Physiologically Based Kinetic Research Articles

Modeling chemical bioaccumulation in snakes, part 1: Model development

Environmental chemical emission influences ecological health to some extent. Predators (e.g., snakes) could bioaccumulate chemicals along the food chain, which also leaves potential health implications on their reproduction. For the difficulty of collecting related biomatrices for exposure assessment, part 1 of this study proposed a modeling method relying on physiologically based kinetic (PBK) theory to estimate snake chronic exposure to environmental chemicals. In the steady state, the biotransfer factors of chemicals produced by the PBK model can indicate a snake’s chronic internal exposure to environmental chemicals and their potential for bioaccumulation at this level of the food web. Specifically, 3074 organic chemicals were compelled into the dataset for PBK modeling (part 2 of the study). The modeling framework covered the physiological process of the skin to consider shed snakeskin as a potential biomarker for future study. The proposed modeling approach was integrated into a spreadsheet, enabling the modification of input values to simulate outcomes for a wide range of chemical and snake species. The proposed model can help assess the ecological risks of environmental chemicals and quantify their behavior in the food web.

Modeling chemical bioaccumulation in snakes, part 2: Model testing and high-throughput simulation

In part 2 of the physiologically based kinetic (PBK) model for snakes, using default and generic input values, the simulation outcomes showed that chemicals with moderate lipophilicity, low volatility, and low biotransformability exhibited a high potential for biotransfer in the snake’s skin. Furthermore, the inclusion or exclusion of the skin compartment in the PBK model had a substantial impact on the fate, transport, and distribution of these chemicals within the snake’s body. In comparison to the elimination routes via blood transport and volatilization, the shedding of skin and growth processes did not contribute substantially to the overall kinetics of chemical elimination from the skin for most chemicals. The proposed model has demonstrated a consistent alignment with the observed patterns of chemical distribution, as supported by certain experimental data. Furthermore, it has the potential to provide an explanation for and enhance the understanding of the discrepancies found in other field observations. The modeling exercise clearly illustrated the significant role of the skin compartment in the biotransfer of chemicals within the snake’s body and highlighted the importance of including the snake’s physiological features into the PBK model. To further enhance the model’s performance and accuracy, additional research focused on obtaining specific physiological data pertaining to snakes would be beneficial.

Development of a Generic Physiologically Based Kinetic Model for the Prediction of Internal Exposure to Organophosphate Pesticides.

Since their introduction into agriculture, the toxicity of organophosphate (OP) pesticides has been widely studied in animal models. However, next generation risk assessment (NGRA) intends to maximize the use of novel approach methodologies based on in vitro and in silico methods. Therefore, this study describes the development and evaluation of a generic physiologically based kinetic (PBK) model for acute exposure to OP pesticides in rats and humans using quantitative structure property relationships and data from published in vitro studies. The models were evaluated using in vivo studies from the literature for chlorpyrifos, diazinon, fenitrothion, methyl-parathion, ethyl-parathion, dimethoate, chlorfenvinphos, and profenofos. Evaluation was performed by comparing simulated and in vivo observed time profiles for blood, plasma, or urinary concentrations and other toxicokinetic parameters. Of simulated concentration-time profiles, 87 and 91% were within a 5-fold difference from observed toxicokinetic data from rat and human studies, respectively. Only for dimethyl-organophosphates further refinement of the model is required. It is concluded that the developed generic PBK model provides a new tool to assess species differences in rat and human kinetics of OP pesticides. This approach provides a means to perform NGRA for these compounds and could also be adopted for other classes of compounds.

