Toxicokinetic modeling and its applications in chemical risk assessment

A pharmacokinetic model of cis- and trans-permethrin disposition in rats and humans with aggregate exposure application

Permethrin is a broad-spectrum pyrethroid insecticide and among the most widely used insecticides in homes and crops. Managing the risks for pesticides such as permethrin depends on the ability to consider diverse exposure scenarios and their relative risks. Physiologically based pharmacokinetic models of delta methrin disposition were modified to describe permethrin kinetics in the rat and human. Unlike formulated deltamethrin which consists of a single stereoisomer, permethrin is formulated as a blend of cis- and trans-diastereomers. We assessed time courses for cis-permethrin and trans-permethrin in several tissues (brain, blood, liver, and fat) in the rat following oral administration of 1 and 10mg/kg permethrin (cis/trans: 40/60). Accurate simulation of permethrin in the rat suggests that a generic model structure is promising for modeling pyrethroids. Human in vitro data and appropriate anatomical information were used to develop a provisional model of permethrin disposition with structures for managing oral, dermal, and inhalation routes of exposure. The human permethrin model was used to evaluate dietary and residential exposures in the U.S. population as estimated by EPA's Stochastic Human Exposure and Dose Simulation model. Simulated cis- and trans-DCCA, metabolites of permethrin, were consistent with measured values in the National Health and Nutrition Examination Survey, indicating that the model holds promise for assessing population exposures and quantifying dose metrics.

Toxicokinetics as a key to the integrated toxicity risk assessment based primarily on non-animal approaches

Toxicokinetics (TK) is the endpoint that informs about the penetration into and fate within the body of a toxic substance, including the possible emergence of metabolites. Traditionally, the data needed to understand those phenomena have been obtained in vivo. Currently, with a drive towards non-animal testing approaches, TK has been identified as a key element to integrate the results from in silico, in vitro and already available in vivo studies. TK is needed to estimate the range of target organ doses that can be expected from realistic human external exposure scenarios. This information is crucial for determining the dose/concentration range that should be used for in vitro testing. Vice versa, TK is necessary to convert the in vitro results, generated at tissue/cell or sub-cellular level, into dose response or potency information relating to the entire target organism, i.e. the human body (in vitro-in vivo extrapolation, IVIVE). Physiologically based toxicokinetic modelling (PBTK) is currently regarded as the most adequate approach to simulate human TK and extrapolate between in vitro and in vivo contexts. The fact that PBTK models are mechanism-based which allows them to be 'generic' to a certain extent (various extrapolations possible) has been critical for their success so far. The need for high-quality in vitro and in silico data on absorption, distribution, metabolism as well as excretion (ADME) as input for PBTK models to predict human dose-response curves is currently a bottleneck for integrative risk assessment.

Physiologically-based pharmacokinetic (PBPK) models in toxicity testing and risk assessment

Physiologically-based pharmacokinetic (PBPK) modeling offers a scientifically-sound framework for integrating mechanistic data on absorption, distribution, metabolism and elimination to predict the time-course of parent chemical, metabolite(s) or biomarkers in the exposed organism. A major advantage of PBPK models is their ability to forecast the impact of specific mechanistic processes and determinants on the tissue dose. In this regard, they facilitate integration of data obtained with in vitro and in silico methods, for making predictions of the tissue dosimetry in the whole animal, thus reducing and/or refining the use of animals in pharmacokinetic and toxicity studies. This chapter presents the principles and practice of PBPK modeling, as well as the application of these models in toxicity testing and health risk assessments.

A probabilistic risk assessment approach used to prioritize chemical constituents in mainstream smoke of cigarettes sold in China

The chemical and physical complexity of cigarette mainstream smoke (MSS) presents a challenge in the understanding of risk for smoking-related diseases. Quantitative risk assessment is a useful tool for assessing the toxicological risks that may be presented by smoking currently available commercial cigarettes. In this study, yields of a selected group of chemical constituents were quantified in machine-generated MSS from 30 brands of cigarettes sold in China. Using constituent yields, exposure estimates specific to and representative of the Chinese population, and available dose-response data, a Monte Carlo method was applied to simulate probability distributions for incremental lifetime cancer risk (ILCR), hazard quotient (HQ), and margin of exposure (MOE) values for each constituent as appropriate. Measures of central tendency were extracted from the outcome distributions and constituents were ranked according to these three risk assessment indices. The constituents for which ILCR >10(-4), HQ >1, and MOE <10,000 included acetaldehyde, acrylonitrile, benzene, cadmium, formaldehyde, and pyridine. While limitations exist to this methodology in estimating the absolute magnitude of health risk contributed by each MSS constituent, this approach provides a plausible and objective framework for the prioritization of toxicants in cigarette smoke and is valuable in guiding tobacco risk management.

Determination of tissue to blood partition coefficients for nonvolatile herbicides, insecticides, and fungicides using negligible depletion solid-phase microextraction (nd-SPME) and ultrafiltration

Partition coefficients (PCs) are used in physiologically based pharmacokinetic (PBPK) models to estimate the free concentration of a chemical in specific blood or organs. Biological PC(tissue:blood) (tissue to blood) values were determined for a series of nonvolatile herbicides, insecticides, and fungicides in liver, brain, skin, fat, kidneys, and muscle of male Sprague-Dawley rats using two different analytical methods. The free phase concentration (in phosphate-buffered saline) of a given chemical was measured in the presence and absence of tissue (including blood) and used to calculate the PC, defined as the ratio of the concentration of the chemical in saline to the concentration in the tissue. PCs were determined for 13 compounds with aqueous solubility ranging from 20 to 4100 mg/L, molecular weights from 187.3 to 342.2 g/mol, and log K (ow) values from -0.18 to 3.9. An ultrafiltration high-performance liquid chromatography (HPLC) method was implemented for compounds with log K (ow) near 0.1 or less and a negligible depletion solid-phase microextraction (nd-SPME) method for compounds with higher log K (ow). PC(tissue:saline) coefficients of variation were 0.13 (n = 3 compounds) on average for the HPLC method and 0.29 (n = 10 compounds) for the nd-SPME method. Presented here is one of the most comprehensive data sets of biological partition coefficients for herbicides, insecticides, and fungicides.

