Evaluation of physiologically based pharmacokinetic models for use in risk assessment

Evaluation of a Proportional Response Addition Approach to Mixture Risk Assessment and Predictive Toxicology Using Data on Four Trihalomethanes from the U.S. EPA's Multiple-Purpose Design Study

In this study, proportional response addition (Prop-RA), a model for predicting response from chemical mixture exposure, is demonstrated and evaluated by statistically analyzing data on all possible binary combinations of the four regulated trihalomethanes (THMs). These THMs were the subject of a multipurpose toxicology study specifically designed to evaluate Prop-RA. The experimental design used a set of doses common to all components and mixtures, providing hepatotoxicity data on the four single THMs and the binary combinations. In Prop-RA, the contribution of each component to mixture toxicity is proportional to its fraction in the mixture based on its response at the total mixture dose. The primary analysis consisted of 160 evaluations. Statistically significant departures from the Prop-RA prediction were found for seven evaluations, with three predications that were greater than and four that were less than the predicted response; interaction magnitudes (n-fold difference in response vs. prediction) ranged from 1.3 to 1.4 for the former and 2.6 to 3.8 for the latter. These predictions support the idea that Prop-RA works best with chemicals where the effective dose ranges overlap. Prop-RA does not assume the similarity of toxic action or independence, but it can be applied to a mixture of components that affect the same organ/system, with perhaps unknown toxic modes of action.

Physiologically-based pharmacokinetic model for evaluating gender-specific exposures of N-nitrosodimethylamine (NDMA)

N-nitrosodimethylamine (NDMA) is classified as a human carcinogen and could be produced by both natural and industrial processes. Although its toxicity and histopathology have been well-studied in animal species, there is insufficient data on the blood and tissue exposures that can be correlated with the toxicity of NDMA. The purpose of this study was to evaluate gender-specific pharmacokinetics/toxicokinetics (PKs/TKs), tissue distribution, and excretion after the oral administration of three different doses of NDMA in rats using a physiologically-based pharmacokinetic (PBPK) model. The major target tissues for developing the PBPK model and evaluating dose metrics of NDMA included blood, gastrointestinal (GI) tract, liver, kidney, lung, heart, and brain. The predictive performance of the model was validated using sensitivity analysis, (average) fold error, and visual inspection of observations versus predictions. Then, a Monte Carlo simulation was performed to describe the magnitudes of inter-individual variability and uncertainty of the single model predictions. The developed PBPK model was applied for the exposure simulation of daily oral NDMA to estimate blood concentration ranges affecting health effects following acute-duration (≤ 14 days), intermediate-duration (15-364 days), and chronic-duration (≥ 365 days) intakes. The results of the study could be used as a scientific basis for interpreting the correlation between in vivo exposures and toxicological effects of NDMA.

Levels, Toxic Effects, and Risk Assessment of Pyrrolizidine Alkaloids in Foods: A Review

Pyrrolizidine alkaloids (PAs) are naturally occurring secondary metabolites of plants. To date, more than 660 types of PAs have been identified from an estimated 6000 plants, and approximately 120 of these PAs are hepatotoxic. As a result of PAs being found in spices, herbal teas, honey, and milk, PAs are considered contaminants in foods, posing a potential risk to human health. Here, we summarize the chemical structure, toxic effects, levels, and regulation of PAs in different countries to provide a better understanding of their toxicity and risk assessment. With recent research on the risk assessment of PAs, this review also discusses the challenges facing this field, aiming to provide a scientific basis for PA toxicity research and safety assessment.

Pathogenetic role of alveolar surfactant depleted by phosgene: Biophysical mechanisms and peak inhalation exposure metrics

In contrast to water-soluble respiratory tract irritants in their gas phase, the physicochemical properties of 'hydrophilicity' vs. 'lipophilicity' are the preponderant factors that dictate the site of major retention of the gas at the portal of entry. The lipophilic physical properties of phosgene gas facilitate retention in the alveolar region lined with amphipathic pulmonary surfactant (PS). The relationship between exposure and adverse health outcomes is complex, may vary over time, and is dependent on the biokinetics, biophysics, and pool size of PS relative to the inhaled dose of phosgene. Kinetic PS depletion is hypothesized to occur as inhalation followed by inhaled dose-dependent PS depletion. A kinetic model was developed to better understand the variables characterizing the inhaled dose rates of phosgene vs. PS pool size reconstitution. Modeling and empirical data from published evidence revealed that phosgene gas unequivocally follows a concentration x exposure (C × t) metric, independent of the frequency of exposure. The modeled and empirical data support the hypothesis that the exposure standards of phosgene are described best by a C × t time-averaged metric. Modeled data favorably duplicate expert panel-derived standards. Peak exposures within a reasonable range are of no concern.

In-depth analysis of patterns in selection of different physiologically based pharmacokinetic modeling tools: PartI - Applications and rationale behind the use of open source-code software

PBPK applications published in the literature support a greater adoption of non-open source-code (NOSC) software as opposed to open source-code (OSC) alternatives. However, a significant number of PBPK modelers are still using OSC software, understanding the rationale for the use of this modality is important and may help those embarking on PBPK modeling. No previous analysis of PBPK modeling trends has included the rationale of the modeler. An in-depth analysis of PBPK applications of OSC software is warranted to determine the true impact of OSC software on the rise of PBPK. Publications focussing on PBPK modeling applications, which used OSC software, were identified by systematically searching the scientific literature for original articles. A total of 171 articles were extracted from the narrowed subset. The rise in the use of OSC software for PBPK applications was greater than the general discipline of pharmacokinetics (9 vs. 4), but less than the overall growth of the PBPK area (9 vs. 43). Our report demonstrates conclusively that the surge in PBPK usage is primarily attributable to the availability and implementations of NOSC software. Modelers preferred not to share the reasons for their selection of certain modeling software and no 'explicit' rationale was given to support the use of OSC analysed by this study. As the preference for NOSC versus OSC software tools in the PBPK area continues to be divided, initiatives to add the rationale in using one form over another to every future PBPK modeling report will be a welcomed and informative addition.

