A physiologically-based pharmacokinetic model of methotrexate incorporating hepatic excretion via multidrug-resistance-associated protein 2 (Mrp2) in mice, rats, dogs, and humans.

An updated physiologically-based pharmacokinetic (PBPK) model of methotrexate (MTX) was built based on an earlier model developed by Bischoff et al. (1971). MTX has been known to be a substrate of multidrug-resistance-associated protein 2 (Mrp2). A three-dimensional quantitative structure-activity relationship model (3D-QSAR) of Mrp2 was developed by Hirono et al. (2005). In our updated PBPK model of MTX, using the computational chemistry-derived binding affinity (Km), a Mrp2-mediated biliary excretion process was incorporated as the MTX excretory pathway. Our model simulation results are consistent with numerous datasets obtained from mice, rats, dogs, and humans, at a variety of dose levels. Comparisons were made between our updated PBPK model and the earlier one from Bischoff et al. using a PBPK Index approach. Our new PBPK model was further verified against additional pharmacokinetic datasets from rats under special experimental conditions (cannulated bile duct) and Eisai hyperbirilubinemic rats.

Performance Assessment and Translation of Physiologically Based Pharmacokinetic Models From acslX to Berkeley Madonna, MATLAB, and R Language: Oxytetracycline and Gold Nanoparticles As Case Examples.

Many physiologically based pharmacokinetic (PBPK) models for environmental chemicals, drugs, and nanomaterials have been developed to aid risk and safety assessments using acslX. However, acslX has been rendered sunset since November 2015. Alternative modeling tools and tutorials are needed for future PBPK applications. This forum article aimed to: (1) demonstrate the performance of 4 PBPK modeling software packages (acslX, Berkeley Madonna, MATLAB, and R language) tested using 2 existing models (oxytetracycline and gold nanoparticles); (2) provide a tutorial of PBPK model code conversion from acslX to Berkeley Madonna, MATLAB, and R language; (3) discuss the advantages and disadvantages of each software package in the implementation of PBPK models in toxicology, and (4) share our perspective about future direction in this field. Simulation results of plasma/tissue concentrations/amounts of oxytetracycline and gold from different models were compared visually and statistically with linear regression analyses. Simulation results from the original models were correlated well with results from the recoded models, with time-concentration/amount curves nearly superimposable and determination coefficients of 0.86-1.00. Step-by-step explanations of the recoding of the models in different software programs are provided in the Supplementary Data. In summary, this article presents a tutorial of PBPK model code conversion for a small molecule and a nanoparticle among 4 software packages, and a performance comparison of these software packages in PBPK model implementation. This tutorial helps beginners learn PBPK modeling, provides suggestions for selecting a suitable tool for future projects, and may lead to the transition from acslX to alternative modeling tools.

An epimer of deoxynivalenol: purification and structure identification of 3-epi-deoxynivalenol.

In an investigation of deoxynivalenol (DON)-transformation products by Devosia mutans 17-2-E-8, the major product was identified as 3-epi-DON. This DON-transformation product was analysed by liquid chromatography and identified by congruent retention time and UV/Vis spectrum, as well as mass spectrometric data. Nuclear magnetic resonance (NMR) experiments including correlation spectroscopy (COSY), heteronuclear single quantum coherence (HSQC) and nuclear overhauser effect (NOE) were conducted for structural characterisation of 3-epi-DON. High-speed counter-current chromatography (HSCCC) was applied to scale up the separation of 3-epi-DON from DON in a D. mutans 17-2-E-8 culture. From the culture where 100 mg DON was applied, 56 mg of 3-epi-DON (purity of 96.8%) was obtained from the HSCCC. The purified 3-epi-DON will be used for toxicological characterisation studies of this chemical.

Improving the risk assessment of lipophilic persistent environmental chemicals in breast milk.

