PBTK modelling platforms and parameter estimation tools to enable animal-free risk assessment: recommendations from a joint EPAA--EURL ECVAM ADME workshop

Big Question to Developing Solutions: A Decade of Progress in the Development of Aquatic New Approach Methodologies from 2012 to 2022

In 2012, 20 key questions related to hazard and exposure assessment and environmental and health risks of pharmaceuticals and personal care products in the natural environment were identified. A decade later, this article examines the current level of knowledge around one of the lowest-ranking questions at that time, number 19: "Can nonanimal testing methods be developed that will provide equivalent or better hazard data compared with current in vivo methods?" The inclusion of alternative methods that replace, reduce, or refine animal testing within the regulatory context of risk and hazard assessment of chemicals generally faces many hurdles, although this varies both by organism (human-centric vs. other), sector, and geographical region or country. Focusing on the past 10 years, only works that might reasonably be considered to contribute to advancements in the field of aquatic environmental risk assessment are highlighted. Particular attention is paid to methods of contemporary interest and importance, representing progress in (1) the development of methods which provide equivalent or better data compared with current in vivo methods such as bioaccumulation, (2) weight of evidence, or (3) -omic-based applications. Evolution and convergence of these risk assessment areas offer the basis for fundamental frameshifts in how data are collated and used for the protection of taxa across the breadth of the aquatic environment. Looking to the future, we are at a tipping point, with a need for a global and inclusive approach to establish consensus. Bringing together these methods (both new and old) for regulatory assessment and decision-making will require a concerted effort and orchestration. Environ Toxicol Chem 2024;43:559-574. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Fish Physiologically Based Toxicokinetic Modeling Approach for In Vitro-In Vivo and Cross-Species Extrapolation of Endocrine-Disrupting Chemicals in Risk Assessment

High-throughput in vitro assays combined with in vitro-in vivo extrapolation (IVIVE) leverage in vitro responses to predict the corresponding in vivo exposures and thresholds of concern. The integrated approach is also expected to offer the potential for efficient tools to provide estimates of chemical toxicity to various wildlife species instead of animal testing. However, developing fish physiologically based toxicokinetic (PBTK) models for IVIVE in ecological applications is challenging, especially for plausible estimation of an internal effective dose, such as fish equivalent concentration (FEC). Here, a fish PBTK model linked with the IVIVE approach was established, with parameter optimization of chemical unbound fraction, pH-dependent ionization and hepatic clearance, and integration of temperature effect and growth dilution. The fish PBTK-IVIVE approach provides not only a more precise estimation of tissue-specific concentrations but also a reasonable approximation of FEC targeting the estrogenic potency of endocrine-disrupting chemicals. Both predictions were compared with in vivo data and were accurate for most indissociable/dissociable chemicals. Furthermore, the model can help determine cross-species variability and sensitivity among the five fish species. Using the available IVIVE-derived FEC with target pathways is helpful to develop predicted no-effect concentration for chemicals with similar mode of action and support screening-level ecological risk assessment.

Human biomonitoring and toxicokinetics as key building blocks for next generation risk assessment

Human health risk assessment is historically built upon animal testing, often following Organisation for Economic Co-operation and Development (OECD) test guidelines and exposure assessments. Using combinations of human relevant in vitro models, chemical analysis and computational (in silico) approaches bring advantages compared to animal studies. These include a greater focus on the human species and on molecular mechanisms and kinetics, identification of Adverse Outcome Pathways and downstream Key Events as well as the possibility of addressing susceptible populations and additional endpoints. Much of the advancement and progress made in the Next Generation Risk Assessment (NGRA) have been primarily focused on new approach methodologies (NAMs) and physiologically based kinetic (PBK) modelling without incorporating human biomonitoring (HBM). The integration of toxicokinetics (TK) and PBK modelling is an essential component of NGRA. PBK models are essential for describing in quantitative terms the TK processes with a focus on the effective dose at the expected target site. Furthermore, the need for PBK models is amplified by the increasing scientific and regulatory interest in aggregate and cumulative exposure as well as interactions of chemicals in mixtures. Since incorporating HBM data strengthens approaches and reduces uncertainties in risk assessment, here we elaborate on the integrated use of TK, PBK modelling and HBM in chemical risk assessment highlighting opportunities as well as challenges and limitations. Examples are provided where HBM and TK/PBK modelling can be used in both exposure assessment and hazard characterization shifting from external exposure and animal dose/response assays to animal-free, internal exposure-based NGRA.