Machine learning and artificial intelligence in physiologically based pharmacokinetic modeling

Physiologically based pharmacokinetic (PBPK) models are useful tools in drug development and risk assessment of environmental chemicals. PBPK model development requires the collection of species-specific physiological, and chemical-specific absorption, distribution, metabolism, and excretion (ADME) parameters, which can be a time-consuming and expensive process. This raises a need to create computational models capable of predicting input parameter values for PBPK models, especially for new compounds. In this review, we summarize an emerging paradigm for integrating PBPK modeling with machine learning (ML) or artificial intelligence (AI)-based computational methods. This paradigm includes 3 steps (1) obtain time-concentration PK data and/or ADME parameters from publicly available databases, (2) develop ML/AI-based approaches to predict ADME parameters, and (3) incorporate the ML/AI models into PBPK models to predict PK summary statistics (eg, area under the curve and maximum plasma concentration). We also discuss a neural network architecture "neural ordinary differential equation (Neural-ODE)" that is capable of providing better predictive capabilities than other ML methods when used to directly predict time-series PK profiles. In order to support applications of ML/AI methods for PBPK model development, several challenges should be addressed (1) as more data become available, it is important to expand the training set by including the structural diversity of compounds to improve the prediction accuracy of ML/AI models; (2) due to the black box nature of many ML models, lack of sufficient interpretability is a limitation; (3) Neural-ODE has great potential to be used to generate time-series PK profiles for new compounds with limited ADME information, but its application remains to be explored. Despite existing challenges, ML/AI approaches will continue to facilitate the efficient development of robust PBPK models for a large number of chemicals.

A Machine Learning Model to Estimate Toxicokinetic Half-Lives of Per- and Polyfluoro-Alkyl Substances (PFAS) in Multiple Species

Per- and polyfluoroalkyl substances (PFAS) are a diverse group of man-made chemicals that are commonly found in body tissues. The toxicokinetics of most PFAS are currently uncharacterized, but long half-lives (t_½) have been observed in some cases. Knowledge of chemical-specific t_½ is necessary for exposure reconstruction and extrapolation from toxicological studies. We used an ensemble machine learning method, random forest, to model the existing in vivo measured t_½ across four species (human, monkey, rat, mouse) and eleven PFAS. Mechanistically motivated descriptors were examined, including two types of surrogates for renal transporters: (1) physiological descriptors, including kidney geometry, for renal transporter expression and (2) structural similarity of defluorinated PFAS to endogenous chemicals for transporter affinity. We developed a classification model for t_½ (Bin 1: <12 h; Bin 2: <1 week; Bin 3: <2 months; Bin 4: >2 months). The model had an accuracy of 86.1% in contrast to 32.2% for a y-randomized null model. A total of 3890 compounds were within domain of the model, and t_½ was predicted using the bin medians: 4.9 h, 2.2 days, 33 days, and 3.3 years. For human t_½, 56% of PFAS were classified in Bin 4, 7% were classified in Bin 3, and 37% were classified in Bin 2. This model synthesizes the limited available data to allow tentative extrapolation and prioritization.

Development, testing, parameterisation, and calibration of a human PBK model for the plasticiser, di (2-ethylhexyl) adipate (DEHA) using in silico, in vitro and human biomonitoring data

Introduction: A physiologically based biokinetic model for di (2-ethylhexyl) adipate (DEHA) based on a refined model for di-(2-propylheptyl) phthalate (DPHP) was developed to interpret the metabolism and biokinetics of DEHA following a single oral dosage of 50 mg to two male and two female volunteers. Methods: The model was parameterized using in vitro and in silico methods such as, measured intrinsic hepatic clearance scaled from in vitro to in vivo and algorithmically predicted parameters such as plasma unbound fraction and tissue:blood partition coefficients (PCs). Calibration of the DEHA model was achieved using concentrations of specific downstream metabolites of DEHA excreted in urine. The total fractions of ingested DEHA eliminated as specific metabolites were estimated and were sufficient for interpreting the human biomonitoring data. Results: The specific metabolites of DEHA, mono-2-ethyl-5-hydroxyhexyl adipate (5OH-MEHA), mono-2-ethyl-5-oxohexyl adipate (5oxo-MEHA), mono-5-carboxy-2-ethylpentyl adipate (5cx-MEPA) only accounted for ∼0.45% of the ingested DEHA. Importantly, the measurements of adipic acid, a non-specific metabolite of DEHA, proved to be important in model calibration. Discussion: The very prominent trends in the urinary excretion of the metabolites, 5cx-MEPA and 5OH-MEHA allowed the important absorption mechanisms of DEHA to be modelled. The model should be useful for the study of exposure to DEHA of the general human population.

Development, testing, parameterisation, and calibration of a human PBPK model for the plasticiser, di-(2-ethylhexyl) terephthalate (DEHTP) using in silico, in vitro and human biomonitoring data

A physiologically based pharmacokinetic model for di-(2-ethylhexyl) terephthalate (DEHTP) based on a refined model for di-(2-propylheptyl) phthalate (DPHP) was developed to interpret the metabolism and biokinetics of DEHTP following a single oral dose of 50 mg to three male volunteers. In vitro and in silico methods were used to generate parameters for the model. For example, measured intrinsic hepatic clearance scaled from in vitro to in vivo and plasma unbound fraction and tissue:blood partition coefficients (PCs) were predicted algorithmically. Whereas the development and calibration of the DPHP model was based upon two data streams, blood concentrations of parent chemical and first metabolite and the urinary excretion of metabolites, the model for DEHTP was calibrated against a single data stream, the urinary excretion of metabolites. Despite the model form and structure being identical significant quantitative differences in lymphatic uptake between the models were observed. In contrast to DPHP the fraction of ingested DEHTP entering lymphatic circulation was much greater and of a similar magnitude to that entering the liver with evidence for the dual uptake mechanisms discernible in the urinary excretion data. Further, the absolute amounts absorbed by the study participants, were much higher for DEHTP relative to DPHP. The in silico algorithm for predicting protein binding performed poorly with an error of more than two orders of magnitude. The extent of plasma protein binding has important implications for the persistence of parent chemical in venous blood-inferences on the behaviour of this class of highly lipophilic chemicals, based on calculations of chemical properties, should be made with extreme caution. Attempting read across for this class of highly lipophilic chemicals should be undertaken with caution since basic adjustments to PCs and metabolism parameters would be insufficient, even when the structure of the model itself is appropriate. Therefore, validation of a model parameterized entirely with in vitro and in silico derived parameters would need to be calibrated against several human biomonitoring data streams to constitute a data rich source chemical to afford confidence for future evaluations of other similar chemicals using the read-across approach.