Lipophilic persistent environmental chemicals (LPECs) have the potential to accumulate within a woman's body lipids over the course of many years prior to pregnancy, to partition into human milk, and to transfer to infants upon breastfeeding. As a result of this accumulation and partitioning, a breastfeeding infant's intake of these LPECs may be much greater than his/her mother's average daily exposure. Because the developmental period sets the stage for lifelong health, it is important to be able to accurately assess chemical exposures in early life. In many cases, current human health risk assessment methods do not account for differences between maternal and infant exposures to LPECs or for lifestage-specific effects of exposure to these chemicals. Because of their persistence and accumulation in body lipids and partitioning into breast milk, LPECs present unique challenges for each component of the human health risk assessment process, including hazard identification, dose-response assessment, and exposure assessment. Specific biological modeling approaches are available to support both dose-response and exposure assessment for lactational exposures to LPECs. Yet, lack of data limits the application of these approaches. The goal of this review is to outline the available approaches and to identify key issues that, if addressed, could improve efforts to apply these approaches to risk assessment of lactational exposure to these chemicals.

Lifetime PCB 153 bioaccumulation and pharmacokinetics in pilot whales: Bayesian population PBPK modeling and Markov chain Monte Carlo simulations.

Physiologically based pharmacokinetic (PBPK) models for wild animal populations such as marine mammals typically have a high degree of model uncertainty and variability due to the scarcity of information and the embryonic nature of this field. Parameters values used in marine mammals models are usually taken from other mammalian species (e.g. rats or mice) and might not be entirely suitable to properly explain the kinetics of pollutants in marine mammals. Therefore, several parameters for a PBPK model for the bioaccumulation and pharmacokinetics of PCB 153 in long-finned pilot whales were estimated in the present study using the Bayesian approach executed with Markov chain Monte Carlo (MCMC) simulations. This method uses 'prior' information of the parameters, either from the literature or from previous model runs. The advantage is that this method uses such 'prior' parameters to calculate probability distributions to determine 'posterior' values that best explain the field observations. Those field observations or datasets were PCB 153 concentrations in blubber of long-finned pilot whales from Sandy Cape and Stanley, Tasmania, Australia. The model predictions showed an overall decrease in PCB 153 levels in blubber over the lifetime of the pilot whales. All parameters from the Sandy Cape model were updated using the Stanley dataset, except for the concentration of PCB 153 in the milk. The model presented here is a promising and preliminary start to PBPK modeling in long-finned pilot whales that would provide a basis for non-invasive studies in these protected marine mammals.

Application of Bayesian population physiologically based pharmacokinetic (PBPK) modeling and Markov chain Monte Carlo simulations to pesticide kinetics studies in protected marine mammals: DDT, DDE, and DDD in harbor porpoises.

Physiologically based pharmacokinetic (PBPK) modeling in marine mammals is a challenge because of the lack of parameter information and the ban on exposure experiments. To minimize uncertainty and variability, parameter estimation methods are required for the development of reliable PBPK models. The present study is the first to develop PBPK models for the lifetime bioaccumulation of p,p'-DDT, p,p'-DDE, and p,p'-DDD in harbor porpoises. In addition, this study is also the first to apply the Bayesian approach executed with Markov chain Monte Carlo simulations using two data sets of harbor porpoises from the Black and North Seas. Parameters from the literature were used as priors for the first "model update" using the Black Sea data set, the resulting posterior parameters were then used as priors for the second "model update" using the North Sea data set. As such, PBPK models with parameters specific for harbor porpoises could be strengthened with more robust probability distributions. As the science and biomonitoring effort progress in this area, more data sets will become available to further strengthen and update the parameters in the PBPK models for harbor porpoises as a species anywhere in the world. Further, such an approach could very well be extended to other protected marine mammals.

A physiologically based pharmacokinetic model of rifampin in mice.

