Validation of a physiological modeling framework for simulating the toxicokinetics of chemicals in mixtures

Kinetically-derived maximal dose (KMD) indicates lack of human carcinogenicity of ethylbenzene

The kinetically-derived maximal dose (KMD) is defined as the maximal external dose at which kinetics are unchanged relative to lower doses, e.g., doses at which kinetic processes are not saturated. Toxicity produced at doses above the KMD can be qualitatively different from toxicity produced at lower doses. Here, we test the hypothesis that neoplastic lesions reported in the National Toxicology Program's (NTP) rodent cancer bioassay with ethylbenzene are a high-dose phenomenon secondary to saturation of elimination kinetics. To test this, we applied Bayesian modeling on kinetic data for ethylbenzene from rats and humans to estimate the Vmax and Km for the Michaelis-Menten equation that governs the elimination kinetics. Analysis of the Michaelis-Menten elimination curve generated from those Vmax and Km values indicated KMD ranges for venous ethylbenzene of 8-17 mg/L in rats and 10-18 mg/L in humans. Those venous concentrations are produced by inhalation concentrations of around 200 ppm ethylbenzene, which is well above typical human exposures. These KMD estimates support the hypothesis that neoplastic lesions seen in the NTP rodent bioassay occur secondary to saturation of ethylbenzene elimination pathways and are not relevant for human risk assessment. Thus, ethylbenzene does not pose a credible cancer risk to humans under foreseeable exposure conditions. Cancer risk assessments focused on protecting human health should avoid endpoint data from rodents exposed to ethylbenzene above the KMD range and future toxicological testing should focus on doses below the KMD range.

A Physiologically Based Pharmacokinetic (PBPK) Modeling Framework for Mixtures of Dioxin-like Compounds

Humans are exposed to persistent organic pollutants, such as dioxin-like compounds (DLCs), as mixtures. Understanding and predicting the toxicokinetics and thus internal burden of major constituents of a DLC mixture is important for assessing their contributions to health risks. PBPK models, including dioxin models, traditionally focus on one or a small number of compounds; developing new or extending existing models for mixtures often requires tedious, error-prone coding work. This lack of efficiency to scale up for multi-compound exposures is a major technical barrier toward large-scale mixture PBPK simulations. Congeners in the DLC family, including 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), share similar albeit quantitatively different toxicokinetic and toxicodynamic properties. Taking advantage of these similarities, here we reported the development of a human PBPK modeling framework for DLC mixtures that can flexibly accommodate an arbitrary number of congeners. Adapted from existing TCDD models, our mixture model contains the blood and three diffusion-limited compartments-liver, fat, and rest of the body. Depending on the number of congeners in a mixture, varying-length vectors of ordinary differential equations (ODEs) are automatically generated to track the tissue concentrations of the congeners. Shared ODEs are used to account for common variables, including the aryl hydrocarbon receptor (AHR) and CYP1A2, to which the congeners compete for binding. Binary and multi-congener mixture simulations showed that the AHR-mediated cross-induction of CYP1A2 accelerates the sequestration and metabolism of DLC congeners, resulting in consistently lower tissue burdens than in single exposure, except for the liver. Using dietary intake data to simulate lifetime exposures to DLC mixtures, the model demonstrated that the relative contributions of individual congeners to blood or tissue toxic equivalency (TEQ) values are markedly different than those to intake TEQ. In summary, we developed a mixture PBPK modeling framework for DLCs that may be utilized upon further improvement as a quantitative tool to estimate tissue dosimetry and health risks of DLC mixtures.

Effects of inhaled combined Benzene, Toluene, Ethylbenzene, and Xylenes (BTEX): Toward an environmental exposure model

Combined environmental exposures to the volatile organic compounds (VOCs) Benzene, Toluene, Ethylbenzene, and Xylene (BTEX) pose clear risks to public health. Research into these risks is under-studied even as BTEX levels in the atmosphere are predicted to rise. This review focuses on the available literature using single- and combined-BTEX component inhaled solvent exposures in animal models, necessarily also drawing on findings from models of inhalant abuse and occupational exposures. Health effects of these exposures are discussed for multiple organ systems, but with particular attention on neurobehavioral outcomes such as locomotor activity, impulsivity, learning, and psychopharmacological responses. It is clear that animal models have significant differences in the concentrations, durations and patterns of exposure. Experimental evidence of the deleterious health and neurobehavioral consequences of exposures to the individual components of BTEX were found, but these effects were typically assessed using concentrations and exposure patterns not characteristic of environmental exposure. Future studies with animal models designed appropriately to explore combined BTEX will be necessary and advantageous to discovering health outcomes and more subtle neurobehavioral impacts of long-term environmental exposures.

Area under the blood concentration-time curve (AUC) of ethylbenzene concentration in rats: relationship to inhalation and oral administration route-dose

For human risk assessment of toxic chemicals, especially volatile organic compounds (VOCs), the Ministry of the Environment, Government of Japan, has called for the interconversion of inhalation-dose and oral-dose data, two common exposure routes. To address this issue, the present study investigated the time-course changes of ethylbenzene (EB) concentrations in the blood of rats during and after 6-hr inhalation exposure to EB (25, 50, 100, and 200 ppm) and after oral administration of EB by a single oral gavage (25, 50, 100, and 200 mg/kg) of EB. The Area Under the blood concentration-time Curve (AUC) at each blood collection time point (0, 30, 60, 120, 180, 360, 420, 540, and 1440 min, after starting exposure) was determined. The inhalation dose of 25 ppm corresponded closely to the oral administration of 25 mg/kg・bw (r value of 0.859), and the inhalation dose of 200 ppm correlated with the oral administration of 100 mg/kg・bw (r value of 0.948). These results suggest that this comparison using the AUC data at each blood collection time point is valuable for understanding the route- and dose-effects of EB. This study will improve risk assessment of human exposure to EB and other VOCs.

