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

Toxicity of soil leaching liquor from coking plant in developmental zebrafish embryos/larvae model

The coking industry in China is the largest coke supplier in the world. Contaminated soil in industrial areas poses a serious threat to human and ecosystems. Most of the studies investigated the toxicity of soil from coking plant on soil microorganisms, while the toxic effects of soil leaching liquor on aquatics are limited. In this study, the composition of soil leaching liquor from a coking plant in Taiyuan (TY) was analyzed, and the developmental toxicity on zebrafish was evaluated. The results showed that a total of 91 polycyclic aromatic hydrocarbons were detected in the leaching liquor, followed by phenols and benzene series. The leaching liquor induced developmental impairment in zebrafish larvae, including delayed incubation, deficits in locomotor behavior, vascular and cardiac dysplasia, and impaired neurodevelopment. The results of metabolomics analysis showed that TY soil leaching liquor induced significant metabolic profile disturbances in zebrafish embryos/larvae. The developmental toxicity of the leaching liquor metabolic disorders may be associated with the leaching liquor-induced abnormalities in zebrafish embryonic development. Metabolic pathways were identified by arginine and proline metabolism, phosphotransferase system, starch and sucrose metabolism, steroid biosynthesis, beta-alanine metabolism, and nucleotide metabolism pathways.

A novel method to derive a human safety limit for PFOA by gene expression profiling and modelling

Perfluorooctanoic acid (PFOA) is a persistent environmental contaminant that can accumulate in the human body due to its long half-life. This substance has been associated with liver, pancreatic, testicular and breast cancers, liver steatosis and endocrine disruption. PFOA is a member of a large group of substances also known as "forever chemicals" and the vast majority of substances of this group lack toxicological data that would enable their effective risk assessment in terms of human health hazards. This study aimed to derive a health-based guidance value for PFOA intake (ng/kg BW/day) from in vitro transcriptomics data. To this end, we developed an in silico workflow comprising five components: (i) sourcing in vitro hepatic transcriptomics concentration-response data; (ii) deriving molecular points of departure using BMDExpress3 and performing pathway analysis using gene set enrichment analysis (GSEA) to identify the most sensitive molecular pathways to PFOA exposure; (iii) estimating freely-dissolved PFOA concentrations in vitro using a mass balance model; (iv) estimating in vivo doses by reverse dosimetry using a PBK model for PFOA as part of a quantitative in vitro to in vivo extrapolation (QIVIVE) algorithm; and (v) calculating a tolerable daily intake (TDI) for PFOA. Fourteen percent of interrogated genes exhibited in vitro concentration-response relationships. GSEA pathway enrichment analysis revealed that "fatty acid metabolism" was the most sensitive pathway to PFOA exposure. In vitro free PFOA concentrations were calculated to be 2.9% of the nominal applied concentrations, and these free concentrations were input into the QIVIVE workflow. Exposure doses for a virtual population of 3,000 individuals were estimated, from which a TDI of 0.15 ng/kg BW/day for PFOA was calculated using the benchmark dose modelling software, PROAST. This TDI is comparable to previously published values of 1.16, 0.69, and 0.86 ng/kg BW/day by the European Food Safety Authority. In conclusion, this study demonstrates the combined utility of an "omics"-derived molecular point of departure and in silico QIVIVE workflow for setting health-based guidance values in anticipation of the acceptance of in vitro concentration-response molecular measurements in chemical risk assessment.

Predicting the in vivo developmental toxicity of fenarimol from in vitro toxicity data using PBTK modelling-facilitated reverse dosimetry approach

In vitro methods are widely used in modern toxicological testing; however, the data cannot be directly employed for risk assessment. In vivo toxicity of chemicals can be predicted from in vitro data using physiologically based toxicokinetic (PBTK) modelling-facilitated reverse dosimetry (PBTK-RD). In this study, a minimal-PBTK model was constructed to predict the in-vivo kinetic profile of fenarimol (FNL) in rats and humans. The model was verified by comparing the observed and predicted pharmacokinetics of FNL for rats (calibrator) and further applied to humans. Using the PBTK-RD approach, the reported in vitro developmental toxicity data for FNL was translated to in vivo dose-response data to predict the assay equivalent oral dose in rats and humans. The predicted assay equivalent rat oral dose (36.46 mg/kg) was comparable to the literature reported in vivo BMD10 value (22.8 mg/kg). The model was also employed to derive the chemical-specific adjustment factor (CSAF) for interspecies toxicokinetics variability of FNL. Further, Monte Carlo simulations were performed to predict the population variability in the plasma concentration of FNL and to derive CSAF for intersubject human kinetic differences. The comparison of CSAF values for interspecies and intersubject toxicokinetic variability with their respective default values revealed that the applied uncertainty factors were adequately protective.

New Approach Methodologies for the Endocrine Activity Toolbox: Environmental Assessment for Fish and Amphibians

Multiple in vivo test guidelines focusing on the estrogen, androgen, thyroid, and steroidogenesis pathways have been developed and validated for mammals, amphibians, or fish. However, these tests are resource-intensive and often use a large number of laboratory animals. Developing alternatives for in vivo tests is consistent with the replacement, reduction, and refinement principles for animal welfare considerations, which are supported by increasing mandates to move toward an "animal-free" testing paradigm worldwide. New approach methodologies (NAMs) hold great promise to identify molecular, cellular, and tissue changes that can be used to predict effects reliably and more efficiently at the individual level (and potentially on populations) while reducing the number of animals used in (eco)toxicological testing for endocrine disruption. In a collaborative effort, experts from government, academia, and industry met in 2020 to discuss the current challenges of testing for endocrine activity assessment for fish and amphibians. Continuing this cross-sector initiative, our review focuses on the current state of the science regarding the use of NAMs to identify chemical-induced endocrine effects. The present study highlights the challenges of using NAMs for safety assessment and what work is needed to reduce their uncertainties and increase their acceptance in regulatory processes. We have reviewed the current NAMs available for endocrine activity assessment including in silico, in vitro, and eleutheroembryo models. New approach methodologies can be integrated as part of a weight-of-evidence approach for hazard or risk assessment using the adverse outcome pathway framework. The development and utilization of NAMs not only allows for replacement, reduction, and refinement of animal testing but can also provide robust and fit-for-purpose methods to identify chemicals acting via endocrine mechanisms. Environ Toxicol Chem 2023;42:757-777. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Utility of a Systematic Approach to Selecting Candidate Prodrugs: A case Study using Candesartan Ester Analogues

