A Generic Pharmacokinetic Model for Quantifying Mother-to-Offspring Transfer of Lipophilic Persistent Environmental Chemicals.

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.

FutureTox IV Workshop Summary: Predictive Toxicology for Healthy Children.

FutureTox IV, a Society of Toxicology Contemporary Concepts in Toxicology workshop, was held in November 2018. Building upon FutureTox I, II, and III, this conference focused on the latest science and technology for in vitro profiling and in silico modeling as it relates to predictive developmental and reproductive toxicity (DART). Publicly available high-throughput screening data sets are now available for broad in vitro profiling of bioactivities across large inventories of chemicals. Coupling this vast amount of mechanistic data with a deeper understanding of molecular embryology and post-natal development lays the groundwork for using new approach methodologies (NAMs) to evaluate chemical toxicity, drug efficacy, and safety assessment for embryo-fetal development. NAM is a term recently adopted in reference to any technology, methodology, approach, or combination thereof that can be used to provide information on chemical hazard and risk assessment to avoid the use of intact animals (U.S. Environmental Protection Agency [EPA], Strategic plan to promote the development and implementation of alternative test methods within the tsca program, 2018, https://www.epa.gov/sites/production/files/2018-06/documents/epa_alt_strat_plan_6-20-18_clean_final.pdf). There are challenges to implementing NAMs to evaluate chemicals for developmental toxicity compared with adult toxicity. This forum article reviews the 2018 workshop activities, highlighting challenges and opportunities for applying NAMs for adverse pregnancy outcomes (eg, preterm labor, malformations, low birth weight) as well as disorders manifesting postnatally (eg, neurodevelopmental impairment, breast cancer, cardiovascular disease, fertility). DART is an important concern for different regulatory statutes and test guidelines. Leveraging advancements in such approaches and the accompanying efficiencies to detecting potential hazards to human development are the unifying concepts toward implementing NAMs in DART testing. Although use of NAMs for higher level regulatory decision making is still on the horizon, the conference highlighted novel testing platforms and computational models that cover multiple levels of biological organization, with the unique temporal dynamics of embryonic development, and novel approaches for estimating toxicokinetic parameters essential in supporting in vitro to in vivo extrapolation.

A cross-platform approach to characterize and screen potential neurovascular unit toxicants.

Development of the neurovascular unit (NVU) is a complex, multistage process that requires orchestrated cell signaling mechanisms across several cell types and ultimately results in formation of the blood-brain barrier. Typical high-throughput screening (HTS) assays investigate single biochemical or single cell responses following chemical insult. As the NVU comprises multiple cell types interacting at various stages of development, a methodology combining high-throughput results across pertinent cell-based assays is needed to investigate potential chemical-induced disruption to the development of this complex cell system. To this end, we implemented a novel method for screening putative NVU disruptors across diverse assay platforms to predict chemical perturbation of the developing NVU. HTS assay results measuring chemical-induced perturbations to cellular key events across angiogenic and neurogenic outcomes in vitro were combined to create a cell-based prioritization of NVU hazard. Chemicals were grouped according to similar modes of action to train a logistic regression literature model on a training set of 38 chemicals. This model utilizes the chemical-specific pairwise mutual information score for PubMed MeSH annotations to represent a quantitative measure of previously published results. Taken together, this study presents a methodology to investigate NVU developmental hazard using cell-based HTS assays and literature evidence to prioritize screening of putative NVU disruptors towards a knowledge-driven characterization of neurovascular developmental toxicity. The results from these screening efforts demonstrate that chemicals representing a range of putative vascular disrupting compound (pVDC) scores can also produce effects on neurogenic outcomes and characterizes possible modes of action for disrupting the developing NVU.

Profiling the ToxCast Library With a Pluripotent Human (H9) Stem Cell Line-Based Biomarker Assay for Developmental Toxicity.