Physiology-based toxicokinetic modelling in the frame of the European Human Biomonitoring Initiative

Given the opportunities provided by internal dosimetry modelling in the interpretation of human biomonitoring (HBM) data, the assessment of the links between exposure to chemicals and observed HBM data can be effectively supported by PBTK modelling. This paper gives a comprehensive review of available human PBTK models for compounds selected as a priority by the European Human Biomonitoring Initiative (HBM4EU). We highlight their advantages and deficiencies and suggest steps for advanced internal dose modelling. The review of the available PBTK models highlighted the conceptual differences between older models compared to the ones developed recently, reflecting commensurate differences in research questions. Due to the lack of coordinated strategies for deriving useful biomonitoring data for toxicokinetic properties, significant problems in model parameterisation still remain; these are further increased by the lack of human toxicokinetic data due to ethics issues. Finally, questions arise as well as to the extent they are really representative of interindividual variability. QSARs for toxicokinetic properties is a complementary approach for PBTK model parameterisation, especially for data poor chemicals. This approach could be expanded to model chemico-biological interactions such as intestinal absorption and renal clearance; this could serve the development of more complex generic PBTK models that could be applied to newly derived chemicals. Another gap identified is the framework for mixture interaction terms among compounds that could eventually interact in metabolism. From the review it was concluded that efforts should be shifted toward the development of generic multi-compartmental and multi-route models, supported by targeted biomonitoring coupled with parameterisation by both QSAR approach and experimental (in-vivo and in-vitro) data for newly developed and data poor compounds.

Predictions of bisphenol A hepatic clearance in the isolated perfused rat liver (IPRL): impact of albumin binding and of co-administration with naproxen

1. This study aimed (i) to characterise hepatic clearance (CL) of bisphenol A (BPA) and naproxen (NAP) administered alone or in binary mixtures to highlight the influence of a binding to albumin (ALB) using an isolated perfused rat liver (IPRL) system; and (ii) to compare results of prediction algorithms with measured clearance rates. 2. The IPRL system and liver microsomes were used to determine the metabolic constants of BPA and NAP either in the presence or absence of ALB. In this study, the IPRL was used as proxy for the in vivo situation. Accordingly, diverse in vitro-to-in vivo and in vivo-to-in vivo extrapolations (IVIVEs) were made to predict CL of BPA determined in situ/in vivo with ALB from metabolic data determined without ALB by using different binding correction methods (i.e., direct and conventional scaling as well as a novel scaling considering an ALB-facilitated uptake mechanism). 3. The addition of ALB significantly influenced the liver kinetics of BPA and NAP either administered alone or in binary mixtures, which was reflected in the Michaelis-Menten constants. Analysis of concomitant exposures of BPA and NAP gave a fully competitive inhibition. Furthermore, the IVIVE method based on the ALB-facilitated uptake mechanism provided the most accurate predictions of CL_{in vivo} as compared with the other IVIVE methods when the impact of ALB is considered. 4. Our findings support the notion that high binding to ALB reduces the biotransformation of BPA and NAP when administered alone or in mixtures in the IPRL system. However, the free drug concentration in liver in vivo is probably higher than expected since the IVIVE method based on a potential ALB-facilitated uptake mechanism is the most robust prediction method. Overall, this study should improve the physiologically-based pharmacokinetic (PBPK) modelling of chemical-drug interactions.

Developing a Physiologically-Based Pharmacokinetic Model Knowledgebase in Support of Provisional Model Construction

Developing physiologically-based pharmacokinetic (PBPK) models for chemicals can be resource-intensive, as neither chemical-specific parameters nor in vivo pharmacokinetic data are easily available for model construction. Previously developed, well-parameterized, and thoroughly-vetted models can be a great resource for the construction of models pertaining to new chemicals. A PBPK knowledgebase was compiled and developed from existing PBPK-related articles and used to develop new models. From 2,039 PBPK-related articles published between 1977 and 2013, 307 unique chemicals were identified for use as the basis of our knowledgebase. Keywords related to species, gender, developmental stages, and organs were analyzed from the articles within the PBPK knowledgebase. A correlation matrix of the 307 chemicals in the PBPK knowledgebase was calculated based on pharmacokinetic-relevant molecular descriptors. Chemicals in the PBPK knowledgebase were ranked based on their correlation toward ethylbenzene and gefitinib. Next, multiple chemicals were selected to represent exact matches, close analogues, or non-analogues of the target case study chemicals. Parameters, equations, or experimental data relevant to existing models for these chemicals and their analogues were used to construct new models, and model predictions were compared to observed values. This compiled knowledgebase provides a chemical structure-based approach for identifying PBPK models relevant to other chemical entities. Using suitable correlation metrics, we demonstrated that models of chemical analogues in the PBPK knowledgebase can guide the construction of PBPK models for other chemicals.

Risk assessment of environmental mixture effects

Determining interactions of multi-component environmental mixtures towards accurate risk assessment.

Assessing human variability in kinetics for exposures to multiple environmental chemicals: a physiologically based pharmacokinetic modeling case study with dichloromethane, benzene, toluene, ethylbenzene, and m-xylene

The objective of this study was to compare the magnitude of interindividual variability in internal dose for inhalation exposure to single versus multiple chemicals. Physiologically based pharmacokinetic models for adults (AD), neonates (NEO), toddlers (TODD), and pregnant women (PW) were used to simulate inhalation exposure to "low" (RfC-like) or "high" (AEGL-like) air concentrations of benzene (Bz) or dichloromethane (DCM), along with various levels of toluene alone or toluene with ethylbenzene and xylene. Monte Carlo simulations were performed and distributions of relevant internal dose metrics of either Bz or DCM were computed. Area under the blood concentration of parent compound versus time curve (AUC)-based variability in AD, TODD, and PW rose for Bz when concomitant "low" exposure to mixtures of increasing complexities occurred (coefficient of variation (CV) = 16-24%, vs. 12-15% for Bz alone), but remained unchanged considering DCM. Conversely, AUC-based CV in NEO fell (15 to 5% for Bz; 12 to 6% for DCM). Comparable trends were observed considering production of metabolites (AMET), except for NEO's CYP2E1-mediated metabolites of Bz, where an increased CV was observed (20 to 71%). For "high" exposure scenarios, Cmax-based variability of Bz and DCM remained unchanged in AD and PW, but decreased in NEO (CV= 11-16% to 2-6%) and TODD (CV= 12-13% to 7-9%). Conversely, AMET-based variability for both substrates rose in every subpopulation. This study analyzed for the first time the impact of multiple exposures on interindividual variability in toxicokinetics. Evidence indicates that this impact depends upon chemical concentrations and biochemical properties, as well as the subpopulation and internal dose metrics considered.