Development of prodrugs is a useful strategy to overcome some disadvantages of candidate drugs. Recently, we established a systematic approach to selecting appropriate prodrugs, and validated the utility of this approach using oseltamivir analogues. In this study, the utility of the approach was further examined using candesartan cilexetil and 20 kinds of its analogues having various types of side chain as model compounds. Log D values of analogues (2.5 to 4.7) were higher than that of candesartan (1.0), their active metabolite, and the results were reasonable for the purpose of improving permeability of candesartan. The analogues tended to be more soluble in artificial intestinal fluids than in artificial gastric fluid, owing to their acidic physicochemical characteristics. Their membrane permeabilities were not correlated with log D values, which can be attributed to the metabolism in Caco-2 cells used in this system. In human hepatocytes and enterocytes, 11 out of the 20 analogues were immediately hydrolyzed to candesartan, and species differences were observed in the hydrolysis efficiency. This study confirmed the utility of the systematic approach for selection of appropriate prodrugs that could be proceeded to in vivo pharmacokinetics study, with selection of suitable experimental animals.

Advancing New Approach Methodologies (NAMs) for Tobacco Harm Reduction: Synopsis from the 2021 CORESTA SSPT-NAMs Symposium

New approach methodologies (NAMs) are emerging chemical safety assessment tools consisting of in vitro and in silico (computational) methodologies intended to reduce, refine, or replace (3R) various in vivo animal testing methods traditionally used for risk assessment. Significant progress has been made toward the adoption of NAMs for human health and environmental toxicity assessment. However, additional efforts are needed to expand their development and their use in regulatory decision making. A virtual symposium was held during the 2021 Cooperation Centre for Scientific Research Relative to Tobacco (CORESTA) Smoke Science and Product Technology (SSPT) conference (titled "Advancing New Alternative Methods for Tobacco Harm Reduction"), with the goals of introducing the concepts and potential application of NAMs in the evaluation of potentially reduced-risk (PRR) tobacco products. At the symposium, experts from regulatory agencies, research organizations, and NGOs shared insights on the status of available tools, strengths, limitations, and opportunities in the application of NAMs using case examples from safety assessments of chemicals and tobacco products. Following seven presentations providing background and application of NAMs, a discussion was held where the presenters and audience discussed the outlook for extending the NAMs toxicological applications for tobacco products. The symposium, endorsed by the CORESTA In Vitro Tox Subgroup, Biomarker Subgroup, and NextG Tox Task Force, illustrated common ground and interest in science-based engagement across the scientific community and stakeholders in support of tobacco regulatory science. Highlights of the symposium are summarized in this paper.

Impact of High-Throughput Model Parameterization and Data Uncertainty on Thyroid-Based Toxicological Estimates for Pesticide Chemicals

Chemical-induced alteration of maternal thyroid hormone levels may increase the risk of adverse neurodevelopmental outcomes in offspring. US federal risk assessments rely almost exclusively on apical endpoints in animal models for deriving points of departure (PODs). New approach methodologies (NAMs) such as high-throughput screening (HTS) and mechanistically informative in vitro human cell-based systems, combined with in vitro to in vivo extrapolation (IVIVE), supplement in vivo studies and provide an alternative approach to calculate/determine PODs. We examine how parameterization of IVIVE models impacts the comparison between IVIVE-derived equivalent administered doses (EADs) from thyroid-relevant in vitro assays and the POD values that serve as the basis for risk assessments. Pesticide chemicals with thyroid-based in vitro bioactivity data from the US Tox21 HTS program were included (n = 45). Depending on the model structure used for IVIVE analysis, up to 35 chemicals produced EAD values lower than the POD. A total of 10 chemicals produced EAD values higher than the POD regardless of the model structure. The relationship between IVIVE-derived EAD values and the in vivo-derived POD values is highly dependent on model parameterization. Here, we derive a range of potentially thyroid-relevant doses that incorporate uncertainty in modeling choices and in vitro assay data.

Use of physiologically based kinetic modeling-facilitated reverse dosimetry to predict in vivo acute toxicity of tetrodotoxin in rodents

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.

Derivation of a Human In Vivo Benchmark Dose for Bisphenol A from ToxCast In Vitro Concentration Response Data Using a Computational Workflow for Probabilistic Quantitative In Vitro to In Vivo Extrapolation

A computational workflow which integrates physiologically based kinetic (PBK) modelling; global sensitivity analysis (GSA), Approximate Bayesian Computation (ABC), Markov Chain Monte Carlo (MCMC) simulation and the Virtual Cell Based Assay (VCBA) for the estimation of the active, free in vitro concentration of chemical in the reaction medium was developed to facilitate quantitative in vitro to in vivo extrapolation (QIVIVE). The workflow was designed to estimate parameter and model uncertainty within a computationally efficient framework. The workflow was tested using a human PBK model for bisphenol A (BPA) and high throughput screening (HTS) in vitro concentration-response data, for estrogen and pregnane X receptor activation determined in human liver and kidney cell lines, from the ToxCast/Tox21 database. In vivo benchmark dose 10% lower confidence limits (BMDL10) for oral uptake of BPA (ng/kg BW/day) were calculated from the in vivo dose-responses and compared to the human equivalent dose (HED) BMDL10 for relative kidney weight change in the mouse derived by European Food Safety Authority (EFSA). Three from four in vivo BMDL10 values calculated in this study were similar to the EFSA values whereas the fourth was much smaller. The derivation of an uncertainty factor (UF) to accommodate the uncertainties associated with measurements using human cell lines in vitro, extrapolated to in vivo, could be useful for the derivation of Health Based Guidance Values (HBGV).