Enhanced prediction of internal concentrations of phenolic endocrine disrupting chemicals and their metabolites in fish by a physiologically based toxicokinetic incorporating metabolism (PBTK-MT) model

Bisphenol A (BPA), 4-nonylphenol (4-NP), and triclosan (TCS) are phenolic endocrine disrupting chemicals (EDCs), which are widely detected in aquatic environments and further bioaccumulated and metabolized in fish. Physiologically based toxicokinetic (PBTK) models have been used to describe the absorption, distribution, metabolism, and excretion (ADME) of parent compounds in fish, whereas the metabolites are less explored. In this study, a PBTK incorporating metabolism (PBTK-MT) model for BPA, 4-NP, and TCS was established to enhance the performance of the traditional PBTK model. The PBTK-MT model comprised 16 compartments, showing great accuracy in predicting the internal concentrations of three compounds and their glucuronidated and sulfated conjugates in fish. The impact of typical hepatic metabolism on the PBTK-MT model was successfully resolved by optimizing the mechanism for deriving the partition coefficients between the blood and liver. The PBTK-MT model exhibited a potential data gap-filling capacity for unknown parameters through a backward extrapolation approach of parameters. Model sensitivity analysis suggested that only five parameters were sensitive in at least two PBTK-MT models, while most parameters were insensitive. The PBTK-MT model will contribute to a well understanding of the environmental behavior and risks of pollutants in aquatic biota.

Evaluation of a rapid, generic human gestational dose model

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.

Towards best use and regulatory acceptance of generic physiologically based kinetic (PBK) models for in vitro-to-in vivo extrapolation (IVIVE) in chemical risk assessment

With an increasing need to incorporate new approach methodologies (NAMs) in chemical risk assessment and the concomitant need to phase out animal testing, the interpretation of in vitro assay readouts for quantitative hazard characterisation becomes more important. Physiologically based kinetic (PBK) models, which simulate the fate of chemicals in tissues of the body, play an essential role in extrapolating in vitro effect concentrations to in vivo bioequivalent exposures. As PBK-based testing approaches evolve, it will become essential to standardise PBK modelling approaches towards a consensus approach that can be used in quantitative in vitro-to-in vivo extrapolation (QIVIVE) studies for regulatory chemical risk assessment based on in vitro assays. Based on results of an ECETOC expert workshop, steps are recommended that can improve regulatory adoption: (1) define context and implementation, taking into consideration model complexity for building fit-for-purpose PBK models, (2) harmonise physiological input parameters and their distribution and define criteria for quality chemical-specific parameters, especially in the absence of in vivo data, (3) apply Good Modelling Practices (GMP) to achieve transparency and design a stepwise approach for PBK model development for risk assessors, (4) evaluate model predictions using alternatives to in vivo PK data including read-across approaches, (5) use case studies to facilitate discussions between modellers and regulators of chemical risk assessment. Proof-of-concepts of generic PBK modelling approaches are published in the scientific literature at an increasing rate. Working on the previously proposed steps is, therefore, needed to gain confidence in PBK modelling approaches for regulatory use.

Development, Testing, Parameterisation and Calibration of a Human PBPK Model for the Plasticiser, Di-(2-propylheptyl) Phthalate (DPHP) Using in Silico, in vitro and Human Biomonitoring Data

A physiologically based pharmacokinetic model for Di-(2-propylheptyl) phthalate (DPHP) was developed to interpret the biokinetics in humans after single oral doses. The model was parameterized with in vitro and in silico derived parameters and uncertainty and sensitivity analysis was used during the model development process to assess structure, biological plausibility and behaviour prior to simulation and analysis of human biological monitoring data. To provide possible explanations for some of the counter-intuitive behaviour of the biological monitoring data the model included a simple lymphatic uptake process for DPHP and enterohepatic recirculation (EHR) for DPHP and the mono ester metabolite mono-(2-propylheptyl) phthalate (MPHP). The model was used to simultaneously simulate the concentration-time profiles of blood DPHP, MPHP and the urinary excretion of two metabolites, mono-(2-propyl-6-hydroxyheptyl) phthalate (OH-MPHP) and mono-(2-propyl-6-carboxyhexyl) phthalate (cx-MPHP). The availability of blood and urine measurements permitted a more robust qualitative and quantitative investigation of the importance of EHR and lymphatic uptake. Satisfactory prediction of blood DPHP and urinary metabolites was obtained whereas blood MPHP was less satisfactory. However, the delayed peak of DPHP concentration relative to MPHP in blood and second order metabolites in urine could be explained as a result of three processes: 1) DPHP entering the systemic circulation from the lymph, 2) rapid and very high protein binding and 3) the efficiency of the liver in removing DPHP absorbed via the hepatic route. The use of sensitivity analysis is considered important in the evaluation of uncertainty around in vitro and in silico derived parameters. By quantifying their impact on model output sufficient confidence in the use of a model should be afforded. This approach could expand the use of PBPK models since parameterization with in silico techniques allows for rapid model development. This in turn could assist in reducing the use of animals in toxicological evaluations by enhancing the utility of “read across” techniques.

Toxicokinetic Models for Bioconcentration of Organic Contaminants in Two Life Stages of White Sturgeon (Acipenser transmontanus)

The white sturgeon (Acipenser transmontanus) is an endangered ancient fish species that is known to be particularly sensitive to certain environmental contaminants, partly because of the uptake and subsequent toxicity of lipophilic pollutants prone to bioconcentration as a result of their high lipid content. To better understand the bioconcentration of organic contaminants in this species, toxicokinetic (TK) models were developed for the embryo-larval and subadult life stages. The embryo-larval model was designed as a one-compartment model and validated using whole-body measurements of benzo[a]pyrene (B[a]P) metabolites from a waterborne exposure to B[a]P. A physiologically based TK (PBTK) model was used for the subadult model. The predictive power of the subadult model was validated with an experimental data set of four chemicals. Results showed that the TK models could accurately predict the bioconcentration of organic contaminants for both life stages of white sturgeon within 1 order of magnitude of measured values. These models provide a tool to better understand the impact of environmental contaminants on the health and the survival of endangered white sturgeon populations.

A Physiological-Based Pharmacokinetic Model For The Broad Spectrum Antimicrobial Zinc Pyrithione: II. Dermal Absorption And Dosimetry In The Rat

The broad spectrum antimicrobial/antifungal zinc pyrithione (ZnPT) is used in products ranging from antifouling paint to antidandruff shampoo. The hazard profile of ZnPT was established based upon comprehensive toxicological testing, and products containing this biocide have been safely used for years. The purpose of this study was to create a dermal physiologically based pharmacokinetic (PBPK) model for ZnPT in the rat for improving dose-response analysis of ZnPT-induced toxicity where reversible hindlimb weakness was the endpoint used as the basis for ZnPT risk assessments. Previously, we developed a PBPK model which simulated the kinetics of pyrithione (PT) and its major metabolites 2-(methylsulfonyl)pyridine and S-glucuronide conjugates in blood and tissues of rats following oral ZnPT administration. The dermal model was optimized utilizing in vitro dermal penetration investigations conducted with rat skin and with historical data from a dermal repeat dose study using rats. The model replicated the observed temporal patterns and elimination kinetics of [¹⁴C]PT equivalents in blood and urine during and following repeated dermal dosing and replicated the observed dose-dependencies of absorption, blood [¹⁴C]PT equivalents and plasma PT concentrations. The model provided internal dosimetry predictions for a benchmark dose analysis of hindlimb weakness in rats that combined dermal, gavage and dietary studies into a single internal dose-response model with area-under-the-curve (AUC) for plasma PT, the toxic moiety in the rat, as the internal dose metric. This PBPK model has predictive validity for calculating internal doses of PT and/or [¹⁴C]PT equivalents from different routes of exposure in the rat.