Kinetic modelling of in vitro cell-based assays to characterize non-specific bindings and ADME processes in a static and a perfused fluidic system

Recently, physiologically based perfusion in vitro systems have been developed to provide cell culture environment close to in vivo cell environment (e.g., fluidic conditions, organ interactions). In this work, we model and compare the fate of a chemical, benzo[a]pyrene (B[a]P), in a perfusion and a standard (static well-plate) system. These in vitro systems are composed of Caco-2 and HepG2 cells so as to mimic absorption across the small intestine and intestinal and hepatic metabolism. Compartmental models were developed and calibrated with B[a]P kinetics data in the culture medium to estimate the apparent permeability of Caco-2 cells, the in vitro biotransformation of B[a]P, as well as the different routes of loss by non-specific adsorption. Our results show that non-specific binding is the main process responsible for the depletion of B[a]P in the culture media: at steady state, only 40% and 24% of the total concentration of B[a]P are bioavailable in the static and perfused systems, respectively. We also showed that Caco-2 permeability in the perfused culture system is closer to in vivo conditions than the one obtained in the static system and that higher cellular metabolic activities are observed in static conditions. Perfused in vitro systems combined with kinetic modelling are promising tools for studying in vitro the different processes involved in the toxicokinetics of xenobiotics.

A Workflow for Global Sensitivity Analysis of PBPK Models

Physiologically based pharmacokinetic (PBPK) models have a potentially significant role in the development of a reliable predictive toxicity testing strategy. The structure of PBPK models are ideal frameworks into which disparate in vitro and in vivo data can be integrated and utilized to translate information generated, using alternative to animal measures of toxicity and human biological monitoring data, into plausible corresponding exposures. However, these models invariably include the description of well known non-linear biological processes such as, enzyme saturation and interactions between parameters such as, organ mass and body mass. Therefore, an appropriate sensitivity analysis (SA) technique is required which can quantify the influences associated with individual parameters, interactions between parameters and any non-linear processes. In this report we have defined the elements of a workflow for SA of PBPK models that is computationally feasible, accounts for interactions between parameters, and can be displayed in the form of a bar chart and cumulative sum line (Lowry plot), which we believe is intuitive and appropriate for toxicologists, risk assessors, and regulators.

A physiologically-based kinetic model for the prediction of plasma cholesterol concentrations in the mouse

The LDL cholesterol (LDL-C) and HDL cholesterol (HDL-C) concentrations are determined by the activity of a complex network of reactions in several organs. Physiologically-based kinetic (PBK) computational models can be used to describe these different reactions in an integrated, quantitative manner. A PBK model to predict plasma cholesterol levels in the mouse was developed, validated, and analyzed. Kinetic parameters required for defining the model were obtained using data from published experiments. To construct the model, a set of appropriate submodels was selected from a set of 65,536 submodels differing in the kinetic expressions of the reactions. A submodel was considered appropriate if it had the ability to correctly predict an increased or decreased plasma cholesterol level for a training set of 5 knockout mouse strains. The model thus defined consisted of 8 appropriate submodels and was validated using data from an independent set of 9 knockout mouse strains. The model prediction is the average prediction of 8 appropriate submodels. Remarkably, these submodels had in common that the rate of cholesterol transport from the liver to HDL was not dependent on hepatic cholesterol concentrations. The model appeared able to accurately predict in a quantitative way the plasma cholesterol concentrations of all 14 knockout strains considered, including the frequently used Ldlr-/- and Apoe-/- mouse strains. The model presented is a useful tool to predict the effect of knocking out genes that act in important steps in cholesterol metabolism on total plasma cholesterol, HDL-C and LDL-C in the mouse.

Technological challenges of addressing new and more complex migrating products from novel food packaging materials

The risk assessment of migration products resulting from packaging material has and continues to pose a difficult challenge. In most jurisdictions, there are regulatory requirements for the approval or notification of food contact substances that will be used in packaging. These processes generally require risk assessment to ensure safety concerns are addressed. The science of assessing food contact materials was instrumental in the development of the concept of Threshold of Regulation and the Threshold of Toxicological Concern procedures. While the risk assessment process is in place, the technology of food packaging continues to evolve to include new initiatives, such as the inclusion of antimicrobial substances or enzyme systems to prevent spoilage, use of plastic packaging intended to remain on foods as they are being cooked, to the introduction of more rigid, stable and reusable materials, and active packaging to extend the shelf-life of food. Each new technology brings with it the potential for exposure to new and possibly novel substances as a result of migration, interaction with other chemical packaging components, or, in the case of plastics now used in direct cooking of products, degradation products formed during heating. Furthermore, the presence of trace levels of certain chemicals from packaging that were once accepted as being of low risk based on traditional toxicology studies are being challenged on the basis of reports of adverse effects, particularly with respect to endocrine disruption, alleged to occur at very low doses. A recent example is the case of bisphenol A. The way forward to assess new packaging technologies and reports of very low dose effects in non-standard studies of food contact substances is likely to remain controversial. However, the risk assessment paradigm is sufficiently robust and flexible to be adapted to meet these challenges. The use of the Threshold of Regulation and the Threshold of Toxicological Concern concepts may play a critical role in the risk assessment of new food packaging technologies in the future.

A generalized physiologically-based toxicokinetic modeling system for chemical mixtures containing metals

Background

Humans are routinely and concurrently exposed to multiple toxic chemicals, including various metals and organics, often at levels that can cause adverse and potentially synergistic effects. However, toxicokinetic modeling studies of exposures to these chemicals are typically performed on a single chemical basis. Furthermore, the attributes of available models for individual chemicals are commonly estimated specifically for the compound studied. As a result, the available models usually have parameters and even structures that are not consistent or compatible across the range of chemicals of concern. This fact precludes the systematic consideration of synergistic effects, and may also lead to inconsistencies in calculations of co-occurring exposures and corresponding risks. There is a need, therefore, for a consistent modeling framework that would allow the systematic study of cumulative risks from complex mixtures of contaminants.

Methods

A Generalized Toxicokinetic Modeling system for Mixtures (GTMM) was developed and evaluated with case studies. The GTMM is physiologically-based and uses a consistent, chemical-independent physiological description for integrating widely varying toxicokinetic models. It is modular and can be directly "mapped" to individual toxicokinetic models, while maintaining physiological consistency across different chemicals. Interaction effects of complex mixtures can be directly incorporated into the GTMM.

Conclusions

The application of GTMM to different individual metals and metal compounds showed that it explains available observational data as well as replicates the results from models that have been optimized for individual chemicals. The GTMM also made it feasible to model toxicokinetics of complex, interacting mixtures of multiple metals and nonmetals in humans, based on available literature information. The GTMM provides a central component in the development of a "source-to-dose-to-effect" framework for modeling population health risks from environmental contaminants. As new data become available on interactions of multiple chemicals, the GTMM can be iteratively parameterized to improve mechanistic understanding of human health risks from exposures to complex mixtures of chemicals.