Considering the cumulative risk of mixtures of chemicals - a challenge for policy makers

BACKGROUND

The current paradigm for the assessment of the health risk of chemical substances focuses primarily on the effects of individual substances for determining the doses of toxicological concern in order to inform appropriately the regulatory process. These policy instruments place varying requirements on health and safety data of chemicals in the environment. REACH focuses on safety of individual substances; yet all the other facets of public health policy that relate to chemical stressors put emphasis on the effects of combined exposure to mixtures of chemical and physical agents. This emphasis brings about methodological problems linked to the complexity of the respective exposure pathways; the effect (more complex than simple additivity) of mixtures (the so-called 'cocktail effect'); dose extrapolation, i.e. the extrapolation of the validity of dose-response data to dose ranges that extend beyond the levels used for the derivation of the original dose-response relationship; the integrated use of toxicity data across species (including human clinical, epidemiological and biomonitoring data); and variation in inter-individual susceptibility associated with both genetic and environmental factors.

METHODS

In this paper we give an overview of the main methodologies available today to estimate the human health risk of environmental chemical mixtures, ranging from dose addition to independent action, and from ignoring interactions among the mixture constituents to modelling their biological fate taking into account the biochemical interactions affecting both internal exposure and the toxic potency of the mixture.

RESULTS

We discuss their applicability, possible options available to policy makers and the difficulties and potential pitfalls in implementing these methodologies in the frame of the currently existing policy framework in the European Union. Finally, we suggest a pragmatic solution for policy/regulatory action that would facilitate the evaluation of the health effects of chemical mixtures in the environment and consumer products.

CONCLUSIONS

One universally applicable methodology does not yet exist. Therefore, a pragmatic, tiered approach to regulatory risk assessment of chemical mixtures is suggested, encompassing (a) the use of dose addition to calculate a hazard index that takes into account interactions among mixture components; and (b) the use of the connectivity approach in data-rich situations to integrate mechanistic knowledge at different scales of biological organization.

Physiologically based pharmacokinetic/toxicokinetic modeling

Physiologically based pharmacokinetic (PBPK) models differ from conventional compartmental pharmacokinetic models in that they are based to a large extent on the actual physiology of the organism. The application of pharmacokinetics to toxicology or risk assessment requires that the toxic effects in a particular tissue are related in some way to the concentration time course of an active form of the substance in that tissue. The motivation for applying pharmacokinetics is the expectation that the observed effects of a chemical will be more simply and directly related to a measure of target tissue exposure than to a measure of administered dose. The goal of this work is to provide the reader with an understanding of PBPK modeling and its utility as well as the procedures used in the development and implementation of a model to chemical safety assessment using the styrene PBPK model as an example.

A generic, cross-chemical predictive PBTK model with multiple entry routes running as application in MS Excel; design of the model and comparison of predictions with experimental results

AIM

Physiologically based toxicokinetic (PBTK) models are computational tools, which simulate the absorption, distribution, metabolism, and excretion of chemicals. The purpose of this study was to develop a physiologically based pharmacokinetic (PBPK) model with a high level of transparency. The model should be able to predict blood and urine concentrations of environmental chemicals and metabolites, given a certain environmental or occupational exposure scenario.

MODEL

The model refers to a reference human of 70 kg. The partition coefficients of the parent compound and its metabolites (blood:air and tissue:blood partition coefficients of 11 organs) are estimated by means of quantitative structure-property relationship, in which five easily available physicochemical properties of the compound are the independent parameters. The model gives a prediction of the fate of the compound, based on easily available chemical properties; therefore, it can be applied as a generic model applicable to multiple compounds. Three routes of uptake are considered (inhalation, dermal, and/or oral) as well as two built-in exercise levels (at rest and at light work). Dermal uptake is estimated by the use of a dermal diffusion-based module that considers dermal deposition rate and duration of deposition. Moreover, evaporation during skin contact is fully accounted for and related to the volatility of the substance. Saturable metabolism according to Michaelis-Menten kinetics can be modelled in any of 11 organs/tissues or in liver only. Renal tubular resorption is based on a built-in algorithm, dependent on the (log) octanol:water partition coefficient. Enterohepatic circulation is optional at a user-defined rate. The generic PBTK model is available as a spreadsheet application in MS Excel. The differential equations of the model are programmed in Visual Basic. Output is presented as numerical listing over time in tabular form and in graphs. The MS Excel application of the PBTK model is available as freeware.

EXPERIMENTAL

The accuracy of the model prediction is illustrated by simulating experimental observations. Published experimental inhalation and dermal exposure studies on a series of different chemicals (pyrene, N-methyl-pyrrolidone, methyl-tert-butylether, heptane, 2-butoxyethanol, and ethanol) were selected to compare the observed data with the model-simulated data. The examples show that the model-predicted concentrations in blood and/or urine after inhalation and/or transdermal uptake have an accuracy of within an order of magnitude.

CONCLUSIONS

It is advocated that this PBTK model, called IndusChemFate, is suitable for 'first tier assessments' and for early explorations of the fate of chemicals and/or metabolites in the human body. The availability of a simple model with a minimum burden of input information on the parent compound and its metabolites might be a stimulation to apply PBTK modelling more often in the field of biomonitoring and exposure science.

Acute treatment with kerosene damages the dermal barrier and alters the distribution of topically applied benzo(a)pyrene in mice

The dermal route is important in many occupational exposures. Some materials may reduce the barrier function of the skin to enhance absorption and effect on internal organs. We have reported previously that kerosene cleaning following treatment with used engine oil increased DNA adduct levels in the lungs of mice compared with animals treated with used oil alone. To investigate what other physiological parameters might be affected by kerosene, we conducted in vitro and in vivo measurements of skin barrier function. We also topically applied (3)H-BAP(100 nM in 25 μL acetone) and washed half the mice with 25 μL kerosene 1 hr after carcinogen application. Groups of four mice were euthanized from 1 to 72 hr after treatment. Skin, lungs, and livers were harvested from each animal and stored separately. Kerosene application reduced the barrier function of the skin in vitro beyond the effect of the acetone vehicle and the vehicle plus BAP. In vivo studies indicated that kerosene treatment reduced the barrier function at 4 and 8 hr post application and that the barrier function recovered at 24 hr after a single treatment. The fraction of the radiolabel remaining in the skin of animals treated with (3)H-BAP and washed with kerosene was significantly less than those not washed, beginning at 24 hr (p< 0.05). Fractional distribution to the lungs and livers of these animals became significantly elevated at this time. Kerosene treatment compromises dermal barrier function and the ability of the skin to retain water, enhances carcinogen absorption, and alters organ distribution. This appears to contribute to the increase in BAP DNA adducts we reported earlier.

