A stochastic whole-body physiologically based pharmacokinetic model to assess the impact of inter-individual variability on tissue dosimetry over the human lifespan

PBPK modeling to support risk assessment of pyrethroid exposure in French pregnant women

BACKGROUND

Pyrethroids are widely used pesticides and are suspected to affect children's neurodevelopment. The characterization of pyrethroid exposure during critical windows of development, such as fetal development and prenatal life, is essential to ensure a better understanding of pyrethroids potential effects within the concept of Developmental Origins of Health and Disease.

OBJECTIVE

The aim of this study was to estimate maternal exposure of French pregnant women from biomonitoring data and simulate maternal and fetal internal concentrations of 3 pyrethroids (permethrin, cypermethrin and deltamethrin) using a multi-substance pregnancy-PBPK (physiologically based pharmacokinetics) model. The estimated maternal exposures were compared to newly proposed toxicological reference values (TRV) children specific also called draft child-specific reference value to assess pyrethroid exposure risk during pregnancy i.e. during the in utero exposure period.

METHODS

A pregnancy-PBPK model was developed based on an existing adult pyrethroids model. The maternal exposure to each parent compound of pregnant women of the Elfe (French Longitudinal Study since Childhood) cohort was estimated by reverse dosimetry based on urinary biomonitoring data. To identify permethrin and cypermethrin contribution to their common urinary biomarkers of exposure, an exposure ratio based on biomarkers in hair was tested. Finally, exposure estimates were compared to current and draft child-specific reference values derived from rodent prenatal and postnatal exposure studies.

RESULTS

The main contributor to maternal pyrethroid diet intake is cis-permethrin. In blood, total internal concentrations main contributor is deltamethrin. In brain, the major contributors to internal pyrethroid exposure are deltamethrin for fetuses and cis-permethrin for mothers. Risk is identified only for permethrin when referring to the draft child-specific reference value. 2.5% of the population exceeded permethrin draft child-specific reference value.

CONCLUSIONS

A new reverse dosimetry approach using PBPK model combined with human biomonitoring data in urine and hair was proposed to estimate Elfe pregnant population exposure to a pyrethroids mixture with common metabolites.

Estimating the dynamic early life exposure to PFOA and PFOS of the HELIX children: Emerging profiles via prenatal exposure, breastfeeding, and diet

In utero and children's exposure to per- and polyfluoroalkyl substances (PFAS) is a major concern in health risk assessment as early life exposures are suspected to induce adverse health effects. Our work aims to estimate children's exposure (from birth to 12 years old) to PFOA and PFOS, using a Physiologically-Based Pharmacokinetic (PBPK) modelling approach. A model for PFAS was updated to simulate the internal PFAS exposures during the in utero life and childhood, and including individual characteristics and exposure scenarios (e.g., duration of breastfeeding, weight at birth, etc.). Our approach was applied to the HELIX cohort, involving 1,239 mother-child pairs with measured PFOA and PFOS plasma concentrations at two sampling times: maternal and child plasma concentrations (6 to 12 y.o). Our model predicted an increase in plasma concentrations during fetal development and childhood until 2 y.o when the maximum concentrations were reached. Higher plasma concentrations of PFOA than PFOS were predicted until 2 y.o, and then PFOS concentrations gradually became higher than PFOA concentrations. From 2 to 8 y.o, mean concentrations decreased from 3.1 to 1.88 µg/L or ng/mL (PFOA) and from 4.77 to 3.56 µg/L (PFOS). The concentration-time profiles vary with the age and were mostly influenced by in utero exposure (on the first 4 months after birth), breastfeeding (from 5 months to 2 (PFOA) or 5 (PFOS) y.o of the children), and food intake (after 3 (PFOA) or 6 (PFOS) y.o of the children). Similar measured biomarker levels can correspond to large differences in the simulated internal exposures, highlighting the importance to investigate the children's exposure over the early life to improve exposure classification. Our approach demonstrates the possibility to simulate individual internal exposures using PBPK models when measured biomarkers are scarce, helping risk assessors in gaining insight into internal exposure during critical windows, such as early life.

Inter-individual exposure variability interpretation through reflection of biological age algorithm in physiologically based toxicokinetic model: Application to human risk assessment of di-isobutyl-phthalate

Age-related changes and interindividual variability in the degree of exposure to hazardous substances in the environment are pertinent factors to be considered in human risk assessment. Existing risk assessments remain in a one-size-fits-all approach, often without due consideration of inter-individual toxicokinetic variability factors, such as age. The purpose of this study was to advance from the existing risk assessment of hazardous substances based on toxicokinetics to a precise human risk assessment by additionally considering the effects of physiologic and metabolic fluctuations and interindividual variability in age. Qualitative age-associated physiologic and metabolic changes in humans, obtained through a meta-analysis, were quantitatively modeled to produce the final biological age algorithm (BAA). The developed BAAs (for males) were extended and applied to the reported testicular reproductive toxicity-focused di-isobutyl-phthalate (DiBP)-mono-isobutyl-phthalate (MiBP) physiologically based toxicokinetic (PBTK) model in males. The advanced PBTK model combined with the BAA was applied to the human risk assessment based on MiBP biomonitoring data. As a result, the specialized DiBP external exposure values for each age could be estimated. Additionally, by applying the Monte Carlo simulation, the distribution of internal exposure diversity among individuals according to the same external exposure dose could be estimated. The contributions of physiologic and metabolic factors to the age-dependent toxicokinetic changes were approximately 93.41-99.99 and 0.01-6.59%, respectively. In addition, the relative contribution of metabolic factors was major in infants and continued to decrease as age increased (up to about age 30 years). This study provides a step-by-step platform that can be widely applied to overcome the limitations of existing toxicokinetic models that still require interindividual pharmacokinetic variability explanations. This will be important for the rationalization and explanation of inter-individual variability in the pharmacokinetics of many substances.