A Bayesian population PBPK model for multiroute chloroform exposure

A Bayesian hierarchical model was developed to estimate the parameters in a physiologically based pharmacokinetic (PBPK) model for chloroform using prior information and biomarker data from different exposure pathways. In particular, the model provides a quantitative description of the changes in physiological parameters associated with hot-water bath and showering scenarios. Through Bayesian inference, uncertainties in the PBPK parameters were reduced from the prior distributions. Prediction of biomarker data with the calibrated PBPK model was improved by the calibration. The posterior results indicate that blood flow rates varied under two different exposure scenarios, with a two-fold increase of the skin's blood flow rate predicted in the hot-bath scenario. This result highlights the importance of considering scenario-specific parameters in PBPK modeling. To demonstrate the application of a probability approach in toxicological assessment, results from the posterior distributions from this calibrated model were used to predict target tissue dose based on the rate of chloroform metabolized in liver. This study demonstrates the use of the Bayesian approach to optimize PBPK model parameters for typical household exposure scenarios.

Physiologically based pharmacokinetic modeling of deltamethrin: development of a rat and human diffusion-limited model

Mirfazaelian et al. developed a physiologically based pharmacokinetic (PBPK) model for the pyrethroid pesticide deltamethrin in the rat. This model describes gastrointestinal (GI) tract absorption as a saturable process mediated by phase III efflux transporters which pump deltamethrin out of the intestinal enterocytes into the GI tract lumen, resulting in minimal net absorption at low concentrations and increasing absorption at higher concentrations. In the present study, the dose dependency in absorption of deltamethrin was examined in male Long Evans rats using po exposures predicted by the Mirfazaelian model to yield different po bioavailability values. No difference in the bioavailability from single po doses of 0.3 and 3.0 mg/kg deltamethrin was observed. Based on this finding, the Mirfazaelian PBPK model was modified to exclude a saturable absorption process. Other changes to the Mirfazaelian model included describing all tissue compartments with diffusion-limited kinetics and a single blood compartment. These changes improved model predictions of deltamethrin tissue concentration data from the present study and the literature. The rat model was then scaled to humans. The model predicted a twofold greater peak deltamethrin brain concentration and threefold greater area under the curve (AUC(0-48 h)) for humans following an po exposure of 1 mg/kg. Based on this model, humans would have greater distribution of deltamethrin to the brain for the same administered po dose compared to rats. The relative sensitivity to deltamethrin between rats and humans depends on both pharmacokinetic and pharmacodynamic differences. Species differences in the pharmacodynamic responses to deltamethrin between rats and humans remain uncharacterized.

Brain Toxicokinetics of Prometryne in Mice

Prometryne is a methylthio-s-triazine herbicide. Significant trace amounts are found in the environment, mainly in water, soil, and food plants. The aim of this study was to establish brain and blood prometryne levels after single oral dose (1 g kg-1) in adult male and female mice. Prometryne was measured using the GC/MS assay at 1, 2, 4, 8, and 24 h after prometryne administration. Peak brain and blood prometryne values were observed 1 h after administration and they decreased in a time-dependent manner. Male mice had consistently higher brain and blood prometryne levels than female mice. The observed prometryne kinetics was similar to that reported for the structurally related herbicide atrazine.

Physiologically based modeling of p-tert-octylphenol kinetics following intravenous, oral or subcutaneous exposure in male and female Sprague-Dawley rats

The objective of this study was to develop a physiologically based pharmacokinetic (PBPK) model for p-tert-octylphenol (OP) for understanding the qualitative and quantitative determinants of its kinetics in Sprague-Dawley rats. Compartments of the PBPK model included the liver, richly perfused tissues, poorly perfused tissues, reproductive tissues, adipose tissue and subcutaneous space, in which OP uptake was described as a blood flow- or a membrane diffusion-limited process. The PBPK model successfully simulated previously published data on blood and tissue OP concentrations in Sprague-Dawley rats following oral, intravenous (i.v.) or subcutaneous (s.c.) routes. The model predicted that OP concentrations would reach 6.8, 13.8 and 27.9 ng ml(-1) (male) and 7.2, 14.7 and 31.4 ng ml(-1) (female), 4 h after a single i.v. dose of 2, 4 and 8 mg kg(-1), respectively. The model also predicted that OP concentrations would reach 53.3, 134.8 and 271.2 ng ml(-1) (male) and 87.4, 221.4 and 449.7 ng ml(-1) (female) 4 h after a single oral dose (50, 125 and 250 mg kg(-1)) and that, 4 h after a single s.c. dose (125 mg kg(-1)), OP concentrations would reach 111.3 ng ml(-1) (male) and 121.6 ng ml(-1). A marked sex difference was seen in blood and tissue OP concentrations. This was reflected in the model by a gender-specific maximal velocity of metabolism (V(max)) that was higher (1.77 x) in male than in female rats. Further studies are required to elucidate the mechanism underlying the gender differences and to evaluate whether that is also observed in humans.

Trichloroethylene risk assessment: a review and commentary

Trichloroethylene (TCE) is a widespread environmental contaminant that is carcinogenic when given in high, chronic doses to certain strains of mice and rats. The capacity of TCE to cause cancer in humans is less clear. The current maximum contaminant level (MCL) of 5 ppb (microg/L) is based on an US Environment Protection Agency (USEPA) policy decision rather than the underlying science. In view of major advances in understanding the etiology and mechanisms of chemically induced cancer, USEPA began in the late 1990s to revise its guidelines for cancer risk assessment. TCE was chosen as the pilot chemical. The USEPA (2005) final guidelines emphasized a "weight-of-evidence" approach with consideration of dose-response relationships, modes of action, and metabolic/toxicokinetic processes. Where adequate data are available to support reversible binding of the carcinogenic moiety to biological receptors as the initiating event (i.e., a threshold exists), a nonlinear approach is to be used. Otherwise, the default assumption of a linear (i.e., nonthreshold) dose-response is utilized. When validated physiologically based pharmacokinetic (PBPK) models are available, they are to be used to predict internal dosimetry as the basis for species and dose extrapolations. The present article reviews pertinent literature and discusses areas where research may resolve some outstanding issues and facilitate the reassessment process. Key research needs are proposed, including role of dichloroacetic acid (DCA) in TCE-induced liver tumorigenesis in humans; extension of current PBPK models to predict target organ deposition of trichloroacetic acid (TCA) and DCA in humans ingesting TCE in drinking water; use of human hepatocytes to ascertain metabolic rate constants for use in PBPK models that incorporate variability in metabolism of TCE by potentially sensitive subpopulations; measurement of the efficiency of first-pass elimination of trace levels of TCE in drinking water; and assessment of exogenous factors' (e.g., alcohol, drugs) ability to alter metabolic activation and risks at such low-level exposure.

Predicting plasma concentrations of bisphenol A in children younger than 2 years of age after typical feeding schedules, using a physiologically based toxicokinetic model

BACKGROUND

Concerns have recently been raised regarding the safety of potential human exposure to bisphenol A (BPA), an industrial chemical found in some polycarbonate plastics and epoxy resins. Of particular interest is the exposure of young children to BPA via food stored in BPA-containing packaging.

