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

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

New approach methodologies (NAMs) for human-relevant biokinetics predictions. Meeting the paradigm shift in toxicology towards an animal-free chemical risk assessment

For almost fifteen years, the availability and regulatory acceptance of new approach methodologies (NAMs) to assess the absorption, distribution, metabolism and excretion (ADME/biokinetics) in chemical risk evaluations are a bottleneck. To enhance the field, a team of 24 experts from science, industry, and regulatory bodies, including new generation toxicologists, met at the Lorentz Centre in Leiden, The Netherlands. A range of possibilities for the use of NAMs for biokinetics in risk evaluations were formulated (for example to define species differences and human variation or to perform quantitative in vitro-in vivo extrapolations). To increase the regulatory use and acceptance of NAMs for biokinetics for these ADME considerations within risk evaluations, the development of test guidelines (protocols) and of overarching guidance documents is considered a critical step. To this end, a need for an expert group on biokinetics within the Organisation of Economic Cooperation and Development (OECD) to supervise this process was formulated. The workshop discussions revealed that method development is still required, particularly to adequately capture transporter mediated processes as well as to obtain cell models that reflect the physiology and kinetic characteristics of relevant organs. Developments in the fields of stem cells, organoids and organ-on-a-chip models provide promising tools to meet these research needs in the future.

Potential of ToxCast Data in the Safety Assessment of Food Chemicals.

Tox21 and ToxCast are high-throughput in vitro screening programs coordinated by the U.S. National Toxicology Program and the U.S. Environmental Protection Agency, respectively, with the goal of forecasting biological effects in vivo based on bioactivity profiling. The present study investigated whether mechanistic insights in the biological targets of food-relevant chemicals can be obtained from ToxCast results when the chemicals are grouped according to structural similarity. Starting from the 556 direct additives that have been identified in the ToxCast database by Karmaus et al. [Karmaus, A. L., Trautman, T. D., Krishan, M., Filer, D. L., and Fix, L. A. (2017). Curation of food-relevant chemicals in ToxCast. Food Chem. Toxicol. 103, 174-182.], the results showed that, despite the limited number of assays in which the chemical groups have been tested, sufficient results are available within so-called "DNA binding" and "nuclear receptor" target families to profile the biological activities of the defined chemical groups for these targets. The most obvious activity identified was the estrogen receptor-mediated actions of the chemical group containing parabens and structurally related gallates, as well the chemical group containing genistein and daidzein (the latter 2 being particularly active toward estrogen receptor ß as a potential health benefit). These group effects, as well as the biological activities of other chemical groups, were evaluated in a series of case studies. Overall, the results of the present study suggest that high-throughput screening data could add to the evidence considered for regulatory risk assessment of food chemicals and to the evaluation of desirable effects of nutrients and phytonutrients. The data will be particularly useful for providing mechanistic information and to fill data gaps with read-across.

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.

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.

Evaluation of Interindividual Human Variation in Bioactivation and DNA Adduct Formation of Estragole in Liver Predicted by Physiologically Based Kinetic/Dynamic and Monte Carlo Modeling.

Estragole is a known hepatocarcinogen in rodents at high doses following metabolic conversion to the DNA-reactive metabolite 1'-sulfooxyestragole. The aim of the present study was to model possible levels of DNA adduct formation in (individual) humans upon exposure to estragole. This was done by extending a previously defined PBK model for estragole in humans to include (i) new data on interindividual variation in the kinetics for the major PBK model parameters influencing the formation of 1'-sulfooxyestragole, (ii) an equation describing the relationship between 1'-sulfooxyestragole and DNA adduct formation, (iii) Monte Carlo modeling to simulate interindividual human variation in DNA adduct formation in the population, and (iv) a comparison of the predictions made to human data on DNA adduct formation for the related alkenylbenzene methyleugenol. Adequate model predictions could be made, with the predicted DNA adduct levels at the estimated daily intake of estragole of 0.01 mg/kg bw ranging between 1.6 and 8.8 adducts in 10(8) nucleotides (nts) (50th and 99th percentiles, respectively). This is somewhat lower than values reported in the literature for the related alkenylbenzene methyleugenol in surgical human liver samples. The predicted levels seem to be below DNA adduct levels that are linked with tumor formation by alkenylbenzenes in rodents, which were estimated to amount to 188-500 adducts per 10(8) nts at the BMD10 values of estragole and methyleugenol. Although this does not seem to point to a significant health concern for human dietary exposure, drawing firm conclusions may have to await further validation of the model's predictions.