A mechanistic modeling framework for predicting metabolic interactions in complex mixtures

BACKGROUND

Computational modeling of the absorption, distribution, metabolism, and excretion of chemicals is now theoretically able to describe metabolic interactions in realistic mixtures of tens to hundreds of substances. That framework awaits validation.

OBJECTIVES

Our objectives were to a) evaluate the conditions of application of such a framework, b) confront the predictions of a physiologically integrated model of benzene, toluene, ethylbenzene, and m-xylene (BTEX) interactions with observed kinetics data on these substances in mixtures and, c) assess whether improving the mechanistic description has the potential to lead to better predictions of interactions.

METHODS

We developed three joint models of BTEX toxicokinetics and metabolism and calibrated them using Markov chain Monte Carlo simulations and single-substance exposure data. We then checked their predictive capabilities for metabolic interactions by comparison with mixture kinetic data.

RESULTS

The simplest joint model (BTEX interacting competitively for cytochrome P450 2E1 access) gives qualitatively correct and quantitatively acceptable predictions (with at most 50% deviations from the data). More complex models with two pathways or back-competition with metabolites have the potential to further improve predictions for BTEX mixtures.

CONCLUSIONS

A systems biology approach to large-scale prediction of metabolic interactions is advantageous on several counts and technically feasible. However, ways to obtain the required parameters need to be further explored.

Evaluating pharmacokinetic and pharmacodynamic interactions with computational models in supporting cumulative risk assessment

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

An integrated QSAR-PBPK modelling approach for predicting the inhalation toxicokinetics of mixtures of volatile organic chemicals in the rat

The objective of this study was to predict the inhalation toxicokinetics of chemicals in mixtures using an integrated QSAR-PBPK modelling approach. The approach involved: (1) the determination of partition coefficients as well as V(max) and K(m) based solely on chemical structure for 53 volatile organic compounds, according to the group contribution approach; and (2) using the QSAR-driven coefficients as input in interaction-based PBPK models in the rat to predict the pharmacokinetics of chemicals in mixtures of up to 10 components (benzene, toluene, m-xylene, o-xylene, p-xylene, ethylbenzene, dichloromethane, trichloroethylene, tetrachloroethylene, and styrene). QSAR-estimated values of V(max) varied compared with experimental results by a factor of three for 43 out of 53 studied volatile organic compounds (VOCs). K(m) values were within a factor of three compared with experimental values for 43 out of 53 VOCs. Cross-validation performed as a ratio of predicted residual sum of squares and sum of squares of the response value indicates a value of 0.108 for V(max) and 0.208 for K(m). The integration of QSARs for partition coefficients, V(max) and K(m), as well as setting the K(m) equal to K(i) (metabolic inhibition constant) within the mixture PBPK model allowed to generate simulations of the inhalation pharmacokinetics of benzene, toluene, m-xylene, o-xylene, p-xylene, ethylbenzene, dichloromethane, trichloroethylene, tetrachloroethylene and styrene in various mixtures. Overall, the present study indicates the potential usefulness of the QSAR-PBPK modelling approach to provide first-cut evaluations of the kinetics of chemicals in mixtures of increasing complexity, on the basis of chemical structure.

The impact of CYP2E1 genetic variability on risk assessment of VOC mixtures

Humans are simultaneously exposed to multiple chemicals in the environment. Many of the chemicals use the same enzymes in their metabolic pathways. Competitive inhibition may occur as one of the possible interactions between the xenobiotics in human body. For example, many volatile organic compounds (VOCs) are metabolized using P450 enzymes, specifically CYP2E1. Inheritable gene alterations may result in changes of function of the enzymes in different human subpopulations. Variations in quantity and/or quality of particular isoenzymes may cause differences in the metabolism of VOCs. These variations may cause higher sensitivity in certain populations. Using examples of three different mixtures, this review paper outlines the variances in CYP2E1 isoenzymes, effect of exposure to such mixtures on sensitive populations, and approaches to mixtures risk assessment.

A PBPK Modeling Assessment of the Competitive Metabolic Interactions of JP-8 Vapor with Two Constituents,m-Xylene and Ethylbenzene

Jet Propellant 8 (JP-8) is a kerosene-based jet fuel used in the military and is composed of hundreds of hydrocarbons. A PBPK model was developed to assess the metabolic interactions of JP-8 vapor on two prominent constituents of JP-8 vapor, m-xylene (XYL) and ethylbenzene (EBZ). A limited number of rats were exposed to JP-8 vapor in a Leach chamber for 4 h to 380, 1100, or 2700 mg/m3 (total hydrocarbon). Several individual hydrocarbons were monitored in the chamber atmosphere, including XYL, EBZ, and the total hydrocarbon concentration. Blood and liver were harvested and analyzed by a novel headspace SPME/GC-MS method that allowed for identification of individual hydrocarbons and low limits of detection. The PBPK model was able to describe the metabolic interactions between XYL, EBZ, and a lumped aromatic fraction of JP-8 vapor estimated to be 18 to 25% of the fuel vapor. Competitive inhibition of XYL and EBZ metabolism was observed for JP-8 vapor inhalation exposures of 1100 and 2700 mg/m3. Future inhalation studies with jet fuel include aerosol exposures and expansion of the PBPK models to include other hydrocarbons such as n-alkanes and upper respiratory tract dosimetry of aerosol droplets.