The Stemina devTOX quickPredict platform is a human pluripotent stem cell-based assay that predicts the developmental toxicity potential based on changes in cellular metabolism following chemical exposure [Palmer, J. A., Smith, A. M., Egnash, L. A., Conard, K. R., West, P. R., Burrier, R. E., Donley, E. L. R., and Kirchner, F. R. (2013). Establishment and assessment of a new human embryonic stem cell-based biomarker assay for developmental toxicity screening. Birth Defects Res. B Dev. Reprod. Toxicol. 98, 343-363]. Using this assay, we screened 1065 ToxCast phase I and II chemicals in single-concentration or concentration-response for the targeted biomarker (ratio of ornithine to cystine secreted or consumed from the media). The dataset from the Stemina (STM) assay is annotated in the ToxCast portfolio as STM. Major findings from the analysis of ToxCast_STM dataset include (1) 19% of 1065 chemicals yielded a prediction of developmental toxicity, (2) assay performance reached 79%-82% accuracy with high specificity (> 84%) but modest sensitivity (< 67%) when compared with in vivo animal models of human prenatal developmental toxicity, (3) sensitivity improved as more stringent weights of evidence requirements were applied to the animal studies, and (4) statistical analysis of the most potent chemical hits on specific biochemical targets in ToxCast revealed positive and negative associations with the STM response, providing insights into the mechanistic underpinnings of the targeted endpoint and its biological domain. The results of this study will be useful to improving our ability to predict in vivo developmental toxicants based on in vitro data and in silico models.

Molecular characterization of a toxicological tipping point during human stem cell differentiation.

Endoderm gives rise to the gut tube in the early embryo. We differentiated human induced pluripotent stem cells (hiPSCs) to embryonic endoderm to identify a "tipping point" at which the developing system did not recover from perturbations caused by exposure to all-trans retinoic acid (ATRA). Differentiating hiPSC-derived endoderm exposed to five concentrations of ATRA between 0.001 and 10 µM at 6 h, 96 h, or 192 h was assessed for forkhead box A2 (FOXA2) protein expression and global gene transcript expression. A tipping point of 17 ±â€¯11 nM was identified where patterns of differentially expressed genes supported a developmental trajectory shift indicating a potential teratogenic outcome. This concentration is between women's endogenous ATRA blood plasma levels and teratogenic levels of circulating isotretinoin, an ATRA isomer used to treat acne. Taken together, these data suggest that this approach is a sensitive method to identify a point of departure for chemicals that impact early embryonic development.

The counterdiffusion of HCl and NH3: An experimental and modeling analysis of topochemistry, diffusion, reaction, and phase transitions.

Vapor-phase ammonia, NH3(g), and hydrochloric acid, HCl(g), undergo a series of complex reactions, including nucleation and growth, to form solid ammonium chloride, NH4Cl(s). The counterdiffusional experiment, whereby HCl(g) and NH3(g) diffuse from opposite ends of a tube and react to form spatiotemporally complex patterns, has a rich history of study. In this paper, we combine experimental data, molecular simulations, and analysis and simulations of a partial differential equation model to address the questions of where the first unobserved vapor product NH4Cl(g) and visually observable precipitate NH4Cl(s) form and how these positions depend on experimental parameters. These analyses yield a consistent picture which involves a moving reaction front as well as previously unobserved heterogeneous nucleation, wall nucleation, and homogeneous nucleation. The experiments combined with modeling allow for an estimate of the heterogeneous and homogeneous nucleation thresholds for the vapor-to-solid phase transition. The results, synthesized with the literature on this vapor-to-particle reaction, inform a discussion of the details of the reaction mechanism, including the role of water, which concludes the paper.

Systems Modeling of Developmental Vascular Toxicity.

The more than 80,000 chemicals in commerce present a challenge for hazard assessments that toxicity testing in the 21st century strives to address through high-throughput screening (HTS) assays. Assessing chemical effects on human development adds an additional layer of complexity to the screening, with a need to capture complex and dynamic events essential for proper embryo-fetal development. HTS data from ToxCast/Tox21 informs systems toxicology models, which incorporate molecular targets and biological pathways into mechanistic models describing the effects of chemicals on human cells, 3D organotypic culture models, and small model organisms. Adverse Outcome Pathways (AOPs) provide a useful framework for integrating the evidence derived from these in silico and in vitro systems to inform chemical hazard characterization. To illustrate this formulation, we have built an AOP for developmental toxicity through a mode of action linked to embryonic vascular disruption (Aop43). Here, we review the model for quantitative prediction of developmental vascular toxicity from ToxCast HTS data and compare the HTS results to functional vascular development assays in complex cell systems, virtual tissues, and small model organisms. ToxCast HTS predictions from several published and unpublished assays covering different aspects of the angiogenic cycle were generated for a test set of 38 chemicals representing a range of putative vascular disrupting compounds (pVDCs). Results boost confidence in the capacity to predict adverse developmental outcomes from HTS in vitro data and model computational dynamics for in silico reconstruction of developmental systems biology. Finally, we demonstrate the integration of the AOP and developmental systems toxicology to investigate the unique modes of action of two angiogenesis inhibitors.