High-throughput PBTK models for in vitro to in vivo extrapolation

INTRODUCTION

Toxicity data are unavailable for many thousands of chemicals in commerce and the environment. Therefore, risk assessors need to rapidly screen these chemicals for potential risk to public health. High-throughput screening (HTS) for in vitro bioactivity, when used with high-throughput toxicokinetic (HTTK) data and models, allows characterization of these thousands of chemicals.

AREAS COVERED

This review covers generic physiologically based toxicokinetic (PBTK) models and high-throughput PBTK modeling for in vitro-in vivo extrapolation (IVIVE) of HTS data. We focus on 'httk', a public, open-source set of computational modeling tools and in vitro toxicokinetic (TK) data.

EXPERT OPINION

HTTK benefits chemical risk assessors with its ability to support rapid chemical screening/prioritization, perform IVIVE, and provide provisional TK modeling for large numbers of chemicals using only limited chemical-specific data. Although generic TK model design can increase prediction uncertainty, these models provide offsetting benefits by increasing model implementation accuracy. Also, public distribution of the models and data enhances reproducibility. For the httk package, the modular and open-source design can enable the tool to be used and continuously improved by a broad user community in support of the critical need for high-throughput chemical prioritization and rapid dose estimation to facilitate rapid hazard assessments.

Quantitative in Vitro to in Vivo Extrapolation (QIVIVE) for Predicting Reduced Anogenital Distance Produced by Anti-Androgenic Pesticides in a Rodent Model for Male Reproductive Disorders

BACKGROUND

Many pesticides can antagonize the androgen receptor (AR) or inhibit androgen synthesis in vitro but their potential to cause reproductive toxicity related to disruption of androgen action during fetal life is difficult to predict. Currently no approaches for using in vitro data to anticipate such in vivo effects exist. Prioritization schemes that limit unnecessary in vivo testing are urgently needed.

OBJECTIVES

The aim was to develop a quantitative in vitro to in vivo extrapolation (QIVIVE) approach for predicting in vivo anti-androgenicity arising from gestational exposures and manifesting as a shortened anogenital distance (AGD) in male rats.

METHODS

We built a physiologically based pharmacokinetic (PBK) model to simulate concentrations of chemicals in the fetus resulting from maternal dosing. The predicted fetal levels were compared with analytically determined concentrations, and these were judged against in vitro active concentrations for AR antagonism and androgen synthesis suppression.

RESULTS

We first evaluated our model by using in vitro and in vivo anti-androgenic data for procymidone, vinclozolin, and linuron. Our PBK model described the measured fetal concentrations of parent compounds and metabolites quite accurately (within a factor of five). We applied the model to nine current-use pesticides, all with in vitro evidence for anti-androgenicity but missing in vivo data. Seven pesticides (fludioxonil, cyprodinil, dimethomorph, imazalil, quinoxyfen, fenhexamid, o-phenylphenol) were predicted to produce a shortened AGD in male pups, whereas two (λ-cyhalothrin, pyrimethanil) were anticipated to be inactive. We tested these expectations for fludioxonil, cyprodinil, and dimethomorph and observed shortened AGD in male pups after gestational exposure. The measured fetal concentrations agreed well with PBK-modeled predictions.

DISCUSSION

Our QIVIVE model newly identified fludioxonil, cyprodinil, and dimethomorph as in vivo anti-androgens. With the examples investigated, our approach shows great promise for predicting in vivo anti-androgenicity (i.e., AGD shortening) for chemicals with in vitro activity and for minimizing unnecessary in vivo testing. https://doi.org/10.1289/EHP6774.

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.

Interspecies prediction of pharmacokinetics and tissue distribution of doxorubicin by physiologically-based pharmacokinetic modeling

The aim of the study was to develop a physiologically-based pharmacokinetic (PBPK) model to describe and predict whole-body disposition of doxorubicin following intravenous administration. The PBPK model was established using previously published data in mice and included 10 tissue compartments: lungs, heart, brain, muscle, kidneys, pancreas, intestine, liver, spleen, adipose tissue, and plasma. Individual tissues were described by either perfusion-limited or permeability-limited models. All parameters were simultaneously estimated and the final model was able to describe murine data with good precision. The model was used for predicting doxorubicin disposition in rats, rabbits, dogs, and humans using interspecies scaling approaches and was qualified using plasma and tissue observed data. Reasonable prediction of the plasma pharmacokinetics and tissue distribution was achieved across all species. In conclusion, the PBPK model developed based on a rich dataset obtained from mice, was able to reasonably predict the disposition of doxorubicin in other preclinical species and humans. Applicability of the model for special populations, such as patients with hepatic impairment, was also demonstrated. The proposed model will be a valuable tool for optimization of exposure profiles of doxorubicin in human patients.

Integrating in vitro data and physiologically based kinetic modeling-facilitated reverse dosimetry to predict human cardiotoxicity of methadone

Development of novel testing strategies to detect adverse human health effects is of interest to replace in vivo-based drug and chemical safety testing. The aim of the present study was to investigate whether physiologically based kinetic (PBK) modeling-facilitated conversion of in vitro toxicity data is an adequate approach to predict in vivo cardiotoxicity in humans. To enable evaluation of predictions made, methadone was selected as the model compound, being a compound for which data on both kinetics and cardiotoxicity in humans are available. A PBK model for methadone in humans was developed and evaluated against available kinetic data presenting an adequate match. Use of the developed PBK model to convert concentration–response curves for the effect of methadone on human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM) in the so-called multi electrode array (MEA) assay resulted in predictions for in vivo dose–response curves for methadone-induced cardiotoxicity that matched the available in vivo data. The results also revealed differences in protein plasma binding of methadone to be a potential factor underlying variation between individuals with respect to sensitivity towards the cardiotoxic effects of methadone. The present study provides a proof-of-principle of using PBK modeling-based reverse dosimetry of in vitro data for the prediction of cardiotoxicity in humans, providing a novel testing strategy in cardiac safety studies.