OBJECTIVES

In this study we assessed the age dependence of the toxicokinetics of BPA and its glucuronidated metabolite, BPA-Glu, using a coupled BPA-BPA-Glu physiologically based toxicokinetic (PBTK) model.

METHODS

Using information gathered from toxicokinetic studies in adults, we built a PBTK model. We then scaled the model to children < 2 years of age based on the age dependence of physiologic parameters relevant for absorption, distribution, metabolism, and excretion.

RESULTS

We estimated the average steady-state BPA plasma concentration in newborns to be 11 times greater than that in adults when given the same weight-normalized dose. Because of the rapid development of the glucuronidation process, this ratio dropped to 2 by 3 months of age. Simulation of typical feeding exposures, as estimated by regulatory authorities, showed a 5-fold greater steady-state BPA plasma concentration in 3- and 6-month-olds compared with adults, reflecting both a reduced capacity for BPA metabolism and a greater weight-normalized BPA exposure. Because of uncertainty in defining the hepatic BPA intrinsic clearance in adults, these values represent preliminary estimates.

CONCLUSIONS

Simulations of the differential BPA dosimetry between adults and young children point to the need for more sensitive analytical methods for BPA to define, with greater certainty, the adult hepatic BPA intrinsic clearance, as well as a need for external exposure data in young children.

Physiology-based simulations of a pathological condition: prediction of pharmacokinetics in patients with liver cirrhosis

BACKGROUND

Liver cirrhosis is a progressive disease characterized by loss of functional hepatocytes with concomitant connective tissue and nodule formation in the liver. The morphological and physiological changes associated with the disease substantially affect drug pharmacokinetics. Whole-body physiologically based pharmacokinetic (WB-PBPK) modelling is a predictive technique that quantitatively relates the pharmacokinetic parameters of a drug to such (patho-)physiological conditions.

OBJECTIVE

To extend an existing WB-PBPK model, based on the physiological changes associated with liver cirrhosis, which allows for prediction of drug pharmacokinetics in patients with liver cirrhosis.

METHODS

The literature was searched for quantitative measures of the physiological changes associated with the presence of Child-Pugh class A through C liver cirrhosis. The parameters that were included were the organ blood flows, cardiac index, plasma binding protein concentrations, haematocrit, functional liver volume, hepatic enzymatic activity and glomerular filtration rate. Predictions of pharmacokinetic profiles and parameters were compared with literature data for the model compounds alfentanil, lidocaine (lignocaine), theophylline and levetiracetam.

RESULTS

The predicted versus observed plasma concentration-time profiles for alfentanil and lidocaine were similar, such that the pharmacokinetic changes associated with Child-Pugh class A, B and C liver cirrhosis were adequately described. The theophylline elimination half-life was greatly increased in Child-Pugh class B and C patients compared with controls, as predicted by the model. Levetiracetam urinary excretion was consistently reduced with disease progression and very closely resembled observed values.

CONCLUSION

Consideration of the physiological differences between healthy individuals and patients with liver cirrhosis was important for the simulation of drug pharmacokinetics in this compromised group. The WB-PBPK model was altered to incorporate these physiological differences with the result of adequate simulation of drug pharmacokinetics. The information provided in this study will allow other researchers to further validate this liver cirrhosis model within a WB-PBPK model.

Application of Magnetic Resonance (MR) Imaging for the Development and Validation of Computational Fluid Dynamic (CFD) Models of the Rat Respiratory System

Computational fluid dynamic (CFD) models of the respiratory system provide a quantitative basis for extrapolating the localized dose of inhaled materials and improving human health risk assessments based upon inhalation studies conducted in animals. Nevertheless, model development and validation have historically been tedious and time-consuming tasks. In recognition of this, we previously reported on the use of proton (1H) magnetic resonance (MR) imaging for visualizing nasal-sinus passages in the rat, and for speeding computational mesh generation. Here, the generation and refinement of meshes for rat nasal airways are described in more detail and simulated airflows are presented. To extend the CFD models to the complete respiratory tract, three-dimensional (3D) 1H MR imaging of rat pulmonary casts was also utilized to construct pulmonary airway meshes using procedures developed for the nasal airways. Furthermore, the feasibility of validating CFD predictions with MR was tested by imaging hyperpolarized 3He gas at physiological flow rates in a straight pipe with a diameter comparable to the rat trachea. Results from these diverse studies highlight the potential utility of MR imaging not only for speeding CFD development but also possibly for model validation.

Is a quantitative risk assessment of air quality in underground parking garages possible?

Little information is available about the health risks associated with time spent in underground parking garages. The objective of this study was to determine whether it is possible to quantify the health risks associated with these garages without epidemiologic data on the subject. We followed the standard procedure for health risk assessment. We searched the literature for pollutant concentrations in the air samples of underground parking garages, the hazards associated with their inhalation, and their toxicological reference values. Conditions of occupational and user exposure were estimated by scenarios and taken into account to discuss toxicological reference values by modifying (with Haber's law) the adjustment factors for exposure frequency and duration. Risk quantification was possible for 39 pollutants. Acute exposures to CO and NO2 exceed toxicological reference values, as does chronic exposure to benzene for threshold effects. The risk of a carcinogenic effect associated with benzene may be greater than 10(-5). Excess exposure to air pollution indicators (PM and NO2) is also elevated, judging by the WHO Air Quality Guidelines, and also when comparing to levels with reported effects in epidemiologic studies. The risk associated with underground parking garages can be evaluated only in part. The information available is nonetheless sufficient to justify actions to reduce exposure.

PRACTICAL IMPLICATIONS

The risks associated with exposure in underground parking garages cannot be thoroughly evaluated because of inadequate knowledge of exposures and of the toxicity of pollutants. The available knowledge is nonetheless sufficient to advise that risk management measures should be taken to reduce both acute and chronic exposures.

The relevance of animal models for aerosol studies

Animal models are essential for understanding the fates and effects of inhaled materials, because invasive methods are frequently necessary to provide the desired information. Because of the variability in humans of particle deposition, clearance, and effects, numerous animal models have been used in inhalation studies. Furthermore, humans are not typical mammals in some ways that affect inhalation phenomena. Humans have less fur, longer gestation and life times, simplified nasal structure, and symmetric bronchial branching in relation to other mammals. However, experience, plus the genetic similarity among mammals, underpins the use of animal models. Mammals are varied with respect to their inhaled particle deposition and clearance phenomena. Total inhaled aerosol deposition probability versus particle-size curves are qualitatively similar for various mammals of similar body mass, despite airway anatomy differences. However, more species variation is seen in regional particle deposition curves, complicating aerosol study design. The rates of clearance of deposited slowly dissolving particles are animal species dependent, apparently due to differences in gross, subgross, and cellular respiratory tract biology. Clearance rates for rapidly dissolving particles are not strongly species dependent. Inhalation toxicology studies require several animal species. Rodents are among the most frequently used, but for studies of lung development, diseases, exercise, etc., and for extrapolation to humans, larger mammals are also needed. Fortunately, the research database, and excellent monographs on inhalation phenomena provide ample guidance for study design.