Development of a physiologically based toxicokinetic model for lead in pregnant women: The role of bone tissue in the maternal and fetal internal exposure

Epidemiological studies have shown associations between prenatal exposure to lead (Pb) and neurodevelopmental effects in young children. Prenatal exposure is generally characterized by measuring the concentration in the umbilical cord at delivery or in the maternal blood during pregnancy. To assess internal Pb exposure during prenatal life, we developed a pregnancy physiologically based pharmacokinetic (p-PBPK) model that to simulates Pb levels in blood and target tissues in the fetus, especially during critical periods for brain development. An existing Pb PBPK model was adapted to pregnant women and fetuses. Using data from literature, both the additional maternal bone remodeling, that causes Pb release into the blood, and the Pb placental transfers were estimated by Bayesian inference. Additional maternal bone remodeling was estimated to start at 21.6 weeks. Placental transfers were estimated between 4.6 and 283 L.day-1 at delivery with high interindividual variability. Once calibrated, the p-PBPK model was used to simulate fetal exposure to Pb. Internal fetal exposure greatly varies over the pregnancy with two peaks of Pb levels in blood and brain at the end of the 1st and 3rd trimesters. Sensitivity analysis shows that the fetal blood lead levels are affected by the maternal burden of bone Pb via maternal bone remodeling and by fetal bone formation at different pregnancy stages. Coupling the p-PBPK model with an effect model such as an adverse outcome pathway could help to predict the effects on children's neurodevelopment.

Systematic review of physiologically based kinetic lactation models for transfer of xenobiotic compounds to milk

Lactational elimination has been described mathematically for nearly 50 years. Over 40 published articles, containing >50 physiologically based kinetic (PBK) lactation models were included in the systematic review. These PBK models described the lactational elimination of xenobiotic compounds in humans, rats, mice, and dairy cows and goats. A total of 78 compounds have been modelled, ranging from industrial chemicals, pesticides, to pain medication, antibiotics, and caffeine. Few models included several species or compounds, and models were thus generally not translational or generic. Three dairy cow models mechanistically described the intramammary disposition of pharmaceuticals after intramammary administration, including volume changes caused by milking, while empirically describing the remaining pharmacokinetics. The remaining models were semi- or whole body PBK models, describing long-term exposure of environmental pollutants, or short-term exposure of pharmaceuticals. The absolute majority described the disposition to the mammary gland or milk with perfusion limited compartments, but permeability limited models were available as well. With long-term exposure, models often included changes in milk volume and/or consumption by the offspring, and changes in body weight of offspring. Periodic emptying of the mammary gland, as with feeding or milking, was sparsely applied. Rodent models used similar physiological parameters, while values of physiological parameters applied in human models could range widely. When milk composition was included in the models, it most often included the fat content. The review gives an extensive overview of the applied functions and modelling strategies of PBK lactation models.

PBPK Modeling to Simulate the Fate of Compounds in Living Organisms

Pharmacokinetics study the fate of xenobiotics in a living organism. Physiologically based pharmacokinetic (PBPK) models provide realistic descriptions of xenobiotics' absorption, distribution, metabolism, and excretion processes. They model the body as a set of homogeneous compartments representing organs, and their parameters refer to anatomical, physiological, biochemical, and physicochemical entities. They offer a quantitative mechanistic framework to understand and simulate the time-course of the concentration of a substance in various organs and body fluids. These models are well suited for performing extrapolations inherent to toxicology and pharmacology (e.g., between species or doses) and for integrating data obtained from various sources (e.g., in vitro or in vivo experiments, structure-activity models). In this chapter, we describe the practical development and basic use of a PBPK model from model building to model simulations, through implementation with an easily accessible free software.

Physiologically-based pharmacokinetic modeling of benzo(a)pyrene and the metabolite in humans of different ages

Age-specific differences in the pharmacokinetics of benzo(a)pyrene (BaP) and its metabolite 3-hydroxybenzo(a)pyrene (3-OHBaP) potentially affect time courses of tissue concentration; however, the quantitative impact of these differences is not well characterized. Our objective was to quantify the effect of age-specific differences in physiological and biochemical parameters on the pharmacokinetics of BaP and 3-OHBaP from newborn at birth to adulthood following inhalation exposure. The time courses of BaP and 3-OHBaP were simulated by using a physiologically based pharmacokinetic model with Advanced Continuous Simulation Language (ACSLX). The concentrations of BaP increased with age in the liver but decreased with age in most tissues, urine, and blood. The concentrations of 3-OHBaP were the highest in the newborns. Our results also showed that the concentration of BaP has almost reached a steady state in the kidney, liver, lung, rapidly perfused tissues, slowly perfused tissues, and skin except for adipose tissues. However, the concentration of 3-OHBaP has reached a steady state in all tissues. This study suggests that age-specific parameters have an effect on the pharmacokinetics of BaP and 3-OHBaP. In particular, tissue concentration in the newborns is higher than other age groups, which indicates that the newborns are susceptible to environmental BaP exposure.

Estimating human exposure to pyrethroids' mixtures from biomonitoring data using physiologically based pharmacokinetic modeling