Incorporation of in vitro metabolism data and physiologically based pharmacokinetic modeling in a risk assessment for chloroprene

Objective: To develop a physiologically based pharmacokinetic (PBPK) model for chloroprene in the mouse, rat and human, relying only on in vitro data to estimate tissue metabolism rates and partitioning, and to apply the model to calculate an inhalation unit risk (IUR) for chloroprene.Materials and methods: Female B6C3F1 mice were the most sensitive species/gender for lung tumors in the 2-year bioassay conducted with chloroprene. The PBPK model included tissue metabolism rate constants for chloroprene estimated from results of in vitro gas uptake studies using liver and lung microsomes. To assess the validity of the PBPK model, a 6-hr, nose-only chloroprene inhalation study was conducted with female B6C3F1 mice in which both chloroprene blood concentrations and ventilation rates were measured. The PBPK model was then used to predict dose measures - amounts of chloroprene metabolized in lungs per unit time - in mice and humans.Results: The mouse PBPK model accurately predicted in vivo pharmacokinetic data from the 6-hr, nose-only chloroprene inhalation study. The PBPK model was used to conduct a cancer risk assessment based on metabolism of chloroprene to reactive epoxides in the lung, the target tissue in mice. The IUR was over100-fold lower than the IUR from the EPA Integrated Risk Information System (IRIS), which was based on inhaled chloroprene concentration. The different result from the PBPK model risk assessment arises from use of the more relevant tissue dose metric, amount metabolized, rather than inhaled concentrationDiscussion and conclusions: The revised chloroprene PBPK model is based on the best available science, including new test animal in vivo validation, updated literature review and a Markov-Chain Monte Carlo analysis to assess parameter uncertainty. Relying on both mouse and human metabolism data also provides an important advancement in the use of quantitative in vitro to in vivo extrapolation (QIVIVE). Inclusion of the best available science is especially important when deriving a toxicity value based on species extrapolation for the potential carcinogenicity of a reactive metabolite.

Development, Testing, Parameterization, and Calibration of a Human Physiologically Based Pharmacokinetic Model for the Plasticizer, Hexamoll® Diisononyl-Cyclohexane-1, 2-Dicarboxylate Using In Silico, In Vitro, and Human Biomonitoring Data

A physiologically based pharmacokinetic model for Hexamoll^® diisononyl-cyclohexane-1, 2-dicarboxylate was developed to interpret the biokinetics in humans after single oral doses. The model was parameterized with in vitro and in silico derived parameters and uncertainty and sensitivity analysis was used during the model development process to assess structure, biological plausibility and behavior prior to simulation and analysis of human biological monitoring data. The model provided good simulations of the urinary excretion (Curine) of two metabolites; cyclohexane-1,2-dicarboxylic acid mono hydroxyisononyl ester (OH-MINCH) and cyclohexane-1, 2-dicarboxylic acid mono carboxyisononyl ester (cx-MINCH) from the biotransformation of mono-isononyl-cyclohexane-1, 2-dicarboxylate (MINCH), the monoester metabolite of di-isononyl-cyclohexane-1,2-dicarboxylate. However, good simulations could be obtained, with and without, a lymphatic compartment. Selection of an appropriate model structure was informed by sensitivity analysis which could identify and quantify the contribution to variability in Curine by parameters, such as, the fraction of oral dose that directly entered the lymphatic compartment and therefore by-passed the liver and the fraction of MINCH bio-transformed to cx-MINCH and OH-MINCH. By constraining these parameters within biologically plausible limits the presence of a lymphatic compartment was deemed an important component of model structure. Furthermore, the use of sensitivity analysis is important in the evaluation of uncertainty around in silico derived parameters. By quantifying their impact on model output sufficient confidence in the use of a model should be afforded. This type of approach could expand the use of physiologically based pharmacokinetic models since parameterization with in silico techniques allows for rapid model development. This in turn could assist in reducing the use of animals in toxicological evaluations by enhancing the utility of “read across” techniques.

Empirical models for anatomical and physiological changes in a human mother and fetus during pregnancy and gestation

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.

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 internal exposure and physiologically-based toxicokinetic modeling for 21st-century risk assessments

Scientifically sound, risk-informed evaluation of chemicals is essential to protecting public health. Systematically leveraging information from exposure, toxicology, and epidemiology studies can provide a holistic understanding of how real-world exposure to chemicals may impact the health of populations, including sensitive and vulnerable individuals and life-stages. Increasingly, public health policy makers are employing toxicokinetic (TK) modeling tools to integrate these data streams and predict potential human health impact. Development of a suite of tools for predicting internal exposure, including physiologically-based toxicokinetic (PBTK) models, is being driven by needs to address large numbers of data-poor chemicals efficiently, translate bioactivity, and mechanistic information from new in vitro test systems, and integrate multiple lines of evidence to enable scientifically sound, risk-informed decisions. New modeling approaches are being designed "fit for purpose" to inform specific decision contexts, with applications ranging from rapid screening of hundreds of chemicals, to improved prediction of risks during sensitive stages of development. New data are being generated experimentally and computationally to support these models. Progress to meet the demand for internal exposure and PBTK modeling tools will require transparent publication of models and data to build credibility in results, as well as opportunities to partner with decision makers to evaluate and build confidence in use of these for improved decisions that promote safe use of chemicals.

Risk to human health related to the presence of perfluorooctane sulfonic acid and perfluorooctanoic acid in food

The European Commission asked EFSA for a scientific evaluation on the risks to human health related to the presence of perfluorooctane sulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) in food. Regarding PFOS and PFOA occurrence, the final data set available for dietary exposure assessment contained a total of 20,019 analytical results (PFOS n = 10,191 and PFOA n = 9,828). There were large differences between upper and lower bound exposure due to analytical methods with insufficient sensitivity. The CONTAM Panel considered the lower bound estimates to be closer to true exposure levels. Important contributors to the lower bound mean chronic exposure were 'Fish and other seafood', 'Meat and meat products' and 'Eggs and egg products', for PFOS, and 'Milk and dairy products', 'Drinking water' and 'Fish and other seafood' for PFOA. PFOS and PFOA are readily absorbed in the gastrointestinal tract, excreted in urine and faeces, and do not undergo metabolism. Estimated human half-lives for PFOS and PFOA are about 5 years and 2-4 years, respectively. The derivation of a health-based guidance value was based on human epidemiological studies. For PFOS, the increase in serum total cholesterol in adults, and the decrease in antibody response at vaccination in children were identified as the critical effects. For PFOA, the increase in serum total cholesterol was the critical effect. Also reduced birth weight (for both compounds) and increased prevalence of high serum levels of the liver enzyme alanine aminotransferase (ALT) (for PFOA) were considered. After benchmark modelling of serum levels of PFOS and PFOA, and estimating the corresponding daily intakes, the CONTAM Panel established a tolerable weekly intake (TWI) of 13 ng/kg body weight (bw) per week for PFOS and 6 ng/kg bw per week for PFOA. For both compounds, exposure of a considerable proportion of the population exceeds the proposed TWIs.