Evaluation of the interindividual human variation in bioactivation of methyleugenol using physiologically based kinetic modeling and Monte Carlo simulations.

The present study aims at predicting the level of formation of the ultimate carcinogenic metabolite of methyleugenol, 1'-sulfooxymethyleugenol, in the human population by taking variability in key bioactivation and detoxification reactions into account using Monte Carlo simulations. Depending on the metabolic route, variation was simulated based on kinetic constants obtained from incubations with a range of individual human liver fractions or by combining kinetic constants obtained for specific isoenzymes with literature reported human variation in the activity of these enzymes. The results of the study indicate that formation of 1'-sulfooxymethyleugenol is predominantly affected by variation in i) P450 1A2-catalyzed bioactivation of methyleugenol to 1'-hydroxymethyleugenol, ii) P450 2B6-catalyzed epoxidation of methyleugenol, iii) the apparent kinetic constants for oxidation of 1'-hydroxymethyleugenol, and iv) the apparent kinetic constants for sulfation of 1'-hydroxymethyleugenol. Based on the Monte Carlo simulations a so-called chemical-specific adjustment factor (CSAF) for intraspecies variation could be derived by dividing different percentiles by the 50th percentile of the predicted population distribution for 1'-sulfooxymethyleugenol formation. The obtained CSAF value at the 90th percentile was 3.2, indicating that the default uncertainty factor of 3.16 for human variability in kinetics may adequately cover the variation within 90% of the population. Covering 99% of the population requires a larger uncertainty factor of 6.4. In conclusion, the results showed that adequate predictions on interindividual human variation can be made with Monte Carlo-based PBK modeling. For methyleugenol this variation was observed to be in line with the default variation generally assumed in risk assessment.

Physiologically based kinetic models for the alkenylbenzene elemicin in rat and human and possible implications for risk assessment.

The present study describes physiologically based kinetic (PBK) models for the alkenylbenzene elemicin (3,4,5-trimethoxyallylbenzene) in rat and human, based on the PBK models previously developed for the structurally related alkenylbenzenes estragole, methyleugenol, and safrole. Using the newly developed models, the level of metabolic activation of elemicin in rat and human was predicted to obtain insight in species differences in the bioactivation of elemicin and read across to the other methoxy allylbenzenes, estragole and methyleugenol. Results reveal that the differences between rat and human in the formation of the proximate carcinogenic metabolite 1'-hydroxyelemicin and the ultimate carcinogenic metabolite 1'-sulfoxyelemicin are limited (<3.8-fold). In addition, a comparison was made between the relative importance of bioactivation for elemicin and that of estragole and methyleugenol. Model predictions indicate that compound differences in the formation of the 1'-sulfoxymetabolites are limited (<11-fold) in rat and human liver. The insights thus obtained were used to perform a risk assessment for elemicin using the margin of exposure (MOE) approach and read across to the other methoxy allylbenzene derivatives for which in vivo animal tumor data are available. This reveals that elemicin poses a lower priority for risk management as compared to its structurally related analogues estragole and methyleugenol. Altogether, the results obtained indicate that PBK modeling provides an important insight in the occurrence of species differences in the metabolic activation of elemicin. Moreover, they provide an example of how PBK modeling can facilitate a read across in risk assessment from compounds for which in vivo toxicity studies are available to a compound for which only limited toxicity data have been described, thus contributing to the development of alternatives for animal testing.