One problem associated with regimen-based development of antituberculosis (anti-TB) drugs is the difficulty of a systematic and thorough in vivo evaluation of the large number of possible regimens that arise from consideration of multiple drugs tested together. A mathematical model capable of simulating the pharmacokinetics and pharmacodynamics of experimental combination chemotherapy of TB offers a way to mitigate this problem by extending the use of available data to investigate regimens that are not initially tested. In order to increase the available mathematical tools needed to support such a model for preclinical anti-TB drug development, we constructed a preliminary whole-body physiologically based pharmacokinetic (PBPK) model of rifampin in mice, using data from the literature. Interindividual variability was approximated using Monte Carlo (MC) simulation with assigned probability distributions for the model parameters. An MC sensitivity analysis was also performed to determine correlations between model parameters and plasma concentration to inform future model development. Model predictions for rifampin concentrations in plasma, liver, kidneys, and lungs, following oral administration, were generally in agreement with published experimental data from multiple studies. Sensitive model parameters included those descriptive of oral absorption, total clearance, and partitioning of rifampin between blood and muscle. This PBPK model can serve as a starting point for the integration of rifampin pharmacokinetics in mice into a larger mathematical framework, including the immune response to Mycobacterium tuberculosis infection, and pharmacokinetic models for other anti-TB drugs.

An in silico approach for evaluating a fraction-based, risk assessment method for total petroleum hydrocarbon mixtures.

Both the Massachusetts Department of Environmental Protection (MADEP) and the Total Petroleum Hydrocarbon Criteria Working Group (TPHCWG) developed fraction-based approaches for assessing human health risks posed by total petroleum hydrocarbon (TPH) mixtures in the environment. Both organizations defined TPH fractions based on their expected environmental fate and by analytical chemical methods. They derived toxicity values for selected compounds within each fraction and used these as surrogates to assess hazard or risk of exposure to the whole fractions. Membership in a TPH fraction is generally defined by the number of carbon atoms in a compound and by a compound's equivalent carbon (EC) number index, which can predict its environmental fate. Here, we systematically and objectively re-evaluate the assignment of TPH to specific fractions using comparative molecular field analysis and hierarchical clustering. The approach is transparent and reproducible, reducing inherent reliance on judgment when toxicity information is limited. Our evaluation of membership in these fractions is highly consistent (˜80% on average across various fractions) with the empirical approach of MADEP and TPHCWG. Furthermore, the results support the general methodology of mixture risk assessment to assess both cancer and noncancer risk values after the application of fractionation.

Computational toxicology: Physiologically based pharmacokinetic models (PBPK) for lifetime exposure and bioaccumulation of polybrominated diphenyl ethers (PBDEs) in marine mammals.

Due to migration of harbour porpoises towards more polluted areas like the North Sea and their sensitivity towards pollution, there is a need for proper conservation measures for this species. As a consequence, knowledge about the pollutant's kinetics is required. The present study is the first to investigate the kinetics of PBDEs in marine mammals using PBPK modeling as a non-destructive tool for describing the chemical's kinetics in a protected animal species. The models were developed and parameterized using data from the literature and Black Sea harbour porpoises through computer optimization. The predictability of these models in time was assessed by reverse dosimetry modeling using data from North Sea porpoises (1990-2008). From these predictions, PBDE 99 levels were found to decrease the fastest, followed by PBDE 153, 47 and 100. Results show that the PBPK models can be applied for harbour porpoises from different regions and also simulate time trends.

Antiproliferative activity of pomiferin in normal (MCF-10A) and transformed (MCF-7) breast epithelial cells.