Use of physiologically based kinetic modeling to predict neurotoxicity and genotoxicity of methylglyoxal in humans

This study aimed to evaluate human neurotoxicity and genotoxicity risks from dietary and endogenous methylglyoxal (MGO), utilizing physiologically based kinetic (PBK) modeling-facilitated reverse dosimetry as a new approach methodology (NAM) to extrapolate in vitro toxicity data to in vivo dose-response predictions. A human PBK model was defined based on a newly developed and evaluated mouse model enabling the translation of in vitro toxicity data for MGO from human stem cell-derived neurons and WM-266-4 melanoma cells into quantitative human in vivo toxicity data and subsequent risk assessment by the margin of exposure (MOE) approach. The results show that the MOEs resulting from daily dietary intake did not raise a concern for endpoints for neurotoxicity including mitochondrial function, cytotoxicity, and apoptosis, while those for DNA adduct formation could not exclude a concern over genotoxicity. Endogenous MGO formation, especially under diabetic conditions, resulted in MOEs that raised concern not only for genotoxicity but also for some of the neurotoxicity endpoints evaluated. Thus, the results also point to the importance of taking the endogenous levels into account in the risk assessment of MGO.

Species specific kinetics of imidacloprid and carbendazim in mouse and rat and consequences for biomonitoring

This study aimed to develop physiologically based kinetic (PBK) models to predict the blood concentrations of imidacloprid and carbendazim and their primary metabolites 5-hydroxy-imidacloprid and 2-aminobenzimidazole after single or repeated oral exposure in mouse (Mus musculus), and compare this to corresponding kinetic data in rat (Rattus norvegicus). PBK model constants for conversion of imidacloprid and carbendazim and formation and clearance of their selected primary metabolites were quantified by in vitro mouse liver microsomal and S9 incubations. The performance of the newly developed PBK models was evaluated, based on a comparison to available literature data, showing that the models performed well. Predictions made were also compared to results from PBK model simulations for rats reported previously to obtain insight in species dependent differences in kinetics of these pesticides. The results thus obtained revealed substantial species differences in kinetics for these two pesticides between mouse and rat, especially for imidacloprid and to a lesser extent for carbendazim. Repeated dose PBK model simulations revealed that the models can facilitate estimation of external exposure levels under wildlife conditions based on internal blood concentrations of the parent compound. The rate of conversion and liver volume fraction were shown to influence the accuracy of these predictions with lower values providing less variable outcomes. It is concluded that PBK modeling provides a new approach methodology of use for wildlife biomonitoring studies and that results of the present study facilitate benchmarking of the species and compounds for which kinetics enable this with sufficient accuracy.

OS02-02 Establishing scientific confidence in physiologically based kinetic (PBK) models for quantitative in vitro-to-in vivo extrapolations (QIVIVE) in the absence of in vivo kinetic data

OS02-02 Establishing scientific confidence in physiologically based kinetic (PBK) models for quantitative in vitro-to-in vivo extrapolations (QIVIVE) in the absence of in vivo kinetic data

S20-01 Principles of quantitative In Vitro to in vivo extrapolation (QIVIVE) applying physiologically based kinetic (PBK) modelling for DNT IVB

S20-01 Principles of quantitative In Vitro to in vivo extrapolation (QIVIVE) applying physiologically based kinetic (PBK) modelling for DNT IVB

P05-28 Developing an open-source harmonized Physiologically Based Kinetic (PBK) model for 4 PFAS (PFOS, PFOA, PFNA, and PFHxS) to assess the toxicological profile of forever chemicals

P05-28 Developing an open-source harmonized Physiologically Based Kinetic (PBK) model for 4 PFAS (PFOS, PFOA, PFNA, and PFHxS) to assess the toxicological profile of forever chemicals

P03-09 Predictive performance of physiologically based kinetic (PBK) models based on in-silico/in vitro-in vivo extrapolation (IS/IVIVE)

P03-09 Predictive performance of physiologically based kinetic (PBK) models based on in-silico/in vitro-in vivo extrapolation (IS/IVIVE)

Advancing ecotoxicological studies: Utilizing new approach methodologies to enable cross-species extrapolation and reduce avian testing