Development and validation of a physiology-based model for the prediction of pharmacokinetics/toxicokinetics in rabbits

The environmental fates of pharmaceuticals and the effects of crop protection products on non-target species are subjects that are undergoing intense review. Since measuring the concentrations and effects of xenobiotics on all affected species under all conceivable scenarios is not feasible, standard laboratory animals such as rabbits are tested, and the observed adverse effects are translated to focal species for environmental risk assessments. In that respect, mathematical modelling is becoming increasingly important for evaluating the consequences of pesticides in untested scenarios. In particular, physiologically based pharmacokinetic/toxicokinetic (PBPK/TK) modelling is a well-established methodology used to predict tissue concentrations based on the absorption, distribution, metabolism and excretion of drugs and toxicants. In the present work, a rabbit PBPK/TK model is developed and evaluated with data available from the literature. The model predictions include scenarios of both intravenous (i.v.) and oral (p.o.) administration of small and large compounds. The presented rabbit PBPK/TK model predicts the pharmacokinetics (Cmax, AUC) of the tested compounds with an average 1.7-fold error. This result indicates a good predictive capacity of the model, which enables its use for risk assessment modelling and simulations.

A physiologically based pharmacokinetic model for the broad-spectrum antimicrobial zinc pyrithione: I. Development and verification

The broad-spectrum antimicrobial zinc pyrithione (ZnPT) is used in numerous products ranging from in-can preservative/mildicide in paints to antidandruff shampoo. Although products containing ZnPT have a long history of safe use, regulatory agencies routinely set limits of exposure based upon toxicological considerations. The objective of this study was to create a physiologically based pharmacokinetic (PBPK) model for ZnPT in the rat for improving dose-response analysis of ZnPT-induced toxicity, reversible hindlimb weakness, the endpoint that has been used as the basis for ZnPT risk assessments. A rat oral PBPK model was developed that includes compartments for plasma, liver, kidneys, muscle, brain, and rapidly and slowly perfused tissues. Pyrithione metabolism to 2-(methylsulfonyl)pyridine (MSP) and glucuronide conjugates was incorporated into the model. The model was parameterized and optimized based upon data from single-dose intravenous (iv) and oral gavage pharmacokinetic studies of radiolabeled pyrithione ([¹⁴C]PT) administered as zinc [¹⁴C]-pyrithione (Zn-[¹⁴C]PT) to adult female rats. It was further evaluated and refined using data from repeated, multidose oral gavage and dietary studies of Zn[¹⁴C]PT in the adult female rat that included measurements of plasma PT concentration, the putative toxic species. The model replicated the observed short-term elimination kinetics of PT in plasma and [¹⁴C]PT in whole blood following single doses and longer term temporal patterns of plasma and blood concentrations during repeated dosing schedules. The model also accounted for production and rapid elimination of S-glucuronide conjugates (SG) of 2-pyridinethiol and 2-pyridinethiol-1-oxide in urine, as well as production and slower elimination of MSP, the major [¹⁴C]PT species in blood within several hours following administration of ZnPT. The model provided internal dosimetry predictions for a benchmark dose (BMD) analysis of hindlimb weakness in rats, and was used to combine gavage and dietary studies into a single internal dose-response model with area under the curve (AUC) for plasma PT as the internal dose metric. This PBPK model has predictive validity for calculating internal doses of PT and/or [¹⁴C]PT from different routes of exposure in the rat.

Use of Physiologically Based Kinetic Modeling-Based Reverse Dosimetry to Predict in Vivo Toxicity from in Vitro Data

The development of reliable nonanimal based testing strategies, such as in vitro bioassays, is the holy grail in current human safety testing of chemicals. However, the use of in vitro toxicity data in risk assessment is not straightforward. One of the main issues is that concentration-response curves from in vitro models need to be converted to in vivo dose-response curves. These dose-response curves are needed in toxicological risk assessment to obtain a point of departure to determine safe exposure levels for humans. Recent scientific developments enable this translation of in vitro concentration-response curves to in vivo dose-response curves using physiologically based kinetic (PBK) modeling-based reverse dosimetry. The present review provides an overview of the examples available in the literature on the prediction of in vivo toxicity using PBK modeling-based reverse dosimetry of in vitro toxicity data, showing that proofs-of-principle are available for toxicity end points ranging from developmental toxicity, nephrotoxicity, hepatotoxicity, and neurotoxicity to DNA adduct formation. This review also discusses the promises and pitfalls, and the future perspectives of the approach. Since proofs-of-principle available so far have been provided for the prediction of toxicity in experimental animals, future research should focus on the use of in vitro toxicity data obtained in human models to predict the human situation using human PBK models. This would facilitate human- instead of experimental animal-based approaches in risk assessment.

Integrating in vitro data and physiologically based kinetic (PBK) modelling to assess the in vivo potential developmental toxicity of a series of phenols

Toxicity outcomes derived in vitro do not always reflect in vivo toxicity values, which was previously observed for a series of phenols tested in the embryonic stem cell test (EST). Translation of in vitro data to the in vivo situation is therefore an important, but still limiting step for the use of in vitro toxicity outcomes in the safety assessment of chemicals. The aim of the present study was to translate in vitro embryotoxicity data for a series of phenols to in vivo developmental toxic potency values for the rat by physiologically based kinetic (PBK) modelling-based reverse dosimetry. To this purpose, PBK models were developed for each of the phenols. The models were parameterised with in vitro-derived values defining metabolism and transport of the compounds across the intestinal and placental barrier and with in silico predictions and data from the literature. Using PBK-based reverse dosimetry, in vitro concentration–response curves from the EST were translated into in vivo dose–response curves from which points of departure (PoDs) were derived. The predicted PoDs differed less than 3.6-fold from PoDs derived from in vivo toxicity data for the phenols available in the literature. Moreover, the in vitro PBK-based reverse dosimetry approach could overcome the large disparity that was observed previously between the in vitro and the in vivo relative potency of the series of phenols. In conclusion, this study shows another proof-of-principle that the in vitro PBK approach is a promising strategy for non-animal-based safety assessment of chemicals.

