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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.

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Pyrrolizidine alkaloids (PAs) and their N-oxides (PA-N-oxides) are phytotoxins found in food, feed and the environment. Yet, limited data exist from which the relative potency of a PA-N-oxide relative to its corresponding PA (REPPANO to PA) can be defined. This study aims to investigate the influence of dose, fraction bioactivated and endpoint on the REPPANO to PA of a series of pyrrolizidine N-oxides using in vitro-in silico data and physiologically based kinetic (PBK) modeling. The first endpoint used to calculate the REPPANO to PA was the ratio of the area under the concentration-time curve of PA resulting from an oral dose of PA-N-oxide divided by that from an equimolar dose of PA (Method 1). The second endpoint was the ratio of the amount of pyrrole-protein adducts formed under these conditions (Method 2). REPPANO to PA values appeared to decrease with increasing dose, with the decrease for Method 2 already starting at lower dose level than for Method 1. At dose levels as low as estimated daily human intakes, REPPANO to PA values amounted to 0.92, 0.81, 0.78, and 0.68 for retrorsine N-oxide, seneciphylline N-oxide, riddelliine N-oxide and senecivernine N-oxide, respectively, and became independent of the dose or fraction bioactivated, because no GSH depletion, saturation of PA clearance or PA-N-oxide reduction occurs. Overall, the results demonstrate the strength of using PBK modeling in defining REPPANO to PA values, thereby substantiating the use of the same approach for other PA-N-oxides for which in vivo data are lacking.

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Current points of departure used to derive health-based guidance values for deoxynivalenol (DON) are based on studies in laboratory animals. Here, an animal-free testing approach was adopted in which a reverse dosimetry physiologically based kinetic (PBK) modeling is used to predict in vivo dose response curves for DON's effects on intestinal pro-inflammatory cytokine secretion and intestinal bile acid reabsorption in humans from concentration-effect relationships for DON in vitro. The calculated doses for inducing a 5% added effect above the background level (ED5) of DON for increasing IL-1ß secretion in intestinal tissue and for increasing the amounts in the colon lumen of glycochenodeoxycholic acid (GCDCA) were 246 and 36 µg/kg bw/day, respectively. These in vitro-in silico-derived ED5 values were compared to human dietary DON exposure levels, indicating that the risk of DON's effects on these end points occurring in various human populations cannot be excluded. This in vitro-in silico approach provides a novel testing strategy for hazard and risk assessment without using laboratory animals.

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Over 1,000 pyrrolizidine alkaloids (PAs) and their N-oxides (PA-N-oxides) occur in 3% of all flowering plants. PA-N-oxides are toxic when reduced to their parent PAs, which are bioactivated into pyrrole intermediates that generate protein- and DNA-adducts resulting in liver toxicity and carcinogenicity. Literature data for senecionine N-oxide in rats indicate that the relative potency (REP) value of this PA-N-oxide compared to its parent PA senecionine varies with the endpoint used. The first endpoint was the ratio between the area under the concentration-time curve (AUC) for senecionine upon dosing senecionine N-oxide or an equimolar dose of senecionine, while the second endpoint was the ratio between the amount for pyrrole-protein adducts formed under these conditions. This study aimed to investigate the mode of action underlying this endpoint dependent REP value for senecionine N-oxide with physiologically based kinetic (PBK) modeling. Results obtained reveal that limitation of 7-GS-DHP adduct formation due to GSH depletion, resulting in increased pyrrole-protein adduct formation, occurs more likely upon high dose oral PA administration than upon an equimolar dose of PA-N-oxide. At high dose levels, this results in a lower REP value when based on pyrrole-protein adduct levels than when based on PA concentrations. At low dose levels, the difference no longer exists. Altogether, the results of the study show how the REP value for senecionine N-oxide depends on dose and endpoint used, and that PBK modeling provides a way to characterize REP values for PA-N-oxides at realistic low dietary exposure levels, thus reducing the need for animal experiments.