Ecological risk assessments of agrochemicals have traditionally depended on in vivo guideline tests using northern bobwhite and mallard to provide relevant endpoints for avian species. However, these studies have limitations, including animal welfare concerns, the time and cost involved, limited potential for extrapolation to more realistic exposure conditions, and the lack of mechanistic understanding. The proof-of-concept work presented a case study for thiamethoxam in three avian species, demonstrating the potential of physiologically based kinetic (PBK) modeling to enable dosimetry extrapolations that inform hazard characterization in risk assessment, and reduce the use of avian testing. The model structure for northern bobwhite and mallard contained ten compartments, while an additional ovulation model was included for chicken in the physiological state of egg-laying. The model was first parameterized and evaluated for chicken and northern bobwhite using in vitro kinetic measurements and in vivo toxicokinetic (TK) data. The chicken model was then extrapolated to mallard based on allometric scaling. The models were then used to map the TK profiles across species by simulating internal dose metrics in different avian toxicology studies. These metrics, including peak blood concentrations (Cmax) and area under the curve (AUC) for blood concentration, were determined for acute, subacute, or chronic toxicity endpoints for mallard and northern bobwhite, enabling a quantitative cross-species and cross-route comparison of dosimetry. The results suggested that the chronic toxicological response of birds exposed to thiamethoxam is highly dependent on internal exposure, while mallard appeared to be more dynamically sensitive to thiamethoxam on an acute oral exposure basis. The case study increases the confidence in using new approach methodologies (NAMs) for interpreting avian toxicity studies and facilitating in vitro-in silico-based ecological risk assessments of agrochemicals.

Imazalil and prochloraz toxicokinetics in fish probed by a physiologically based kinetic (PBK) model.

Azole fungicides are highly suspected endocrine disruptors (EDs) and are frequently detected in surface water. Among them, there are prochloraz (PCZ), a commonly used moleculefor ED studies, and imazalil (IMZ), a highly suspected ED. Little is known about their toxicokinetic (TK) behavior in fish. Hence, research suggested that an improved risk assessment could be achieved by gaining insight into their TK behavior. The aim of this study is to understand and model the TK of both substances in different fish species, irrespective of the scheme of exposure. TK data from the literature were retrieved including different modes of exposure (per os and waterborne). In addition, two experiments on zebrafish exposed to either IMZ or PCZ were performed to address the lack of in vivo TK data. A physiologically based kinetic (PBK) model applied to IMZ and PCZ was developed, capable of modeling different exposure scenarios. The parameters of the PBK model were simultaneously calibrated on datasets reporting internal concentration in several organs in three fish species (original and literature datasets) by Bayesian methods (Monte Carlo Markov Chain). Model predictions were then compared to other experimental data (i.e., excluded from the calibration step) to assess the predictive performance of the model. The results strongly suggest that PCZ and IMZ are actively transported across the gills, resulting in a small fraction being effectively absorbed by the fish. The model's results also confirm that both molecules are extensively metabolized by the liver into mainly glucuronate conjugates. Overall, the model performances were satisfying, predicting internal concentrations in several key organs. On average, 90% of experimental data were predicted within a two-fold range. The PBK model allows the understanding of IMZ and PCZ kinetics profiles by accurately predicting internal concentrations in three different fish species regardless of the exposure scenario. This enables a proper understanding of the mechanism of action of EDs at the molecular initiating event (MIE) by predicting bioaccumulation in target organs, thus linking this MIE to a possible adverse outcome.

Physiologically based Kinetic Modeling-Facilitated Quantitative In Vitro to In Vivo Extrapolation to Predict the Effects of Aloe-Emodin in Rats and Humans.

Aloe-emodin, a natural hydroxyanthraquinone, exerts both adverse and protective effects. This study aimed at investigating these potential effects of aloe-emodin in humans upon the use of food supplements and herbal medicines using a physiologically based kinetic (PBK) modeling-facilitated quantitative in vitro to in vivo extrapolation (QIVIVE) approach. For this, PBK models in rats and humans were established for aloe-emodin including its active metabolite rhein and used to convert in vitro data on hepatotoxicity, nephrotoxicity, reactive oxidative species (ROS) generation, and Nrf2 induction to corresponding in vivo dose-response curves, from which points of departure (PODs) were derived by BMD analysis. The derived PODs were subsequently compared to the estimated daily intakes (EDIs) resulting from the use of food supplements or herbal medicines. It is concluded that the dose levels of aloe-emodin from food supplements or herbal medicines are unlikely to induce toxicity, ROS generation, or Nrf2 activation in liver and kidney.

