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Addressing human anatomical and physiological variability is a crucial component of human health risk assessment of chemicals. Experts have recommended probabilistic chemical risk assessment paradigms in which distributional adjustment factors are used to account for various sources of uncertainty and variability, including variability in the pharmacokinetic behavior of a given substance in different humans. In practice, convenient assumptions about the distribution forms of adjustment factors and human equivalent doses (HEDs) are often used. Parameters such as tissue volumes and blood flows are likewise often assumed to be lognormally or normally distributed without evaluating empirical data for consistency with these forms. In this work, we performed dosimetric extrapolations using physiologically based pharmacokinetic (PBPK) models for dichloromethane (DCM) and chloroform that incorporate uncertainty and variability to determine if the HEDs associated with such extrapolations are approximately lognormal and how they depend on the underlying distribution shapes chosen to represent model parameters. We accounted for uncertainty and variability in PBPK model parameters by randomly drawing their values from a variety of distribution types. We then performed reverse dosimetry to calculate HEDs based on animal points of departure for each set of sampled parameters. Corresponding samples of HEDs were tested to determine the impact of input parameter distributions on their central tendencies, extreme percentiles, and degree of conformance to lognormality. This work demonstrates that the measurable attributes of human variability should be considered more carefully and that generalized assumptions about parameter distribution shapes may lead to inaccurate estimates of extreme percentiles of HEDs.
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Modelos Biológicos , Humanos , Animais , Medição de Risco , Clorofórmio/farmacocinética , Incerteza , Distribuição Tecidual , Relação Dose-Resposta a DrogaRESUMO
Chemical risk assessors use physiologically based pharmacokinetic (PBPK) models to perform dosimetric calculations, including extrapolations between exposure scenarios, species, and populations of interest. Assessors should complete a thorough quality assurance (QA) review to ensure biological accuracy and correct implementation prior to using these models. This process can be time-consuming, and we developed a PBPK model template that allows for faster, more efficient QA review. The model template consists of a single model "superstructure" with equations and logic commonly found in PBPK models, allowing users to implement a wide variety of chemical-specific PBPK models. QA review can be completed more quickly than for conventional PBPK model implementations because the general model equations have already been reviewed and only parameters describing chemical-specific model and exposure scenarios need review for any given model implementation. We have expanded a previous version of the PBPK model template by adding features commonly included in PBPK models for volatile organic compounds (VOCs). We included multiple options for representing concentrations in blood, describing metabolism, and modeling gas exchange processes to allow for inhalation exposures. We created PBPK model template implementations of published models for seven VOCs: dichloromethane, methanol, chloroform, styrene, vinyl chloride, trichloroethylene, and carbon tetrachloride. Simulations performed using our template implementations matched published simulation results to a high degree of accuracy (maximum observed percent error: 1%). Thus, the model template approach can now be applied to a broader class of chemical-specific PBPK models while continuing to bolster efficiency of QA processes that should be conducted prior to using models for risk assessment applications.
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Chemical risk assessment considers potentially susceptible populations including pregnant women and developing fetuses. Humans encounter thousands of chemicals in their environments, few of which have been fully characterized. Toxicokinetic (TK) information is needed to relate chemical exposure to potentially bioactive tissue concentrations. Observational data describing human gestational exposures are unavailable for most chemicals, but physiologically based TK (PBTK) models estimate such exposures. Development of chemical-specific PBTK models requires considerable time and resources. As an alternative, generic PBTK approaches describe a standardized physiology and characterize chemicals with a set of standard physical and TK descriptors - primarily plasma protein binding and hepatic clearance. Here we report and evaluate a generic PBTK model of a human mother and developing fetus. We used a published set of formulas describing the major anatomical and physiological changes that occur during pregnancy to augment the High-Throughput Toxicokinetics (httk) software package. We simulated the ratio of concentrations in maternal and fetal plasma and compared to literature in vivo measurements. We evaluated the model with literature in vivo time-course measurements of maternal plasma concentrations in pregnant and non-pregnant women. Finally, we prioritized chemicals measured in maternal serum based on predicted fetal brain concentrations. This new model can be used for TK simulations of 859 chemicals with existing human-specific in vitro TK data as well as any new chemicals for which such data become available. This gestational model may allow for in vitro to in vivo extrapolation of point of departure doses relevant to reproductive and developmental toxicity.