Physiologically based modeling of the inhalation pharmacokinetics of ethylbenzene in B6C3F1 mice

A physiologically based pharmacokinetic (PBPK) model was developed for inhaled ethylbenzene (EB) in B6C3F1 mice. The mouse physiological parameters were obtained from the literature, but the blood:air and tissue:air partition coefficients were determined by vial equilibration technique. The maximal velocity for hepatic metabolism (Vmax) obtained from a previously published rat study was increased by a factor of approximately 3 to account for enzyme induction during repeated exposures. The Michaelis affinity constant (Km) for hepatic metabolism of EB, obtained from a previously published rat PBPK modeling study, was kept unchanged during single and repeated exposure scenarios. Hepatic metabolism alone could not adequately describe the clearance of EB from mouse blood. Additional metabolism was assumed to be localized in the lung. The parameters for pulmonary metabolism were obtained by optimization of PBPK model fits to kinetic data collected following exposures to 75-1000 ppm. The PBPK model successfully predicted all available blood and tissue concentration data in mice exposed to 75 or 750 ppm EB. Overall, the results indicate that the rate of EB clearance is markedly higher in B6C3F1 mice than rats or humans and exceeds the hepatic metabolism capacity. Available biochemical evidence is consistent with a significant role for pulmonary metabolism; however, the extent to which the extrahepatic metabolism is localized in the lung is unclear. Overall, the PBPK model developed for the mouse adequately simulated the blood and tissue kinetics of EB by accounting for its high rate of clearance.

Exposure to multiple environmental agents and their effect

INTRODUCTION

All children are exposed to multiple physical, chemical and biological challenges that can result in adverse health effects before and after birth. In this context, the danger of multiple exposures cannot be assessed from a single-chemical approach as used in classical toxicology.

AIM

To open up a 'negotiation space' for the problem of multiple exposure to environmental stressors, defined as any physical, chemical or biological entity that can induce an adverse response. In this context, two further questions obtain: to what extent can synergistic risks be assessed, and how far could potential adverse effects be prevented by enhanced regulation?

METHODS

A discussion of two general approaches is taken: 1) the investigation of mixtures such as smoking or air pollution without specifying the individual agents, and 2) the investigation of individual substances with a focus on possible interactions in the context of dose to receptor.

RESULTS

Although mixtures of compounds can have effects, it may not be possible to ascribe causation to a single compound. Furthermore, cumulative low-dose insult can, in some circumstances, be more toxic than a single high-dose exposure, e.g. endocrine disruptive effects of a combination of PCBs and dioxins which disrupt the thyroid hormone status; this tends to contradict elements of classical toxicology, . These cumulative insults may further combine with heavy metals and can disrupt the heme synthesis. It is possible that groups of pollutants could be used to test their cumulative capacity to multiple stress-susceptible receptor targets as is done in smoking and air pollution. This methodology could be used for further groups of potential pollutants, for example those associated with cleaning products, or cosmetics. Testing individual substances with a focus on interactions means that not only chemicals but also concurrent diseases should be taken into account. We suggest that the enhanced regulation of potential multiple stressors falls into two discrete categories. The first comprises a more precautionary approach (as demonstrated by the banning of chemicals such as some brominated flame retardants in Europe). The second comprises a more 'permissive' liberal approach involving the initial study of an individual compound, and subsequent interrogation of that compound in combination with another (as demonstrated by lowering the carcinogenicity of aflatoxin by vaccination against hepatitis B).

CONCLUSIONS

It is necessary to define and study groups of multiple stressors as in US EPA's Framework for Cumulative Risk Assessment (U.S. EPA 2003). Recent increased knowledge of the greater sensitivity of the unborn baby, the infant and the child, has led to general recognition that a higher degree of precaution is now needed in regulating for multiple stressors on the young. The more liberal permissive approach proceeding from established effects of the individual exposures is becoming less acceptable now that we know that there is much we do not understand about chronic effects of stressors during the early development phases. Conflicts over which approach to take may have to be resolved through engagement and negotiation with a wide community of stakeholders. This "community of interest" may include fundamental research scientists, practicing clinical paediatricians, patient groups, and others concerned with the health and wellbeing of infants and children.

Review of the toxicity of chemical mixtures: Theory, policy, and regulatory practice

An analysis of current mixture theory, policy, and practice was conducted by examining standard reference texts, regulatory guidance documents, and journal articles. Although this literature contains useful theoretical concepts, clear definitions of most terminology, and well developed protocols for study design and statistical analysis, no general theoretical basis for the mechanisms and interactions of mixture toxicity could be discerned. There is also a poor understanding of the relationship between exposure-based and internal received dose metrics. This confounds data interpretation and limits reliable determinations of the nature and extent of additivity. The absence of any generally accepted classification scheme for either modes/mechanisms of toxic action or of mechanisms of toxicity interactions is problematic as it produces a cycle in which research and policy are interdependent and mutually limiting. Current regulatory guidance depends heavily on determination of toxicological similarity concluded from the presence of a few prominent constituents, assumed from a common toxicological effect, or presumed from an alleged similar toxic mode/mechanism. Additivity, or the lack of it, is largely based on extrapolation of existing knowledge for single chemicals in this context. Thus, regulatory risk assessment protocols lack authoritative theoretical underpinnings, creating substantial uncertainty. Development of comprehensive classification schemes for modes/mechanisms of toxic action and mechanisms of interaction is needed to ensure a sound theoretical foundation for mixture-related regulatory activity and provide a firm basis for iterative hypothesis development and experimental testing.

Inhalation pharmacokinetics of ethylbenzene in B6C3F1 mice

The objective of the present study was to characterize the inhalation pharmacokinetics of ethylbenzene (EB) in male and female B6C3F1 mice following single and repeated exposures. Initially, groups of 28 male and female mice were exposed for 4 h to 75, 200, 500, or 1000 ppm in order to determine potential non-linearity in the kinetics of EB. Then, groups of male and female mice were exposed for 6 h to 75 ppm and 750 ppm (corresponding to the NTP exposures) for 1 or 7 consecutive days, to evaluate whether EB kinetics was altered during repeated exposures, The maximal blood concentration (Cmax; mean+/-SD, n=4) observed in female mice at the end of a 4-h exposure to 75, 200, 500, and 1000 ppm was 0.53+/-0.18, 2.26+/-0.38, 19.17+/-2.74, and 82.36+/-16.66 mg/L, respectively. The areas under the concentration vs. time curve (AUCs) following 4-h exposure to 75, 200, 500, and 1000 ppm were 88.5, 414.0, 3612.2, and 19,104.1 mg/L/min, respectively, in female mice, and 116.7, 425.7, 3148.3, and 16,039.1 mg/L/min in male mice. The comparison of Cmax and the kinetic profile of EB in mice exposed to 75 ppm suggests that they are similar between 1-day and 7-day exposures. However, at 750 ppm, the rate of EB elimination would appear to be greater after repeated exposures than single exposure, the pattern being evident in both male and female mice. Overall, the single and repeated exposure pharmacokinetic data collected in the present study suggest that EB kinetics is saturable at exposure concentrations exceeding 500 ppm (and therefore at 750 ppm used in the NTP mouse cancer bioassay) but is in the linear range at the lower concentration used in the bioassay (75 ppm). These data suggest that consideration of the nature and magnitude of non-linear kinetics and induction of metabolism during repeated exposures is essential for the conduct of a scientifically sound analysis of EB cancer dose-response data collected in B6C3F1 mice.