Metabolites in the regulatory risk assessment of pesticides in the EU

A large majority of chemicals is converted into metabolites through xenobiotic-metabolising enzymes. Metabolites may present a spectrum of characteristics varying from similar to vastly different compared with the parent compound in terms of both toxicokinetics and toxicodynamics. In the pesticide arena, the role of metabolism and metabolites is increasingly recognised as a significant factor particularly for the design and interpretation of mammalian toxicological studies and in the toxicity assessment of pesticide/metabolite-associated issues for hazard characterization and risk assessment purposes, including the role of metabolites as parts in various residues in ecotoxicological adversities. This is of particular relevance to pesticide metabolites that are unique to humans in comparison with metabolites found in in vitro or in vivo animal studies, but also to disproportionate metabolites (quantitative differences) between humans and mammalian species. Presence of unique or disproportionate metabolites may underlie potential toxicological concerns. This review aims to present the current state-of-the-art of comparative metabolism and metabolites in pesticide research for hazard and risk assessment, including One Health perspectives, and future research needs based on the experiences gained at the European Food Safety Authority.

Priorities and Challenges in Methodology for Human Health Risk Assessment from Combined Exposure to Multiple Chemicals

This paper reviews key elements in the assessment of human health effects from combined exposure to multiple chemicals taking into consideration current knowledge and challenges to identify areas where scientific advancement is mostly needed and proposes a decision-making scheme on the basis of existing methods and tools. The assumption of dose addition and estimation of the hazard index (HI) is considered as a starting point in component-based risk assessments. When, based on the generic HI approach, an unacceptable risk is identified, more specific risk assessment options may be implemented sequentially or in parallel depending on problem formulation, characteristics of the chemical group under assessment, exposure levels, data availability and resources. For prospective risk assessments, the reference point index/margin of exposure (RPI/MOET) (Option 1) or modified RPI/normalized MOET (mRPI/nMOET) (Option 2) approaches may be implemented focusing on the specific mixture effect. Relative potency factors (RPFs) may also be used in the RPI approach since a common uncertainty factor for each mixture component is introduced in the assessment. Increased specificity in the risk assessment may also be achieved when exposure of selected population groups is considered (Option 3/exposure). For retrospective risk assessments, human biomonitoring data available for vulnerable population groups (Option 3/susceptibility) may present more focused scenarios for consideration in human health risk management decisions. In data-poor situations, the option of using the mixture assessment factor (MAF) is proposed (Option 4), where an additional uncertainty factor is applied on each mixture component prior to estimating the HI. The magnitude of the MAF may be determined by the number of mixture components, their individual potencies and their proportions in the mixture, as previously reported. It is acknowledged that implementation of currently available methods and tools for human health risk assessment from combined exposure to multiple chemicals by risk assessors will be enhanced by ongoing scientific developments on new approach methodologies (NAMs), integrated approaches to testing and assessment (IATA), uncertainty analysis tools, data sharing platforms, risk assessment software as well as guideline development to meet legislative requirements.

Risk assessment in the 21st century: where are we heading?

Reliance on animal tests for chemical safety assessment is increasingly being challenged, not only because of ethical reasons, but also because they procrastinate regulatory decisions and because of concerns over the transferability of results to humans. New approach methodologies (NAMs) need to be fit for purpose and new thinking is required to reconsider chemical legislation, validation of NAMs and opportunities to move away from animal tests. This article summarizes the presentations from a symposium at the 2022 Annual Congress of the British Toxicology Society on the topic of the future of chemical risk assessment in the 21st century. The symposium included three case-studies where NAMs have been used in safety assessments. The first case illustrated how read-across augmented with some in vitro tests could be used reliably to perform the risk assessment of analogues lacking data. The second case showed how specific bioactivity assays could identify an NAM point of departure (PoD) and how this could be translated through physiologically based kinetic modelling in an in vivo PoD for the risk assessment. The third case showed how adverse-outcome pathway (AOP) information, including molecular-initiating event and key events with their underlying data, established for certain chemicals could be used to produce an in silico model that is able to associate chemical features of an unstudied substance with specific AOPs or AOP networks. The manuscript presents the discussions that took place regarding the limitations and benefits of these new approaches, and what are the barriers and the opportunities for their increased use in regulatory decision making.

Pharmacokinetics of Novel Furoxan/Coumarin Hybrids in Rats Using LC-MS/MS Method and Physiologically Based Pharmacokinetic Model