Predicting the in vivo developmental toxicity of benzo[a]pyrene (BaP) in rats by an in vitro-in silico approach

Developmental toxicity testing is an animal-intensive endpoints in toxicity testing and calls for animal-free alternatives. Previous studies showed the applicability of an in vitro–in silico approach for predicting developmental toxicity of a range of compounds, based on data from the mouse embryonic stem cell test (EST) combined with physiologically based kinetic (PBK) modelling facilitated reverse dosimetry. In the current study, the use of this approach for predicting developmental toxicity of polycyclic aromatic hydrocarbons (PAHs) was evaluated, using benzo[a]pyrene (BaP) as a model compound. A rat PBK model of BaP was developed to simulate the kinetics of its main metabolite 3-hydroxybenzo[a]pyrene (3-OHBaP), shown previously to be responsible for the developmental toxicity of BaP. Comparison to in vivo kinetic data showed that the model adequately predicted BaP and 3-OHBaP blood concentrations in the rat. Using this PBK model and reverse dosimetry, a concentration–response curve for 3-OHBaP obtained in the EST was translated into an in vivo dose–response curve for developmental toxicity of BaP in rats upon single or repeated dose exposure. The predicted half maximal effect doses (ED₅₀) amounted to 67 and 45 mg/kg bw being comparable to the ED₅₀ derived from the in vivo dose–response data reported for BaP in the literature, of 29 mg/kg bw. The present study provides a proof of principle of applying this in vitro–in silico approach for evaluating developmental toxicity of BaP and may provide a promising strategy for predicting the developmental toxicity of related PAHs, without the need for extensive animal testing.

Development of a Generic Physiologically Based Kinetic Model to Predict In Vivo Uterotrophic Responses Induced by Estrogenic Chemicals in Rats Based on In Vitro Bioassays

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.

Derivation of a Human In Vivo Benchmark Dose for Perfluorooctanoic Acid From ToxCast In Vitro Concentration-Response Data Using a Computational Workflow for Probabilistic Quantitative In Vitro to In Vivo Extrapolation

A computational workflow which integrates physiologically based kinetic (PBK) modeling, global sensitivity analysis (GSA), approximate Bayesian computation (ABC), and Markov Chain Monte Carlo (MCMC) simulation was developed to facilitate quantitative in vitro to in vivo extrapolation (QIVIVE). The workflow accounts for parameter and model uncertainty within a computationally efficient framework. The workflow was tested using a human PBK model for perfluorooctanoic acid (PFOA) and high throughput screening (HTS) in vitro concentration–response data, determined in a human liver cell line, from the ToxCast/Tox21 database. In vivo benchmark doses (BMDs) for PFOA intake (ng/kg BW/day) and drinking water exposure concentrations (µg/L) were calculated from the in vivo dose responses and compared to intake values derived by the European Food Safety Authority (EFSA). The intake benchmark dose lower confidence limit (BMDL₅) of 0.82 was similar to 0.86 ng/kg BW/day for altered serum cholesterol levels derived by EFSA, whereas the intake BMDL₅ of 6.88 was six-fold higher than the value of 1.14 ng/kg BW/day for altered antibody titer also derived by the EFSA. Application of a chemical-specific adjustment factor (CSAF) of 1.4, allowing for inter-individual variability in kinetics, based on biological half-life, gave an intake BMDL₅ of 0.59 for serum cholesterol and 4.91 (ng/kg BW/day), for decreased antibody titer, which were 0.69 and 4.31 the EFSA-derived values, respectively. The corresponding BMDL₅ for drinking water concentrations, for estrogen receptor binding activation associated with breast cancer, pregnane X receptor binding associated with altered serum cholesterol levels, thyroid hormone receptor α binding leading to thyroid disease, and decreased antibody titer (pro-inflammation from cytokines) were 0.883, 0.139, 0.086, and 0.295 ng/ml, respectively, with application of no uncertainty factors. These concentrations are 5.7-, 36-, 58.5-, and 16.9-fold lower than the median measured drinking water level for the general US population which is approximately, 5 ng/ml.

Physiologically based kinetic modelling based prediction of in vivo rat and human acetylcholinesterase (AChE) inhibition upon exposure to diazinon

The present study predicts in vivo human and rat red blood cell (RBC) acetylcholinesterase (AChE) inhibition upon diazinon (DZN) exposure using physiological based kinetic (PBK) modelling-facilitated reverse dosimetry. Due to the fact that both DZN and its oxon metabolite diazoxon (DZO) can inhibit AChE, a toxic equivalency factor (TEF) was included in the PBK model to combine the effect of DZN and DZO when predicting in vivo AChE inhibition. The PBK models were defined based on kinetic constants derived from in vitro incubations with liver fractions or plasma of rat and human, and were used to translate in vitro concentration-response curves for AChE inhibition obtained in the current study to predicted in vivo dose-response curves. The predicted dose-response curves for rat matched available in vivo data on AChE inhibition, and the benchmark dose lower confidence limits for 10% inhibition (BMDL10 values) were in line with the reported BMDL10 values. Humans were predicted to be 6-fold more sensitive than rats in terms of AChE inhibition, mainly because of inter-species differences in toxicokinetics. It is concluded that the TEF-coded DZN PBK model combined with quantitative in vitro to in vivo extrapolation (QIVIVE) provides an adequate approach to predict RBC AChE inhibition upon acute oral DZN exposure, and can provide an alternative testing strategy for derivation of a point of departure (POD) in risk assessment.