An integrated QSPR-PBPK modelling approach for in vitro-in vivo extrapolation of pharmacokinetics in rats

In vitro data on metabolism and partitioning may be integrated within physiologically-based pharmacokinetic (PBPK) models to provide simulations of the kinetics and bioaccumulation of chemicals in intact organisms. Quantitative structure-property relationship (QSPR) modelling of available in vitro data may be performed to predict metabolism rates and partition coefficients (PCs) for developing in vivo PBPK models. The objective of the present study was to develop an integrated QSPR-PBPK modelling approach for the conduct of in vitro to in vivo extrapolation. For this purpose, data on rat blood:air (P(b)) and fat:air (P(f)) PCs, as well as intrinsic metabolic clearance (CL(int)) obtained using rat liver slices for some C(5)-C(10) volatile organic compounds (VOCs) were compiled from the literature. Multilinear additive QSPR models for P(f), P(b) and CL(int) were developed based on the number and nature of molecular fragments in these VOCs (CH(3), CH(2), CH, C, C=C, H, benzene ring and H in benzene ring structure). The mean estimated/experimental (est/exp) ratios (+/-SD; range) were 1.0 (+/-0.04; 0.93 - 1.06) for log P(f), 1.08 (+/-0.26; 0.70 - 1.62) for log P(b), and 1.07 (+/- 0.21; 0.80 - 1.44) for CL(int). By accounting for the difference in the content of neutral lipids in fat and other tissues, the liver : air and muscle : air PCs of the compounds investigated in this study, with the excerption of n-decane, were adequately predicted from P(f). Integrating the QSPRs for P(f), P(b) and CL(int) within a rat PBPK model, simulations of inhalation pharmacokinetics of several VOCs were generated on the basis of molecular structure, for a given exposure scenario. The integrated QSPR-PBPK model developed in this study is a potentially useful tool for predicting in vivo kinetics and bioaccumulation of chemicals in rats under poor data situations.

Extrahepatic metabolism by CYP2E1 in PBPK modeling of lipophilic volatile organic chemicals: impacts on metabolic parameter estimation and prediction of dose metrics

Physiologically based pharmacokinetic (PBPK) models are increasingly available for environmental chemicals and applied in risk assessments. Volatile organic compounds (VOCs) are important pollutants in air, soil, and water. CYP2E1 metabolically activates many VOCs in animals and humans. Despite its presence in extrahepatic tissues, the metabolism by CYP2E1 is often described as restricted to the liver in PBPK models, unless target tissue dose metrics in extrahepatic tissues are needed for the model application, including risk assessment. The impact of accounting for extrahepatic metabolism by CYP2E1 on the estimation of metabolic parameters and the prediction of dose metrics was evaluated for three lipophilic VOCs: vinyl chloride, trichloroethylene, and carbon tetrachloride. Metabolic parameters estimated from fitting gas uptake data with and without extrahepatic metabolism were similar. The impact of extrahepatic metabolism on PBPK predictions was evaluated using inhalation exposure scenarios relevant for animal toxicity studies and human risk assessment. Although small, the relative role of extrahepatic metabolism and the differences in the predicted dose metrics were greater at low exposure concentrations. The impact was species dependent and influenced by Km for CYP2E1. The current study indicates that inhalation modeling for several representative VOCs that are CYP2E1 substrates is not affected by the inclusion of extrahepatic metabolism, implying that liver-only metabolism may be a reasonable simplification for PBPK modeling of lipophilic VOCs. The PBPK predictions using this assumption can be applied confidently for risk assessment, but this conclusion should not necessarily be applied to VOCs that are metabolized by other enzymes.

Whole-body physiologically based pharmacokinetic models

This review summarizes the most recent developments in and applications of physiologically based pharmacokinetic (PBPK) modeling methodology originating from both the pharmaceutical and environmental toxicology areas. It focuses on works published in the last 5 years, although older seminal papers have also been referenced. After a brief introduction to the field and several essential definitions, the main body of the text is structured to follow the major steps of a typical PBPK modeling exercise. Various applications of the methodology are briefly described. The major future trends and perspectives are outlined. The main conclusion from the review of the available literature is that PBPK modeling, despite its obvious potential and recent incremental developments, has not taken the place it deserves, especially in pharmaceutical and drug development sciences.

Organ growth functions in maturing male Sprague-Dawley rats based on a collective database

Ten different organ weights (liver, spleen, kidneys, heart, lungs, brain, adrenals, testes, epididymes, and seminal vesicles) of male Sprague-Dawley (S-D) rats of different ages (1-280 d) were extracted based on a thorough literature survey database. A generalized Michaelis-Menten (GMM) model, used to fit organ weights versus age in a previous study (Schoeffner et al., 1999) based on a limited data, was used to find the best fit model for the present expanded data compilation. The GMM model has the functional form: Wt = (Wt(o).K(gamma) + Wt(max).Age(gamma))/(K(gamma) + Age(gamma)) where Wt is organ/tissue weight at a specified age, Wt(o) and Wt(max) are weight at birth and maximal growth, respectively, and K and gamma are constants. Organ weights were significantly correlated with their respective ages for all organs and tissues. GMM-derived organ growth and percent body weight (%BW) fractions of different tissues were plotted against animal age and compared with experimental values as well as previously published models. The GMM-based organ growth and %BW fraction profiles were in general agreement with our empirical data as well as with previous studies. The present model was compared with the GMM model developed previously for six organs--liver, spleen, kidneys, heart, lungs, and brain--based on a limited data, and no significant difference was noticed between the two sets of predictions. It was concluded that the GMM models presented herein for different male S-D rats organs (liver, spleen, kidneys, heart, lungs, brain, adrenals, testes, epididymes, and seminal vesicles) are capable of predicting organ weights and %BW ratios accurately at different ages.

A Cheminformatic Toolkit for Mining Biomedical Knowledge

PURPOSE

Cheminformatics can be broadly defined to encompass any activity related to the application of information technology to the study of properties, effects and uses of chemical agents. One of the most important current challenges in cheminformatics is to allow researchers to search databases of biomedical knowledge, using chemical structures as input.