Novel furoxan/coumarin hybrids were synthesized, and pharmacologic studies showed that the compounds displayed potent antiproliferation activities via downregulating both the phosphatidylinositide 3-kinase (PI3K) pathway and the mitogen-activated protein kinase (MAPK) pathway. To investigate the preclinical pharmacokinetic (PK) properties of three candidate compounds (CY-14S-4A83, CY-16S-4A43, and CY-16S-4A93), liquid chromatography, in tandem with the mass spectrometry LC-MS/MS method, was developed and validated for the simultaneous determination of these compounds. The absorption, distribution, metabolism, and excretion (ADME) properties were investigated in in vitro studies and in rats. Meanwhile, physiologically based pharmacokinetic (PBPK) models were constructed using only in vitro data to obtain detailed PK information. Good linearity was observed over the concentration range of 0.01−1.0 μg/mL. The free drug fraction (fu) values of the compounds were less than 3%, and the clearance (CL) values were 414.5 ± 145.7 mL/h/kg, 2624.6 ± 648.4 mL/h/kg, and 500.6 ± 195.2 mL/h/kg, respectively. The predicted peak plasma concentration (Cmax) and the area under the concentration-time curve (AUC) were overestimated for the CY-16S-4A43 PBPK model compared with the experimental ones (fold error > 2), suggesting that tissue accumulation and additional elimination pathways may exist. In conclusion, the LC-MS/MS method was successively applied in the preclinical PK studies, and the detailed information from PBPK modeling may improve decision-making in subsequent new drug development.

Diastereoselective metabolism of homomenthyl salicylate (homosalate): Identification of relevant human exposure biomarkers

Homosalate (HMS) is a salicylate UV filter broadly used in sunscreens and personal care products. The aim of this study was the collection of human toxicokinetic data on HMS as a tool for risk assessment. For this purpose, metabolism and urinary excretion after a single oral HMS dose (98.2-149.1 µg (kg body weight)^-1) were investigated in four volunteers (two male, two female). As commercial products generally contain a mixture of cis- and trans-HMS, both cis-rich and trans-rich isomer mixtures were studied to investigate possible differences in metabolism. Initial metabolite screening tentatively identified six oxidative metabolite subgroups, of which hydroxylated and carboxylic acid metabolites were studied in more detail. Unchanged parent HMS and the previously identified HMS metabolites 5-((2-hydroxybenzoyl)oxy)-3,3-dimethylcyclohexane-1-carboxylic acid (HMS-CA) and 3-hydroxy-3,5,5-trimethylcyclohexyl 2-hydroxybenzoate (3OH-HMS), respectively, were quantified separately as cis- and trans-isomers via authentic standards by isotope dilution analysis. In addition, further alkyl-hydroxylated and carboxylic acid metabolites were investigated semi-quantitatively. Peak concentrations in urine were reached 1.5-6.3 h post-dose and more than 80 % of each of the quantitatively investigated metabolites (and at least 70 % of the semi-quantitatively investigated metabolites) was excreted within the first 24 h. Plasma and urine data indicated that oral bioavailability of cis-HMS was one order of magnitude below that of trans-HMS. Furthermore, the mean total urinary excretion fraction (F_ue) for the metabolites derived from trans-HMS (6.4 %) was two orders of magnitude higher than for the metabolites derived from cis-HMS (0.045 %). Our data proves diastereoselectivity in toxicokinetics of cis- and trans-HMS, emphasizing the necessity to address isomer ratios in future studies including HMS exposure and risk assessments.

Simulating toxicokinetic variability to identify susceptible and highly exposed populations

BACKGROUND

Toxicokinetic (TK) data needed for chemical risk assessment are not available for most chemicals. To support a greater number of chemicals, the U.S. Environmental Protection Agency (EPA) created the open-source R package "httk" (High Throughput ToxicoKinetics). The "httk" package provides functions and data tables for simulation and statistical analysis of chemical TK, including a population variability simulator that uses biometrics data from the National Health and Nutrition Examination Survey (NHANES).

OBJECTIVE

Here we modernize the "HTTK-Pop" population variability simulator based on the currently available data and literature. We provide explanations of the algorithms used by "httk" for variability simulation and uncertainty propagation.

METHODS

We updated and revised the population variability simulator in the "httk" package with the most recent NHANES biometrics (up to the 2017-18 NHANES cohort). Model equations describing glomerular filtration rate (GFR) were revised to more accurately represent physiology and population variability. The model output from the updated "httk" package was compared with the current version.

RESULTS

The revised population variability simulator in the "httk" package now provides refined, more relevant, and better justified estimations.

SIGNIFICANCE

Fulfilling the U.S. EPA's mission to provide open-source data and models for evaluations and applications by the broader scientific community, and continuously improving the accuracy of the "httk" package based on the currently available data and literature.

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.

IVIVE: Facilitating the Use of In Vitro Toxicity Data in Risk Assessment and Decision Making

During the past few decades, the science of toxicology has been undergoing a transformation from observational to predictive science. New approach methodologies (NAMs), including in vitro assays, in silico models, read-across, and in vitro to in vivo extrapolation (IVIVE), are being developed to reduce, refine, or replace whole animal testing, encouraging the judicious use of time and resources. Some of these methods have advanced past the exploratory research stage and are beginning to gain acceptance for the risk assessment of chemicals. A review of the recent literature reveals a burst of IVIVE publications over the past decade. In this review, we propose operational definitions for IVIVE, present literature examples for several common toxicity endpoints, and highlight their implications in decision-making processes across various federal agencies, as well as international organizations, including those in the European Union (EU). The current challenges and future needs are also summarized for IVIVE. In addition to refining and reducing the number of animals in traditional toxicity testing protocols and being used for prioritizing chemical testing, the goal to use IVIVE to facilitate the replacement of animal models can be achieved through their continued evolution and development, including a strategic plan to qualify IVIVE methods for regulatory acceptance.