Prediction of dose-dependent in vivo acetylcholinesterase inhibition by profenofos in rats and humans using physiologically based kinetic (PBK) modeling-facilitated reverse dosimetry

Organophosphate pesticides (OPs) are known to inhibit acetylcholine esterase (AChE), a critical effect used to establish health-based guidance values. This study developed a combined in vitro–in silico approach to predict AChE inhibition by the OP profenofos in rats and humans. A physiologically based kinetic (PBK) model was developed for both species. Parameter values for profenofos conversion to 4-bromo-2-chlorophenol (BCP) were derived from in vitro incubations with liver microsomes, liver cytosol, and plasma from rats (catalytic efficiencies of 1.1, 2.8, and 0.19 ml/min/mg protein, respectively) and humans (catalytic efficiencies of 0.17, 0.79, and 0.063 ml/min/mg protein, respectively), whereas other chemical-related parameter values were derived using in silico calculations. The rat PBK model was evaluated against literature data on urinary excretion of conjugated BCP. Concentration-dependent inhibition of rat and human AChE was determined in vitro and these data were translated with the PBK models to predicted dose-dependent AChE inhibition in rats and humans in vivo. Comparing predicted dose-dependent AChE inhibition in rats to literature data on profenofos-induced AChE inhibition revealed an accurate prediction of in vivo effect levels. Comparison of rat predictions (BMDL10 of predicted dose–response data of 0.45 mg/kg bw) and human predictions (BMDL10 of predicted dose–response data of 0.01 mg/kg bw) suggests that humans are more sensitive than rats, being mainly due to differences in kinetics. Altogether, the results demonstrate that in vivo AChE inhibition upon acute exposure to profenofos was closely predicted in rats, indicating the potential of this novel approach method in chemical hazard assessment.

Prediction of the dose range for adverse neurological effects of amiodarone in patients from an in vitro toxicity test by in vitro-in vivo extrapolation

Amiodarone is an antiarrhythmic agent inducing adverse effects on the nervous system, among others. We applied physiologically based pharmacokinetic (PBPK) modeling combined with benchmark dose modeling to predict, based on published in vitro data, the in vivo dose of amiodarone which may lead to adverse neurological effects in patients. We performed in vitro–in vivo extrapolation (IVIVE) from concentrations measured in the cell lysate of a rat brain 3D cell model using a validated human PBPK model. Among the observed in vitro effects, inhibition of choline acetyl transferase (ChAT) was selected as a marker for neurotoxicity. By reverse dosimetry, we transformed the in vitro concentration–effect relationship into in vivo effective human doses, using the calculated in vitro area under the curve (AUC) of amiodarone as the pharmacokinetic metric. The upper benchmark dose (BMDU) was calculated and compared with clinical doses eliciting neurological adverse effects in patients. The AUCs in the in vitro brain cell culture after 14-day repeated dosing of nominal concentration equal to 1.25 and 2.5 µM amiodarone were 1.00 and 1.99 µg*h/mL, respectively. The BMDU was 385.4 mg for intravenous converted to 593 mg for oral application using the bioavailability factor of 0.65 as reported in the literature. The predicted dose compares well with neurotoxic doses in patients supporting the hypothesis that impaired ChAT activity may be related to the molecular/cellular mechanisms of amiodarone neurotoxicity. Our study shows that predicting effects from in vitro data together with IVIVE can be used at the initial stage for the evaluation of potential adverse drug reactions and safety assessment in humans.

Open-Framework Zn Compound with Cationic-π Interaction: Photochromism and Benzene Series Detection

Photochromic open-framework compounds are of potential application in detection/sensors. The issue of improving the detection limits has received much attention. We synthesized a new open-framework Zn compound, namely, compound 1 ([Zn(MQ)(IPA)Cl]·5H₂O) (MQ = N-methyl-4,4'-bipyridinium, IPA = m-phthalic acid), which showed a 1D channel structure by a cationic-π interaction. It is noteworthy that this compound is an effective detector for aniline though luminescence emission, which exhibited unprecedented detection limits in photochromic open-framework compounds.

Defining in vivo dose-response curves for kidney DNA adduct formation of aristolochic acid I in rat, mouse and human by an in vitro and physiologically based kinetic modeling approach

Aristolochic acid I (AAI) is a well-known genotoxic kidney carcinogen. Metabolic conversion of AAI into the DNA-reactive aristolactam-nitrenium ion is involved in the mode of action of tumor formation. This study aims to predict in vivo AAI-DNA adduct formation in the kidney of rat, mouse and human by translating the in vitro concentration-response curves for AAI-DNA adduct formation to the in vivo situation using physiologically based kinetic (PBK) modeling-based reverse dosimetry. DNA adduct formation in kidney proximal tubular LLC-PK1 cells exposed to AAI was quantified by liquid chromatography-electrospray ionization-tandem mass spectrometry. Subsequently, the in vitro concentration-response curves were converted to predicted in vivo dose-response curves in rat, mouse and human kidney using PBK models. Results obtained revealed a dose-dependent increase in AAI-DNA adduct formation in the rat, mouse and human kidney and the predicted DNA adduct levels were generally within an order of magnitude compared with values reported in the literature. It is concluded that the combined in vitro PBK modeling approach provides a novel way to define in vivo dose-response curves for kidney DNA adduct formation in rat, mouse and human and contributes to the reduction, refinement and replacement of animal testing.

Systematic Approach for Screening of Prodrugs: Evaluation Using Oseltamivir Analogues as Models

Prodrug development is a common approach in drug development. In a recent study, we established a systematic strategy for selecting prodrugs with improved membrane permeability or solubility based on log D value, solubility in artificial intestinal fluids, membrane permeability, and metabolic instability. The purpose of this study was to evaluate the utility of this strategy using oseltamivir and 23 kinds of oseltamivir analogues having various types of side chain as well as their active metabolite, oseltamivir acid. Log D values of oseltamivir and analogues (2.0 to 4.9) were higher than that of oseltamivir acid (0.7), supporting the previous development of oseltamivir to improve permeability of oseltamivir acid. Solubilities of analogues in artificial intestinal fluids were over 80%, except the compound with the highest lipophilicity. Positive correlation was observed between membrane permeability and log D values of analogues. In metabolic profiles, species differences in the hydrolysis efficiency were observed depending on analogues. Using our strategy, it was demonstrated that oseltamivir and some analogues are appropriate prodrugs that could be advanced to in vivo pharmacokinetic studies, with selection of suitable animals. This study confirmed the utility of our strategy for narrowing down of candidate compounds to proceed into in vivo study.