Pomiferin and osajin are prenylated isoflavones from Osage orange fruit that both have potent antioxidant activity in a variety of assays. Pomiferin, in particular, has strong activity against the superoxide anion in a photochemiluminescence (PCL) assay system. In vitro, pomiferin, but not osajin, demonstrated selective antiproliferative activity against the tumorigenic breast epithelial cell line MCF-7 (IC(50) = 5.2 µM) with limited toxicity toward nontumorigenic breast epithelial cells (MCF-10A). The differential sensitivity of normal and tumorigenic cells to the antiproliferative action of pomiferin was examined further by using cDNA microarrays. With a stringent cutoff of p < 0.01, a total of 94 genes were significantly differentially expressed between MCF-7 and MCF-10A cells; 80 up-regulated and 14 down-regulated when cells were exposed to 5 µM pomiferin for 24 h. Fold changes by microarray analysis were confirmed using RT-qPCR, and the most significant changes were found with genes related to antioxidant enzymes. Genes involved in mitotic inhibition and apoptotic regulations were also found to be up-regulated. Pomiferin is therefore a good anticancer candidate agent that may be useful either alone or in combination with other therapeutic agents and, because of its selectivity toward tumor cells, likely to have fewer side effects that classic chemotherapy drugs.

A non-invasive approach to study lifetime exposure and bioaccumulation of PCBs in protected marine mammals: PBPK modeling in harbor porpoises.

In the last decade, physiologically based pharmacokinetic (PBPK) models have increasingly been developed to explain the kinetics of environmental pollutants in wildlife. For marine mammals specifically, these models provide a new, non-destructive tool that enables the integration of biomonitoring activities and in vitro studies. The goals of the present study were firstly to develop PBPK models for several environmental relevant PCB congeners in harbor porpoises (Phocoena phocoena), a species that is sensitive to pollution because of its limited metabolic capacity for pollutant transformation. These models were tested using tissue data of porpoises from the Black Sea. Secondly, the predictive power of the models was investigated for time trends in the PCB concentrations in North Sea harbor porpoises between 1990 and 2008. Thirdly, attempts were made to assess metabolic capacities of harbor porpoises for the investigated PCBs. In general, results show that parameter values from other species (rodents, humans) are not always suitable in marine mammal models, most probably due to differences in physiology and exposure. The PCB 149 levels decrease the fastest in male harbor porpoises from the North Sea in a time period of 18years, whereas the PCB 101 levels decrease the slowest. According to the models, metabolic breakdown of PCB 118 is probably of lesser importance compared to other elimination pathways. For PCB 101 and 149 however, the presence of their metabolites can be attributed to bioaccumulation of metabolites from the prey and to metabolic breakdown of the parent compounds in the harbor porpoises.

Critical analysis of literature on low-dose synergy for use in screening chemical mixtures for risk assessment.

There is increasing interest in the use of tiered approaches in risk assessment of mixtures or co-exposures to chemicals for prioritization. One possible screening-level risk assessment approach is the threshold of toxicological concern (TTC). To date, default assumptions of dose or response additivity have been used to characterize the toxicity of chemical mixtures. Before a screening-level approach could be used, it is essential to know whether synergistic interactions can occur at low, environmentally relevant exposure levels. Studies demonstrating synergism in mammalian test systems were identified from the literature, with emphasis on studies performed at doses close to the points of departure (PODs) for individual chemicals. This search identified 90 studies on mixtures. Few included quantitative estimates of low-dose synergy; calculations of the magnitude of interaction were included in only 11 papers. Quantitative methodology varied across studies in terms of the null hypothesis, response measured, POD used to test for synergy, and consideration of the slope of the dose-response curve. It was concluded that consistent approaches should be applied for quantification of synergy, including that synergy be defined in terms of departure from dose additivity; uniform procedures be developed for assessing synergy at low exposures; and the method for determining the POD for calculating synergy be standardized. After evaluation of the six studies that provided useful quantitative estimates of synergy, the magnitude of synergy at low doses did not exceed the levels predicted by additive models by more than a factor of 4.

Pharmacokinetics and physiologically-based pharmacokinetic modeling of nanoparticles.