Predictive Performance of Next Generation Physiologically Based Kinetic (PBK) Model Predictions in Rats Based on In Vitro and In Silico Input Data

The goal of the present study was to assess the predictive performance of a minimal generic rat physiologically based kinetic (PBK) model based on in vitro and in silico input data to predict peak plasma concentrations (Cmax) upon single oral dosing. To this purpose, a dataset was generated of 3960 Cmax predictions for 44 compounds, applying different combinations of in vitro and in silico approaches for chemical parameterization, and comparison of the predictions to reported in vivo data. Best performance was obtained when (1) the hepatic clearance was parameterized based on in vitro measured intrinsic clearance values, (2) the method of Rodgers and Rowland for calculating partition coefficients, and (3) in silico calculated fraction unbound plasma and Papp values (the latter especially for very lipophilic compounds). Based on these input data, the median Cmax of 32 compounds could be predicted within 10-fold of the observed Cmax, with 22 out of these 32 compounds being predicted within 5-fold, and 8 compounds within 2-fold. Overestimations of more than 10-fold were observed for 12 compounds, whereas no underestimations of more than 10-fold occurred. Median Cmax predictions were frequently found to be within 10-fold of the observed Cmax when the scaled unbound hepatic intrinsic clearance (Clint,u) was either higher than 20 l/h or lower than 1 l/h. Similar findings were obtained with a test set of 5 in-house BASF compounds. Overall, this study provides relevant insights in the predictive performance of a minimal PBK model based on in vitro and in silico input data.

Probabilistic risk assessment - the keystone for the future of toxicology

Safety sciences must cope with uncertainty of models and results as well as information gaps. Acknowledging this uncertainty necessitates embracing probabilities and accepting the remaining risk. Every toxicological tool delivers only probable results. Traditionally, this is taken into account by using uncertainty / assessment factors and worst-case / precautionary approaches and thresholds. Probabilistic methods and Bayesian approaches seek to characterize these uncertainties and promise to support better risk assessment and, thereby, improve risk management decisions. Actual assessments of uncertainty can be more realistic than worst-case scenarios and may allow less conservative safety margins. Most importantly, as soon as we agree on uncertainty, this defines room for improvement and allows a transition from traditional to new approach methods as an engineering exercise. The objective nature of these mathematical tools allows to assign each methodology its fair place in evidence integration, whether in the context of risk assessment, systematic reviews, or in the definition of an integrated testing strategy (ITS) / defined approach (DA) / integrated approach to testing and assessment (IATA). This article gives an overview of methods for probabilistic risk assessment and their application for exposure assessment, physiologically-based kinetic modelling, probability of hazard assessment (based on quantitative and read-across based structure-activity relationships, and mechanistic alerts from in vitro studies), individual susceptibility assessment, and evidence integration. Additional aspects are opportunities for uncertainty analysis of adverse outcome pathways and their relation to thresholds of toxicological concern. In conclusion, probabilistic risk assessment will be key for constructing a new toxicology paradigm – probably!

Integrating in vitro chemical transplacental passage into a generic PBK model: A QIVIVE approach

With the increasing application of cell culture models as primary tools for predicting chemical safety, the quantitative extrapolation of the effective dose from in vitro to in vivo (QIVIVE) is of increasing importance. For developmental toxicity this requires scaling the in vitro observed dose-response characteristics to in vivo fetal exposure, while integrating maternal in vivo kinetics during pregnancy, in particular transplacental transfer. Here the transfer of substances across the placental barrier, has been studied using the in vitro BeWo cell assay and six embryotoxic compounds of different kinetic complexity. The BeWo assay results were incorporated in an existing generic Physiologically Based Kinetic (PBK) model which for this purpose was extended with rat pregnancy. Finally, as a "proof of principle", the BeWo PBK model was used to perform a QIVIVE based on developmental toxicity as observed in various different in vitro toxicity assays. The BeWo results illustrated different transport profiles of the chemicals across the BeWo monolayer, allocating the substances into two distinct groups: the 'quickly-transported' and the 'slowly-transported'. BeWo PBK exposure simulations during gestation were compared to experimentally measured maternal blood and fetal concentrations and a reverse dosimetry approach was applied to translate in vitro observed embryotoxicity into equivalent in vivo dose-response curves. This approach allowed for a direct comparison of the in vitro dose-response characteristics as observed in the Whole Embryo Culture (WEC), and the Embryonic Stem Cell test (cardiac:ESTc and neural:ESTn) with in vivo rat developmental toxicity data. Overall, the in vitro to in vivo comparisons suggest a promising future for the application of such QIVIVE methodologies for screening and prioritization purposes of developmental toxicants. Nevertheless, the clear need for further improvements is acknowledged for a wider application of the approach in chemical safety assessment.