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Modelos Biológicos , Feminino , Humanos , Medição de Risco , ToxicocinéticaRESUMO
Lipophilic persistent environmental chemicals (LPECs) can accumulate in a woman's body and transfer to her developing child across the placenta and via breast milk. To assess health risks associated with developmental exposures to LPECs, we developed a pharmacokinetic (PK) model that quantifies mother-to-offspring transfer of LPECs during pregnancy and lactation and facilitates internal dosimetry calculations for offspring. We parameterized the model for mice, rats, and humans using time-varying functions for body mass and milk consumption rates. The only required substance-specific parameter is the elimination half-life of the LPEC in the animal species of interest. We used the model to estimate whole-body concentrations in mothers and offspring following maternal exposures to hexachlorobenzene (HCB) and 2,2',4,4',5,5'-hexachlorobiphenyl (PCB 153) and compared these with measured concentrations from animal studies. We also compared estimated concentrations for humans to those generated using a previously published human LPEC PK model. Finally, we compared human equivalent doses (HEDs) calculated using our model and an allometric scaling method. Estimated and observed whole-body concentrations of HCB and PCB 153 in offspring followed similar trends and differed by less than 60%. Simulations of human exposure yielded concentration estimates comparable to those generated using the previously published model, with concentrations in offspring differing by less than 12%. HEDs calculated using our PK model were about 2 orders of magnitude lower than those generated using allometric scaling. Our PK model can be used to calculate internal dose metrics for offspring and corresponding HEDs and thus informs assessment of developmental toxicity risks associated with LPECs.
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Poluentes Ambientais , Hexaclorobenzeno , Animais , Poluentes Ambientais/farmacocinética , Poluentes Ambientais/toxicidade , Feminino , Hexaclorobenzeno/toxicidade , Humanos , Lactação , Camundongos , Leite Humano/química , Modelos Biológicos , Mães , Bifenilos Policlorados , Gravidez , RatosRESUMO
Non-targeted analysis (NTA) methods are widely used for chemical discovery but seldom employed for quantitation due to a lack of robust methods to estimate chemical concentrations with confidence limits. Herein, we present and evaluate new statistical methods for quantitative NTA (qNTA) using high-resolution mass spectrometry (HRMS) data from EPA's Non-Targeted Analysis Collaborative Trial (ENTACT). Experimental intensities of ENTACT analytes were observed at multiple concentrations using a semi-automated NTA workflow. Chemical concentrations and corresponding confidence limits were first estimated using traditional calibration curves. Two qNTA estimation methods were then implemented using experimental response factor (RF) data (where RF = intensity/concentration). The bounded response factor method used a non-parametric bootstrap procedure to estimate select quantiles of training set RF distributions. Quantile estimates then were applied to test set HRMS intensities to inversely estimate concentrations with confidence limits. The ionization efficiency estimation method restricted the distribution of likely RFs for each analyte using ionization efficiency predictions. Given the intended future use for chemical risk characterization, predicted upper confidence limits (protective values) were compared to known chemical concentrations. Using traditional calibration curves, 95% of upper confidence limits were within ~tenfold of the true concentrations. The error increased to ~60-fold (ESI+) and ~120-fold (ESI-) for the ionization efficiency estimation method and to ~150-fold (ESI+) and ~130-fold (ESI-) for the bounded response factor method. This work demonstrates successful implementation of confidence limit estimation strategies to support qNTA studies and marks a crucial step towards translating NTA data in a risk-based context.
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Incerteza , Calibragem , Espectrometria de Massas/métodosRESUMO
BACKGROUND: Naphthalene is a polycyclic aromatic hydrocarbon that has been associated with health effects, including cancer. As the state of the science on naphthalene toxicity continues to evolve, updated toxicity reference value(s) may be required to support human health risk assessment. OBJECTIVES: We present a systematic evidence map of studies that could be used to derive toxicity reference value(s) for naphthalene. METHODS: Human and animal health effect studies and physiologically based pharmacokinetic (PBPK) models were identified from a literature search based on populations, exposures, comparators, and outcomes (PECO) criteria. Human and animal studies meeting PECO criteria were refined to a smaller subset considered most informative for deriving chronic reference value(s), which are preferred for assessing risk to the general public. This subset was evaluated for risk of bias and sensitivity, and the suitability of each study for dose-response analysis was qualitatively assessed. Lowest observed adverse effect levels (LOAELs) were extracted and summarized. Other potentially relevant studies (e.g., mechanistic and toxicokinetic studies) were tracked as supplemental information but not evaluated further. Existing reference values for naphthalene are also summarized. RESULTS: We identified 26 epidemiology studies and 16 animal studies that were considered most informative for further analysis. Eleven PBPK models were identified. The available epidemiology studies generally had significant risk of bias and/or sensitivity concerns and were mostly found to have low suitability for dose-response analysis due to the nature of the exposure measurements. The animal studies had fewer risk of bias and sensitivity concerns and were mostly found to be suitable for dose-response analysis. CONCLUSION: Although both epidemiological and animal studies of naphthalene provide weight of evidence for hazard identification, the available animal studies appear more suitable for reference value derivation. PBPK models and mechanistic and toxicokinetic data can be applied to extrapolate these animal data to humans, considering mode of action and interspecies metabolic differences. https://doi.org/10.1289/EHP7381.