The worldwide commerce involving nanoparticles will soon reach $1 trillion and already we have more than 600 commercial products containing nanoparticles. Because nanoparticles are invisible and little is known about their toxicities, there has been concern about health effects in humans. As toxicology is a continuum of pharmacokinetics and pharmacodynamics, this is a review of recent advances on pharmacokinetics and physiologically-based pharmacokinetic (PBPK) modeling involving nanoparticles. We provide a synopsis of the state-of-the-science on the absorption, distribution, metabolism, and excretion (ADME) of nanoparticles in mammals, as well as some of the unique applications of pharmacokinetics to nanotechnology. Earlier, the main emphasis of pharmacokinetics of nanoparticles centered around the "control release" of drugs. Thus, drugs encapsulated by lipidic nanoparticles or bound to nano-particles form a controlled-release mechanism. The end results included, among others, enhancement of therapeutic duration and reversion of multidrug resistance. As the science advances in this area, the resulting achievements included: (1) utilizing nanoparticles as delivery vehicle for drugs, drug combinations, or genetic materials; (2) capitalizing on physico-chemical properties and tissue affinity of nanoparticles for medical imaging; (3) potentiating drug effects on immunotoxin and anticancer drugs; and (4) creating "stealth" capability from body's defense system. More recently, the application of biologically-based computer modeling to nanoparticles made it possible not only for inter-species, inter-routes, and inter-dose extrapolations but also for the integration of the modern tumor biology and computational technology for the possible improvement of cancer chemotherapy. Although pharmacokinetics and PBPK modeling of nanoparticles are still in their infancy, impressive innovations have already been demonstrated in their applications to medical sciences. Nanotoxicology is one of the most promising and fertile areas of science given the importance of nanoparticles to the economy of the 21st century, their possible environmental fates, as well as the potential health concerns of these particles.

Physiologically based pharmacokinetic (PBPK) models for lifetime exposure to PCB 153 in male and female harbor porpoises (Phocoena phocoena): model development and evaluation.

Physiologically based pharmacokinetic (PBPK) models were developed for the most persistent polychlorinated biphenyl (PCB 153) in male and female harbor porpoises (Phocoena phocoena) to elucidate processes such as uptake, distribution, and elimination. Due to its limited metabolic capacities, long life span, and top position in marine food chains, this species is highly sensitive to pollution. The models consist of 5 compartments, liver, blubber, kidney, brain, and a compartment which accounts for the rest of the body, all connected through blood. All physiological and biochemical parameters were extracted from the literature, except for the brain/blood partition coefficient and rate of excretion, which were both fitted to data sets used for validation of the models. These data sets were compiled from our own analyses performed with GC-MS on tissue samples of harbor porpoises. The intake of PCB 153 was from milk from birth to 4 months, and after weaning fish was the main food source. Overall, these models reveal that concentrations of PCB 153 in males increase with age but suggest that, as the animals grow older, metabolic transformation can be a possible pathway for elimination as well. In contrast, the model for females confirms that gestation and lactation are key processes for eliminating PCB 153 as body burdens decrease with age. These PBPK models are capable of simulating the bioaccumulation of PCB 153 during the entire life span of approximately 20 years of the harbor porpoises.

Isolation of deoxynivalenol-transforming bacteria from the chicken intestines using the approach of PCR-DGGE guided microbial selection.