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Physiologically-based kinetic (PBK) modeling is a valuable tool to understand the kinetics of nanoparticles (NPs) in vivo. However, estimating PBK parameters remains challenging and commonly requires animal studies. To develop predictive models to estimate PBK parameter values based on NP characteristics, a database containing PBK parameter values and corresponding NP characteristics is needed. As a first step toward this objective, this study estimates PBK parameters for gold NPs (AuNPs) and provides a comparison of two different NPs. Two animal experiments are conducted in which varying doses of AuNPs attached with polyethylene glycol (PEG) are administered intravenously to rats. The resulting Au concentrations are used to estimate PBK model parameters. The parameters are compared with PBK parameters previously estimated for poly(alkyl cyanoacrylate) NPs loaded with cabazitaxel and for LipImage 815. This study shows that a small initial database of PBK parameters collected for three NPs is already sufficient to formulate new hypotheses on NP characteristics that may be predictive of PBK parameter values. Further research should focus on developing a larger database and on developing quantitative models to predict PBK parameter values.

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In this study, the ability of a new in vitro/in silico quantitative in vitro-in vivo extrapolation (QIVIVE) methodology was assessed to predict the in vivo neurotoxicity of tetrodotoxin (TTX) in rodents. In vitro concentration-response data of TTX obtained in a multielectrode array assay with primary rat neonatal cortical cells and in an effect study with mouse neuro-2a cells were quantitatively extrapolated into in vivo dose-response data, using newly developed physiologically based kinetic (PBK) models for TTX in rats and mice. Incorporating a kidney compartment accounting for active renal excretion in the PBK models proved to be essential for its performance. To evaluate the predictions, QIVIVE-derived dose-response data were compared with in vivo data on neurotoxicity in rats and mice upon oral and parenteral dosing. The results revealed that for both rats and mice the predicted dose-response data matched the data from available in vivo studies well. It is concluded that PBK modeling-based reserve dosimetry of in vitro TTX effect data can adequately predict the in vivo neurotoxicity of TTX in rodents, providing a novel proof-of-principle for this methodology.

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The present study aimed at incorporating active renal excretion via the organic cation transporter 2 (OCT2) into a generic rat physiologically based kinetic (PBK) model using an in vitro human renal proximal tubular epithelial cell line (SA7K) and mepiquat chloride (MQ) as the model compound. The Vmax (10.5 pmol/min/mg protein) and Km (20.6 µM) of OCT2 transport of MQ were determined by concentration-dependent uptake in SA7K cells using doxepin as inhibitor. PBK model predictions incorporating these values in the PBK model were 6.7-8.4-fold different from the reported in vivo data on the blood concentration of MQ in rat. Applying an overall scaling factor that also corrects for potential differences in OCT2 activity in the SA7K cells and in vivo kidney cortex and species differences resulted in adequate predictions for in vivo kinetics of MQ in rat (2.3-3.2-fold). The results indicate that using SA7K cells to define PBK parameters for active renal OCT2 mediated excretion with adequate scaling enables incorporation of renal excretion via the OCT2 transporter in PBK modelling to predict in vivo kinetics of mepiquat in rat. This study demonstrates a proof-of-principle on how to include active renal excretion into generic PBK models.

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SCOPE: High-level exposure to aflatoxin B1 (AFB1) is known to cause acute liver damage and fatality in animals and humans. The intakes actually causing this acute toxicity have so far been estimated based on AFB1 levels in contaminated foods or biomarkers in serum. The aim of the present study is to predict the doses causing acute liver toxicity of AFB1 in rats and humans by an in vitro-in silico testing strategy. METHODS AND RESULTS: Physiologically based kinetic (PBK) models for AFB1 in rats and humans are developed. The models are used to translate in vitro concentration-response curves for cytotoxicity in primary rat and human hepatocytes to in vivo dose-response curves using reverse dosimetry. From these data, the dose levels at which toxicity would be expected are obtained and compared to toxic dose levels from available rat and human case studies on AFB1 toxicity. The results show that the in vitro-in silico testing strategy can predict dose levels causing acute toxicity of AFB1 in rats and human. CONCLUSIONS: Quantitative in vitro in vivo extrapolation (QIVIVE) using PBK modeling-based reverse dosimetry can predict AFB1 doses that cause acute liver toxicity in rats and human.