Advancing PFAS risk assessment: Integrative approaches using agent-based modelling and physiologically-based kinetic for environmental and health safety

Per- and polyfluoroalkyl substances (PFAS), ubiquitous in a myriad of consumer and industrial products, and depending on the doses of exposure represent a hazard to both environmental and public health, owing to their persistent, mobile, and bio accumulative properties. These substances exhibit long half-lives in humans and can induce potential immunotoxic effects at low exposure levels, sparking growing concerns. While the European Food Safety Authority (EFSA) has assessed the risk to human health related to the presence of PFAS in food, in which a reduced antibody response to vaccination in infants was considered as the most critical human health effect, a comprehensive grasp of the molecular mechanisms spearheading PFAS-induced immunotoxicity is yet to be attained. Leveraging modern computational tools, including the Agent-Based Model (ABM) Universal Immune System Simulator (UISS) and Physiologically Based Kinetic (PBK) models, a deeper insight into the complex mechanisms of PFAS was sought. The adapted UISS serves as a vital tool in chemical risk assessments, simulating the host immune system's reactions to diverse stimuli and monitoring biological entities within specific adverse health contexts. In tandem, PBK models unravelling PFAS' biokinetics within the body i.e. absorption, distribution, metabolism, and elimination, facilitating the development of time-concentration profiles from birth to 75 years at varied dosage levels, thereby enhancing UISS-TOX's predictive abilities. The integrated use of these computational frameworks shows promises in leveraging new scientific evidence to support risk assessments of PFAS. This innovative approach not only allowed to bridge existing data gaps but also unveiled complex mechanisms and the identification of unanticipated dynamics, potentially guiding more informed risk assessments, regulatory decisions, and associated risk mitigations measures for the future.

PBK models to predict internal and external dose levels following oral exposure of rats to imidacloprid and carbendazim

Monitoring oral exposure to pesticides in wildlife is crucial for assessing environmental risks and preventing adverse effects on non-target species. Traditionally, this requires invasive tissue sampling, raising ethical, regulatory, and economic concerns. To address this gap, our study aims to develop a method for assessing external oral dose levels in rats using physiologically-based kinetic (PBK) modeling based on blood concentration levels of two pesticides, imidacloprid and carbendazim, and one of their primary metabolites. We utilized in vitro metabolic kinetic data from hepatic microsomal and S9 incubations to inform our models. These models were then evaluated by comparing their predictions with existing in vivo experimental data from the literature. Our results demonstrate that the models provide accurate predictions, presenting a novel in vitro and in silico approach for environmental exposure and risk assessment of pesticides. This methodology has the potential for application in wildlife species, advancing the frontier of knowledge in non-invasive pesticide exposure assessment.

Application of a generic PBK model for beef cattle: Tissue/fluid correlations of paracetamol and NSAIDs

Nonsteroidal Anti-Inflammatory Drugs (NSAIDs) and paracetamol can be administered off-label to cattle. Since the use of these veterinary medicines in cattle may pose a public health risk after meat consumption, it is important to translate measured concentrations in urine and tissues into concentrations in meat for human consumption. A generic physiologically-based kinetic (PBK) model for cattle can enable this translation. In this work, a beef cattle PBK model was applied to calculate the relationships between concentrations in different bovine tissues and those were compared to measured concentrations in different matrices. Sixty-seven kidney samples, the corresponding urine and meat samples, and available 19 serum samples were analysed. Overall, 70% of the PBK model predictions are within a 2-fold factor and relationships for kidney/meat, urine/meat, and plasma/meat ratios were established. The conversions of measured kidney concentrations into meat concentrations were mostly within a factor two, while those based on plasma and urine were underpredicted. Based on these ratios, plasma and urine could be used as an appropriate surrogate matrix for a fast, simple in vivo sample screening test under field conditions, such as in local farms and slaughterhouses, to predict a maximum residue level exceedance in meat, reducing the number of test samples.