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Naftalenos , Animais , Estudos Epidemiológicos , Naftalenos/toxicidade , Valores de Referência , Medição de RiscoRESUMO
Physiologically based pharmacokinetic (PBPK) models are commonly used in risk assessments to perform inter- and intraspecies extrapolations as well as to extrapolate between different dosing scenarios; however, they must first undergo quality assurance review, which can be a time-consuming process, especially when model code is not readily available. We developed and implemented (using R and MCSim) a PBPK model template capable of replicating published model results for several chemical-specific PBPK models. This model template allows for faster quality assurance review because the general model equations only need to be reviewed once, and application to a specific chemical then only requires reviewing input parameters. The model template can implement PBPK models with oral and intravenous exposure routes, varying numbers of tissue compartments, renal reabsorption, and multiple elimination pathways, including fecal, urinary, and biliary. Using the model template, we reproduced published model simulation results for perfluorohexanesulfonic acid, perfluorononanoic acid, perfluorodecanoic acid, perfluorooctanoate, and perflouorooctane sulfonate. We also show that the template can be a useful tool for identifying potential model errors. Thus, the model template allows for faster evaluation and review of published PBPK models and provides a proof of concept for using this approach with broader classes of chemical-specific PBPK models.
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Modelos Biológicos , Simulação por Computador , Humanos , Medição de RiscoRESUMO
BACKGROUND: Human exposures to bisphenol A (BPA) are widespread. The current study addresses uncertainties regarding human pharmacokinetics of BPA following dermal exposure. OBJECTIVE: To examine the absorption, distribution, metabolism and excretion of BPA in humans following dermal administration. METHODS: We dermally administered deuterated BPA (d6-BPA) to 10 subjects (6 men and 4 women) at a dose of 100 µg/kg over a 12-hour period and conducted blood and urine analysis from the beginning of dosing through a three- or six-day period. We present time-course serum and urine concentrations of total and unconjugated ("free") d6-BPA and used this information to calculate terminal half-life and area under the curve. RESULTS AND CONCLUSIONS: Detectable serum levels of total d6-BPA were observed at 1.4 h after the start of dosing, and a maximum serum concentration (Cmax) of 3.26 nM was observed. Free d6-BPA was detectable in serum 2.8 h after start of dermal administration, with Cmax of 0.272 nM. Beginning at approximately seven hours and continuing to 12 h (which corresponds to cessation of exposure), the concentration of free and total serum d6-BPA plateaued. The terminal half-lives of total d6-BPA and free d6-BPA in the body were 21.4 ± 9.81 h and 17.6 ± 7.69 h, respectively. Elimination from the body was rate-limited by kinetics in the dermal compartment. Free d6-BPA was a greater percentage of the area under the curve of total serum BPA (8.81%) compared to the 0.56% observed in our previously published oral study. Recovery of total d6-BPA in urine was <2% of the applied dose after six days. Analysis of the area under the curve for dermal and oral administration revealed that 2.2% of the dermal dose became systemically available. These data are in line with prior studies indicating how pharmacokinetics of BPA differ following oral and dermal exposures. Dermal exposure resulted in a longer apparent half-life and higher free:total d6-BPA ratio compared to oral.
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Compostos Benzidrílicos , Fenóis , Administração Cutânea , Administração Oral , Feminino , Meia-Vida , Humanos , MasculinoRESUMO
Naphthalene, a volatile organic compound present in moth repellants and petroleum-based fuels, has been shown to induce toxicity in mice and rats during chronic inhalation exposures. Although simpler default methods exist for extrapolating toxicity points of departure from animals to humans, using a physiologically based pharmacokinetic (PBPK) model to perform such extrapolations is generally preferred. Confidence in PBPK models increases when they have been validated using both animal and human in vivo pharmacokinetic (PK) data. A published inhalation PBPK model for naphthalene was previously shown to predict rodent PK data well, so we sought to evaluate this model using human PK data. The most reliable human data available come from a controlled skin exposure study, but the inhalation PBPK model does not include a skin exposure route; therefore, we extended the model by incorporating compartments representing the stratum corneum and the viable epidermis and parameters that determine absorption and rate of transport through the skin. The human data revealed measurable blood concentrations of naphthalene present in the subjects prior to skin exposure, so we also introduced a continuous dose-rate parameter to account for these baseline blood concentration levels. We calibrated the three new parameters in the modified PBPK model using data from the controlled skin exposure study but did not modify values for any other parameters. Model predictions then fell within a factor of 2 of most (96%) of the human PK observations, demonstrating that this model can accurately predict internal doses of naphthalene and is thus a viable tool for use in human health risk assessment.