Human biomonitoring data provide evidence to exposure of environmental chemicals. Physiologically based pharmacokinetic (PBPK) modelling together with an adequate exposure scenario allows to transpose measured concentrations of chemicals or their metabolites into exposure levels, as daily intakes. In France, high levels of urinary pyrethroids metabolites have been measured in populations. Our work aims at estimating the exposure of the French ENNS cohort to mixtures of four pyrethroids (deltamethrin, permethrin, cypermethrin, and cyfluthrin) from the urinary concentrations of five pyrethroids' metabolites commonly measured in biomonitoring studies. We developed a modelling approach based on a global toxicokinetic model that accounts for the cumulative exposure to pyrethroids as some of the metabolites can be shared by several parent compounds and for human inter-individual variability in metabolism. The median of the individual daily intakes was estimated to 8.1 ng/kg bw/day for permethrin, 17.7 ng/kg bw/day for cypermethrin, 20.4 ng/kg bw/day for cyfluthrin and 34.3 ng/kg bw/day for deltamethrin leading to similar weights for the pair permethrin and cypermethrin (36%), cyfluthrin (31%) and deltamethrin (33%) to the cumulative exposure. Accounting for human variability enabled to explain some of the variations in the metabolites' levels within the cohort. The cumulative exposure was then weighted by their toxicities towards three neurotoxic effects to calculate margins of exposure (MOE). Low MOE values were always associated with high measured concentrations of metabolites in urine and the lowest MOEs were observed for the autonomic division. No risks associated with reconstructed mixtures of pyrethroids were expected for the ENNS cohort. Our approach is an asset to analyse the biomarkers of exposure to pyrethroids simultaneously and could be easily adapted to any local or national specificities in pyrethroids' exposure or populations.

Assessing the impacts on fetal dosimetry of the modelling of the placental transfers of xenobiotics in a pregnancy physiologically based pharmacokinetic model

The developmental origin of health and diseases theory supports the critical role of the fetal exposure to children's health. We developed a physiologically based pharmacokinetic model for human pregnancy (pPBPK) to simulate the maternal and fetal dosimetry throughout pregnancy. Four models of the placental exchanges of chemicals were assessed on ten chemicals for which maternal and fetal data were available. These models were calibrated using non-animal methods: in vitro (InV) or ex vivo (ExV) data, a semi-empirical relationship (SE), or the limitation by the placental perfusion (PL). They did not impact the maternal pharmacokinetics but provided different profiles in the fetus. The PL and InV models performed well even if the PL model overpredicted the fetal exposure for some substances. The SE and ExV models showed the lowest global performance and the SE model a tendency to underprediction. The comparison of the profiles showed that the PL model predicted an increase in the fetal exposure with the pregnancy age, whereas the ExV model predicted a decrease. For the SE and InV models, a small decrease was predicted during the second trimester. All models but the ExV one, presented the highest fetal exposure at the end of the third trimester. Global sensitivity analyses highlighted the predominant influence of the placental transfers on the fetal exposure, as well as the metabolic clearance and the fraction unbound. Finally, the four transfer models could be considered depending on the framework of the use of the pPBPK model and the availability of data or resources to inform their parametrization.

Artificial Intelligence and Machine Learning in Computational Nanotoxicology: Unlocking and Empowering Nanomedicine

Advances in nanomedicine, coupled with novel methods of creating advanced materials at the nanoscale, have opened new perspectives for the development of healthcare and medical products. Special attention must be paid toward safe design approaches for nanomaterial-based products. Recently, artificial intelligence (AI) and machine learning (ML) gifted the computational tool for enhancing and improving the simulation and modeling process for nanotoxicology and nanotherapeutics. In particular, the correlation of in vitro generated pharmacokinetics and pharmacodynamics to in vivo application scenarios is an important step toward the development of safe nanomedicinal products. This review portrays how in vitro and in vivo datasets are used in in silico models to unlock and empower nanomedicine. Physiologically based pharmacokinetic (PBPK) modeling and absorption, distribution, metabolism, and excretion (ADME)-based in silico methods along with dosimetry models as a focus area for nanomedicine are mainly described. The computational OMICS, colloidal particle determination, and algorithms to establish dosimetry for inhalation toxicology, and quantitative structure-activity relationships at nanoscale (nano-QSAR) are revisited. The challenges and opportunities facing the blind spots in nanotoxicology in this computationally dominated era are highlighted as the future to accelerate nanomedicine clinical translation.

PBPK model reporting template for chemical risk assessment applications

Physiologically-based pharmacokinetic (PBPK) modeling analysis does not stand on its own for regulatory purposes but is a robust tool to support drug/chemical safety assessment. While the development of PBPK models have grown steadily since their emergence, only a handful of models have been accepted to support regulatory purposes due to obstacles such as the lack of a standardized template for reporting PBPK analysis. Here, we expand the existing guidances designed for pharmaceutical applications by recommending additional elements that are relevant to environmental chemicals. This harmonized reporting template can be adopted and customized by public health agencies receiving PBPK model submission, and it can also serve as general guidance for submitting PBPK-related studies for publication in journals or other modeling sharing purposes. The current effort represents one of several ongoing collaborations among the PBPK modeling and risk assessment communities to promote, when appropriate, incorporating PBPK modeling to characterize the influence of pharmacokinetics on safety decisions made by regulatory agencies.

Development of a generic lifelong physiologically based biokinetic model for exposome studies

The current study within the frame of the HEALS project aims at the development of a lifelong physiologically based biokinetic (PBBK) model for exposome studies. The aim was to deliver a comprehensive modelling framework for addressing a large chemical space. Towards this aim, the delivered model can easily adapt parameters from existing ad-hoc models or complete the missing compound specific parameters using advanced quantitative structure activity relationship (QSAR). All major human organs are included, as well as arterial, venous, and portal blood compartments. Xenobiotics and their metabolites are linked through the metabolizing tissues. This is mainly the liver, but also other sites of metabolism might be considered (intestine, brain, skin, placenta) based on the presence or not of the enzymes involved in the metabolism of the compound of interest. Each tissue is described by three mass balance equations for (a) red blood cells, (b) plasma and interstitial tissue and (c) cells respectively. The anthropometric parameters of the models are time dependent, so as to provide a lifetime internal dose assessment, as well as to describe the continuously changing physiology of the mother and the developing fetus. An additional component of flexibility is that the biokinetic processes that relate to metabolism are related with either Michaelis-Menten kinetics, as well as intrinsic clearance kinetics. The capability of the model is demonstrated in the assessment of internal exposure and the prediction of expected biomonitored levels in urine for three major compounds within the HEALS project, namely bisphenol A (BPA), Bis(2-ethylhexyl) phthalate (DEHP) and cadmium (Cd). The results indicated that the predicted urinary levels fit very well with the ones from human biomonitoring (HBM) studies; internal exposure to plasticizers is very low (in the range of ng/L), while internal exposure to Cd is in the range of μg/L.