Host Developmental Toxicity of BPA and BPA Alternatives Is Inversely Related to Microbiota Disruption in Zebrafish.

Host-associated microbiota can biotransform xenobiotics, mediate health effects of chemical exposure, and play important roles in early development. Bisphenol A (BPA) is a widespread environmental chemical that has been associated with adverse endocrine and neurodevelopmental effects, some of which may be mediated by microbiota. Growing public concern over the safety of BPA has resulted in its replacement with structurally similar alternatives. In this study, we evaluated whether BPA and BPA alternatives alter microbiota and modulate secondary adverse behavioral effects in zebrafish. Zebrafish were developmentally exposed to BPA, Bisphenol AF (BPAF), Bisphenol B (BPB), Bisphenol F (BPF), or Bisphenol S (BPS). At 10 days post fertilization (dpf), toxicity assessments were completed and 16S rRNA gene sequencing was performed to evaluate potential chemical-dependent shifts in microbial community structure and predicted function. A standard light/dark behavioral assay was used to assess locomotor activity. Based on developmental toxicity assessments at 10 dpf, a range of potencies was observed: BPAF > BPB > BPF ∼ BPA > BPS. Analysis of 16S rRNA gene sequencing data showed significant concentration-dependent disruption of microbial community structure and enrichment of putative microbial functions with exposure to BPS, BPA, or BPF, but not BPB or BPAF. Interestingly, microbial disruption was inversely related to host developmental toxicity and estrogenicity. Exposure to BP analogs did not cause behavioral effects at 10 dpf. Our findings indicate that some BP analogs disrupt host microbiota early in life and demonstrate novel chemical-microbiota interactions that may add important context to current hazard identification strategies.

A Novel Method for the Development of Environmental Public Health Indicators and Benchmark Dose Estimation Using a Health-Based End Point for Chlorpyrifos.

BACKGROUND: Organophosphorus (OP) compounds are the most widely used group of insecticides in the world. Risk assessments for these chemicals have focused primarily on 10% inhibition of acetylcholinesterase in the brain as the critical metric of effect. Aside from cholinergic effects resulting from acute exposure, many studies suggest a linkage between cognitive deficits and long-term OP exposure. OBJECTIVE: In this proof-of-concept study, we focused on one of the most widely used OP insecticides in the world, chlorpyrifos (CPF), and utilized an existing physiologically based pharmacokinetic (PBPK) model and a novel pharmacodynamic (PD) dose-response model to develop a point of departure benchmark dose estimate for cognitive deficits following long-term, low-dose exposure to this chemical in rodents. METHODS: Utilizing a validated PBPK/PD model for CPF, we generated a database of predicted biomarkers of exposure and internal dose metrics in both rat and human. Using simulated peak brain CPF concentrations, we developed a dose-response model to predict CPF-induced spatial memory deficits and correlated these changes to relevant biomarkers of exposure to derive a benchmark dose specific to neurobehavioral changes. We extended these cognitive deficit predictions to humans and simulated corresponding exposures using a model parameterized for humans. RESULTS: Results from this study indicate that the human-equivalent benchmark dose (BMD) based on a 15% cognitive deficit as an end point is lower than that using the present threshold for 10% brain AChE inhibition. This predicted human-equivalent subchronic BMD threshold compares to occupational exposure levels determined from biomarkers of exposure and corresponds to similar exposure conditions where deficits in cognition are observed. CONCLUSIONS: Quantitative PD models based on neurobehavioral testing in animals offer an important addition to the methodologies used for establishing useful environmental public health indicators and BMDs, and predictions from such models could help inform the human health risk assessment for chlorpyrifos. https://doi.org/10.1289/EHP1743.

Blood-brain barrier development: Systems modeling and predictive toxicology.

The blood-brain barrier (BBB) serves as a gateway for passage of drugs, chemicals, nutrients, metabolites, and hormones between vascular and neural compartments in the brain. Here, we review BBB development with regard to the microphysiology of the neurovascular unit (NVU) and the impact of BBB disruption on brain development. Our focus is on modeling these complex systems. Extant in silico models are available as tools to predict the probability of drug/chemical passage across the BBB; in vitro platforms for high-throughput screening and high-content imaging provide novel data streams for profiling chemical-biological interactions; and engineered human cell-based microphysiological systems provide empirical models with which to investigate the dynamics of NVU function. Computational models are needed that bring together kinetic and dynamic aspects of NVU function across gestation and under various physiological and toxicological scenarios. This integration will inform adverse outcome pathways to reduce uncertainty in translating in vitro data and in silico models for use in risk assessments that aim to protect neurodevelopmental health.