BACKGROUND: Contamination of grains with trichothecene mycotoxins, especially deoxynivalenol (DON), has been an ongoing problem for Canada and many other countries. Mycotoxin contamination creates food safety risks, reduces grain market values, threatens livestock industries, and limits agricultural produce exports. DON is a secondary metabolite produced by some Fusarium species of fungi. To date, there is a lack of effective and economical methods to significantly reduce the levels of trichothecene mycotoxins in food and feed, including the efforts to breed Fusarium pathogen-resistant crops and chemical/physical treatments to remove the mycotoxins. Biological approaches, such as the use of microorganisms to convert the toxins to non- or less toxic compounds, have become a preferred choice recently due to their high specificity, efficacy, and environmental soundness. However, such approaches are often limited by the availability of microbial agents with the ability to detoxify the mycotoxins. In the present study, an approach with PCR-DGGE guided microbial selection was developed and used to isolate DON -transforming bacteria from chicken intestines, which resulted in the successful isolation of several bacterial isolates that demonstrated the function to transform DON to its de-epoxy form, deepoxy-4-deoxynivalenol (DOM-1), a product much less toxic than DON. RESULTS: The use of conventional microbiological selection strategies guided by PCR-DGGE (denaturing gradient gel electrophoresis) bacterial profiles for isolating DON-transforming bacteria has significantly increased the efficiency of the bacterial selection. Ten isolates were identified and isolated from chicken intestines. They were all able to transform DON to DOM-1. Most isolates were potent in transforming DON and the activity was stable during subculturing. Sequence data of partial 16S rRNA genes indicate that the ten isolates belong to four different bacterial groups, Clostridiales, Anaerofilum, Collinsella, and Bacillus. CONCLUSIONS: The approach with PCR-DGGE guided microbial selection was effective in isolating DON-transforming bacteria and the obtained bacterial isolates were able to transform DON.

Predicting activation enthalpies of cytochrome-P450-mediated hydrogen abstractions. 2. Comparison of semiempirical PM3, SAM1, and AM1 with a density functional theory method.

Predicting the biotransformation of xenobiotics is important in the chemical and pharmaceutical industries, as well as in toxicology. Here, we extend and evaluate the rapid methodology of Korzekwa, Jones, and Gillette (J. Am. Chem. Soc. 1990, 112, 7042-7046 ) to estimate the activation enthalpy (DeltaH) of hydrogen-abstraction by cytochrome P450 (CYP) enzymes, using the p-nitrosophenoxy radical (PNPO) as a simple surrogate for the CYP active oxygen species. The DeltaH is estimated with a linear regression model using the reaction enthalpy and ionization energy (of the substrate radical) as predictor variables, calculated by semiempirical (SE) methods. While Korzekwa et al. used the SE method AM1, we applied PM3 and SAM1 and compared the results of the three methods. For 24 substrates, the AM1-, PM3-, and SAM1-derived regression models showed R(2) values of 0.89, 0.90, and 0.93, respectively, for the correlation between calculated and predicted DeltaH. Furthermore, we compared the DeltaH() calculated semiempirically using PNPO radical with density functional theory (DFT) B3LYP activation energies calculated by Olsen et al. (J. Med. Chem. 2006, 49, 6489-6499 ) using a more realistic iron-oxo-porphine model, and the results revealed limitations of the PNPO radical model. Thus, predictive models developed using SE predictors provide rapid and generally internally consistent results, but they should be interpreted and used cautiously.

Effect of PCBs on the lactational transfer of methyl mercury in mice: PBPK modeling.

MeHg and PCB exposure to lactating mice were analyzed and a physiologically-based pharmacokinetic (PBPK) model was developed to describe the lactational transfer of MeHg in mice. The influence of albumin on the lactational transfer of MeHg was incorporated into the PBPK model. Experimental results with lactating mice and their pups showed that co-exposure with PCB congeners increased the lactational transfer of MeHg to the pups, which was associated with the rise of albumin levels in maternal blood. Observed results were matched with PBPK model simulations conducted under the assumptions that (1) MeHg bound to plasma albumin is transferred to maternal milk, and (2) PCB congeners may increase the lactational transfer of MeHg by escalating albumin levels in maternal blood. Further refinement of PBPK model quantitatively described the pharmacokinetic changes of MeHg by co-exposure with PCBs in pup's tissues.

Population physiologically based pharmacokinetic modeling for the human lactational transfer of PCB-153 with consideration of worldwide human biomonitoring results.