Critical assessment and integration of separate lines of evidence for risk assessment of chemical mixtures

Humans are exposed to multiple chemicals on a daily basis instead of to just a single chemical, yet the majority of existing toxicity data comes from single-chemical exposure. Multiple factors must be considered such as the route, concentration, duration, and the timing of exposure when determining toxicity to the organism. The need for adequate model systems (in vivo, in vitro, in silico and mathematical) is paramount for better understanding of chemical mixture toxicity. Currently, shortcomings plague each model system as investigators struggle to find the appropriate balance of rigor, reproducibility and appropriateness in mixture toxicity studies. Significant questions exist when comparing single-to mixture-chemical toxicity concerning additivity, synergism, potentiation, or antagonism. Dose/concentration relevance is a major consideration and should be subthreshold for better accuracy in toxicity assessment. Previous work was limited by the technology and methodology of the time, but recent advances have resulted in significant progress in the study of mixture toxicology. Novel technologies have added insight to data obtained from in vivo studies for predictive toxicity testing. These include new in vitro models: omics-related tools, organs-on-a-chip and 3D cell culture, and in silico methods. Taken together, all these modern methodologies improve the understanding of the multiple toxicity pathways associated with adverse outcomes (e.g., adverse outcome pathways), thus allowing investigators to better predict risks linked to exposure to chemical mixtures. As technology and knowledge advance, our ability to harness and integrate separate streams of evidence regarding outcomes associated with chemical mixture exposure improves. As many national and international organizations are currently stressing, studies on chemical mixture toxicity are of primary importance.

Prediction of maternal and foetal exposures to perfluoroalkyl compounds in a Spanish birth cohort using toxicokinetic modelling

Prenatal exposures to perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) have been associated with child health outcomes, but many of these associations remain poorly characterized. The aim of this work was to provide new indicators of foetal exposure for the Spanish INMA birth cohort. First, a pregnancy and lactation physiologically based pharmacokinetic (PBPK) model was calibrated in a population framework to provide quantitative estimates for the PFOA and PFOS placental transfers in humans. The estimated distributions indicated that PFOA crosses the placental barrier at a rate three times higher than PFOS and shows a higher variability between mothers. The PBPK model was then used to back-calculate the time-varying daily intakes of the INMA mothers corrected for their individual history from a spot maternal concentration. We showed the importance of accounting for the mothers' history as different dietary intakes can result in similar measured concentrations at one time point. Finally, the foetal exposure was simulated in target organs over pregnancy using the PBPK model and the estimated maternal intakes. We showed that the pattern of PFOA and PFOS exposures varies greatly among the foetuses. About a third has levels of either one compound always higher than the levels of the other compound. The other two thirds showed different ranking of PFOA and PFOS in terms of concentrations in the target organs. Our simulated foetal exposures bring additional information to the measured maternal spot concentrations and can help to better characterize the prenatal exposure in target organs during windows of susceptibility.

Estimating the cumulative human exposures to pyrethroids by combined multi-route PBPK models: Application to the French population

Human biomarkers of exposure to pyrethroid insecticides are usually urinary concentrations of metabolites that can be specific to a pyrethroid or common to several compounds. We developed a global toxicokinetic model that links the external exposure to four widely-used pyrethroids and their isomers (deltamethrin and cis and trans isomers of permethrin, cypermethrin, and cyfluthrin) to the urinary concentrations of metabolites (cis- and trans-DCCA, 3-PBA, F-PBA and DBCA). This global model includes physiologically based pharmacokinetic models for each parent compound and one-compartment models for the metabolites. Existing in vivo, in vitro and in silico data were used for model calibration, and human toxicokinetic data for model evaluation. Overall, the global model reproduced the data accurately as about 90% of predictions were inside the 3-fold error interval. A sensitivity analysis showed that the most influent parameter for each urinary metabolite concentration was the fraction of parent compound that is transformed into that metabolite. The global model was then tested with realistic exposures for the French population: the predictions were consistent with biomonitoring data. The global model is a tool that will improve the interpretation of biomonitoring data for pyrethroids.

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.

Challenges Associated With Applying Physiologically Based Pharmacokinetic Modeling for Public Health Decision-Making

The development and application of physiologically based pharmacokinetic (PBPK) models in chemical toxicology have grown steadily since their emergence in the 1980s. However, critical evaluation of PBPK models to support public health decision-making across federal agencies has thus far occurred for only a few environmental chemicals. In order to encourage decision-makers to embrace the critical role of PBPK modeling in risk assessment, several important challenges require immediate attention from the modeling community. The objective of this contemporary review is to highlight 3 of these challenges, including: (1) difficulties in recruiting peer reviewers with appropriate modeling expertise and experience; (2) lack of confidence in PBPK models for which no tissue/plasma concentration data exist for model evaluation; and (3) lack of transferability across modeling platforms. Several recommendations for addressing these 3 issues are provided to initiate dialog among members of the PBPK modeling community, as these issues must be overcome for the field of PBPK modeling to advance and for PBPK models to be more routinely applied in support of public health decision-making.