Characterizing the Effects of Race/Ethnicity on Acetaminophen Pharmacokinetics Using Physiologically Based Pharmacokinetic Modeling.

BACKGROUND AND OBJECTIVES: Acetaminophen (APAP, paracetamol) is currently the principal cause of acute liver failure in both the USA and the UK. However, relatively little is known about the influence of genes and race/ethnicity on the disposition of APAP and the extent to which genetic variation and ethnicity may predispose individuals to a higher risk of APAP-induced hepatotoxicity. The objective of this research was to develop subpopulation-specific physiologically based pharmacokinetic (PBPK) models for two genetically different groups (Western Europeans and East Asians) and then use the models to quantify the difference in absorption, distribution, metabolism, and excretion (ADME) of APAP between these groups. METHODS: A comprehensive set of human pharmacokinetic data mined from the literature was divided into two groups based on ethnicity as an indicator of the expected abundance of phenol-metabolizing alleles. Using these datasets and a Bayesian hierarchical framework, subpopulation-specific physiologically based pharmacokinetic models for APAP were developed and tested for the two groups. RESULTS: Model simulations were in good agreement with experimental data for both time-dependent parent and metabolite concentrations and summary pharmacokinetic parameters. In addition, simulations were conducted to characterize the difference between ADME in these groups with regard to urinary excretion and APAP area under the curve (AUC) in the liver. Although not dramatic at therapeutic dosing levels, these results demonstrated the divergence in the liver-specific APAP concentrations and AUC between the two groups and suggested that differences in glucuronidation capacity may play a role in this disparity. CONCLUSIONS: Overall, the models developed in this study, and others created using this type of hierarchical methodology, are expected to be useful in quantifying ADME in a subpopulation-specific manner and reducing prediction uncertainty compared to that from generalized PBPK modeling approaches.

Physiologically Based Pharmacokinetic Model of Rifapentine and 25-Desacetyl Rifapentine Disposition in Humans.

Rifapentine (RPT) is a rifamycin antimycobacterial and, as part of a combination therapy, is indicated for the treatment of pulmonary tuberculosis (TB) caused by Mycobacterium tuberculosis Although the results from a number of studies indicate that rifapentine has the potential to shorten treatment duration and enhance completion rates compared to other rifamycin agents utilized in antituberculosis drug regimens (i.e., regimens 1 to 4), its optimal dose and exposure in humans are unknown. To help inform such an optimization, a physiologically based pharmacokinetic (PBPK) model was developed to predict time course, tissue-specific concentrations of RPT and its active metabolite, 25-desacetyl rifapentine (dRPT), in humans after specified administration schedules for RPT. Starting with the development and verification of a PBPK model for rats, the model was extrapolated and then tested using human pharmacokinetic data. Testing and verification of the models included comparisons of predictions to experimental data in several rat tissues and time course RPT and dRPT plasma concentrations in humans from several single- and repeated-dosing studies. Finally, the model was used to predict RPT concentrations in the lung during the intensive and continuation phases of a current recommended TB treatment regimen. Based on these results, it is anticipated that the PBPK model developed in this study will be useful in evaluating dosing regimens for RPT and for characterizing tissue-level doses that could be predictors of problems related to efficacy or safety.

Chronic exposure to water pollutant trichloroethylene increased epigenetic drift in CD4(+) T cells.

AIM: Autoimmune disease and CD4(+) T-cell alterations are induced in mice exposed to the water pollutant trichloroethylene (TCE). We examined here whether TCE altered gene-specific DNA methylation in CD4(+) T cells as a possible mechanism of immunotoxicity. MATERIALS & METHODS: Naive and effector/memory CD4(+) T cells from mice exposed to TCE (0.5 mg/ml in drinking water) for 40 weeks were examined by bisulfite next-generation DNA sequencing. RESULTS: A probabilistic model calculated from multiple genes showed that TCE decreased methylation control in CD4(+) T cells. Data from individual genes fitted to a quadratic regression model showed that TCE increased gene-specific methylation variance in both CD4 subsets. CONCLUSION: TCE increased epigenetic drift of specific CpG sites in CD4(+) T cells.

A novel approach for estimating ingested dose associated with paracetamol overdose.