Proteomic analysis suggests that monoterpenes in lemongrass disrupt Ca2+ homeostasis in Haemaphysalis longicornis leading to mitochondrial depolarization and cytotoxicity

Complex mixtures of bioactive ingredients in plant essential oils present complex chemistries which involve different modes of action. An increasing body of scientific reports has recently focused on the acaricidal activities of plant essential oils attributed to their monoterpene components, but information about their underlying molecular mechanism of action is scarce. Here, after the chemical analysis of lemongrass oil, a proteomic analysis of the ovary, salivary gland, and midgut of Haemaphysalis longicornis exposed to Cymbopogon citratus (lemongrass) essential oil was performed via data-independent acquisition mass spectrometry (DIA-MS) technology to further elucidate the molecular mechanisms involved. Pathway analysis reveals the activation of metabolic pathways mediated by oxidoreductases and transferases. Furthermore, the upregulation of various calcium-associated proteins and the upregulation of cytochrome c1, cytochrome c oxidase polypeptide IV, and programmed cell death protein 6-like isoform X1 suggest a cytotoxic mode of action via the formation of reactive oxygen species (ROS), mitochondrial Ca²⁺ overload, mitochondrial uncoupling, and depolarization, and ATP depletion leading to either apoptotic or necrotic death. Morphological alterations observed after the RNAi of a major detoxification enzyme (glutathione S-transferase) merit further investigation. Hence, the cytotoxic mode of action exhibited by C. citratus oil could be vital for the development of eco-friendly acaricide.

Screening and prioritization of nano- and microplastic particle toxicity studies for evaluating human health risks - development and application of a toxicity study assessment tool

Concern regarding the human health implications that exposure to nano- and microplastic particles (NMPs) potentially represents is increasing. While there have been several years of research reporting on the ecotoxicological effects of NMPs, human health toxicology studies have only recently emerged. The available human health hazard data are thus limited, with potential concern regarding the relevance and reliability for understanding the potential human health implications. In this study we develop and apply a NMP toxicity screening assessment tool (NMP-TSAT) for evaluating human health effects studies against a suite of quality assurance and quality control (QA/QC) criteria for both in vivo and in vitro studies. A total of 74 studies representing either inhalation or oral exposure pathways were identified and evaluated. Assessment categories include particle characterization, experimental design, and applicability for risk assessment; with critical and non-critical criteria organized to allow screening and prioritization. It is observed that the majority of studies evaluated using the NMP-TSAT have been performed on monodisperse particles, predominately spheres (≈60%), consisting of polystyrene (≈46%). The majority of studies have tested particles < 5 μm, with a minimal particle size of 10 nm and a maximum particle size of about 200 μm. The total assessment score (TAS) possible for in vivo studies is 52, whereas for in vitro studies it is 46, which is based on receiving a maximum score of 2 against 26 and 23 criteria, respectively. The evaluated TAS ranged from between 12 and 44 and 16-34, for in vivo and in vitro studies, respectively. Given the challenges associated with prioritizing studies based on ranking them according to their TAS we propose a Tiered approach, whereby studies are initially screened based on how they score against various critical criteria, which have been defined for their relevance for assessing the hazards and risks for human health. In this instance, studies that score a minimum of '1' against each of the critical criteria, regardless of how they rank according to their TAS, are prioritized as part of a Tier 1 screening and prioritization phase, which would then be followed by an expert evaluation, representing a Tier 2 level of assessment. Using this approach we identify 10 oral ingestion and 2 inhalation studies that score at least 1 against all critical criteria. Lastly, several key observations for strengthening future effects studies are identified, these include a need for the generation and access to standard reference materials representative of human exposure to NMPs for use in toxicity test systems and/or the improved characterization and verification of test particle characteristics, and the adoption of study design guidance, such as recommended by OECD, when conducting either in vivo inhalation or oral ingestion toxicity tests.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1186/s43591-021-00023-x.

