature liver. Greater CYP2E1 metabolism of theophylline relative to caffeine in neonates also occurs. Neonatal PBPK models developed for these drugs may be adapted to other CYP1A2 substrates (e.g., arylamine toxicants). A stepwise approach for modeling environmental toxicants in children is proposed.

Incorporating children's toxicokinetics into a risk framework

Children's responses to environmental toxicants will be affected by the way in which their systems absorb, distribute, metabolize, and excrete chemicals. These toxicokinetic factors vary during development, from in utero where maternal and placental processes play a large role, to the neonate in which emerging metabolism and clearance pathways are key determinants. Toxicokinetic differences between neonates and adults lead to the potential for internal dosimetry differences and increased or decreased risk, depending on the mechanisms for toxicity and clearance of a given chemical. This article raises a number of questions that need to be addressed when conducting a toxicokinetic analysis of in utero or childhood exposures. These questions are organized into a proposed framework for conducting the assessment that involves problem formulation (identification of early life stage toxicokinetic factors and chemical-specific factors that may raise questions/concerns for children); data analysis (development of analytic approach, construction of child/adult or child/animal dosimetry comparisons); and risk characterization (evaluation of how children's toxicokinetic analysis can be used to decrease uncertainties in the risk assessment). The proposed approach provides a range of analytical options, from qualitative to quantitative, for assessing children's dosimetry. Further, it provides background information on a variety of toxicokinetic factors that can vary as a function of developmental stage. For example, the ontology of metabolizing systems is described via reference to pediatric studies involving therapeutic drugs and evidence from in vitro enzyme studies. This type of resource information is intended to help the assessor begin to address the issues raised in this paper.

Whole body pharmacokinetic models

The aim of the current review is to summarise the present status of physiologically based pharmacokinetic (PBPK) modelling and its applications in drug research, and thus serve as a reference point to people interested in the methodology. The review is structured into three major sections. The first discusses the existing methodologies and techniques of PBPK model development. The second describes some of the most interesting PBPK model implementations published. The final section is devoted to a discussion of the current limitations and the possible future developments of the PBPK modelling approach. The current review is focused on papers dealing with the pharmacokinetics and/or toxicokinetics of medicinal compounds; references discussing PBPK models of environmental compounds are mentioned only if they represent considerable methodological developments or reveal interesting interpretations and/or applications.The major conclusion of the review is that, despite its significant potential, PBPK modelling has not seen the development and implementation it deserves, especially in the drug discovery, research and development processes. The main reason for this is that the successful development and implementation of a PBPK model is seen to require the investment of significant experience, effort, time and resources. Yet, a substantial body of PBPK-related research has been accumulated that can facilitate the PBPK modelling and implementation process. What is probably lagging behind is the expertise component, where the demand for appropriately qualified staff far outreaches availability.

Differences in pharmacokinetics between children and adults--II. Children's variability in drug elimination half-lives and in some parameters needed for physiologically-based pharmacokinetic modeling

In earlier work we assembled a database of classical pharmacokinetic parameters (e.g., elimination half-lives; volumes of distribution) in children and adults. These data were then analyzed to define mean differences between adults and children of various age groups. In this article, we first analyze the variability in half-life observations where individual data exist. The major findings are as follows. The age groups defined in the earlier analysis of arithmetic mean data (0-1 week premature; 0-1 week full term; 1 week to 2 months; 2-6 months; 6 months to 2 years; 2-12 years; and 12-18 years) are reasonable for depicting child/adult pharmacokinetic differences, but data for some of the earliest age groups are highly variable. The fraction of individual children's half-lives observed to exceed the adult mean half-life by more than the 3.2-fold uncertainty factor commonly attributed to interindividual pharmacokinetic variability is 27% (16/59) for the 0-1 week age group, and 19% (5/26) in the 1 week to 2 month age group, compared to 0/87 for all the other age groups combined between 2 months and 18 years. Children within specific age groups appear to differ from adults with respect to the amount of variability and the form of the distribution of half-lives across the population. The data indicate departure from simple unimodal distributions, particularly in the 1 week to 2 month age group, suggesting that key developmental steps affecting drug removal tend to occur in that period. Finally, in preparation for age-dependent physiologically-based pharmacokinetic modeling, nationally representative NHANES III data are analyzed for distributions of body size and fat content. The data from about age 3 to age 10 reveal important departures from simple unimodal distributional forms-in the direction suggesting a subpopulation of children that are markedly heavier than those in the major mode. For risk assessment modeling, this means that analysts will need to consider "mixed" distributions (e.g., two or more normal or log-normal modes) in which the proportions of children falling within the major versus highweight/fat modes in the mixture changes as a function of age. Biologically, the most natural interpretation of this is that these subpopulations represent children who have or have not yet received particular signals for change in growth pattern. These apparently distinct subpopulations would be expected to exhibit different disposition of xenobiotics, particularly those that are highly lipophilic and poorly metabolized.

