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.

In vitro-in silico-based prediction of inter-individual and inter-ethnic variations in the dose-dependent cardiotoxicity of R- and S-methadone in humans.

New approach methodologies predicting human cardiotoxicity are of interest to support or even replace in vivo-based drug safety testing. The present study presents an in vitro-in silico approach to predict the effect of inter-individual and inter-ethnic kinetic variations in the cardiotoxicity of R- and S-methadone in the Caucasian and the Chinese population. In vitro cardiotoxicity data, and metabolic data obtained from two approaches, using either individual human liver microsomes or recombinant cytochrome P450 enzymes (rCYPs), were integrated with physiologically based kinetic (PBK) models and Monte Carlo simulations to predict inter-individual and inter-ethnic variations in methadone-induced cardiotoxicity. Chemical specific adjustment factors were defined and used to derive dose-response curves for the sensitive individuals. Our simulations indicated that Chinese are more sensitive towards methadone-induced cardiotoxicity with Margin of Safety values being generally two-fold lower than those for Caucasians for both methadone enantiomers. Individual PBK models using microsomes and PBK models using rCYPs combined with Monte Carlo simulations predicted similar inter-individual and inter-ethnic variations in methadone-induced cardiotoxicity. The present study illustrates how inter-individual and inter-ethnic variations in cardiotoxicity can be predicted by combining in vitro toxicity and metabolic data, PBK modelling and Monte Carlo simulations. The novel methodology can be used to enhance cardiac safety evaluations and risk assessment of chemicals.

Read-across and new approach methodologies applied in a 10-step framework for cosmetics safety assessment - A case study with parabens.

Parabens are esters of para-hydroxybenzoic acid that have been used as preservatives in many types of products for decades including agrochemicals, pharmaceuticals, food and cosmetics. This illustrative case study with propylparaben (PP) demonstrates a 10-step read-across (RAX) framework in practice. It aims at establishing a proof-of-concept for the value added by new approach methodologies (NAMs) in read-across (RAX) for use in a next-generation risk assessment (NGRA) in order to assess consumer safety after exposure to PP-containing cosmetics. In addition to structural and physico-chemical properties, in silico information, toxicogenomics, in vitro toxicodynamic, toxicokinetic data from PBK models, and bioactivity data are used to provide evidence of the chemical and biological similarity of PP and analogues and to establish potency trends for observed effects in vitro. The chemical category under consideration is short (C1-C4) linear chain n-alkyl parabens: methylparaben, ethylparaben, propylparaben and butylparaben. The goal of this case study is to illustrate how a practical framework for RAX can be used to fill a hypothetical data gap for reproductive toxicity of the target chemical PP.

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.

Finding synergies for 3Rs - Toxicokinetics and read-across: Report from an EPAA partners' Forum.

The European Partnership for Alternative Approaches to Animal Testing (EPAA) convened a Partners' Forum Toxicokinetics and Read-Across to provide an overview on research activities to develop in vitro toxicokinetics methods and physiologically-based kinetic (PBK) models and to find synergies to enhance use of toxicokinetic data to strengthen read-across. Currently, lacking toxicokinetic data often prevent the application of read-across. Preferably, toxicokinetic data should be generated using in vitro and in silico tools and anchored towards human relevance. In certain sectors, PBK modelling is being used for risk assessment, but less so in others. Specific activities were identified to facilitate the use of in vitro and in silico toxicokinetic data to support read-across: The collation of available tools indicating the parameters and applicability domains covered; endpoint-specific guidance on toxicokinetics parameters required for read-across; case studies exemplifying how toxicokinetic data help support read-across. Activities to enhance the scientific robustness of read-across include the further user-friendly combination of read-across tools and formal guidance by the authorities specifying the minimum information requirements to justify read-across for a given toxicity endpoint. The EPAA was invited to continue dissemination activities and to explore possibilities to collate a contemporaneous list of open toxicokinetics tools that assist 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.

An integrated QSAR-PBK/D modelling approach for predicting detoxification and DNA adduct formation of 18 acyclic food-borne α,ß-unsaturated aldehydes.