Human health implications of environmental contaminants in Arctic Canada: A review

The objectives of this paper are to: assess the impact of exposure to current levels of environmental contaminants in the Canadian Arctic on human health; identify the data and knowledge gaps that need to be filled by future human health research and monitoring; examine how these issues have changed since our first assessment [Van Oostdam, J., Gilman, A., Dewailly, E., Usher, P., Wheatley, B., Kuhnlein, H. et al., 1999. Human health implications of environmental contaminants in Arctic Canada: a review. Sci Total Environ 230, 1-82]. The primary exposure pathway for contaminants for various organochlorines (OCs) and toxic metals is through the traditional northern diet. Exposures tend to be higher in the eastern than the western Canadian Arctic. In recent dietary surveys among five Inuit regions, mean intakes by 20- to 40-year-old adults in Baffin, Kivalliq and Inuvialuit communities exceeded the provisional tolerable daily intakes (pTDIs) for the OCs, chlordane and toxaphene. The most recent findings in NWT and Nunavut indicate that almost half of the blood samples from Inuit mothers exceeded the level of concern value of 5 microg/L for PCBs, but none exceeded the action level of 100 microg/L. For Dene/Métis and Caucasians of the Northwest Territories exposure to OCs are mostly below this level of concern. Based on the exceedances of the pTDI and of various blood guidelines, mercury and to a lesser extent lead (from the use of lead shot in hunting game) are also concerns among Arctic peoples. The developing foetus is likely to be more sensitive to the effects of OCs and metals than adults, and is the age groups of greatest risk in the Arctic. Studies of infant development in Nunavik have linked deficits in immune function, an increase in childhood respiratory infections and birth weight to prenatal exposure to OCs. Balancing the risks and benefits of a diet of country foods is very difficult. The nutritional benefits of country food and its contribution to the total diet are substantial. Country food contributes significantly more protein, iron and zinc to the diets of consumers than southern/market foods. The increase in obesity, diabetes and cardiovascular disease has been linked to a shift away from a country food diet and a less active lifestyle. These foods are an integral component of good health among Aboriginal peoples. The social, cultural, spiritual, nutritional and economic benefits of these foods must be considered in concert with the risks of exposure to environmental contaminants through their exposure. Consequently, the contamination of country food raises problems which go far beyond the usual confines of public health and cannot be resolved simply by risk-based health advisories or food substitutions alone. All decisions should involve the community and consider many aspects of socio-cultural stability to arrive at a decision that will be the most protective and least detrimental to the communities.

Chemical mixtures: considering the evolution of toxicology and chemical assessment

The assessment of chemical mixtures is a complex topic for toxicologists, regulators, and the public. In this article the linkage between the science of toxicology and the needs of governmental regulatory agencies in the United States is explored through an overview of environmental regulations enacted over the past century and a brief history of modern toxicology. One of the goals of this overview is to encourage both regulators and scientists to consider the benefits and limitations of this science-regulatory relationship as they tackle existing issues such as chemical mixtures. It is clear that a) over the past 100 years chemical regulation and toxicologic research, have in large part, shared a common emphasis on characterization and regulation of individual chemicals. But chemical mixtures have been, and continue to be, evaluated at hazardous waste sites around the United States. For this reason the current U.S. Environmental Protection Agency guidelines for chemical mixtures assessment are also reviewed. These guidelines highlight the current practice of mixtures assessment, which relies primarily on the existing single-chemical database. It is also clear that b) the science and assessment of chemical mixtures are moving forward through the combined efforts of regulatory agencies and scientists from a broad range of disciplines, including toxicology. Because toxicology is at this exciting crossroads, particular attention should be paid to the forces (e.g., public demands, regulatory needs, funding, academic interests) that both promote and limit the growth of this expanding discipline.

A human PBPK model for ethanol describing inhibition of gastric motility

A physiologically based pharmacokinetic model for investigating inter-individual and inter-racial variability in ethanol pharmacokinetics is presented. The model is a substantial modification of an existing model which described some genetic polymorphisms in the hepatic alcohol dehydrogenase enzymes. The model was modified to incorporate a description of ethanol absorption from the stomach and gastro-intestinal tract and the retardation of gastric emptying due to a concentration-dependent inhibition of gastric peristalsis. In addition, intra-venous and intra-arterial routes of administration were added to investigate whether the biological structure of the model provided a core which may be easily adapted for any route of exposure. The model is proposed as suitable for the investigation of the effects of both acute and chronic ethanol exposure.

A spreadsheet program for modeling quantitative structure-pharmacokinetic relationships for inhaled volatile organics in humans

The extent and profile of target tissue exposure to toxicants depend upon the pharmacokinetic processes, namely, absorption, distribution, metabolism and excretion. The present study developed a spreadsheet program to simulate the pharmacokinetics of inhaled volatile organic chemicals (VOCs) in humans based on information from molecular structure. The approach involved the construction of a human physiologically-based pharmacokinetic (PBPK) model, and the estimation of its parameters based on quantitative structure-property relationships (QSPRs) in an Excel spreadsheet. The compartments of the PBPK model consisted of liver, adipose tissue, poorly perfused tissues and richly perfused tissues connected by circulating blood. The parameters required were: human physiological parameters such as cardiac output, breathing rate, tissue volumes and tissue blood flow rates (obtained from the biomedical literature), tissue/air partition coefficients (obtained using QSPRs developed with rat data), blood/air partition coefficients (Pb) and hepatic clearance (CL). Using literature data on human Pb and CL for several VOCs (alkanes, alkenes, haloalkanes and aromatic hydrocarbons), multi-linear additive QSPR models were developed. The numerical contributions to human Pb and CL were obtained for eleven structural fragments (CH3, CH2, CH, C, C [double bond] C, H, Cl, Br, F, benzene ring, and H in the benzene ring structure). Using these data as input, the PBPK model written in an Excel spreadsheet simulated the inhalation pharmacokinetics of ethylbenzene (33 ppm, 7 h) and dichloromethane (100 ppm, 6 h) in humans exposed to these chemicals. The QSPRs developed in this study should be useful for predicting the inhalation pharmacokinetics of VOCs in humans, prior to testing and experimentation.