AIM: In cases of paracetamol (acetaminophen, APAP) overdose, an accurate estimate of tissue-specific paracetamol pharmacokinetics (PK) and ingested dose can offer health care providers important information for the individualized treatment and follow-up of affected patients. Here a novel methodology is presented to make such estimates using a standard serum paracetamol measurement and a computational framework. METHODS: The core component of the computational framework was a physiologically-based pharmacokinetic (PBPK) model developed and evaluated using an extensive set of human PK data. Bayesian inference was used for parameter and dose estimation, allowing the incorporation of inter-study variability, and facilitating the calculation of uncertainty in model outputs. RESULTS: Simulations of paracetamol time course concentrations in the blood were in close agreement with experimental data under a wide range of dosing conditions. Also, predictions of administered dose showed good agreement with a large collection of clinical and emergency setting PK data over a broad dose range. In addition to dose estimation, the platform was applied for the determination of optimal blood sampling times for dose reconstruction and quantitation of the potential role of paracetamol conjugate measurement on dose estimation. CONCLUSIONS: Current therapies for paracetamol overdose rely on a generic methodology involving the use of a clinical nomogram. By using the computational framework developed in this study, serum sample data, and the individual patient's anthropometric and physiological information, personalized serum and liver pharmacokinetic profiles and dose estimate could be generated to help inform an individualized overdose treatment and follow-up plan.

Physiologically based modeling of the pharmacokinetics of acetaminophen and its major metabolites in humans using a Bayesian population approach.

The principal aim of this study was to develop, validate, and demonstrate a physiologically based pharmacokinetic (PBPK) model to predict and characterize the absorption, distribution, metabolism, and excretion of acetaminophen (APAP) in humans. A PBPK model was created that included pharmacologically and toxicologically relevant tissue compartments and incorporated mechanistic descriptions of the absorption and metabolism of APAP, such as gastric emptying time, cofactor kinetics, and transporter-mediated movement of conjugated metabolites in the liver. Through the use of a hierarchical Bayesian framework, unknown model parameters were estimated using a large training set of data from human pharmacokinetic studies, resulting in parameter distributions that account for data uncertainty and inter-study variability. Predictions from the model showed good agreement to a diverse test set of data across several measures, including plasma concentrations over time, renal clearance, APAP absorption, and pharmacokinetic and exposure metrics. The utility of the model was then demonstrated through predictions of cofactor depletion, dose response of several pharmacokinetic endpoints, and the relationship between APAP biomarker levels in the plasma and those in the liver. The model addressed several limitations in previous PBPK models for APAP, and it is anticipated that it will be useful in predicting the pharmacokinetics of APAP in a number of contexts, such as extrapolating across doses, estimating internal concentrations, quantifying population variability, assessing possible impacts of drug coadministration, and, when coupled with a suitable pharmacodynamic model, predicting toxicity.

Modeling toxicodynamic effects of trichloroethylene on liver in mouse model of autoimmune hepatitis.

Chronic exposure to industrial solvent and water pollutant trichloroethylene (TCE) in female MRL+/+mice generates disease similar to human autoimmune hepatitis. The current study was initiated to investigate why TCE-induced autoimmunity targeted the liver. Compared to other tissues the liver has an unusually robust capacity for repair and regeneration. This investigation examined both time-dependent and dose-dependent effects of TCE on hepatoprotective and pro-inflammatory events in liver and macrophages from female MRL+/+mice. After a 12-week exposure to TCE in drinking water a dose-dependent decrease in macrophage production of IL-6 at both the transcriptional and protein level was observed. A longitudinal study similarly showed that TCE inhibited macrophage IL-6 production. In terms of the liver, TCE had little effect on expression of pro-inflammatory genes (Tnfa, Saa2 or Cscl1) until the end of the 40-week exposure. Instead, TCE suppressed hepatic expression of genes involved in IL-6 signaling (Il6r, gp130, and Egr1). Linear regression analysis confirmed liver histopathology in the TCE-treated mice correlated with decreased expression of Il6r. A toxicodynamic model was developed to estimate the effects of TCE on IL-6 signaling and liver pathology under different levels of exposure and rates of repair. This study underlined the importance of longitudinal studies in mechanistic evaluations of immuntoxicants. It showed that later-occurring liver pathology caused by TCE was associated with early suppression of hepatoprotection rather than an increase in conventional pro-inflammatory events. This information was used to create a novel toxicodynamic model of IL-6-mediated TCE-induced liver inflammation.