MATERIALS AND METHODS

An important step towards this goal was the establishment of PubChem, an open, centralized database of small molecules accessible through the World Wide Web. While PubChem is primarily intended to serve as a repository for high throughput screening data from federally-funded screening centers and academic research laboratories, the major impact of PubChem could also reside in its ability to serve as a chemical gateway to biomedical databases such as PubMed.

CONCLUSION

This article will review cheminformatic tools that can be applied to facilitate annotation of PubChem through links to the scientific literature; to integrate PubChem with transcriptomic, proteomic, and metabolomic datasets; to incorporate results of numerical simulations of physiological systems into PubChem annotation; and ultimately, to translate data of chemical genomics screening efforts into information that will benefit biomedical researchers and physician scientists across all therapeutic areas.

Organ growth functions in maturing male Sprague-Dawley rats

Growth equations can be used in physiologically based pharmacokinetic (PBPK) modeling to provide physiological parameters (e.g., body weight, tissue/organ volumes) for maturing rodents. No diligent systematic exercise was found in the literature dealing with growth equations for developing rats' tissues. A generalized Michaelis-Menten (GMM) model, originally developed to fit body weight vs. age data, was chosen to estimate different physiological compartment sizes. The GMM model has the functional form: Wt = (Wt(o).K(gamma) + Wt(max).Age(gamma))/(K(gamma) + Age(gamma)) where Wt is organ/tissue weight at a specified age, Wt(o) and Wt(max) are weight at birth and maximal growth respectively, and K and gamma are constants. Weights of freshly collected organs (liver, spleen, kidneys, heart, lungs, brain, gastrointestinal tract and adipose tissue), measured in male Sprague-Dawley rats of different ages (1-280 d) in our laboratory, were used to evaluate this model's performance. The GMM model was fitted to the organ weights, and the resulting parameters were statistically significant for all organs and tissues. Organ weights were highly correlated with their respective ages. GMM-derived organ growth and percent body weight (%BW) fractions of different tissues were plotted against animal age and compared with experimental values. The GMM-based organ growth and %BW fraction profiles were in general agreement with our empirical data as well as previous studies. The GMM model gave adequately precise weight predictions at all ages for all the tissues/organs examined.

Development of a non-invasive biomonitoring approach to determine exposure to the organophosphorus insecticide chlorpyrifos in rat saliva

Non-invasive biomonitoring approaches are being developed using reliable portable analytical systems to quantify dosimetry utilizing readily obtainable body fluids, such as saliva. In the current study, rats were given single oral gavage doses (1, 10, or 50 mg/kg) of the insecticide chlorpyrifos (CPF). Saliva and blood were then collected from groups of animals (4/time-point) at 3, 6, and 12 h post-dosing, and were analyzed for the CPF metabolite trichloropyridinol (TCP). Trichloropyridinol was detected in both blood and saliva at all doses and the TCP concentration in blood exceeded saliva, although the kinetics in blood and saliva were comparable. A physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) model for CPF incorporated a compartment model to describe the time-course of TCP in blood and saliva. The model adequately simulated the experimental results over the dose ranges evaluated. A rapid and sensitive sequential injection (SI) electrochemical immunoassay was developed to monitor TCP, and the reported detection limit for TCP was 6 ng/L (in water). Computer model simulation in the range of the Allowable Daily Intake (ADI) or Reference Dose (RfD) for CPF (0.01-0.003 mg/kg/day) suggests that the electrochemical immunoassay has adequate sensitivity to detect and quantify TCP in saliva at these low exposure levels. However, to validate this approach, further studies are needed to more fully understand the pharmacokinetics of CPF and TCP excretion in saliva. These initial findings suggest that the utilization of saliva as a biomonitoring matrix, coupled to real-time quantitation and PBPK/PD modeling represents a novel approach with broad application for evaluating both occupational and environmental exposures to CPF.

Development and application of physiologically based pharmacokinetic-modeling tools to support drug discovery

Physiologically based pharmacokinetic (PBPK) modeling integrates physicochemical (PC) and in vitro pharmacokinetic (PK) data using a mechanistic framework of principal ADME (absorption, distribution, metabolism, and excretion) processes into a physiologically based whole-body model. Absorption, distribution, and clearance are modeled by combining compound-specific PC and PK properties with physiological processes. Thereby, isolated in vitro data can be upgraded by means of predicting full concentration-time profiles prior to animal experiments. The integrative process of PBPK modeling leads to a better understanding of the specific ADME processes driving the PK behavior in vivo, and has the power to rationally select experiments for a more focussed PK project support. This article presents a generic disposition model based on tissue-composition-based distribution and directly scaled hepatic clearance. This model can be used in drug discovery to identify the critical PK issues of compound classes and to rationally guide the optimization path of the compounds toward a viable development candidate. Starting with a generic PBPK model, which is empirically based on the most common PK processes, the model will be gradually tailored to the specifics of drug candidates as more and more experimental data become available. This will lead to a growing understanding of the 'drug in the making', allowing a range of predictions to be made for various purposes and conditions. The stage is set for a wide penetration of PK modeling and simulations to form an intrinsic part of a project starting from lead discovery, to lead optimization and candidate selection, to preclinical profiling and clinical trials.

Physiologically based synthetic models of hepatic disposition

Current physiologically based pharmacokinetic (PBPK) models are inductive. We present an additional, different approach that is based on the synthetic rather than the inductive approach to modeling and simulation. It relies on object-oriented programming. A model of the referent system in its experimental context is synthesized by assembling objects that represent components such as molecules, cells, aspects of tissue architecture, catheters, etc. The single pass perfused rat liver has been well described in evaluating hepatic drug pharmacokinetics (PK) and is the system on which we focus. In silico experiments begin with administration of objects representing actual compounds. Data are collected in a manner analogous to that in the referent PK experiments. The synthetic modeling method allows for recognition and representation of discrete event and discrete time processes, as well as heterogeneity in organization, function, and spatial effects. An application is developed for sucrose and antipyrine, administered separately and together. PBPK modeling has made extensive progress in characterizing abstracted PK properties but this has also been its limitation. Now, other important questions and possible extensions emerge. How are these PK properties and the observed behaviors generated? The inherent heuristic limitations of traditional models have hindered getting meaningful, detailed answers to such questions. Synthetic models of the type described here are specifically intended to help answer such questions. Analogous to wet-lab experimental models, they retain their applicability even when broken apart into sub-components. Having and applying this new class of models along with traditional PK modeling methods is expected to increase the productivity of pharmaceutical research at all levels that make use of modeling and simulation.