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SCOPE: To predict gut microbial metabolism of xenobiotics and the resulting plasma concentrations of metabolites formed, an in vitro-in silico-based testing strategy is developed using the isoflavone daidzein and its gut microbial metabolite S-equol as model compounds. METHODS AND RESULTS: Anaerobic rat fecal incubations are optimized and performed to derive the apparent maximum velocities (Vmax ) and Michaelis-Menten constants (Km ) for gut microbial conversion of daidzein to dihydrodaidzein, S-equol, and O-desmethylangolensin, which are input as parameters for a physiologically based kinetic (PBK) model. The inclusion of gut microbiota in the PBK model allows prediction of S-equol concentrations and slightly reduced predicted maximal daidzein concentrations from 2.19 to 2.16 µm. The resulting predicted concentrations of daidzein and S-equol are comparable to in vivo concentrations reported. CONCLUSION: The optimized in vitro approach to quantify kinetics for gut microbial conversions, and the newly developed PBK model for rats that includes gut microbial metabolism, provide a unique tool to predict the in vivo consequences of daidzein microbial metabolism for systemic exposure of the host to daidzein and its metabolite S-equol. The predictions reveal a dominant role for daidzein in ERα-mediated estrogenicity despite the higher estrogenic potency of its microbial metabolite S-equol.

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The present study assessed the potential of a generic physiologically based kinetic (PBK) model to convert in vitro data for estrogenicity to predict the in vivo uterotrophic response in rats for diethylstibestrol (DES), ethinylestradiol (EE2), genistein (GEN), coumestrol (COU), and methoxychlor (MXC). PBK models were developed using a generic approach and in vitro concentration-response data from the MCF-7 proliferation assay and the yeast estrogen screening assay were translated into in vivo dose-response data. Benchmark dose analysis was performed on the predicted data and available in vivo uterotrophic data to evaluate the model predictions. The results reveal that the developed generic PBK model adequate defines the in vivo kinetics of the estrogens. The predicted dose-response data of DES, EE2, GEN, COU, and MXC matched the reported in vivo uterus weight response in a qualitative way, whereas the quantitative comparison was somewhat hampered by the variability in both in vitro and in vivo data. From a safety perspective, the predictions based on the MCF-7 proliferation assay would best guarantee a safe point of departure for further risk assessment although it may be conservative. The current study indicates the feasibility of using a combination of in vitro toxicity data and a generic PBK model to predict the relative in vivo uterotrophic response for estrogenic chemicals.

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SCOPE: It is investigated whether at realistic dietary intake bixin and crocetin could induce peroxisome proliferator-activated receptor γ (PPARγ)-mediated gene expression in humans using a combined in vitro-in silico approach. METHODS AND RESULTS: Concentration-response curves obtained from in vitro PPARγ-reporter gene assays are converted to in vivo dose-response curves using physiologically based kinetic modeling-facilitated reverse dosimetry, from which the benchmark dose levels resulting in a 50% effect above background level (BMD50 ) are predicted and subsequently compared to dietary exposure levels. Bixin and crocetin activated PPARγ-mediated gene transcription in a concentration-dependent manner with similar potencies. Due to differences in kinetics, the predicted BMD50 values for in vivo PPARγ activation are about 30-fold different, amounting to 115 and 3505 mg kg bw-1 for crocetin and bixin, respectively. Human dietary and/or supplemental estimated daily intakes may reach these BMD50 values for crocetin but not for bixin, pointing at better possibilities for in vivo PPARγ activation by crocetin. CONCLUSION: Based on a combined in vitro-in silico approach, it is estimated whether at realistic dietary intakes plasma concentrations of bixin and crocetin are likely to reach concentrations that activate PPARγ-mediated gene expression, without the need for a human intervention study.

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Sensitivity analysis (SA) is an essential tool for modelers to understand the influence of model parameters on model outputs. It is also increasingly used in developing and assessing physiologically based kinetic (PBK) models. For instance, several studies have applied global SA to reduce the computational burden in the Bayesian Markov chain Monte Carlo-based calibration process PBK models. Although several SA algorithms and software packages are available, no comprehensive software package exists that allows users to seamlessly solve differential equations in a PBK model, conduct and visualize SA results, and discriminate between the non-influential model parameters that can be fixed and those that need calibration. Therefore, we developed an R package, named pksensi, to make global SA more accessible in PBK modeling. This package can investigate both uncertainty and sensitivity in PBK models, including those with multivariate model outputs. It also includes functions to check the convergence of the global SA results. Overall, pksensi improves the user experience of performing global SA and can create robust and reproducible results for decision making in PBK model calibration.