Development and intercomparison of single and multicompartment physiologically-based toxicokinetic models: Implications for model selection and tiered modeling frameworks

This study describes the development and intercomparison of generic physiologically-based toxicokinetic (PBTK) models for humans comprised of internally consistent one-compartment (1Co-) and multi-compartment (MCo-) implementations (G-PBTK). The G-PBTK models were parameterized for an adult male (70 kg) using common physiological parameters and in vitro biotransformation rate estimates and subsequently evaluated using independent concentration versus time data (n = 6) and total elimination half-lives (n = 15) for diverse organic chemicals. The model performance is acceptable considering the inherent uncertainty in the biotransformation rate data and the absence of model calibration. The G-PBTK model was then applied using hypothetical neutral organics, acidic ionizable organics and basic ionizable organics (IOCs) to identify combinations of partitioning properties and biotransformation rates leading to substantial discrepancies between 1Co- and MCo-PBTK calculations for whole body concentrations and half-lives. The 1Co- and MCo-PBTK model calculations for key toxicokinetic parameters are broadly consistent unless biotransformation is rapid (e.g., half-life less than five days). When half-lives are relatively short, discrepancies are greatest for the neutral organics and least for the acidic IOCs which follows from the estimated volumes of distribution (e.g., VD_SS = 9.6-15.4 L/kg vs 0.3-1.6 L/kg for the neutral and acidic compounds respectively) and the related approach to internal chemical equilibrium. The model intercomparisons demonstrate that 1Co-PBTK models can be applied with confidence to many exposure scenarios, particularly those focused on chronic or repeat exposures and for prioritization and screening-level decision contexts. However, MCo-PBTK models may be necessary in certain contexts, particularly for intermittent, short-term and highly variable exposures. A key recommendation to guide model selection and the development of tiered PBTK modeling frameworks that emerges from this study is the need to harmonize models with respect to parameterization and process descriptions to the greatest extent possible when proceeding from the application of simpler to more complex modeling tools as part of chemical assessment activities.

OpenCYP: An open source database exploring human variability in activities and frequencies of polymophisms for major cytochrome P-450 isoforms across world populations

The open source database "OpenCYP database" has been developed based on the results of extensive literature searches from the peer-reviewed literature. OpenCYP provides data on human variability on baseline of activities and polymophism frequencies for selected cytochrome P-450 isoforms (CYP1A2, CYP2A6, CYP2D6, CYP3A4/3A5 and CYP3A7) in healthy adult populations from world populations. CYP enzymatic activities were generally expressed as the metabolic ratio (MR) between an unchanged probe drug and its metabolite(s) in urine or plasma measured in healthy adults. Data on other age groups were very limited and fragmented, constituting an important data gap. Quantitative comparisons were often hampered by the different experimental conditions used. However, variability was quite limited for CYP1A2, using caffeine as a probe substrate, with a symmetrical distribution of metabolic activity values. For CYP3A4, human variability was dependent on the probe substrate itself with low variability when data considering the dextromethorphan/demethilathed metabolite MR were used and large variability when the urinary 6β-hydroxycortisol/cortisol ratio was used. The largest variability in CYP activity was shown for CYP2D6 activity, after oral dosing of dextromethorphan, for which genetic polymorphisms are well characterised and constitute a significant source of variability. It is foreseen that the OpenCYP database can contribute to promising tools to support the further development of QIVIVE and PBK models for human risk assessment of chemicals particularly when combined with information on isoform-specific content in cells using proteomic approaches.

Human Variability in Carboxylesterases and carboxylesterase-related Uncertainty Factors for Chemical Risk Assessment

Carboxylesterases (CES) are an important class of enzymes involved in the hydrolysis of a range of chemicals and show large inter-individual variability in vitro. An extensive literature search was performed to identify in vivo probe substrates for CES1 and CES2 together with their protein content and enzymatic activity. Human pharmacokinetic (PK) data on Cmax, clearance, and AUC were extracted from 89 publications and Bayesian meta-analysis was performed using a hierarchical model to derive CES-related variability distributions and related uncertainty factors (UF). The CES-related variability indicated that 97.5% of healthy adults are covered by the kinetic default UF (3.16), except for clopidogrel and dabigatran etexilate. Clopidogrel is metabolised for a small amount by the polymorphic CYP2C19, which can have an impact on the overall pharmacokinetics, while the variability seen for dabigatran etexilate might be due to differences in the absorption, since this can be influenced by food intake. The overall CES-related variability was moderate to high in vivo (<CV 50%), which might be due to possible polymorphism in the enzyme but also to the small sample size available per chemical. The presented CES-related variability can be used in combination with in vitro data to derive pathway-specific distributions.

High-throughput PBTK models for in vitro to in vivo extrapolation

INTRODUCTION

Toxicity data are unavailable for many thousands of chemicals in commerce and the environment. Therefore, risk assessors need to rapidly screen these chemicals for potential risk to public health. High-throughput screening (HTS) for in vitro bioactivity, when used with high-throughput toxicokinetic (HTTK) data and models, allows characterization of these thousands of chemicals.

AREAS COVERED

This review covers generic physiologically based toxicokinetic (PBTK) models and high-throughput PBTK modeling for in vitro-in vivo extrapolation (IVIVE) of HTS data. We focus on 'httk', a public, open-source set of computational modeling tools and in vitro toxicokinetic (TK) data.