Next generation risk assessment for occupational chemical safety – A real world example with sodium-2-hydroxyethane sulfonate

Next Generation Risk Assessment (NGRA) is an exposure-led approach to safety assessment that uses New Approach Methodologies (NAMs). Application of NGRA has been largely restricted to assessments of consumer use of cosmetics and is not currently implemented in occupational safety assessments, e.g. under EU REACH. By contrast, a large proportion of regulatory worker safety assessments are underpinned by toxicological studies using experimental animals. Consequently, occupational safety assessment represents an area that would benefit from increasing application of NGRA to safety decision making. Here, a workflow for conducting NGRA under an occupational safety context was developed, which is illustrated with a case study chemical; sodium 2-hydroxyethane sulphonate (sodium isethionate or SI). Exposures were estimated using a standard occupational exposure model following a comprehensive life cycle assessment of SI and considering factory-specific data. Outputs of this model were then used to estimate internal exposures using a Physiologically Based Kinetic (PBK) model, which was constructed with SI specific Absorption, Distribution, Metabolism and Excretion (ADME) data. PBK modelling indicated a worst-case plasma maximum concentration (Cmax) of 0.8 μM across the SI life cycle. SI bioactivity was assessed in a battery of NAMs relevant to systemic, reproductive, and developmental toxicity; a cell stress panel, high throughput transcriptomics in three cell lines (HepG2, HepaRG and MCF-7 cells), pharmacological profiling and specific assays relating to developmental toxicity (Reprotracker and devTOX quickPredict). Points of Departure (PoDs) for SI ranged from 104 to 5044 µM. Cmax values obtained from PBK modelling of occupational exposures to SI were compared with PoDs from the bioactivity assays to derive Bioactivity Exposure Ratios (BERs) which demonstrated the safety for workers exposed to SI under current levels of factory specific risk management. In summary, the tiered and iterative workflow developed here represents an opportunity for integrating non animal approaches for a large subset of substances for which systemic worker safety assessment is required. Such an approach could be followed to ensure that animal testing is only conducted as a “last resort” e.g. under EU REACH.

Physiologically based kinetic (PBK) modeling of propiconazole using a machine learning-enhanced read-across approach for interspecies extrapolation

A significant challenge in the traditional human health risk assessment of agrochemicals is the uncertainty in quantifying the interspecies differences between animal models and humans. To work toward a more accurate and animal-free risk determination, new approaches such as physiologically based kinetic (PBK) modeling have been used to perform dosimetry extrapolation from animals to humans. However, the regulatory use and acceptance of PBK modeling is limited for chemicals that lack in vivo animal pharmacokinetic (PK) data, given the inability to evaluate models. To address these challenges, this study developed PBK models in the absence of in vivo PK data for the fungicide propiconazole, an activator of constitutive androstane receptor (CAR)/pregnane X receptor (PXR). A fit-for-purpose read-across approach was integrated with hierarchical clustering − an unsupervised machine learning algorithm, to bridge the knowledge gap. The integration allowed the incorporation of a broad spectrum of attributes for analog consideration, and enabled the analog selection in a simple, reproducible, and objective manner. The applicability was evaluated and demonstrated using penconazole (source) and three pseudo-unknown target chemicals (epoxiconazole, tebuconazole and triadimefon). Applying this machine learning-enhanced read-across approach, difenoconazole was selected as the most appropriate analog for propiconazole. A mouse PBK model was developed and evaluated for difenoconazole (source), with the mode of action of CAR/PXR activation incorporated to simulate the in vivo autoinduction of metabolism. The difenoconazole mouse model then served as a template for constructing the propiconazole mouse model. A parallelogram approach was subsequently applied to develop the propiconazole rat and human models, enabling a quantitative assessment of interspecies differences in dosimetry. This integrated approach represents a substantial advancement toward refining risk assessment of propiconazole within the framework of animal alternative safety assessment strategies.