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.

Use of Physiologically Based Kinetic Modeling to Predict Rat Gut Microbial Metabolism of the Isoflavone Daidzein to S-Equol and Its Consequences for ERα Activation

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.

Integrating in vitro testing and physiologically-based pharmacokinetic (PBPK) modelling for chemical liver toxicity assessment-A case study of troglitazone

In vitro to in vivo extrapolation (IVIVE) for next-generation risk assessment (NGRA) of chemicals requires computational modeling and faces unique challenges. Using mitochondria-related toxicity data of troglitazone (TGZ), a prototype drug known for liver toxicity, from HepaRG, HepG2, HC-04, and primary human hepatocytes, we explored inherent uncertainties in IVIVE, including cell models, cellular response endpoints, and dose metrics. A human population physiologically-based pharmacokinetic (PBPK) model for TGZ was developed to predict in vivo doses from in vitro point-of-departure (POD) concentrations. Compared to the 200-800 mg/d dose range of TGZ where liver injury was observed clinically, the predicted POD doses for the mean and top one percentile of the PBPK population were 28-372 and 15-178 mg/d respectively based on C_max dosimetry, and 185-2552 and 83-1010 mg/d respectively based on AUC. In conclusion, although with many uncertainties, integrating in vitro assays and PBPK modeling is promising in informing liver toxicity-inducing TGZ doses.

Fluorescence Turn-On Response Amplified by Space Confinement in Metal-Organic Frameworks

Sensitive fluorescence turn-on response to specific substances is highly desired for development of chemical sensors and switches. Here we utilized a "two-in-one" strategy to prepare ionic metal-organic frameworks (MOFs) functionalized with the cationic bipyridinium receptors at the frameworks and anionic fluorescent indicators in the pores. The MOFs are rendered a fluorescence-resting state because the indicator's fluorescence is efficiently quenched by the ground-state charge-transfer (CT) complexation between the indicator and receptor. Addition of an alkylamine efficiently turns on the fluorescence because the indicator is displaced by the CT complexation between alkylamine with receptor. The turn-on response is highly specific to alkylamines. The MOFs can be used as recyclable sensors for selective and sensitive detection of alkylamines, with ultralow detection limits (0.5 nM). The fluorescence in solid state can be reversibly switched on and off with high contrast. The sensitive and high-contrast response can be attributed to the space confinement effects of the porous frameworks. The confined space can significantly enhance indicator-receptor and analyte-receptor interactions, and thereby both the quenching efficiency in the off state and the displacement efficiency in the on state are amplified.

The role of metabolism in the developmental toxicity of polycyclic aromatic hydrocarbon-containing extracts of petroleum substances

In vitro assays presently used for prenatal developmental toxicity (PDT) testing only assess the embryotoxic potential of parent substances and not that of potentially embryotoxic metabolites. Here we combined a biotransformation system, using hamster liver microsomes, with the ES‐D3 cell differentiation assay of the embryonic stem cell test (EST) to compare the in vitro PDT potency of two 5‐ring polycyclic aromatic hydrocarbons (PAHs), benzo[a]pyrene (BaP) and dibenz[a,h]anthracene (DBA), and dimethyl sulfoxide extracts from five PAH‐containing petroleum substances (PS) and a gas‐to‐liquid base oil (GTLb), with and without bioactivation. In the absence of bioactivation, DBA, but not BaP, inhibited the differentiation of ES‐D3 cells into beating cardiomyocytes in a concentration‐dependent manner. Upon bioactivation, BaP induced in vitro PDT, while its major metabolite 3‐hydroxybenzo[a]pyrene was shown to be active in the EST as well. This means BaP needs biotransformation to exert its embryotoxic effects. GTLb extracts tested negative in the EST, with and without bioactivation. The PS‐induced PDT in the EST was not substantially changed following bioactivation, implying that metabolism may not play a crucial role for the PS extracts under study to exert the in vitro PDT effects. Altogether, these results indicate that although some PAH require bioactivation to induce PDT, some do not and this latter appears to hold for the (majority of) the PS constituents responsible for the in vitro PDT of these complex substances.

The present study combines a biotransformation system, using hamster liver microsomes, with the embryonic stem cell test to compare the in vitro prenatal developmental toxicity potency of two 5‐ring polycyclic aromatic hydrocarbons, benzo[a]pyrene and dibenz[a,h]anthracene, and dimethyl sulfoxide extracts from five PAH‐containing petroleum substances and a gas‐to‐liquid base oil, with and without bioactivation.

The in vivo developmental toxicity of diethylstilbestrol (DES) in rat evaluated by an alternative testing strategy

In the present study, we evaluated an alternative testing strategy to quantitatively predict the in vivo developmental toxicity of the synthetic hormone diethylstilbestrol (DES). To this end, a physiologically based kinetic (PBK) model was defined that was subsequently used to translate concentration-response data for the in vitro developmental toxicity of DES, obtained in the ES-D3 cell differentiation assay, into predicted in vivo dose-response data for developmental toxicity. The previous studies showed that the PBK model-facilitated reverse dosimetry approach is a useful approach to quantitatively predict the developmental toxicity of several developmental toxins. The results obtained in the present study show that the PBK model adequately predicted DES blood concentrations in rats. Further studies revealed that DES tested positive in the ES-D3 differentiation assay and that DES-induced inhibition of the ES-D3 cell differentiation could be counteracted by the estrogen receptor alpha (ERα) antagonist fulvestrant, indicating that the in vitro ES-D3 cell differentiation assay was able to mimic the role of ERα reported in the mode of action underlying the developmental toxicity of DES in vivo. In spite of this, combining these in vitro data with the PBK model did not adequately predict the in vivo developmental toxicity of DES in a quantitative way. It is concluded that although the EST qualifies DES as a developmental toxin and detects the role of ERα in this process, the ES-D3 cell differentiation assay of the EST apparently does not adequately capture the processes underlying DES-induced developmental toxicity in vivo.