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Organophosphates have a long history of use as insecticides over the world. The aim of the present study was to investigate the interethnic differences in kinetics, biomarker formation, and in vivo red blood cell acetylcholinesterase inhibition of chlorpyrifos (CPF) in the Chinese and the Caucasian population. To this purpose, physiologically based kinetic models for CPF in both the Chinese and Caucasian population were developed, and used to study time- and dose-dependent interethnic variation in urinary biomarkers and to convert concentration-response curves for red blood cell acetylcholinesterase inhibition to in vivo dose-response curves in these 2 populations by reverse dosimetry. The results obtained revealed a marked interethnic difference in toxicokinetics of CPF, with lower urinary biomarker levels at similar dose levels and slower CPF bioactivation and faster chlorpyrifos-oxon detoxification in the Chinese compared with the Caucasian population, resulting in 5- to 6-fold higher CPF sensitivity of the Caucasian than the Chinese population. These differences might be related to variation in the frequency of single-nucleotide polymorphisms for the major biotransformation enzymes involved. To conclude, the interethnic variation in kinetics of CPF may affect both its biomarker-based exposure assessment and its toxicity and risk assessment and physiologically based kinetic modeling facilitates the characterization and quantification of these interethnic variations.

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Considering the rapid developments in food safety in the past decade in China, it is of importance to obtain insight into what extent safety and risk assessments of chemicals performed for the Caucasian population apply to the Chinese population. The aim of the present study was to determine physiologically based kinetic (PBK) modeling-based predictions for differences between Chinese and Caucasians in terms of metabolic bioactivation and detoxification of the food-borne genotoxic carcinogen estragole. The PBK models were defined based on kinetic constants for hepatic metabolism derived from in vitro incubations using liver fractions of the two ethnic groups, and used to evaluate the inter-ethnic differences in metabolic activation and detoxification of estragole. The models predicted that at realistic dietary intake levels, only 0.02% of the dose was converted to the ultimate carcinogenic metabolite 1'-sulfooxyestragole in Chinese subjects, whereas this amounted to 0.09% of the dose in Caucasian subjects. Detoxification of 1'-hydroxyestragole, mainly via conversion to 1'-oxoestragole, was similar within the two ethnic groups. The 4.5-fold variation in formation of the ultimate carcinogenic metabolite of estragole accompanied by similar rates of detoxification may indicate a lower risk of estragole for the Chinese population at similar levels of exposure. The study provides a proof of principle for how PBK modeling can identify differences in ethnic sensitivity and provide a more refined risk assessment for a specific ethnic group for a compound of concern.

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Toxicological hazard and risk assessment largely rely on animal testing. For economic and ethical reasons, the development and validation of reliable alternative methods for these animal studies, such as in vitro assays, are urgently needed. In vitro concentration-response curves, however, need to be translated into in vivo dose-response curves for risk assessment purposes. In the present study, we translated in vitro concentration-response data of the antifungal compound tebuconazole, obtained in the ES-D3 cell differentiation assay, into predicted in vivo dose-response data for developmental toxicity using physiologically based kinetic (PBK) modeling-facilitated reverse dosimetry. Using the predicted in vivo dose-response data BMD(L)10 values for developmental toxicity in rat were calculated and compared with NOAEL values for developmental toxicity data in rats as reported in the literature. The results show that the BMDL10 value from predicted dose-response data are a reasonable approximation of the NOAEL values (ca. 3-fold difference). It is concluded that PBK modeling-facilitated reverse dosimetry of in vitro toxicity data is a promising tool to predict in vivo dose-response curves and may have the potential to define a point of departure for deriving safe exposure limits in risk assessment.

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ß-Chloroprene (2-chloro-1,3-butadiene, CD) is used in the manufacture of polychloroprene rubber. Chronic inhalation studies have demonstrated that CD is carcinogenic in B6C3F1 mice and Fischer 344 rats. However, epidemiological studies do not provide compelling evidence for an increased risk of mortality from total cancers of the lung. Differences between the responses observed in animals and humans may be related to differences in toxicokinetics, the metabolism and detoxification of potentially active metabolites, as well as species differences in sensitivity. The purpose of this study was to develop and apply a novel method that combines the results from available physiologically based kinetic (PBK) models for chloroprene with a statistical maximum likelihood approach to test commonality of low-dose risk across species. This method allows for the combined evaluation of human and animal cancer study results to evaluate the difference between predicted risks using both external and internal dose metrics. The method applied to mouse and human CD data supports the hypothesis that a PBK-based metric reconciles the differences in mouse and human low-dose risk estimates and further suggests that, after PBK metric exposure adjustment, humans are equally or less sensitive than mice to low levels of CD exposure.

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