Advancing Chemical Risk Assessment through Human Physiology-Based Biochemical Process Modeling

Physiology-Based BioKinetic (PBBK) models are of increasing interest in modern risk assessment, providing quantitative information regarding the absorption, metabolism, distribution, and excretion (ADME). They focus on the estimation of the effective dose at target sites, aiming at the identification of xenobiotic levels that are able to result in perturbations to the biological pathway that are potentially associated with adverse outcomes. The current study aims at the development of a lifetime PBBK model that covers a large chemical space, coupled with a framework for human biomonitoring (HBM) data assimilation. The methodology developed herein was demonstrated in the case of bisphenol A (BPA), where exposure analysis was based on European HBM data. Based on our calculations, it was found that current exposure levels in Europe are below the temporary Tolerable Daily Intake (t-TDI) of 4 μg/kg_bw/day proposed by the European Food Safety Authority (EFSA). Taking into account age-dependent bioavailability differences, internal exposure was estimated and compared with the biologically effective dose (BED) resulting from translating the EFSA temporary total daily intake (t-TDI) into equivalent internal dose and an alternative internal exposure reference value, namely biological pathway altering dose (BPAD); the use of such a refined exposure metric, showed that environmentally relevant exposure levels are below the concentrations associated with the activation of biological pathways relevant to toxicity based on High Throughput Screening (HTS) in vitro studies.

A Spatio-Temporal Exposure-Hazard Model for Assessing Biological Risk and Impact

We developed a simulation model for quantifying the spatio-temporal distribution of contaminants (e.g., xenobiotics) and assessing the risk of exposed populations at the landscape level. The model is a spatio-temporal exposure-hazard model based on (i) tools of stochastic geometry (marked polygon and point processes) for structuring the landscape and describing the exposed individuals, (ii) a dispersal kernel describing the dissemination of contaminants from polygon sources, and (iii) an (eco)toxicological equation describing the toxicokinetics and dynamics of contaminants in affected individuals. The model was implemented in the briskaR package (biological risk assessment with R) of the R software. This article presents the model background, the use of the package in an illustrative example, namely, the effect of genetically modified maize pollen on nontarget Lepidoptera, and typical comparisons of landscape configurations that can be carried out with our model (different configurations lead to different mortality rates in the treated example). In real case studies, parameters and parametric functions encountered in the model will have to be precisely specified to obtain realistic measures of risk and impact and accurate comparisons of landscape configurations. Our modeling framework could be applied to study other risks related to agriculture, for instance, pathogen spread in crops or livestock, and could be adapted to cope with other hazards such as toxic emissions from industrial areas having health effects on surrounding populations. Moreover, the R package has the potential to help risk managers in running quantitative risk assessments and testing management strategies.

Ecological and human exposure assessment to PBDEs in Adige River

The interest for environmental issues and the concern resulting from the potential exposure to contaminants were the starting point to develop methodologies in order to evaluate the consequences that those might have over both the environment and human health. Considering the feature of POPs, including PBDEs, such as bioaccumulation, biomagnification, long-range transport and adverse effects even long time after exposure, risk assessment of POPs requires specific approaches and tools. In this particular context, the MERLIN-Expo tool was used to assess the aquatic environmental exposure of Adige River to PBDEs and the accumulation of PBDEs in humans through the consumption of possible contaminated local aquatic food. The aquatic food web models provided as output of the deterministic simulation the time trend of concentrations for twenty years of BDE-47 and total PBDEs, expressed using the physico-chemical properties of BDE-47, in aquatic organisms of the food web of Adige River. For BDE-47, the highest accumulated concentrations were detected for two benthic species: Thymallus thymallus and Squalius cephalus whereas the lowest concentrations were obtained for the pelagic specie Salmo trutta marmoratus. The trend obtained for the total PBDEs, calculated using the physico-chemical properties of BDE-47, follows the one of BDE-47. For human exposure, different BDE-47 and total PBDEs concentration trends between children, adolescent, adults and elderly were observed, probably correlated with the human intake of fish products in the daily diet and the ability to metabolize these contaminants. In detail, for the adolescents, adults and elderly a continuous accumulation of the target contaminants during the simulation's years was observed, whereas for children a plateau at the end of the simulation period was perceived.

Modeling Pharmacokinetics

Pharmacokinetics is the study of the fate of xenobiotics in a living organism. Physiologically based pharmacokinetic (PBPK) models provide realistic descriptions of xenobiotics' absorption, distribution, metabolism, and excretion processes. They model the body as a set of homogeneous compartments representing organs, and their parameters refer to anatomical, physiological, biochemical, and physicochemical entities. They offer a quantitative mechanistic framework to understand and simulate the time-course of the concentration of a substance in various organs and body fluids. These models are well suited for performing extrapolations inherent to toxicology and pharmacology (e.g., between species or doses) and for integrating data obtained from various sources (e.g., in vitro or in vivo experiments, structure-activity models). In this chapter, we describe the practical development and basic use of a PBPK model from model building to model simulations, through implementation with an easily accessible free software.

Toxicokinetic models and related tools in environmental risk assessment of chemicals

Environmental risk assessment of chemicals for the protection of ecosystems integrity is a key regulatory and scientific research field which is undergoing constant development in modelling approaches and harmonisation with human risk assessment. This review focuses on state-of-the-art toxicokinetic tools and models that have been applied to terrestrial and aquatic species relevant to environmental risk assessment of chemicals. Both empirical and mechanistic toxicokinetic models are discussed using the results of extensive literature searches together with tools and software for their calibration and an overview of applications in environmental risk assessment. These include simple tools such as one-compartment models, multi-compartment models to physiologically-based toxicokinetic (PBTK) models, mostly available for aquatic species such as fish species and a number of chemical classes including plant protection products, metals, persistent organic pollutants, nanoparticles. Data gaps and further research needs are highlighted.