A Computational Workflow for Probabilistic Quantitative in Vitro to in Vivo Extrapolation

A computational workflow was developed to facilitate the process of quantitative in vitro to in vivo extrapolation (QIVIVE), specifically the translation of in vitro concentration-response to in vivo dose-response relationships and subsequent derivation of a benchmark dose value (BMD). The workflow integrates physiologically based pharmacokinetic (PBPK) modeling; global sensitivity analysis (GSA), Approximate Bayesian Computation (ABC) and Markov Chain Monte Carlo (MCMC) simulation. For a given set of in vitro concentration and response data the algorithm returns the posterior distribution of the corresponding in vivo, population-based dose-response values, for a given route of exposure. The novel aspect of the workflow is a rigorous statistical framework for accommodating uncertainty in both the parameters of the PBPK model (both parameter uncertainty and population variability) and in the structure of the PBPK model itself recognizing that the model is an approximation to reality. Both these sources of uncertainty propagate through the workflow and are quantified within the posterior distribution of in vivo dose for a fixed representative in vitro concentration. To demonstrate this process and for comparative purposes a similar exercise to previously published work describing the kinetics of ethylene glycol monoethyl ether (EGME) and its embryotoxic metabolite methoxyacetic acid (MAA) in rats was undertaken. The computational algorithm can be used to extrapolate from in vitro data to any organism, including human. Ultimately, this process will be incorporated into a user-friendly, freely available modeling platform, currently under development, that will simplify the process of QIVIVE.

Development of a Combined In Vitro Physiologically Based Kinetic (PBK) and Monte Carlo Modelling Approach to Predict Interindividual Human Variation in Phenol-Induced Developmental Toxicity

With our recently developed in vitro physiologically based kinetic (PBK) modelling approach, we could extrapolate in vitro toxicity data to human toxicity values applying PBK-based reverse dosimetry. Ideally information on kinetic differences among human individuals within a population should be considered. In the present study, we demonstrated a modelling approach that integrated in vitro toxicity data, PBK modelling and Monte Carlo simulations to obtain insight in interindividual human kinetic variation and derive chemical specific adjustment factors (CSAFs) for phenol-induced developmental toxicity. The present study revealed that UGT1A6 is the primary enzyme responsible for the glucuronidation of phenol in humans followed by UGT1A9. Monte Carlo simulations were performed taking into account interindividual variation in glucuronidation by these specific UGTs and in the oral absorption coefficient. Linking Monte Carlo simulations with PBK modelling, population variability in the maximum plasma concentration of phenol for the human population could be predicted. This approach provided a CSAF for interindividual variation of 2.0 which covers the 99th percentile of the population, which is lower than the default safety factor of 3.16 for interindividual human kinetic differences. Dividing the dose-response curve data obtained with in vitro PBK-based reverse dosimetry, with the CSAF provided a dose-response curve that reflects the consequences of the interindividual variability in phenol kinetics for the developmental toxicity of phenol. The strength of the presented approach is that it provides insight in the effect of interindividual variation in kinetics for phenol-induced developmental toxicity, based on only in vitro and in silico testing.

Towards a generic physiologically based kinetic model to predict in vivo uterotrophic responses in rats by reverse dosimetry of in vitro estrogenicity data

Physiologically based kinetic (PBK) modelling-based reverse dosimetry is a promising tool for the prediction of in vivo developmental toxicity using in vitro concentration–response data. In the present study, the potential of this approach to predict the dose-dependent increase of uterus weight in rats upon exposure to estrogenic chemicals was assessed. In vitro concentration–response data of 17β-estradiol (E2) and bisphenol A (BPA) obtained in the MCF-7/BOS proliferation assay, the U2OS ER-CALUX assay and the yeast estrogen screen (YES) assay, were translated into in vivo dose–response data in rat, using a PBK model with a minimum number of in vitro and in silico determined parameter values. To evaluate the predictions made, benchmark dose (BMD) analysis was performed on the predicted dose–response data and the obtained BMDL₁₀ values were compared with BMDL₁₀ values derived from data on the effects of E2 and BPA in the uterotrophic assay reported in the literature. The results show that predicted dose–response data of E2 and BPA matched with the data from in vivo studies when predictions were made based on YES assay data. The YES assay-based predictions of the BMDL₁₀ values differed 3.9-fold (E2) and 4.7- to 13.4-fold (BPA) from the BMDL₁₀ values obtained from the in vivo data. The present study provides the proof-of-principle that PBK modelling-based reverse dosimetry of YES assay data using a minimum PBK model can predict dose-dependent in vivo uterus growth caused by estrogenic chemicals. In future studies, the approach should be extended to include other estrogens.