Acyclic α,ß-unsaturated aldehydes present in food raise a concern because the α,ß-unsaturated aldehyde moiety is considered a structural alert for genotoxicity. However, controversy remains on whether in vivo at realistic dietary exposure DNA adduct formation is significant. The aim of the present study was to develop physiologically based kinetic/dynamic (PBK/D) models to examine dose-dependent detoxification and DNA adduct formation of a group of 18 food-borne acyclic α,ß-unsaturated aldehydes without 2- or 3-alkylation, and with no more than one conjugated double bond. Parameters for the PBK/D models were obtained using quantitative structure-activity relationships (QSARs) defined with a training set of six selected aldehydes. Using the QSARs, PBK/D models for the other 12 aldehydes were defined. Results revealed that DNA adduct formation in the liver increases with decreasing bulkiness of the molecule especially due to less efficient detoxification. 2-Propenal (acrolein) was identified to induce the highest DNA adduct levels. At realistic dietary intake, the predicted DNA adduct levels for all aldehydes were two orders of magnitude lower than endogenous background levels observed in disease free human liver, suggesting that for all 18 aldehydes DNA adduct formation is negligible at the relevant levels of dietary intake. The present study provides a proof of principle for the use of QSAR-based PBK/D modelling to facilitate group evaluations and read-across in risk assessment.

Application of partition coefficient methods to predict tissue:plasma affinities in common farm animals: Influence of ionisation state.

Tissue affinities are conventionally determined from in vivo steady-state tissue and plasma or plasma-water chemical concentration data. In silico approaches were initially developed for preclinical species but standardly applied and tested in human physiologically-based kinetic (PBK) models. Recently, generic PBK models for farm animals have been made available and require partition coefficients as input parameters. In the current investigation, data for species-specific tissue compositions have been collected, and prediction of chemical distribution in various tissues of livestock species for cattle, chicken, sheep and swine have been performed. Overall, tissue composition was very similar across the four farm animal species. However, small differences were observed in moisture, fat and protein content in the various organs within each species. Such differences could be attributed to factors such as variations in age, breed, and weight of the animals and general conditions of the animal itself. With regards to the predictions of tissue:plasma partition coefficients, 80 %, 71 %, 77 % of the model predictions were within a factor 10 using the methods of Berezhkovskiy (2004), Rodgers and Rowland (2006) and Schmitt (2008). The method of Berezhkovskiy (2004) was often providing the most reliable predictions except for swine, where the method of Schmitt (2008) performed best. In addition, investigation of the impact of chemical classes on prediction performance, all methods had very similar reliability. Notwithstanding, no clear pattern regarding specific chemicals or tissues could be detected for the values predicted outside a 10-fold change in certain chemicals or specific tissues. This manuscript concludes with the need for future research, particularly focusing on lipophilicity and species differences in protein binding.

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.

New approach methodologies: A quantitative in vitro to in vivo extrapolation case study with PFASs.

PER: and polyfluoroalkyl substances (PFASs) have been associated with increased blood lipids in humans. Perfluorooctanoic acid (PFOA) has been also linked with elevated alanine transferase (ALT) serum levels in humans, and in rodents the liver is a main target organ for many PFASs. With the focus on New Approach Methodologies, the chronic oral equivalent effect doses were calculated for PFOA, PFNA (perfluorononanoic acid), PFHxS (perfluorohexanesulfonic acid) and PFOS (perfluorooctane sulfonic acid) based on in vitro effects measured in the HepaRG cell line. Selected in vitro readouts were considered biomarkers for lipid disturbances and hepatotoxicity. Concentration-response data obtained from HepaRG cells on triglyceride (TG) accumulation and expression changes of 12 selected genes (some involved in cholesterol homeostasis) were converted into corresponding human dose-response data, using physiologically based kinetic (PBK) model-facilitated reverse dosimetry. Next to this, the biokinetics of the chemicals were studied in the cell system. The current European dietary PFASs exposure overlaps with the calculated oral equivalent effect doses, indicating that the latter may lead to interference with hepatic gene expression and lipid metabolism. These findings illustrate an in vitro-in silico methodology, which can be applied for more PFASs, to select those that should be prioritized for further hazard characterization.