Advancing In Vitro-In Vivo Extrapolations of Mechanism-Specific Toxicity Data Through Toxicokinetic Modeling

International legislation, such as the European REACH regulation (registration, evaluation, authorization, and restriction of chemicals), mandates the assessment of potential risks of an ever-growing number of chemicals to the environment and human health. Although this legislation is considered one of the most important investments in consumer safety ever, the downside is that the current testing strategies within REACH rely on extensive animal testing. To address the ethical conflicts arising from these increased testing requirements, decision-makers, such as the European Chemicals Agency (ECHA), are committed to Russel and Burch's 3R principle (i.e., reduction, replacement, refinement) by demanding that animal experiments should be substituted with appropriate alternatives whenever possible. A potential solution of this dilemma might be the application of in vitro bioassays to estimate toxic effects using cells or cellular components instead of whole organisms. Although such assays are particularly useful to assess potential mechanisms of toxic action, scientists require appropriate methods to extrapolate results from the in vitro level to the situation in vivo. Toxicokinetic models are a straightforward means of bridging this gap. The present chapter describes different available options for in vitro-in vivo extrapolation (IVIVE) of mechanism-specific effects focused on fish species and also reviews the implications of confounding factors during the conduction of in vitro bioassays and their influence on the optimal choice of different dose metrics.

Cancer risk of petrochemical workers exposed to airborne PAHs in industrial Lanzhou City, China

This paper reports the connections between red blood cells abnormality risk of petrochemical workers and their exposure to airborne polycyclic aromatic hydrocarbons (PAHs). Urinary 1-hydroxypyrene (1-OHP), as the biomarker of PAHs exposure, was adopted to assess the exposure risk of the petrochemical workers to PAHs in Xigu, the west suburb of Lanzhou where petrochemical industries are located. Fifty-three workers, sub-grouped to 36 petrochemical workers and 17 office workers, participated in this investigation. Logistic regression model and spearman correlation analysis were performed to estimate the associations between PAHs exposure levels and red blood cells abnormality risk of petrochemical workers. Strong associations between some red cell indices (MCH, MCHC, RDW) and 1-OHP concentration were found. Results also show that the red blood cells abnormality risk increased with increasing PAHs exposure level. Compared with office workers, risk level of red blood cells abnormality in petrochemical workers was higher by 41.7 % (OR, 1.417; 95 % CI: 0.368-5.456) than that in office workers. This result was verified by the tissue-to-human blood partition coefficient for pyrene and 1-OHP. The quantitative assessments of the potential health risk through inhalation exposure to PAHs were conducted using the Incremental Lifetime Cancer Risk (ILCR) model. It was found the ILCR from inhalation exposure to PAHs for the petrochemical workers ranged from 10(-5) to 10(-4) with 95 % probability, indicating that petrochemical plant workers were under a high potential cancer risk level.

A PBPK model to estimate PCDD/F levels in adipose tissue: comparison with experimental values of residents near a hazardous waste incinerator

This study was aimed at determining the concentrations of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs) in 15 samples of adipose tissue from subjects who had been living in the vicinity of a hazardous waste incinerator (HWI). The results were compared with levels obtained in previous surveys carried out in 1998 (baseline study), 2002 and 2007. The current (2013) concentrations of PCDD/Fs in adipose tissue ranged from 2.8 to 46.3 pg WHO-TEQ/g fat (mean and median concentrations: 11.5 and 7.4 pg WHO-TEQ/g fat, respectively), being significantly lower (64%) than those observed in 1998. In contrast, no significant differences in the mean PCDD/F concentrations were noted in the period 2002-2013. The significant decrease of the PCDD/F content in fat, also noted in other biological monitors such as plasma and breast milk, is in agreement with the reduction in the dietary intake of PCDD/Fs found in the same area of study. Similarly to other investigations across Europe, an increase of PCDD/F levels in adipose tissue in relation to age was observed, while no significant differences were noted according to gender. A multicompartmental physiologically-based pharmacokinetic (PBPK) model was also applied to estimate the levels of PCDD/Fs in adipose tissue. When comparing the modeled and experimental concentrations of PCDD/Fs in that tissue, very similar values were obtained for the four surveys, which indicates this can be a reliable tool to predict the internal dose of PCDD/Fs.

Toxicokinetics of seven perfluoroalkyl sulfonic and carboxylic acids in pigs fed a contaminated diet

The transfer of a mixture of perfluoroalkyl acids (PFAAs) from contaminated feed into the edible tissues of 24 fattening pigs was investigated. Four perfluoroalkyl sulfonic (PFSAs) and three perfluoroalkyl carboxylic acids (PFCAs) were quantifiable in feed, plasma, edible tissues, and urine. As percentages of unexcreted PFAA, the substances accumulated in plasma (up to 51%), fat, and muscle tissues (collectively, meat 40-49%), liver (under 7%), and kidney (under 2%) for most substances. An exception was perfluorooctanesulfonic acid (PFOS), with lower affinity for plasma (23%) and higher for liver (35%). A toxicokinetic model is developed to quantify the absorption, distribution, and excretion of PFAAs and to calculate elimination half-lives. Perfluorohexanoic acid (PFHxA), a PFCA, had the shortest half-life at 4.1 days. PFSAs are eliminated more slowly (e.g., half-life of 634 days for PFOS). PFAAs in pigs exhibit longer elimination half-lives than in most organisms reported in the literature, but still shorter than in humans.

The use of PBPK models to inform human health risk assessment: case study on perchlorate and radioiodide human lifestage models

Physiologically-based pharmacokinetic (PBPK) models are often submitted to or selected by agencies, such as the U.S. Environmental Protection Agency (U.S. EPA) and Agency for Toxic Substances and Disease Registry, for consideration for application in human health risk assessment (HHRA). Recently, U.S. EPA evaluated the human PBPK models for perchlorate and radioiodide for their ability to estimate the relative sensitivity of perchlorate inhibition on thyroidal radioiodide uptake for various population groups and lifestages. The most well-defined mode of action of the environmental contaminant, perchlorate, is competitive inhibition of thyroidal iodide uptake by the sodium-iodide symporter (NIS). In this analysis, a six-step framework for PBPK model evaluation was followed, and with a few modifications, the models were determined to be suitable for use in HHRA to evaluate relative sensitivity among human lifestages. Relative sensitivity to perchlorate was determined by comparing the PBPK model predicted percent inhibition of thyroidal radioactive iodide uptake (RAIU) by perchlorate for different lifestages. A limited sensitivity analysis indicated that model parameters describing urinary excretion of perchlorate and iodide were particularly important in prediction of RAIU inhibition; therefore, a range of biologically plausible values available in the peer-reviewed literature was evaluated. Using the updated PBPK models, the greatest sensitivity to RAIU inhibition was predicted to be the near-term fetus (gestation week 40) compared to the average adult and other lifestages; however, when exposure factors were taken into account, newborns were found to be populations that need further evaluation and consideration in a risk assessment for perchlorate.