EXPERT OPINION

HTTK benefits chemical risk assessors with its ability to support rapid chemical screening/prioritization, perform IVIVE, and provide provisional TK modeling for large numbers of chemicals using only limited chemical-specific data. Although generic TK model design can increase prediction uncertainty, these models provide offsetting benefits by increasing model implementation accuracy. Also, public distribution of the models and data enhances reproducibility. For the httk package, the modular and open-source design can enable the tool to be used and continuously improved by a broad user community in support of the critical need for high-throughput chemical prioritization and rapid dose estimation to facilitate rapid hazard assessments.

Application of the adverse outcome pathway framework to predict the toxicity of chemicals in the semiconductor manufacturing industry

Background

To solve current issues using big data, solve current issues related to the semiconductor and electronics industry, I tried to establish the data for each toxicity mechanism for adverse outcome pathway (AOP) for the exposure.

Objective

I planned to increase the efficiency of human hazard assessment by searching, analyzing, and linking test data on the relationship between key events occurred at each level, which are the biological targets of chemicals in semiconductor manufacturing.

Results

It was found that 48 kinds of chemicals had 11 AOPs, while 103 chemicals had multiple AOPs, and 26 had case evidence. As a result of AOP analysis, it was found that a total of 320 chemicals had 42 AOPs, and 190 major chemicals corresponded to 11 AOPs. It was found necessary to develop a complex AOP and secure an (inhalation or dermal) exposure scenario for combined exposure at work. As a comparative search (41 out of 190 chemicals) of biomarkers specific to occupational diseases, 12 biomarkers were found to be related to breast cancer. The AOPs for 50 specific chemicals were presented, together with occupational disease-specific AOPs and key events relationship from 50 chemicals, and taxonomic classification for each AOP analysis could be found. With a comparative search, 41 out of 190 chemicals were associated with specific biomarkers for occupational diseases, and 12 mRNA or protein biomarkers were found to be related to breast cancer by cross-validation with the attached Table 24 of the Enforcement Regulations of the OSHAct and the CTD.

Conclusion

The mechanism of occupational diseases caused by chemicals was presented, together with pathological preventions. I believe that a strategy is needed to expand the target organization for each chemical by linking with activities, such as work environment measurement, and cooperating with screening items and methods suitable for toxic chemicals, like AOP tools.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13273-021-00139-4.

Guidance on safety evaluation of sources of nutrients and bioavailability of nutrient from the sources (Revision 1)

Endorsement date	21 January 2021
Implementation date	27 March 2021

This guidance describes the scientific data required to allow an evaluation of the safety of new substances that are proposed for use as sources of nutrients in food supplements, foods for the general population or foods for specific groups and an assessment of the bioavailability of the nutrient from the proposed source. This guidance describes the scientific data required to allow an evaluation of the safety of the source within the established framework for risk assessment of food additives and novel food ingredients and the bioavailability of the nutrient from this source. This document is arranged in five main sections: one on technical data aimed at characterising the proposed source and at identifying potential hazards resulting from its manufacture and stability in food; one on existing authorisations and evaluation, providing an overview of previous assessments on the proposed source and their conclusions; one on proposed uses and exposure assessment section, allowing an estimate of the dietary exposure to the source and the nutrient based on the proposed uses and use levels; one on toxicological data, describing approaches which can be used to identify (in conjunction with data on manufacture and composition) and to characterise hazards of the source and any relevant breakdown products; the final section on bioavailability focuses on determining the extent to which the nutrient from the proposed source is available for use by the body in comparison with one or more forms of the same nutrient that are already permitted for use on the positive lists. This guidance was adopted by the Panel on Food Additives and Nutrient Sources added to Food (ANS Panel) on 16 May 2018. Upon request from EFSA, the present guidance has been revised to inform applicants of new provisions set out in Regulation (EC) No 178/2002, as amended by Regulation (EU) 2019/1381 on the transparency and sustainability of the EU risk assessment in the food chain.