BACKGROUND: One of the most serious human health concerns related to environmental contamination with polychlorinated biphenyls (PCBs) is the presence of these chemicals in breast milk. OBJECTIVES: We developed a physiologically based pharmacokinetic model of PCB-153 in women, and predict its transfer via lactation to infants. The model is the first human, population-scale lactational model for PCB-153. Data in the literature provided estimates for model development and for performance assessment. METHODS: We used physiologic parameters from a cohort in Taiwan and reference values given in the literature to estimate partition coefficients based on chemical structure and the lipid content in various body tissues. Using exposure data from Japan, we predicted acquired body burden of PCB-153 at an average childbearing age of 25 years and compared predictions to measurements from studies in multiple countries. We attempted one example of reverse dosimetry modeling using our PBPK model for possible exposure scenarios in Canadian Inuits, the population with the highest breast milk PCB-153 level in the world. RESULTS: Forward-model predictions agree well with human biomonitoring measurements, as represented by summary statistics and uncertainty estimates. CONCLUSION: The model successfully describes the range of possible PCB-153 dispositions in maternal milk, suggesting a promising option for back-estimating doses for various populations.

Computational and ultrastructural toxicology of a nanoparticle, Quantum Dot 705, in mice.

We conducted pharmacokinetic and toxicology studies on Quantum Dot 705 (QD705) in male ICR mice for up to 6 months after a single intravenous dose. Time-course sacrifices were carried out at 1, 4, and 24 h; 3, 7, 14, and 28 days; and 6 months on groups of six mice per time point. Mass balance studies were also carried out at 24 h, 28 days, and 6 months. Using inductively coupled plasma mass spectrometry, various tissues, urine, and feces were analyzed for cadmium (Cd111), which is a major (46%) component of QD705. On the basis of these experimental studies, a physiologically based pharmacokinetic computer simulation model was developed with excellent predictive capability for the time-dependent kinetic and distributional changes of QD705 in tissues. QD705 persisted and accumulated in the spleen, liver, and kidneys for at least 28 days with little or no disposition but was gradually and partially eliminated by 6 months. Although histological alterations of the spleen, liver, and kidney by light microscopy are unremarkable, investigation using electron microscopy on numerous renal samples revealed definitive mitochondrial alterations in renal tubular epithelial cells at 28 days and 6 months postdosing. Health implications and potential beneficial applications of QD705 are suggested.

Computational toxicology of chloroform: reverse dosimetry using Bayesian inference, Markov chain Monte Carlo simulation, and human biomonitoring data.

BACKGROUND: One problem of interpreting population-based biomonitoring data is the reconstruction of corresponding external exposure in cases where no such data are available. OBJECTIVES: We demonstrate the use of a computational framework that integrates physiologically based pharmacokinetic (PBPK) modeling, Bayesian inference, and Markov chain Monte Carlo simulation to obtain a population estimate of environmental chloroform source concentrations consistent with human biomonitoring data. The biomonitoring data consist of chloroform blood concentrations measured as part of the Third National Health and Nutrition Examination Survey (NHANES III), and for which no corresponding exposure data were collected. METHODS: We used a combined PBPK and shower exposure model to consider several routes and sources of exposure: ingestion of tap water, inhalation of ambient household air, and inhalation and dermal absorption while showering. We determined posterior distributions for chloroform concentration in tap water and ambient household air using U.S. Environmental Protection Agency Total Exposure Assessment Methodology (TEAM) data as prior distributions for the Bayesian analysis. RESULTS: Posterior distributions for exposure indicate that 95% of the population represented by the NHANES III data had likely chloroform exposures < or = 67 microg/L [corrected] in tap water and < or = 0.02 microg/L in ambient household air. CONCLUSIONS: Our results demonstrate the application of computer simulation to aid in the interpretation of human biomonitoring data in the context of the exposure-health evaluation-risk assessment continuum. These results should be considered as a demonstration of the method and can be improved with the addition of more detailed data.