In vitro to in vivo extrapolation of effective dosimetry in developmental toxicity testing: Application of a generic PBK modelling approach

Incorporation of kinetics to quantitative in vitro to in vivo extrapolations (QIVIVE) is a key step for the realization of a non-animal testing paradigm, in the sphere of regulatory toxicology. The use of Physiologically-Based Kinetic (PBK) modelling for determining systemic doses of chemicals at the target site is accepted to be an indispensable element for such purposes. Nonetheless, PBK models are usually designed for a single or a group of compounds and are considered demanding, with respect to experimental data needed for model parameterization. Alternatively, we evaluate here the use of a more generic approach, i.e. the so-called IndusChemFate model, which is based on incorporated QSAR model parametrization. The model was used to simulate the in vivo kinetics of three diverse classes of developmental toxicants: triazoles, glycol ethers' alkoxyacetic acid metabolites and phthalate primary metabolites. The model required specific input per each class of compounds. These compounds were previously tested in three alternative assays: the whole-embryo culture (WEC), the zebrafish embryo test (ZET), and the mouse embryonic stem cell test (EST). Thereafter, the PBK-simulated blood levels at toxic in vivo doses were compared to the respective in vitro effective concentrations. Comparisons pertaining to relative potency and potency ranking with integration of kinetics were similar to previously obtained comparisons. Additionally, all three in vitro systems produced quite comparable results, and hence, a combination of alternative tests is still preferable for predicting the endpoint of developmental toxicity in vivo. This approach is put forward as biologically more plausible since plasma concentrations, rather than external administered doses, constitute the most direct in vivo dose metric.

In vitro-in silico-based analysis of the dose-dependent in vivo oestrogenicity of the soy phytoestrogen genistein in humans

BACKGROUND AND PURPOSE

The in vivo oestrogenicity of genistein and its glycoside genistin is still under debate. The present study aimed to develop a physiologically based kinetic (PBK) model that provides insight in dose-dependent plasma concentrations of genistein aglycone and its metabolites and enables prediction of in vivo oestrogenic effective dose levels of genistein and genistin in humans.

EXPERIMENTAL APPROACH

A PBK model for genistein and genistin in humans was developed based on in vitro metabolic parameters. The model obtained was used to translate in vitro oestrogenic concentration-response curves of genistein to in vivo oestrogenic dose-response curves for intake of genistein and genistin.

KEY RESULTS

The model predicted that genistein-7-O-glucuronide was the major circulating metabolite and that levels of the free aglycone were generally low [0.5-17% of total plasma genistein at oral doses from 0.01 to 50 mg (kg·bw)^-1 ]. The predicted in vivo benchmark dose for 5% response values for oestrogenicity varied between 0.06 and 4.39 mg kg^-1 genistein. For genistin, these values were 1.3-fold higher. These values are in line with reported human data and show that oestrogenic responses can be expected at an Asian dietary and a supplementary intake, while intake resulting from a Western diet may not be effective.

CONCLUSIONS AND IMPLICATIONS

The present study shows how plasma concentrations of genistein and its metabolites and oestrogenic dose levels of genistein in humans can be predicted by combining in vitro oestrogenicity with PBK model-based reverse dosimetry, eliminating the need for human intervention studies.

Physiologically based kinetic modeling of hesperidin metabolism and its use to predict in vivo effective doses in humans

SCOPE

To develop a physiologically based kinetic (PBK) model that describes the absorption, distribution, metabolism, and excretion of hesperidin in humans, enabling the translation of in vitro concentration-response curves to in vivo dose-response curves.

METHODS AND RESULTS

The PBK model for hesperidin in humans was developed based on in vitro metabolic parameters. Hesperidin was predicted to mainly occur in the systemic circulation as different monoglucuronides. The plasma concentrations of hesperidin aglycone (hesperetin) was predicted to be <0.02 mg/L at an oral dose of 50 mg/kg bw. The developed PBK model allowed conversion of in vitro concentration-response curves for different effects to in vivo dose-response curves. The BMD₀₅ (benchmark dose for 5% response) values for protein kinase A inhibition ranged between 135 and 529 mg/kg bw hesperidin, and for inhibition of endothelial cell migration and prostaglandin E₂ and nitric oxide production ranged between 2.19 and 44 mg/kg bw hesperidin. These values are in line with reported human data showing in vivo effects by hesperidin and show that these effects may occur at Western dietary and supplementary intake of hesperidin.

CONCLUSIONS

The developed PBK model adequately predicts absorption, distribution, metabolism, and excretion of hesperidin in humans and allows to evaluate the human in vivo situation without the need for human intervention studies.

Use of physiologically based kinetic modeling-facilitated reverse dosimetry of in vitro toxicity data for prediction of in vivo developmental toxicity of tebuconazole in rats

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.

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.

Integration of Life-Stage Physiologically Based Pharmacokinetic Models with Adverse Outcome Pathways and Environmental Exposure Models to Screen for Environmental Hazards

A computational framework was developed to assist in screening and prioritizing chemicals based on their dosimetry, toxicity, and potential exposures. The overall strategy started with contextualizing chemical activity observed in high-throughput toxicity screening (HTS) by mapping these assays to biological events described in Adverse Outcome Pathways (AOPs). Next, in vitro to in vivo (IVIVE) extrapolation was used to convert an in vitro dose to an external exposure level, which was compared with potential exposure levels to derive an AOP-based margins of exposure (MOE). In this study, the framework was applied to estimate MOEs for chemicals that can potentially cause developmental toxicity following a putative AOP for fetal vasculogenesis/angiogenesis. A physiologically based pharmacokinetic (PBPK) model was developed to describe chemical disposition during pregnancy, fetal, neonatal, and infant to adulthood stages. Using this life-stage PBPK model, maternal exposures were estimated that would yield fetal blood levels equivalent to the chemical concentration that altered in vitro activity of selected HTS assays related to the most sensitive vasculogenesis/angiogenesis putative AOP. The resulting maternal exposure estimates were then compared with potential exposure levels using literature data or exposure models to derive AOP-based MOEs.