Modelling ecological and human exposure to POPs in Venice lagoon - Part II: Quantitative uncertainty and sensitivity analysis in coupled exposure models

The study is focused on applying uncertainty and sensitivity analysis to support the application and evaluation of large exposure models where a significant number of parameters and complex exposure scenarios might be involved. The recently developed MERLIN-Expo exposure modelling tool was applied to probabilistically assess the ecological and human exposure to PCB 126 and 2,3,7,8-TCDD in the Venice lagoon (Italy). The 'Phytoplankton', 'Aquatic Invertebrate', 'Fish', 'Human intake' and PBPK models available in MERLIN-Expo library were integrated to create a specific food web to dynamically simulate bioaccumulation in various aquatic species and in the human body over individual lifetimes from 1932 until 1998. MERLIN-Expo is a high tier exposure modelling tool allowing propagation of uncertainty on the model predictions through Monte Carlo simulation. Uncertainty in model output can be further apportioned between parameters by applying built-in sensitivity analysis tools. In this study, uncertainty has been extensively addressed in the distribution functions to describe the data input and the effect on model results by applying sensitivity analysis techniques (screening Morris method, regression analysis, and variance-based method EFAST). In the exposure scenario developed for the Lagoon of Venice, the concentrations of 2,3,7,8-TCDD and PCB 126 in human blood turned out to be mainly influenced by a combination of parameters (half-lives of the chemicals, body weight variability, lipid fraction, food assimilation efficiency), physiological processes (uptake/elimination rates), environmental exposure concentrations (sediment, water, food) and eating behaviours (amount of food eaten). In conclusion, this case study demonstrated feasibility of MERLIN-Expo to be successfully employed in integrated, high tier exposure assessment.

Integrated exposure and risk characterization of bisphenol-A in Europe

The current study aims at a comprehensive risk characterization of bisphenol A (BPA) supported by an integrated exposure modelling framework that comprises far field and near field exposure modelling coupled to a dynamic lifetime PBTK model. Exposure analysis was done on European data of BPA food residues and human biomonitoring (HBM). The latter were further assimilated through an advanced exposure reconstruction modelling framework to estimate the corresponding external and internal systemic dose of BPA and its metabolites. Special attention was paid on the assessment of exposure to BPA during critical developmental stages such as gestation by modelling the mother-fetus toxicokinetic interaction. Our findings showed that current exposure levels in Europe are below the temporary Tolerable Daily Intake (t-TDI) of 4 μg/kg_bw/d proposed by the European Food Safety Authority. Taking into account age-dependent bioavailability differences, internal exposure of premature neonates hosted in intensive care units was reckoned close to the biologically effective dose (BED) resulting from translating the EFSA temporary total daily intake (t-TDI) into equivalent internal dose. Use of the ToxCast21 Biological Pathway Altering Dose (BPAD) as an alternative internal exposure reference value, resulted in increased margins of safety compared to the conventional exposure/risk characterization scheme.

Modelling the exposure to chemicals for risk assessment: a comprehensive library of multimedia and PBPK models for integration, prediction, uncertainty and sensitivity analysis - the MERLIN-Expo tool

MERLIN-Expo is a library of models that was developed in the frame of the FP7 EU project 4FUN in order to provide an integrated assessment tool for state-of-the-art exposure assessment for environment, biota and humans, allowing the detection of scientific uncertainties at each step of the exposure process. This paper describes the main features of the MERLIN-Expo tool. The main challenges in exposure modelling that MERLIN-Expo has tackled are: (i) the integration of multimedia (MM) models simulating the fate of chemicals in environmental media, and of physiologically based pharmacokinetic (PBPK) models simulating the fate of chemicals in human body. MERLIN-Expo thus allows the determination of internal effective chemical concentrations; (ii) the incorporation of a set of functionalities for uncertainty/sensitivity analysis, from screening to variance-based approaches. The availability of such tools for uncertainty and sensitivity analysis aimed to facilitate the incorporation of such issues in future decision making; (iii) the integration of human and wildlife biota targets with common fate modelling in the environment. MERLIN-Expo is composed of a library of fate models dedicated to non biological receptor media (surface waters, soils, outdoor air), biological media of concern for humans (several cultivated crops, mammals, milk, fish), as well as wildlife biota (primary producers in rivers, invertebrates, fish) and humans. These models can be linked together to create flexible scenarios relevant for both human and wildlife biota exposure. Standardized documentation for each model and training material were prepared to support an accurate use of the tool by end-users. One of the objectives of the 4FUN project was also to increase the confidence in the applicability of the MERLIN-Expo tool through targeted realistic case studies. In particular, we aimed at demonstrating the feasibility of building complex realistic exposure scenarios and the accuracy of the modelling predictions through a comparison with actual measurements.

Multiscale modelling approaches for assessing cosmetic ingredients safety

The European Union's ban on animal testing for cosmetic ingredients and products has generated a strong momentum for the development of in silico and in vitro alternative methods. One of the focus of the COSMOS project was ab initio prediction of kinetics and toxic effects through multiscale pharmacokinetic modeling and in vitro data integration. In our experience, mathematical or computer modeling and in vitro experiments are complementary. We present here a summary of the main models and results obtained within the framework of the project on these topics. A first section presents our work at the organelle and cellular level. We then go toward modeling cell levels effects (monitored continuously), multiscale physiologically based pharmacokinetic and effect models, and route to route extrapolation. We follow with a short presentation of the automated KNIME workflows developed for dissemination and easy use of the models. We end with a discussion of two challenges to the field: our limited ability to deal with massive data and complex computations.

A probabilistic model of human variability in physiology for future application to dose reconstruction and QIVIVE

The risk assessment of environmental chemicals and drugs is undergoing a paradigm shift in approach which seeks the full replacement of animal testing with high throughput, mechanistic, in vitro systems. This new approach will be reliant on the measurement in vitro, of concentration-dependent responses where prolonged excessive perturbations of specific biochemical pathways are likely to lead to adverse health effects in an intact organism. Such an approach requires a framework, into which disparate data generated by in vitro, in silico, and in chemico systems can be integrated and utilized for quantitative in vitro-to-in vivo extrapolation (QIVIVE), ultimately to the human population level. Physiologically based pharmacokinetic (PBPK) models are ideally suited to this and are needed to translate in vitro concentration- response relationships to an exposure or dose, route and duration regime in human populations. Thus, a realistic description of the variation in the physiology of the human population being modeled is critical. Whilst various studies in the past decade have made progress in describing human variability, the algorithms are typically coded in computer programs and as such are unsuitable for reverse dosimetry. In this report we overcome this limitation by developing a hierarchical statistical model using standard probability distributions for the specification of a virtual US and UK human population. The work draws on information from both population databases and cadaver studies.