Approaches to the risk assessment of genotoxic carcinogens in food: A critical appraisal

The present paper examines the particular difficulties presented by low levels of food-borne DNA-reactive genotoxic carcinogens, some of which may be difficult to eliminate completely from the diet, and proposes a structured approach for the evaluation of such compounds. While the ALARA approach is widely applicable to all substances in food that are both carcinogenic and genotoxic, it does not take carcinogenic potency into account and, therefore, does not permit prioritisation based on potential risk or concern. In the absence of carcinogenicity dose-response data, an assessment based on comparison with an appropriate threshold of toxicological concern may be possible. When carcinogenicity data from animal bioassays are available, a useful analysis is achieved by the calculation of margins of exposure (MOEs), which can be used to compare animal potency data with human exposure scenarios. Two reference points on the dose-response relationship that can be used for MOE calculation were examined; the T25 value, which is derived from linear extrapolation, and the BMDL10, which is derived from mathematical modelling of the dose-response data. The above approaches were applied to selected food-borne genotoxic carcinogens. The proposed approach is applicable to all substances in food that are DNA-reactive genotoxic carcinogens and enables the formulation of appropriate semi-quantitative advice to risk managers.

Swine models in the design of more effective medical countermeasures against organophosphorus poisoning

Although the three most commonly used large mammal species in the safety assessment of drugs remain the dog, the macaque and the marmoset, swine, especially minipigs, have also been widely used over the years in many toxicological studies. Swine present a number of interesting biological and physiological characteristics. Similarities in skin properties with humans have led to extensive in vitro and in vivo studies. There is a specific interest in cardiovascular research, as well as in anaesthesiology and critical care medicine due to common features of swine and human physiology. Although knowledge of swine brain structure and functions remains incomplete, data does exist. The multiple blood sampling that is necessary in pharmacokinetic and toxicokinetic studies are possible, as well as multiparametric monitoring and interventions with equipment used in human clinical settings. Practicality (handling), scientific (stress reduction) and ethical (invasive monitoring) reasons have led research teams to incorporate anaesthesia into their paradigms which makes the analysis of data increasingly difficult. Although not substantiated by scientific data, the swine appears to have an intermediate position in the scale of public perception between non-human primates and animals commonly referred to as pets (i.e. dogs and cats) and rodents. The benefits of the swine model justify the use of these animals in the design of more effective medical countermeasures against known chemical warfare agents (nerve agents, vesicants and lung damaging agents). Exposure to organophosphorus (OP) pesticides represents a severe health issue in developing countries, while OP intoxication with the more lethal military nerve agents is not only of military concern but also a terrorist threat. Tailoring therapeutic regimens to the reality of OP poisoning is of the utmost importance when little experimental data and sparse human clinical data are available in the decision making process. We will present some of the advantages and disadvantages of the swine model in OP countermeasures elaborating on two examples. First, we will present the issues related to the use of anaesthesia during experimental OP poisoning and second we will show how results from experiments with swine can be integrated into a kinetic-based dynamic model to evaluate oxime efficacy. A better knowledge of OP poisoning in swine (comparative toxicokinetics, pharmacokinetics and biochemistry) is definitely necessary before accepting it as a first choice non-rodent model. However, there exists a large amount of data in the model on anaesthesia and different types of shock favouring their use for evaluation of complex situations such as the anaesthesia of OP poisoned patients and combined injuries.

The Challenge of Predicting Drug Toxicity in silico

Poor pharmacokinetics, side effects and compound toxicity are frequent causes of late-stage failures in drug development. A safe in silico identification of adverse effects triggered by drugs and chemicals would be highly desirable as it not only bears economical potential but also spawns a variety of ecological benefits: sustainable resource management, reduction of animal models and possibly less risky clinical trials. In computer-aided drug discovery, both existing and hypothetical compounds may be studied; the methods are fast, reproducible, and typically based on human bioregulators, making the question of transferability obsolete. In the recent past, our laboratory contributed towards the development of in silico concepts (--> multi-dimensional QSAR) and validated a series of "virtual test kits" based on the oestrogen, androgen, thyroid, and aryl hydrocarbon receptor (endocrine disruption, receptor-mediated toxicity) as well as on the enzyme cytochrome P450 3A4 (metabolic transformations, drug-drug interactions). The test kits are based on the three-dimensional structure of their target protein (i.e. ER(alphabeta), AR, TR(alphabeta), CYP450) or a surrogate thereof (AhR) and were trained using a representative selection of 362 substances. Subsequent evaluation of 107 compounds different therefrom showed that binding affinities are predicted close to experimental uncertainty. These results suggest that our approach is suited for the in silico identification of adverse effects triggered by drugs and chemicals and encouraged us to compile an Internet Database for the virtual screening of drugs and chemicals for toxic effects.

Improving predictive modeling in pediatric drug development: pharmacokinetics, pharmacodynamics, and mechanistic modeling

A workshop was conducted on November 18-19, 2004, to address the issue of improving predictive models for drug delivery to developing humans. Although considerable progress has been made for adult humans, large gaps remain for predicting pharmacokinetic/pharmacodynamic (PK/PD) outcome in children because most adult models have not been tested during development. The goals of the meeting included a description of when, during development, infants/children become adult-like in handling drugs. The issue of incorporating the most recent advances into the predictive models was also addressed: both the use of imaging approaches and genomic information were considered. Disease state, as exemplified by obesity, was addressed as a modifier of drug pharmacokinetics and pharmacodynamics during development. Issues addressed in this workshop should be considered in the development of new predictive and mechanistic models of drug kinetics and dynamics in the developing human.

Steady-state solutions to PBPK models and their applications to risk assessment I: Route-to-route extrapolation of volatile chemicals

Although analysis of in vivo pharmacokinetic data necessitates use of time-dependent physiologically-based pharmacokinetic (PBPK) models, risk assessment applications are often driven primarily by steady-state and/or integrated (e.g., AUC) dosimetry. To that end, we present an analysis of steady-state solutions to a PBPK model for a generic volatile chemical metabolized in the liver. We derive an equivalent model that is much simpler and contains many fewer parameters than the full PBPK model. The state of the system can be specified by two state variables-the rate of metabolism and the rate of clearance by exhalation. For a given oral dose rate or inhalation exposure concentration, the system state only depends on the blood-air partition coefficient, metabolic constants, and the rates of blood flow to the liver and of alveolar ventilation. At exposures where metabolism is close to linear, only the effective first-order metabolic rate is needed. Furthermore, in this case, the relationship between cumulative exposure and average internal dose (e.g., AUCs) remains the same for time-varying exposures. We apply our analysis to oral-inhalation route extrapolation, showing that for any dose metric, route equivalence only depends on the parameters that determine the system state. Even if the appropriate dose metric is unknown, bounds can be placed on the route-to-route equivalence with very limited data. We illustrate this analysis by showing that it reproduces exactly the PBPK-model-based route-to-route extrapolation in EPA's 2000 risk assessment for vinyl chloride. Overall, we find that in many cases, steady-state solutions exactly reproduce or closely approximate the solutions using the full PBPK model, while being substantially more transparent. Subsequent work will examine the utility of steady-state solutions for analyzing cross-species extrapolation and intraspecies variability.