Evaluation of research activities and research needs to increase the impact and applicability of alternative testing strategies in risk assessment practice.

The present paper aims at identifying strategies to increase the impact and applicability of alternative testing strategies in risk assessment. To this end, a quantitative and qualitative literature evaluation was performed on (a) current research efforts in the development of in vitro methods aiming for alternatives to animal testing, (b) the possibilities and limitations of in vitro methods for regulatory purposes and (c) the potential of physiologically-based kinetic (PBK) modeling to improve the impact and applicability of in vitro methods in risk assessment practice. Overall, the evaluation showed that the focus of state-of-the-art research activities does not seem to be optimally directed at developing in vitro alternatives for those endpoints that are most animal-demanding, such as reproductive and developmental toxicity, and carcinogenicity. A key limitation in the application of in vitro alternatives to such systemic endpoints is that in vitro methods do not provide so-called points of departure, necessary for regulators to set safe exposure limits. PBK-modeling could contribute to overcoming this limitation by providing a method that allows extrapolation of in vitro concentration-response curves to in vivo dose-response curves. However, more proofs of principle are required.

Evaluation of human interindividual variation in bioactivation of estragole using physiologically based biokinetic modeling.

The present study investigates interindividual variation in liver levels of the proximate carcinogenic metabolite of estragole, 1'-hydroxyestragole, due to variation in two key metabolic reactions involved in the formation and detoxification of this metabolite, namely 1'-hydroxylation of estragole and oxidation of 1'-hydroxyestragole. Formation of 1'-hydroxyestragole is predominantly catalyzed by P450 1A2, 2A6, and 2E1, and results of the present study support that oxidation of 1'-hydroxyestragole is catalyzed by 17beta-hydroxysteroid dehydrogenase type 2 (17beta-HSD2). In a first approach, the study defines physiologically based biokinetic (PBBK) models for 14 individual human subjects, revealing a 1.8-fold interindividual variation in the area under the liver concentration-time curve (AUC) for 1'-hydroxyestragole within this group of human subjects. Variation in oxidation of 1'-hydroxyestragole by 17beta-HSD2 was shown to result in larger effects than those caused by variation in P450 enzyme activity. In a second approach, a Monte Carlo simulation was performed to evaluate the extent of variation in liver levels of 1'-hydroxyestragole that could occur in the population as a whole. This analysis could be used to derive a chemical-specific adjustment factor (CSAF), which is defined as the 99th percentile divided by the 50th percentile of the predicted distribution of the AUC of 1'-hydroxyestragole in the liver. The CSAF was estimated to range between 1.6 and 4.0, depending on the level of variation that was taken into account for oxidation of 1'-hydroxyestragole. Comparison of the CSAF to the default uncertainty factor of 3.16 for human variability in biokinetics reveals that the default uncertainty factor adequately protects 99% of the population.

In silico methods for physiologically based biokinetic models describing bioactivation and detoxification of coumarin and estragole: implications for risk assessment.

In chemical safety assessment, information on adverse effects after chronic exposure to low levels of hazardous compounds is essential for estimating human risks. Results from in vitro studies are often not directly applicable to the in vivo situation, and in vivo animal studies often have to be performed at unrealistic high levels of exposure. Physiologically based biokinetic (PBBK) modeling can be used as a platform for integrating in vitro metabolic data to predict dose- and species-dependent in vivo effects on biokinetics, and can provide a method to obtain a better mechanistic basis for extrapolations of data obtained in experimental animal studies to the human situation. Recently, we have developed PBBK models for the bioactivation of the alkenylbenzene estragole to its DNA binding ultimate carcinogenic metabolite 1'-sulfooxyestragole in both rat and human, as well as rat and human PBBK models for the bioactivation of coumarin to its hepatotoxic o-hydroxyphenylacetaldehyde metabolite. This article presents an overview of the results obtained so far with these in silico methods for PBBK modeling, focusing on the possible implications for risk assessment, and some additional considerations and future perspectives.