A preliminary regional PBPK model of lung metabolism for improving species dependent descriptions of 1,3-butadiene and its metabolites

1,3-Butadiene (BD), a volatile organic chemical (VOC), is used in synthetic rubber production and other industrial processes. It is detectable at low levels in ambient air as well as in tobacco smoke and gasoline vapors. Inhalation exposures to high concentrations of BD have been associated with lung cancer in both humans and experimental animals, although differences in species sensitivity have been observed. Metabolically active lung cells such as Pulmonary Type I and Type II epithelial cells and club cells (Clara cells)(1) are potential targets of BD metabolite-induced toxicity. Metabolic capacities of these cells, their regional densities, and distributions vary throughout the respiratory tract as well as between species and cell types. Here we present a physiologically based pharmacokinetic (PBPK) model for BD that includes a regional model of lung metabolism, based on a previous model for styrene, to provide species-dependent descriptions of BD metabolism in the mouse, rat, and human. Since there are no in vivo data on BD pharmacokinetics in the human, the rat and mouse models were parameterized to the extent possible on the basis of in vitro metabolic data. Where it was necessary to use in vivo data, extrapolation from rat to mouse was performed to evaluate the level of uncertainty in the human model. A kidney compartment and description of downstream metabolism were also included in the model to allow for eventual use of available urinary and blood biomarker data in animals and humans to calibrate the model for estimation of BD exposures and internal metabolite levels. Results from simulated inhalation exposures to BD indicate that incorporation of differential lung region metabolism is important in describing species differences in pulmonary response and that these differences may have implications for risk assessments of human exposures to BD.

The human early-life exposome (HELIX): project rationale and design

BACKGROUND

Developmental periods in early life may be particularly vulnerable to impacts of environmental exposures. Human research on this topic has generally focused on single exposure-health effect relationships. The "exposome" concept encompasses the totality of exposures from conception onward, complementing the genome.

OBJECTIVES

The Human Early-Life Exposome (HELIX) project is a new collaborative research project that aims to implement novel exposure assessment and biomarker methods to characterize early-life exposure to multiple environmental factors and associate these with omics biomarkers and child health outcomes, thus characterizing the "early-life exposome." Here we describe the general design of the project.

METHODS

In six existing birth cohort studies in Europe, HELIX will estimate prenatal and postnatal exposure to a broad range of chemical and physical exposures. Exposure models will be developed for the full cohorts totaling 32,000 mother-child pairs, and biomarkers will be measured in a subset of 1,200 mother-child pairs. Nested repeat-sampling panel studies (n = 150) will collect data on biomarker variability, use smartphones to assess mobility and physical activity, and perform personal exposure monitoring. Omics techniques will determine molecular profiles (metabolome, proteome, transcriptome, epigenome) associated with exposures. Statistical methods for multiple exposures will provide exposure-response estimates for fetal and child growth, obesity, neurodevelopment, and respiratory outcomes. A health impact assessment exercise will evaluate risks and benefits of combined exposures.

CONCLUSIONS

HELIX is one of the first attempts to describe the early-life exposome of European populations and unravel its relation to omics markers and health in childhood. As proof of concept, it will form an important first step toward the life-course exposome.

Characterization of the human kinetic adjustment factor for the health risk assessment of environmental contaminants

A default uncertainty factor of 3.16 (√10) is applied to account for interindividual variability in toxicokinetics when performing non-cancer risk assessments. Using relevant human data for specific chemicals, as WHO/IPCS suggests, it is possible to evaluate, and replace when appropriate, this default factor by quantifying chemical-specific adjustment factors for interindividual variability in toxicokinetics (also referred to as the human kinetic adjustment factor, HKAF). The HKAF has been determined based on the distributions of pharmacokinetic parameters (e.g., half-life, area under the curve, maximum blood concentration) in relevant populations. This article focuses on the current state of knowledge of the use of physiologically based algorithms and models in characterizing the HKAF for environmental contaminants. The recent modeling efforts on the computation of HKAF as a function of the characteristics of the population, chemical and its mode of action (dose metrics), as well as exposure scenario of relevance to the assessment are reviewed here. The results of these studies, taken together, suggest the HKAF varies as a function of the sensitive subpopulation and dose metrics of interest, exposure conditions considered (route, duration, and intensity), metabolic pathways involved and theoretical model underlying its computation. The HKAF seldom exceeded the default value of 3.16, except in very young children (i.e., <≈ 3 months) and when the parent compound is the toxic moiety. Overall, from a public health perspective, the current state of knowledge generally suggest that the default uncertainty factor is sufficient to account for human variability in non-cancer risk assessments of environmental contaminants.

A population model of integrative cardiovascular physiology

We present a small integrative model of human cardiovascular physiology. The model is population-based; rather than using best fit parameter values, we used a variant of the Metropolis algorithm to produce distributions for the parameters most associated with model sensitivity. The population is built by sampling from these distributions to create the model coefficients. The resulting models were then subjected to a hemorrhage. The population was separated into those that lost less than 15 mmHg arterial pressure (compensators), and those that lost more (decompensators). The populations were parametrically analyzed to determine baseline conditions correlating with compensation and decompensation. Analysis included single variable correlation, graphical time series analysis, and support vector machine (SVM) classification. Most variables were seen to correlate with propensity for circulatory collapse, but not sufficiently to effect reasonable classification by any single variable. Time series analysis indicated a single significant measure, the stressed blood volume, as predicting collapse in situ, but measurement of this quantity is clinically impossible. SVM uncovered a collection of variables and parameters that, when taken together, provided useful rubrics for classification. Due to the probabilistic origins of the method, multiple classifications were attempted, resulting in an average of 3.5 variables necessary to construct classification. The most common variables used were systemic compliance, baseline baroreceptor signal strength and total peripheral resistance, providing predictive ability exceeding 90%. The methods presented are suitable for use in any deterministic mathematical model.