Prediction of in vivo prenatal chlorpyrifos exposure leading to developmental neurotoxicity in humans based on in vitro toxicity data by quantitative in vitro-in vivo extrapolation.

Introduction: Epidemiological studies in children suggested that in utero exposure to chlorpyrifos (CPF), an organophosphate insecticide, may cause developmental neurotoxicity (DNT). We applied quantitative in vitro-in vivo extrapolation (QIVIVE) based on in vitro concentration and non-choline esterase-dependent effects data combined with Benchmark dose (BMD) modelling to predict oral maternal CPF exposure during pregnancy leading to fetal brain effect concentration. By comparing the results with data from epidemiological studies, we evaluated the contribution of the in vitro endpoints to the mode of action (MoA) for CPF-induced DNT. Methods: A maternal-fetal PBK model built in PK-Sim® was used to perform QIVIVE predicting CPF concentrations in a pregnant women population at 15 weeks of gestation from cell lysate concentrations obtained in human induced pluripotent stem cell-derived neural stem cells undergoing differentiation towards neurons and glia exposed to CPF for 14 days. The in vitro concentration and effect data were used to perform BMD modelling. Results: The upper BMD was converted into maternal doses which ranged from 3.21 to 271 mg/kg bw/day. Maternal CPF blood levels from epidemiological studies reporting DNT findings in their children were used to estimate oral CPF exposure during pregnancy using the PBK model. It ranged from 0.11 to 140 µg/kg bw/day. Discussion: The effective daily intake doses predicted from the in vitro model were several orders of magnitude higher than exposures estimated from epidemiological studies to induce developmental non-cholinergic neurotoxic responses, which were captured by the analyzed in vitro test battery. These were also higher than the in vivo LOEC for cholinergic effects. Therefore, the quantitative predictive value of the investigated non-choline esterase-dependent effects, although possibly relevant for other chemicals, may not adequately represent potential key events in the MoA for CPF-associated DNT.

Development of a Generic PBK Model for Human Biomonitoring with an Application to Deoxynivalenol.

Toxicokinetic modelling provides a powerful tool in relating internal human exposure (i.e., assessed through urinary biomarker levels) to external exposure. Chemical specific toxicokinetic models are available; however, this specificity prevents their application to similar contaminants or to other routes of exposure. For this reason, we investigated whether a generic physiological-based kinetic (PBK) model might be a suitable alternative for a biokinetic model of deoxynivalenol (DON). IndusChemFate (ICF) was selected as a generic PBK model, which could be fit for purpose. Being suited for simulating multiple routes of exposure, ICF has particularly been used to relate the inhalation and dermal exposure of industrial chemicals to their urinary excretion. For the first time, the ICF model was adapted as a generic model for the human biomonitoring of mycotoxins, thereby extending its applicability domain. For this purpose, chemical-specific data for DON and its metabolites were collected directly from the literature (distribution and metabolism) or indirectly (absorption and excretion) by fitting the ICF model to previously described urinary excretion data. The obtained results indicate that this generic model can be used to model the urinary excretion of DON and its glucuronidated metabolites following dietary exposure to DON. Additionally, the present study establishes the basis for further development of the model to include an inhalation exposure route alongside the oral exposure route.

Next Generation Risk Assessment of the Anti-Androgen Flutamide Including the Contribution of Its Active Metabolite Hydroxyflutamide.