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Exposição por Inalação , Modelos Biológicos , Naftalenos/toxicidade , Administração por Inalação , Animais , Camundongos , Ratos , PeleRESUMO
Exposure to a chemical is a critical consideration in the assessment of risk, as it adds real-world context to toxicological information. Descriptions of where and how individuals spend their time are important for characterizing exposures to chemicals in consumer products and in indoor environments. Herein we create an agent-based model (ABM) that simulates longitudinal patterns in human behavior. By basing the ABM upon an artificial intelligence (AI) system, we create agents that mimic human decisions on performing behaviors relevant for determining exposures to chemicals and other stressors. We implement the ABM in a computer program called the Agent-Based Model of Human Activity Patterns (ABMHAP) that predicts the longitudinal patterns for sleeping, eating, commuting, and working. We then show that ABMHAP is capable of simulating behavior over extended periods of time. We propose that this framework, and models based on it, can generate longitudinal human behavior data for use in exposure assessments.
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Inteligência Artificial , Exposição Ambiental/estatística & dados numéricos , Humanos , Medição de Risco/métodosRESUMO
Many parameters treated as constants in traditional physiologically based pharmacokinetic models must be formulated as time-varying quantities when modeling pregnancy and gestation due to the dramatic physiological and anatomical changes that occur during this period. While several collections of empirical models for such parameters have been published, each has shortcomings. We sought to create a repository of empirical models for tissue volumes, blood flow rates, and other quantities that undergo substantial changes in a human mother and her fetus during the time between conception and birth, and to address deficiencies with similar, previously published repositories. We used maximum likelihood estimation to calibrate various models for the time-varying quantities of interest, and then used the Akaike information criterion to select an optimal model for each quantity. For quantities of interest for which time-course data were not available, we constructed composite models using percentages and/or models describing related quantities. In this way, we developed a comprehensive collection of formulae describing parameters essential for constructing a PBPK model of a human mother and her fetus throughout the approximately 40 weeks of pregnancy and gestation. We included models describing blood flow rates through various fetal blood routes that have no counterparts in adults. Our repository of mathematical models for anatomical and physiological quantities of interest provides a basis for PBPK models of human pregnancy and gestation, and as such, it can ultimately be used to support decision-making with respect to optimal pharmacological dosing and risk assessment for pregnant women and their developing fetuses. The views expressed in this article are those of the authors and do not necessarily represent the views or policies of the U.S. Environmental Protection Agency.
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Feto/anatomia & histologia , Feto/fisiologia , Modelos Anatômicos , Modelos Biológicos , Mães , Circulação Sanguínea , Feminino , Feto/metabolismo , Hematócrito , Humanos , Gravidez , Distribuição TecidualRESUMO
BACKGROUND: Through the food and water they ingest, the air they breathe, and the consumer products with which they interact at home and at work, humans are exposed to tens of thousands of chemicals, many of which have not been evaluated to determine their potential toxicities. Furthermore, while current chemical testing tends to focus on individual chemicals, the exposures that people actually experience involve mixtures of chemicals. Unfortunately, the number of mixtures that can be formed from the thousands of environmental chemicals is enormous, and testing all of them would be impossible. OBJECTIVES: We seek to develop and demonstrate a method for identifying those mixtures that are most prevalent in humans. METHODS: We applied frequent itemset mining, a technique traditionally used for market basket analysis, to biomonitoring data from the 2009-2010 cycle of the continuous National Health and Nutrition Examination Survey (NHANES) to identify combinations of chemicals that frequently co-occur in people. RESULTS: We identified 90 chemical combinations consisting of relatively few chemicals that occur in at least 30% of the U.S. population, as well as three supercombinations consisting of relatively many chemicals that occur in a small but nonnegligible proportion of the U.S. population. CONCLUSIONS: We demonstrated how FIM can be used in conjunction with biomonitoring data to narrow a large number of possible chemical combinations down to a smaller set of prevalent chemical combinations. https://doi.org/10.1289/EHP1265.