Studying permethrin exposure in flight attendants using a physiologically based pharmacokinetic model

Assessment of potential health risks to flight attendants from exposure to pyrethroid insecticides, used for aircraft disinsection, is limited because of (a) lack of information on exposures to these insecticides, and (b) lack of tools for linking these exposures to biomarker data. We developed and evaluated a physiologically based pharmacokinetic (PBPK) model to assess the exposure of flight attendants to the pyrethroid insecticide permethrin attributable to aircraft disinsection. The permethrin PBPK model was developed by adapting previous models for pyrethroids, and was parameterized using currently available metabolic parameters for permethrin. The human permethrin model was first evaluated with data from published human studies. Then, it was used to estimate urinary metabolite concentrations of permethrin in flight attendants who worked in aircrafts, which underwent residual and pre-flight spray treatments. The human model was also applied to analyze the toxicokinetics following permethrin exposures attributable to other aircraft disinsection scenarios. Predicted levels of urinary 3-phenoxybenzoic acid (3-PBA), a metabolite of permethrin, following residual disinsection treatment were comparable to the measurements made for flight attendants. Simulations showed that the median contributions of the dermal, oral and inhalation routes to permethrin exposure in flight attendants were 83.5%, 16.1% and 0.4% under residual treatment scenario, respectively, and were 5.3%, 5.0% and 89.7% under pre-flight spray scenario, respectively. The PBPK model provides the capability to simulate the toxicokinetic profiles of permethrin, and can be used in the studies on human exposure to permethrin.

Carbaryl and 1-naphthol tissue levels and related cholinesterase inhibition in male Brown Norway rats from preweaning to senescence

Studies incorporating both toxicokinetic and dynamic factors provide insight into chemical sensitivity differences across the life span. Tissue (brain, plasma, liver) levels of the N-methyl carbamate carbaryl, and its metabolite 1-naphthol, were determined and related to brain and RBC cholinesterase (ChE) inhibition in the same animals. Dose-response (3, 7.5, 15, or 22.5 mg/kg, 40-45 min postdosing) and time course (3 or 15 mg/kg at 30, 60, 120, or 240 min postdosing) of acute effects of carbaryl (oral gavage) in preweanling (postnatal day [PND] 18) and adult male Brown Norway rats from adolescence to senescence (1, 4, 12, 24 mo) were compared. At all ages there were dose-related increases in carbaryl and 1-naphthol in the dose-response study, and the time-course study showed highest carbaryl levels at 30 min postdosing. There were, however, age-related differences in that the 1- and 4-mo rats showed the lowest levels of carbaryl and 1-naphthol, and PND18 and 24-mo rats had similar, higher levels. The fastest clearance (shortest half-lives) was observed in 1- and 4-mo rats. Carbaryl levels were generally higher than 1-naphthol in brain and plasma, but in liver, 1-naphthol levels were similar to or greater than carbaryl. Brain ChE inhibition closely tracked brain carbaryl concentrations regardless of the time after dosing, but there was more variability in the relationship between RBC ChE and plasma carbaryl levels. Within-subject analyses suggested somewhat more brain ChE inhibition at lower carbaryl levels only in the PND18 rats. These findings may reflect maturation followed by decline in kinetic factors over the life span.

Interpreting PCB levels in breast milk using a physiologically based pharmacokinetic model to reconstruct the dynamic exposure of Italian women

Polychlorinated biphenyls (PCBs) are persistent contaminants suspected to cause adverse health effects in humans. As PCBs levels in food have not been monitored frequently in the past, modeling approaches based on environmental data have been proposed to predict the human dietary intake. In this work, we propose to improve these approaches by taking into account internal levels of PCBs in humans. This methodology is based on the analysis of biomonitoring data using exposure and physiologically based pharmacokinetic (PBPK) modeling to determine the most probable scenario of exposure. Breast milk concentrations were measured in Italian women for PCB-138, PCB-153 and PCB-180. For each congener, three exposure scenarios were derived and a PBPK model was used to relate the lifetime exposure to the breast milk levels. For the three PCBs, we determined the most probable scenario of exposure. Our results support the adequacy of the exposure and the PBPK models for PCB-180 and PCB-153, whereas we observed discrepancies between the models and the biomonitoring data for PCB-138. Our intake estimates are in good agreement with previous exposure assessments based solely on food contamination demonstrating the relevance of our approach to reconstruct accurately the exposure and to fill in data gaps on exposure.

Linking fate model in freshwater and PBPK model to assess human internal dosimetry of B(a)P associated with drinking water

In the present study, we demonstrate an integrated modeling approach for predicting internal tissue concentrations of chemicals by coupling a multimedia environmental model and a generic physiologically based pharmacokinetic (PBPK) model. A case study was designed for a region situated on the Seine river watershed, downstream of the Paris megacity, and for benzo(a)pyrene emitted from industrial zones in the region. In this case study, these two models are linked only by water intake from riverine system for the multimedia model into human body for the PBPK model. The limited monitoring data sets of B(a)P concentrations in bottom sediment and in raw river water, obtained at the downstream of Paris, were used to re-construct long-term daily concentrations of B(a)P in river water. The re-construction of long-term series of B(a)P level played a key role for the intermediate model calibration (conducted in multimedia model) and thus for improving model input to PBPK model. In order to take into account the parametric uncertainty in the model inputs, some input parameters relevant for the multimedia model were given by probability density functions (PDFs); some generic PDFs were updated with site-specific measurements by a Bayesian approach. The results of this study showed that the multimedia model fits well with actual annual measurements in sediments over one decade. No accumulation of B(a)P in the organs was observed. In conclusion, this case study demonstrated the feasibility of a full-chain assessment combining multimedia environmental predictions and PBPK modeling, including uncertainty and sensitivity analyses.

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

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