Rapid determination of the synthetic pyrethroid insecticide, deltamethrin, in rat plasma and tissues by HPLC

Deltamethrin (DLM), [(S)-alpha-cyano-d-phenoxybenzyl-(1R,3R)-e-(2,2 dibromovinyl)-2,2-dimethylcyclo-propane-1-carboxylate], is a pyrethroid insecticide widely used in agriculture and households. There are several methods for analysis of DLM in biological fluids and tissues, but these methods are time consuming. They generally involve the extraction of DLM with lipid-soluble solvents such as n-pentane, n-hexane, diethylether or acetone, and subsequent evaporation of the solvent. A more rapid and sensitive high-performance liquid chromatography (HPLC) method to analyze DLM in plasma and tissues (liver, kidney, and brain) was developed and validated according to U.S. Food and Drug Administration (U.S. FDA) and International Conference on Harmonization (ICH) of Technical Requirements for Registration of Pharmaceuticals for Human Use guidelines. The limit of detection (S/N of 3/1) for DLM was 0.01 microg/ml for plasma, liver, kidney and brain. The method performances were shown to be selective for DLM and linear over the concentration range 0.01-20.0 microg/ml. For five replications of samples at 0.05, 0.1, 0.2, 1.5 and 4.0 microg/ml, intraday precision and accuracy values were in the range of 0.7-13.1% relative standard deviation (%R.S.D.) and 1.8-14.1%Error, respectively. Interday (n = 15) precision and accuracy values at 0.05, 0.1, 0.2, 1.5, and 4.0 microg/ml were in the range of 3.2-15.2% (%R.S.D.) and 3.7-14.8%Error, respectively. The absolute recoveries of DLM ranged from 93 to 103% for plasma, 95 to 114% for liver, 97 to 108% for kidney, and 95 to 108% for brain. This method can be quite useful for DLM pharmacokinetic and tissue distribution studies, for which multiple plasma and tissue samples have to be analyzed quickly with high reproducibility.

Mechanistic study of the cellular interplay of transport and metabolism using the synthetic modeling method

PURPOSE

The aims of this study were 1) to demonstrate a new modeling strategy that uses experimental computational models built by the synthetic method and 2) to study the consequences of spatial alignment, or lack thereof, of P-glycoprotein (Pgp) and CYP3A4 on the transport and metabolism of drug-like compounds and the influence of competitive inhibition by metabolites on the transport and metabolism of those compounds.

METHODS

The synthetic method of modeling and simulation was used to construct discrete-event, discrete-space models. Within a framework designed for experimentation, object-oriented software components were assembled into devices representing the efflux transport and metabolism mechanisms within cell monolayers in Caco-2 transwell systems.

RESULTS

Conditions for transport and metabolism synergism (and lack thereof) were identified. Simulations showed how spatial alignment altered the coordinated influences of Pgp and CYP3A4 on absorption of a series of drug-like compounds. Within those experiments, when the metabolites were also substrates of Pgp, the metabolite levels produced were insufficient to give evidence of a competitive inhibitory effect on either transport or metabolism.

CONCLUSIONS

The results provide evidence of the potential value of using this class of models to improve our understanding of how complex cellular processes influence the transport and absorption of compounds, and the consequences of interventions.

Studies of intestinal drug transport using an in silico epithelio-mimetic device

We report the development and use of a synthetic, discrete event, discrete space model that functions as an epithelio-mimetic device (EMD). It is intended to facilitate the study of intestinal transport of drug-like compounds. We represent passive paracellular and transcellular transport, carrier-mediated transport and active efflux using stand-alone components. Systematic verification of the EMD over a wide physiologically realistic range is essential before we can use it to address questions regarding the details of the interacting mechanisms that are believed to influence absorption. We report details of key verification experiments. We demonstrate that this device can generate behaviors similar to those observed in the in vitro Caco-2 transwell system. To do that we used a series of hypothetical drugs and we simulated behaviors for two clinically used drugs, alfentanil and digoxin. The results support the feasibility and practicability of the EMD as a tool to expand the experimental options for better understanding the biological processes involved in intestinal transport and absorption of compounds of interest.

Moving from external exposure concentration to internal dose: duration extrapolation based on physiologically based pharmacokinetic derived estimates of internal dose

The potential human health risk(s) from chemical exposure must frequently be assessed under conditions for which adequate human or animal data are not available. The default method for exposure-duration adjustment, based on Haber's rule, C (external exposure concentration) or C(n) (the ten Berge modification) x t (exposure duration) = K (a constant toxic effect), has been criticized for prediction errors. A promising alternative approach to duration adjustment is based on equivalence of internal dose, that is, target-tissue dose levels, across different exposure durations. A proposed methodology for dose-duration adjustments for acute exposure guideline levels (AEGLs) based on physiologically based pharmacokinetic (PBPK) estimates of dose is illustrated with trichloroethylene (TCE). Steps in this methodology include: (1) selection and evaluation, or development and evaluation, of an appropriate PBPK model; (2) determination of an appropriate measure of internal dose; (3) estimation with the PBPK model of the tissue dose (the target tissue dose) resulting from the external exposure conditions (concentration, duration) of the critical effect; (4) estimation of the external exposure concentrations required to achieve tissue doses equivalent to the target tissue dose at exposure durations of interest; and (5) evaluation of sources of variability and uncertainty. For TCE, this PBPK modeling approach has allowed determination of dose metrics predictive of the acute neurotoxic effects of TCE and dose-duration adjustments based on estimates of internal dose.

Applications of dosimetry modeling to assessment of neurotoxic risk

Risk assessment procedures can be improved through better understanding and use of tissue dose information and linking tissue dose level to adverse outcomes. For volatile organic compounds, such as toluene and trichloroethylene (TCE), blood and brain concentrations can be estimated with physiologically based pharmacokinetic (PBPK) models. Acute changes in the function of the nervous system can be linked to the concentration of test compounds in the blood or brain at the time of neurological assessment. This set of information enables application to a number of risk assessment situations. For example, we have used this approach to recommend duration adjustments for acute exposure guideline levels (AEGLs) for TCE such that the exposure limits for each exposure duration yield identical tissue concentrations at the end of the exposure period. We have also used information on tissue concentration at the time of assessment to compare sensitivity across species, adjusting for species-specific pharmacokinetic differences. Finally this approach has enabled us to compare the relative sensitivity of different compounds on a tissue dose basis, leading to expression of acute solvent effects as ethanol-dose equivalents for purposes of estimating cost-benefit relationships of various environmental control options.