In next generation risk assessment (NGRA), non-animal approaches are used to quantify the chemical concentrations required to trigger bioactivity responses, in order to assure safe levels of human exposure. A limitation of many in vitro bioactivity assays, which are used in an NGRA context as new approach methodologies (NAMs), is that toxicokinetics, including biotransformation, are not adequately captured. The present study aimed to include, as a proof of principle, the bioactivity of the metabolite hydroxyflutamide (HF) in an NGRA approach to evaluate the safety of the anti-androgen flutamide (FLU), using the AR-CALUX assay to derive the NAM point of departure (PoD). The NGRA approach applied also included PBK modelling-facilitated quantitative in vitro to in vivo extrapolation (QIVIVE). The PBK model describing FLU and HF kinetics in humans was developed using GastroPlus™ and validated against human pharmacokinetic data. PBK model-facilitated QIVIVE was performed to translate the in vitro AR-CALUX derived concentration-response data to a corresponding in vivo dose-response curve for the anti-androgenicity of FLU, excluding and including the activity of HF (-HF and +HF, respectively). The in vivo benchmark dose 5% lower confidence limits (BMDL05) derived from the predicted in vivo dose-response curves for FLU, revealed a 440-fold lower BMDL05 when taking the bioactivity of HF into account. Subsequent comparison of the predicted BMDL05 values to the human therapeutic doses and historical animal derived PoDs, revealed that PBK modelling-facilitated QIVIVE that includes the bioactivity of the active metabolite is protective and provides a more appropriate PoD to assure human safety via NGRA, whereas excluding this would potentially result in an underestimation of the risk of FLU exposure in humans.

New approach methods (NAMs) supporting read-across: Two neurotoxicity AOP-based IATA case studies

Read-across approaches are considered key in moving away from in vivo animal testing towards addressing data-gaps using new approach methods (NAMs). Ample successful examples are still required to substantiate this strategy. Here we present and discuss the learnings from two OECD IATA endorsed read-across case studies. They involve two classes of pesticides ­ rotenoids and strobilurins ­ each having a defined mode-of-action that is assessed for its neurological hazard by means of an AOP-based testing strategy coupled to toxicokinetic simulations of human tissue concentrations. The endpoint in question is potential mitochondrial respiratory chain mediated neurotoxicity, specifically through inhibition of complex I or III. An AOP linking inhibition of mitochondrial respiratory chain complex I to the degeneration of dopaminergic neurons formed the basis for both cases but was deployed in two different regulatory contexts. The two cases also exemplify several different read-across concepts: analogue versus category approach, consolidated versus putative AOP, positive versus negative prediction (i.e., neurotoxicity versus low potential for neurotoxicity), and structural versus biological similarity. We applied a range of NAMs to explore the toxicodynamic properties of the compounds, e.g., in silico docking as well as in vitro assays and readouts ­ including transcriptomics ­ in various cell systems, all anchored to the relevant AOPs. Interestingly, although some of the data addressing certain elements of the read-across were associated with high uncertainty, their impact on the overall read-across conclusion remained limited. Coupled to the elaborate regulatory review that the two cases underwent, we propose some generic learnings of AOP-based testing strategies supporting read-across.

Mode of action based risk assessment of the botanical food-borne alkenylbenzene apiol from parsley using physiologically based kinetic (PBK) modelling and read-across from safrole.

The present study developed physiologically-based kinetic (PBK) models for the alkenylbenzene apiol in order to facilitate risk assessment based on read-across from the related alkenylbenzene safrole. Model predictions indicate that in rat liver the formation of the 1'-sulfoxy metabolite is about 3 times lower for apiol than for safrole. These data support that the lower confidence limit of the benchmark dose resulting in a 10% extra cancer incidence (BMDL10) that would be obtained in a rodent carcinogenicity study with apiol may be 3-fold higher for apiol than for safrole. These results enable a preliminary risk assessment for apiol, for which tumor data are not available, using a BMDL10 value of 3 times the BMDL10 for safrole. Based on an estimated BMDL10 for apiol of 5.7-15.3 mg/kg body wt per day and an estimated daily intake of 4 × 10(-5) mg/kg body wt per day, the margin of exposure (MOE) would amount to 140,000-385,000. This indicates a low priority for risk management. The present study shows how PBK modelling can contribute to the development of alternatives for animal testing, facilitating read-across from compounds for which in vivo toxicity studies on tumor formation are available to compounds for which these data are unavailable.