Physiologically-based pharmacokinetic and toxicokinetic models in cancer risk assessment

Physiologically-based pharmacokinetic (PBPK) and toxicokinetic models are increasingly being used for the conduct of high dose to low dose and interspecies extrapolations required in cancer risk assessment. These models, by simulating tissue dose of toxic chemicals, help address the uncertainty associated with the default approaches for interspecies and high dose to low dose extrapolations. The applicability of PBPK models in cancer risk assessment has been demonstrated with a number of chemicals (e.g., acrylonitrile, 2-butoxyethanol, chloroform, 1,4-dioxane, methyl chloroform, methylene chloride, styrene, trichloroethylene, tetrachloroethylene, vinyl chloride, vinyl acetate). Recent advances in PBPK modeling facilitate the consideration of population distribution of parameter values, age-dependent changes in physiology and metabolism, multi-route exposures as well as multichemical interactions for application in cancer risk assessment. Whereas the average values for various input parameters have been used to evaluate the age-dependency of tissue dose, the Markov Chain Monte Carlo technique can be applied to address variability and uncertainty in parameter estimates, thus facilitating a more accurate estimation of cancer risk in the population. The PBPK models also uniquely facilitate the simulation of tissue dose, and thereby cancer risks, associated with multi-route and multichemical exposure situations. Overall, the recent advances reviewed in this article point to the continued enhancement of the scientific basis and applicability of PBPK models in cancer risk assessment.

Seeking solutions to chemical mixtures challenges in public health

The Agency for Toxic Substances and Disease Registry (ATSDR) identifies people near hazardous waste sites who are at potential health risk because of their exposure to environmental chemicals. Nearly, 2000 chemicals have been associated with such sites. Residents of U.S. communities are potentially exposed to hazardous substances through air, soil, drinking water, and food. The agency has determined that more than 73 million people live within a 4-mile radius of waste sites. More than 14 million Americans live within 1 mile of a National Priorities List site, of which 11% are 7 years of age or younger, 12% are 64 years of age or older, 24% are women of childbearing age, and 25% are minorities. The lack of adequate environmental sampling and information on human exposures often restricts ATSDR's evaluation and assessment activities. Assessing human exposure with its attendant health risks and outcomes is complex because many populations have a wide range of reported illnesses, and generally exposures are to mixtures of chemicals. This prompted ATSDR to consider mixtures issues more in depth and to establish a formal mixtures assessment and research program in 1994. In this paper, we present an overview of the agency activities, the genesis, legislative mandates, and pertinence of the mixtures program including applied research and the development of methods for evaluating the impact of multiple-chemical exposure. On the basis of 20-year experience of evaluating and researching environmental chemical mixtures at waste sites, ATSDR convened the International Conference on Chemical Mixtures (ICCM) in 2002. The conference was supported by several federal agencies and scientific organizations and attended by international and national experts. The conference addressed broad topics such as prevalence of exposures to chemical mixtures, importance of interactions at environmentally relevant levels, validity of assuming additivity (dose or response) as default for mixtures assessment, and promising avenues in the three broad areas, viz., research, assessment, and computational tools.

Chemical mixture toxicology: from descriptive to mechanistic, and going on to in silico toxicology

Because of the pioneering vision of certain leaders in the biomedical field, the last two decades witnessed rapid advances in the area of chemical mixture toxicology. Earlier studies utilized conventional toxicology protocol and methods, and they were mainly descriptive in nature. Two good examples might be the parallel series of studies conducted by the U.S. National Toxicology Program and TNO in The Netherlands, respectively. As a natural course of progression, more and more sophistication was incorporated into the toxicology studies of chemical mixtures. Thus, at least the following seven areas of scientific achievements in chemical mixture toxicology are evident in the literature: (a) the application of better and more robust statistical methods; (b) the exploration and incorporation of mechanistic bases for toxicological interactions; (c) the application of physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) modeling; (d) the studies on more complex chemical mixtures; (e) the use of science-based risk assessment approaches; (f) the utilization of functional genomics; and (g) the application of technology. Examples are given for the discussion of each of these areas. Two important concepts emerged from these studies and they are: (1) dose-dependent toxicologic interactions; and (2) "interaction thresholds". Looking into the future, one of the most challenging areas in chemical mixture research is finding the answer to the question "when one tries to characterize the health effects of chemical mixtures, how does one deal with the infinite number of combination of chemicals, and other possible stressors?" Undoubtedly, there will be many answers from different groups of researchers. Our answer, however, is first to focus on the finite (biological processes) rather than the infinite (combinations of chemical mixtures and multiple stressors). The idea is that once we know a normal biological process(es), all stimuli and insults from external stressors are merely perturbations of the normal biological process(es). The next step is to "capture" the biological process(es) by integrating the recent advances in computational technology and modern biology. Here, the computer-assisted Reaction Network Modeling, linked with PBPK modeling, offers a ray of hope to dealing with the complex biological systems.