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

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

PBTK modelling platforms and parameter estimation tools to enable animal-free risk assessment: recommendations from a joint EPAA--EURL ECVAM ADME workshop

Information on toxicokinetics is critical for animal-free human risk assessment. Human external exposure must be translated into human tissue doses and compared with in vitro actual cell exposure associated to effects (in vitro-in vivo comparison). Data on absorption, distribution, metabolism and excretion in humans (ADME) could be generated using in vitro and QSAR tools. Physiologically-based toxicokinetic (PBTK) computer modelling could serve to integrate disparate in vitro and in silico findings. However, there are only few freely-available PBTK platforms currently available. And although some ADME parameters can be reasonably estimated in vitro or in silico, important gaps exist. Examples include unknown or limited applicability domains and lack of (high-throughput) tools to measure penetration of barriers, partitioning between blood and tissues and metabolic clearance. This paper is based on a joint EPAA--EURL ECVAM expert meeting. It provides a state-of-the-art overview of the availability of PBTK platforms as well as the in vitro and in silico methods to parameterise basic (Tier 1) PBTK models. Five high-priority issues are presented that provide the prerequisites for wider use of non-animal based PBTK modelling for animal-free chemical risk assessment.

Combining in vitro embryotoxicity data with physiologically based kinetic (PBK) modelling to define in vivo dose-response curves for developmental toxicity of phenol in rat and human

In vitro assays are often used for the hazard characterisation of compounds, but their application for quantitative risk assessment purposes is limited. This is because in vitro assays cannot provide a complete in vivo dose-response curve from which a point of departure (PoD) for risk assessment can be derived, like the no observed adverse effect level (NOAEL) or the 95 % lower confidence limit of the benchmark dose (BMDL). To overcome this constraint, the present study combined in vitro data with a physiologically based kinetic (PBK) model applying reverse dosimetry. To this end, embryotoxicity of phenol was evaluated in vitro using the embryonic stem cell test (EST), revealing a concentration-dependent inhibition of differentiation into beating cardiomyocytes. In addition, a PBK model was developed on the basis of in vitro and in silico data and data available from the literature only. After evaluating the PBK model performance, effective concentrations (ECx) obtained with the EST served as an input for in vivo plasma concentrations in the PBK model. Applying PBK-based reverse dosimetry provided in vivo external effective dose levels (EDx) from which an in vivo dose-response curve and a PoD for risk assessment were derived. The predicted PoD lies within the variation of the NOAELs obtained from in vivo developmental toxicity data from the literature. In conclusion, the present study showed that it was possible to accurately predict a PoD for the risk assessment of phenol using in vitro toxicity data combined with reverse PBK modelling.

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.

Case study illustrating the WHO IPCS guidance on characterization and application of physiologically based pharmacokinetic models in risk assessment

The World Health Organization (WHO) International Programme on Chemical Safety (IPCS) Guidance on Characterization and Application of Physiologically Based Pharmacokinetic Models in Risk Assessment (IPCS, 2010) describes key principles for risk assessors and model developers. In the WHO Guidance, a template for model documentation was developed and a case study included. Here the WHO Guidance, including the template, is summarized and an additional case study is presented to illustrate its application, based upon an existing risk assessment for 2-butoxyethanol (CAS NO. 111-76-2). The goal of the WHO Guidance and the current paper is to increase regulatory acceptance of complex biologically descriptive pharmacokinetic (or toxicokinetic) models, such as PBPK models, by facilitating communication and successful interaction between modelers and risk assessors.

A methodological frame for assessing benzene induced leukemia risk mitigation due to policy measures

The study relies on the development of a methodology for assessing the determinants that comprise the overall leukemia risk due to benzene exposure and how these are affected by outdoor and indoor air quality regulation. An integrated modeling environment was constructed comprising traffic emissions, dispersion models, human exposure models and a coupled internal dose/biology-based dose-response risk assessment model, in order to assess the benzene imposed leukemia risk, as much as the impact of traffic fleet renewal and smoking banning to these levels. Regarding traffic fleet renewal, several "what if" scenarios were tested. The detailed full-chain methodology was applied in a South-Eastern European urban setting in Greece and a limited version of the methodology in Helsinki. Non-smoking population runs an average risk equal to 4.1·10(-5) compared to 23.4·10(-5) for smokers. The estimated lifetime risk for the examined occupational groups was higher than the one estimated for the general public by 10-20%. Active smoking constitutes a dominant parameter for benzene-attributable leukemia risk, much stronger than any related activity, occupational or not. From the assessment of mitigation policies it was found that the associated leukemia risk in the optimum traffic fleet scenario could be reduced by up to 85% for non-smokers and up to 8% for smokers. On the contrary, smoking banning provided smaller gains for (7% for non-smokers, 1% for smokers), while for Helsinki, smoking policies were found to be more efficient than traffic fleet renewal. The methodology proposed above provides a general framework for assessing aggregated exposure and the consequent leukemia risk from benzene (incorporating mechanistic data), capturing exposure and internal dosimetry dynamics, translating changes in exposure determinants to actual changes in population risk, providing a valuable tool for risk management evaluation and consequently to policy support.

Application of an updated physiologically based pharmacokinetic model for chloroform to evaluate CYP2E1-mediated renal toxicity in rats and mice

Physiologically based pharmacokinetic (PBPK) models are tools for interpreting toxicological data and extrapolating observations across species and route of exposure. Chloroform (CHCl(3)) is a chemical for which there are PBPK models available in different species and multiple sites of toxicity. Because chloroform induces toxic effects in the liver and kidneys via production of reactive metabolites, proper characterization of metabolism in these tissues is essential for risk assessment. Although hepatic metabolism of chloroform is adequately described by these models, there is higher uncertainty for renal metabolism due to a lack of species-specific data and direct measurements of renal metabolism. Furthermore, models typically fail to account for regional differences in metabolic capacity within the kidney. Mischaracterization of renal metabolism may have a negligible effect on systemic chloroform levels, but it is anticipated to have a significant impact on the estimated site-specific production of reactive metabolites. In this article, rate parameters for chloroform metabolism in the kidney are revised for rats, mice, and humans. New in vitro data were collected in mice and humans for this purpose and are presented here. The revised PBPK model is used to interpret data of chloroform-induced kidney toxicity in rats and mice exposed via inhalation and drinking water. Benchmark dose (BMD) modeling is used to characterize the dose-response relationship of kidney toxicity markers as a function of PBPK-derived internal kidney dose. Applying the PBPK model, it was also possible to characterize the dose response for a recent data set of rats exposed via multiple routes simultaneously. Consistent BMD modeling results were observed regardless of species or route of exposure.