PBPK modeling of the percutaneous absorption of perchloroethylene from a soil matrix in rats and humans

Perchloroethylene (PCE) is a widely used volatile organic chemical. Exposures to PCE are primarily through inhalation and dermal contact. The dermal absorption of PCE from a soil matrix was compared in rats and humans using real-time MS/MS exhaled breath technology and physiologically based pharmacokinetic (PBPK) modeling. Studies with rats were performed to compare the effects of loading volume, concentration, and occlusion. In rats, the percutaneous permeability coefficient (K(P)) for PCE was 0.102 +/- 0.017, and was independent of loading volume, concentration, or occlusion. Exhaled breath concentrations peaked within 1 h in nonoccluded exposures, but were maintained over the 5 h exposure period when the system was occluded. Three human volunteers submerged a hand in a container of PCE-laden soil for 2 h and their exhaled breath was continually monitored during and for 2.5 h following exposure. The absorption and elimination kinetics of PCE were slower in these subjects than initially predicted based upon the PBPK model developed from rat dermal kinetic data. The resulting K(P) for humans was over 100-fold lower than for the rat utilizing a single, well-stirred dermal compartment. Therefore, two additional PBPK skin compartment models were evaluated: a parallel model to simulate follicular uptake and a layered model to portray a stratum corneum barrier. The parallel dual dermal compartment model was not capable of describing the exhaled breath kinetics, whereas the layered model substantially improved the fit of the model to the complex kinetics of dermal absorption through the hand. In real-world situations, percutaneous absorption of PCE is likely to be minimal.

The application of physiologically based pharmacokinetic modeling in human health risk assessment of hazardous substances

Physiologically based pharmacokinetic (PBPK) modeling is an important tool for improving the accuracy of human health risk assessments for hazardous substances in the environment. The proper use of PBPK modeling can reduce uncertainties that currently exist in risk assessment procedures by providing more scientifically credible extrapolations across species and routes of exposure, and from high experimental doses to potential environmental exposures. Current applications of PBPK models range from relatively straightforward uses for the extrapolation of chemical kinetics across species, route, and duration of exposure to much more demanding chemical risk assessment applications requiring a description of complex pharmacodynamic phenomena such as mitogenicity and hyperplasia secondary to cytotoxicity. PBPK modeling helps to identify the factors that are most important in determining the health risks associated with exposure to a chemical, and provides a means for estimating the impact of those factors both on the average risk to a population and on the specific risk to an individual. The chief challenge in the application of PBPK modeling in human health risk assessment lies in the need to generate chemical-specific data to support the development and validation of the models. Extensive use of rapidly developing in vitro and structure-activity relationship techniques is needed to provide the data required for the large number of hazardous chemicals currently contaminating the environment.

Physiologically based pharmacokinetic and pharmacodynamic modeling in health risk assessment and characterization of hazardous substances

Recent advances in physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) modeling have introduced novel approaches for evaluating toxicological problems. Because PBPK models are amenable to extrapolation of tissue dosimetry, they are increasingly being applied to chemical risk assessment. A comprehensive listing of PBPK/PD models for environmental chemicals developed to date is referenced. Salient applications of PBPK/PD modeling to health risk assessments and characterization of hazardous substances are illustrated with examples.