Implications of chemical mixtures in public health practice

The Agency for Toxic Substances and Disease Registry (ATSDR) is a federal public health agency that investigates and strives to prevent human health problems produced by exposure to toxic chemicals and their mixtures in the environment. Most human exposures involving toxic chemicals or mixtures are thought to originate from environmental and occupational sources; however, concurrent exposures are also likely from other sources, such as prescription and nonprescription drugs, indoor air pollutants, alcohol, and tobacco smoke. Thus, in evaluating the potential hazard following exposure to environmental mixtures, ATSDR not only considers the inherent joint toxicity of the mixture but also the influence of environmental, demographic, occupational, and lifestyle factors. To foster these goals, ATSDR has pursued a Mixtures Research and Assessment Program that consists of three component efforts: trend analysis, joint toxicity assessment, and experimental testing. Through trend analysis, ATSDR sets priorities for environmental mixtures of concern for which joint toxicity assessments are conducted as needed. If data are not available to conduct appropriate assessments, a research agenda is pursued through established extramural mechanisms. Ultimately, the data generated are used to support ATSDR's work at sites involving exposure to chemical mixtures. This pragmatic approach allows testable hypotheses or research needs to be identified and resolved and enhances our understanding of the mechanisms of joint toxicity. Several collaborative and cooperative efforts with national and international organizations such as the Toxicology and Nutrition Office, the Netherlands, and the Department of Energy are being pursued as part of these activities. ATSDR also develops guidance manuals to consistently and accurately apply current methodologies for the joint toxicity assessment of chemicals. Further, expert panels often are assembled to resolve outstanding scientific issues or obtain expert advice on pertinent issues. Recently, the need for studies on chemical mixtures has been proposed as one of the six priority areas the agency identified in its agenda for public health environmental research. This has been reinforced through the agency's close work with communities whose leaders have spoken passionately about their concern for information on exposures to chemical mixtures. The five other priority research areas the agency identified are exposure, susceptible populations, communities and tribal involvement, evaluation/surveillance of health effects, and health promotion/prevention.

Six interaction profiles for simple mixtures

The Agency for Toxic Substances and Disease Registry (ATSDR) has a program for chemical mixtures that encompasses research on chemical mixtures toxicity, health risk assessment, and development of innovative computational methods. ATSDR prepared a guidance document that instructs users on how to conduct health risk assessment on chemical mixtures (Guidance Manual for the Assessment of Joint Toxic Action of Chemical Mixtures). ATSDR also developed six interaction profiles for chemical mixtures. Two profiles were developed for persistent environmental chemicals that are often found in contaminated fish and also can be detected in human breast milk. The mixture included chlorinated dibenzo-p-dioxins, hexachlorobenzene, dichlorodiphenyl dichloroethane, methyl mercury, and polychlorinated biphenyls. Two profiles each were developed for mixtures of metals and mixtures of volatile organic chemicals (VOCs) that are frequently found at hazardous waste sites. The two metal profiles dealt with (a) lead, manganese, zinc, and copper; and (b) arsenic, cadmium, chromium, and lead; the two VOCs mixtures dealt with (a) 1,1,1-trichloroethane, 1,1-dichloroethane, trichloroethylene, and tetrachloroethylene; and (b) benzene, ethylbenzene, toluene, and xylenes (BTEX). Weight-of-evidence methodology was used to assess the joint toxic action for most of the mixtures. Physiologically based pharmacokinetic modeling was used for BTEX. In most cases, a target-organ toxicity dose modification of the hazard index approach is recommended for conducting exposure-based assessments of noncancer health hazards.

Quantitative structure-property relationships for physiologically based pharmacokinetic modeling of volatile organic chemicals in rats

The objective of present study was to develop quantitative structure-property relationships (QSPRs) for the chemical-specific input parameters of rat physiologically based pharmacokinetic (PBPK) models (i.e., blood:air partition coefficient (P(b)), liver:air partition coefficient (P(l)), muscle:air partition coefficient (P(m)), fat:air partition coefficient (P(f)), and hepatic clearance (CL(h))), for simulating the inhalation pharmacokinetics of volatile organic chemicals (VOCs). The literature data on P(b), P(l), P(f), and P(m) for 46 low-molecular-weight VOCs as well as CL(h) for 25 such VOCs primarily metabolized by CYP2E1 (alkanes, haloalkanes, haloethylenes, and aromatic hydrocarbons) were analysed to develop QSPRs. The QSPRs developed in this study were essentially multilinear additive models, which imply that each fragment in the molecular structure has an additive and constant contribution to partition coefficients and hepatic clearance. Most of the values in the calibration set could be reproduced adequately with the QSPR approach, which involved the calculation of the sum of the frequency of occurrence of fragments (CH(3), CH(2), CH, C, C=C, H, Cl, Br, F, benzene ring, and H in benzene ring structure) times the fragment-specific contributions determined in this study. The QSPRs for P(b), P(l), P(m), P(f), and CL(h) were then included within a PBPK model, which only required the specification of the frequency of occurrence of fragments in a molecule along with exposure concentration and duration as input for conducting pharmacokinetic simulations. This QSPR-PBPK model framework facilitated the prediction of the inhalation pharmacokinetics of four VOCs present in the calibration dataset (toluene, dichloromethane, trichloroethylene, and 1,1,1-trichloroethane) and four VOCs that were not part of the calibration set (1,2,4-trimethyl benzene, ethyl benzene, 1,3-dichloropropene, and 2,2-dichloro-1,1,1-trifluoroethane) but that could be described using the molecular fragments investigated in the present study. The QSPRs developed in this study should be potentially useful for providing a first-cut evaluation of the inhalation pharmacokinetics of VOCs prior to experimentation, as long as the number and nature of the fragments do not exceed the ones in the calibration dataset used in this study.

Biological monitoring of exposure to mixtures

This short review is aimed at establishing general principles of biological monitoring for chemical mixtures. When interactions occur, they appear to be toxicokinetic in nature, often resulting from competition between two or more substances for the same biotransformation enzymes. A threshold is frequently observed for such an interaction, so that it might not influence the relationship between the absorbed dose and the value of the relevant biomarker. The extent of the interaction between pairs of chemicals also depends on the extent of biotransformation of each compound. As a result, the measurement of the parent compound or its metabolite will be differentially influenced by the presence of an interfering chemical. Biological limit values (BLV) are often established from the correlation between the bioindicator concentration in a given biological medium and the airborne concentration of the parent compound. When this relationship is derived from exposure to pure chemicals, it might not always yield an appropriate BLV for monitoring exposure to a mixture that includes this particular chemical. Under certain conditions such as the stability of mixture composition, a single biomarker such as 1-hydroxypyrene in PAH exposure can be used to reflect the overall exposure to a mixture. Finally, there is clearly a need for a greater research effort on the toxicology of mixtures to make biological monitoring a useful tool in occupational health.