Predicting points of departure for risk assessment based on in vitro cytotoxicity data and physiologically based kinetic (PBK) modeling: The case of kidney toxicity induced by aristolochic acid I

Aristolochic acids are naturally occurring nephrotoxins. This study aims to investigate whether physiologically based kinetic (PBK) model-based reverse dosimetry could convert in vitro concentration-response curves of aristolochic acid I (AAI) to in vivo dose response-curves for nephrotoxicity in rat, mouse and human. To achieve this extrapolation, PBK models were developed for AAI in these different species. Subsequently, concentration-response curves obtained from in vitro cytotoxicity models were translated to in vivo dose-response curves using PBK model-based reverse dosimetry. From the predicted in vivo dose-response curves, points of departure (PODs) for risk assessment could be derived. The PBK models elucidated species differences in the kinetics of AAI with the overall catalytic efficiency for metabolic conversion of AAI to aristolochic acid Ia (AAIa) being 2-fold higher for rat and 64-fold higher for mouse than human. Results show that the predicted PODs generally fall within the range of PODs derived from the available in vivo studies. This study provides proof of principle for a new method to predict a POD for in vivo nephrotoxicity by integrating in vitro toxicity testing with in silico PBK model-based reverse dosimetry.

Uncertainties in human health risk assessment of environmental contaminants: A review and perspective

Addressing uncertainties in human health risk assessment is a critical issue when evaluating the effects of contaminants on public health. A range of uncertainties exist through the source-to-outcome continuum, including exposure assessment, hazard and risk characterisation. While various strategies have been applied to characterising uncertainty, classical approaches largely rely on how to maximise the available resources. Expert judgement, defaults and tools for characterising quantitative uncertainty attempt to fill the gap between data and regulation requirements. The experiences of researching 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) illustrated uncertainty sources and how to maximise available information to determine uncertainties, and thereby provide an 'adequate' protection to contaminant exposure. As regulatory requirements and recurring issues increase, the assessment of complex scenarios involving a large number of chemicals requires more sophisticated tools. Recent advances in exposure and toxicology science provide a large data set for environmental contaminants and public health. In particular, biomonitoring information, in vitro data streams and computational toxicology are the crucial factors in the NexGen risk assessment, as well as uncertainties minimisation. Although in this review we cannot yet predict how the exposure science and modern toxicology will develop in the long-term, current techniques from emerging science can be integrated to improve decision-making.

Extended evaluation on the ES-D3 cell differentiation assay combined with the BeWo transport model, to predict relative developmental toxicity of triazole compounds

The mouse embryonic stem D3 (ES-D3) cell differentiation assay is based on the morphometric measurement of cardiomyocyte differentiation and is a promising tool to detect developmental toxicity of compounds. The BeWo transport model, consisting of BeWo b30 cells grown on transwell inserts and mimicking the placental barrier, is useful to determine relative placental transport velocities of compounds. We have previously demonstrated the usefulness of the ES-D3 cell differentiation assay in combination with the in vitro BeWo transport model to predict the relative in vivo developmental toxicity potencies of a set of reference azole compounds. To further evaluate this combined in vitro toxicokinetic and toxicodynamic approach, we combined ES-D3 cell differentiation data of six novel triazoles with relative transport rates obtained from the BeWo model and compared the obtained ranking to the developmental toxicity ranking as derived from in vivo data. The data show that the combined in vitro approach provided a correct prediction for in vivo developmental toxicity, whereas the ES-D3 cell differentiation assay as stand-alone did not. In conclusion, we have validated the combined in vitro approach for developmental toxicity, which we have previously developed with a set of reference azoles, for a set of six novel triazoles. We suggest that this combined model, which takes both toxicodynamic and toxicokinetic aspects into account, should be further validated for other chemical classes of developmental toxicants.

Estimation of in vivo dose of dermally applied chemicals leading to estrogen/androgen receptor-mediated toxicity from in vitro data--Illustration with four reproductive toxicants

We present a quantitative in vitro-in vivo extrapolation framework enabling the estimation of the external dermal exposure dose from in vitro experimental data relevant to a toxicity pathway of interest. The framework adapts elements of the biological pathway altering dose (BPAD) method [Judson et al. Chem Res Toxicol 2011;24:451] to the case of dermal exposure. Dermal doses of four toxicants equivalent to concentrations characterizing their effect on estrogen receptor α or androgen receptor activity in chemical-activated luciferase expression (CALUX) assays are estimated. The analysis shows that dermal BPADs, calculated from one in vitro concentration, can differ by up to a factor of 55, due to the impact applied dose and dermal exposure scenarios can have on skin permeation kinetics. These features should therefore be taken into account in risk assessment of dermally applied chemicals.

Species extrapolation of life-stage physiologically-based pharmacokinetic (PBPK) models to investigate the developmental toxicology of ethanol using in vitro to in vivo (IVIVE) methods

To provide useful alternatives to in vivo animal studies, in vitro assays for dose-response assessments of xenobiotic chemicals must use concentrations in media and target tissues that are within biologically-plausible limits. Determining these concentrations is a complex matter, which can be facilitated by applying physiologically-based pharmacokinetic (PBPK) models in an in vitro to in vivo extrapolation (IVIVE) paradigm. We used ethanol (EtOH), a ubiquitous chemical with defined metrics for in vivo and in vitro embryotoxicity, as a model chemical to evaluate this paradigm. A published series of life-stage PBPK models for rats was extended to mice, yielding simulations that adequately predicted in vivo blood EtOH concentrations (BECs) from oral, intraperitoneal, and intravenous routes in nonpregnant and pregnant adult mice. The models were then extrapolated to nonpregnant and pregnant humans, replicating BEC data within a factor of two. The rodent models were then used to conduct IVIVEs for rodent and whole-embryo culture embryotoxicity data (neural tube closure defects, morphological changes). A second IVIVE was conducted for exposure scenarios in pregnant women during critical windows of susceptibility for developmental toxicity, such as the first 6-to-8 weeks (prerecognition period) or mid-to-late pregnancy period, when EtOH consumption is associated with fetal alcohol spectrum disorders. Incorporation of data from human embryonic stem cell studies led to a model-supported linkage of in vitro concentrations with plausible exposure ranges for pregnant women. This effort demonstrates benefits and challenges associated with use of multispecies PBPK models to estimate in vivo tissue concentrations associated with in vitro embryotoxicity studies.