From hazard to risk prioritization: a case study to predict drug-induced cholestasis using physiologically based kinetic modeling

Cholestasis is characterized by hepatic accumulation of bile acids. Clinical manifestation of cholestasis only occurs in a small proportion of exposed individuals. The present study aims to develop a new approach methodology (NAM) to predict drug-induced cholestasis as a result of drug-induced hepatic bile acid efflux inhibition and the resulting bile acid accumulation. To this end, hepatic concentrations of a panel of drugs were predicted by a generic physiologically based kinetic (PBK) drug model. Their effects on hepatic bile acid efflux were incorporated in a PBK model for bile acids. The predicted bile acid accumulation was used as a measure for a drug’s cholestatic potency. The selected drugs were known to inhibit hepatic bile acid efflux in an assay with primary suspension-cultured hepatocytes and classified as common, rare, or no for cholestasis incidence. Common cholestasis drugs included were atorvastatin, chlorpromazine, cyclosporine, glimepiride, ketoconazole, and ritonavir. The cholestasis incidence of the drugs appeared not to be adequately predicted by their Ki for inhibition of hepatic bile acid efflux, but rather by the AUC of the PBK model predicted internal hepatic drug concentration at therapeutic dose level above this Ki. People with slower drug clearance, a larger bile acid pool, reduced bile salt export pump (BSEP) abundance, or given higher than therapeutic dose levels were predicted to be at higher risk to develop drug-induced cholestasis. The results provide a proof-of-principle of using a PBK-based NAM for cholestasis risk prioritization as a result of transporter inhibition and identification of individual risk factors.

Systematic evaluation of high-throughput PBK modelling strategies for the prediction of intravenous and oral pharmacokinetics in humans

Physiologically based kinetic (PBK) modelling offers a mechanistic basis for predicting the pharmaco-/toxicokinetics of compounds and thereby provides critical information for integrating toxicity and exposure data to replace animal testing with in vitro or in silico methods. However, traditional PBK modelling depends on animal and human data, which limits its usefulness for non-animal methods. To address this limitation, high-throughput PBK modelling aims to rely exclusively on in vitro and in silico data for model generation. Here, we evaluate a variety of in silico tools and different strategies to parameterise PBK models with input values from various sources in a high-throughput manner. We gather 2000 + publicly available human in vivo concentration–time profiles of 200 + compounds (IV and oral administration), as well as in silico, in vitro and in vivo determined compound-specific parameters required for the PBK modelling of these compounds. Then, we systematically evaluate all possible PBK model parametrisation strategies in PK-Sim and quantify their prediction accuracy against the collected in vivo concentration–time profiles. Our results show that even simple, generic high-throughput PBK modelling can provide accurate predictions of the pharmacokinetics of most compounds (87% of Cmax and 84% of AUC within tenfold). Nevertheless, we also observe major differences in prediction accuracies between the different parameterisation strategies, as well as between different compounds. Finally, we outline a strategy for high-throughput PBK modelling that relies exclusively on freely available tools. Our findings contribute to a more robust understanding of the reliability of high-throughput PBK modelling, which is essential to establish the confidence necessary for its utilisation in Next-Generation Risk Assessment.

Physiologically based kinetic (PBK) modeling as a new approach methodology (NAM) for predicting systemic levels of gut microbial metabolites

There is a clear need to develop new approach methodologies (NAMs) that combine in vitro and in silico testing to reduce and replace animal use in chemical risk assessment. Physiologically based kinetic (PBK) models are gaining popularity as NAMs in toxico/pharmacokinetics, but their coverage of complex metabolic pathways occurring in the gut are incomplete. Chemical modification of xenobiotics by the gut microbiome plays a critical role in the host response, for example, by prolonging exposure to harmful metabolites, but there is not a comprehensive approach to quantify this impact on human health. There are examples of PBK models that have implemented gut microbial biotransformation of xenobiotics with the gut as a dedicated metabolic compartment. However, the integration of microbial metabolism and parameterization of PBK models is not standardized and has only been applied to a few chemical transformations. A challenge in this area is the measurement of microbial metabolic kinetics, for which different fermentation approaches are used. Without a standardized method to measure gut microbial metabolism ex vivo/in vitro, the kinetic constants obtained will lead to conflicting conclusions drawn from model predictions. Nevertheless, there are specific cases where PBK models accurately predict systemic concentrations of gut microbial metabolites, offering potential solutions to the challenges outlined above. This review focuses on models that integrate gut microbial bioconversions and use ex vivo/in vitro methods to quantify metabolic constants that accurately represent in vivo conditions.