In Silico Prediction of Input Parameters for Simplified Physiologically Based Pharmacokinetic Models for Estimating Plasma, Liver, and Kidney Exposures in Rats after Oral Doses of 246 Disparate Chemicals

Recently developed computational models can estimate plasma, hepatic, and renal concentrations of industrial chemicals in rats. Typically, the input parameter values (i.e., the absorption rate constant, volume of systemic circulation, and hepatic intrinsic clearance) for simplified physiologically based pharmacokinetic (PBPK) model systems are calculated to give the best fit to measured or reported in vivo blood substance concentration values in animals. The purpose of the present study was to estimate in silico these three input pharmacokinetic parameters using a machine learning algorithm applied to a broad range of chemical properties obtained from several cheminformatics software tools. These in silico estimated parameters were then incorporated into PBPK models for predicting internal exposures in rats. Following this approach, simplified PBPK models were set up for 246 drugs, food components, and industrial chemicals with a broad range of chemical structures. We had previously generated PBPK models for 158 of these substances, whereas 88 for which concentration series data were available in the literature were newly modeled. The values for the absorption rate constant, volume of systemic circulation, and hepatic intrinsic clearance could be generated in silico by equations containing between 14 and 26 physicochemical properties. After virtual oral dosing, the output concentration values of the 246 compounds in plasma, liver, and kidney from rat PBPK models using traditionally determined and in silico estimated input parameters were well correlated (r ≥ 0.83). In summary, by using PBPK models consisting of chemical receptor (gut), metabolizing (liver), excreting (kidney), and central (main) compartments with in silico-derived input parameters, the forward dosimetry of new chemicals could provide the plasma/tissue concentrations of drugs and chemicals after oral dosing, thereby facilitating estimates of hematotoxic, hepatotoxic, or nephrotoxic potential as a part of risk assessment.

Inter-phenotypic differences in CYP2C9 and CYP2C19 metabolism: Bayesian meta-regression of human population variability in kinetics and application in chemical risk assessment

Quantifying variability in pharmacokinetics (PK) and toxicokinetics (TK) provides a science-based approach to refine uncertainty factors (UFs) for chemical risk assessment. In this context, genetic polymorphisms in cytochromes P450 (CYPs) drive inter-phenotypic differences and may result in reduction or increase in metabolism of drugs or other xenobiotics. Here, an extensive literature search was performed to identify PK data for probe substrates of the human polymorphic isoforms CYP2C9 and CYP2C19. Relevant data from 158 publications were extracted for markers of chronic exposure (clearance and area under the plasma concentration-time curve) and analysed using a Bayesian meta-regression model. Enzyme function (EF), driven by inter-phenotypic differences across a range of allozymes present in extensive and poor metabolisers (EMs and PMs), and fraction metabolised (Fm), were identified as exhibiting the highest impact on the metabolism. The Bayesian meta-regression model provided good predictions for such inter-phenotypic differences. Integration of population distributions for inter-phenotypic differences and estimates for EF and Fm allowed the derivation of CYP2C9- and CYP2C19-related UFs which ranged from 2.7 to 12.7, and were above the default factor for human variability in TK (3.16) for PMs and major substrates (Fm >60%). These results provide population distributions and pathway-related UFs as conservative in silico options to integrate variability in CYP2C9 and CYP2C19 metabolism using in vitro kinetic evidence and in the absence of human data. The future development of quantitative extrapolation models is discussed with particular attention to integrating human in vitro and in vivo PK or TK data with pathway-related variability for chemical risk assessment.

Human variability in glutathione-S-transferase activities, tissue distribution and major polymorphic variants: Meta-analysis and implication for chemical risk assessment

The input into the QIVIVE and Physiologically-Based kinetic and dynamic models of drug metabolising enzymes performance and their inter-individual differences significantly improve the modelling performance, supporting the development and integration of alternative approaches to animal testing. Bayesian meta-analyses allow generating and integrating statistical distributions with human in vitro metabolism data for quantitative in vitro-in vivo extrapolation. Such data are lacking on glutathione-S-transferases (GSTs). This paper reports for the first time results on the human variability of GST activities in healthy individuals, their tissue localisation and the frequencies of their major polymorphic variants by means of extensive literature search, data collection, data base creation and meta-analysis. A limited number of papers focussed on in vivo GST inter-individual differences in humans. Ex-vivo total GST activity without discriminating amongst isozymes is generally reported, resulting in a high inter-individual variability. The highest levels of cytosolic GSTs in humans are measured in the kidney, liver, adrenal glands and blood. The frequencies of GST polymorphisms for cytosolic isozymes in populations of different geographical ancestry were also presented. Bayesian meta-analyses to derive GST-related uncertainty factors provided uncertain estimates, due to the limited database. Considering the relevance of GST activities and their pivotal role in cellular adaptive response mechanisms to chemical stressors, further studies are needed to identify GST probe substrates for specific isozymes and quantify inter-individual differences.

A workflow to build PBTK models for novel species

Physiology-based pharmacokinetic and toxicokinetic (PBPK/TK) models allow us to simulate the concentration of xenobiotica in the plasma and different tissues of an organism. PBPK/TK models are therefore routinely used in many fields of life sciences to simulate the physiological concentration of exogenous compounds in plasma and tissues. The application of PBTK models in ecotoxicology, however, is currently hampered by the limited availability of models for focal species. Here, we present a best practice workflow that describes how to build PBTK models for novel species. To this end, we extrapolated eight previously established rabbit models for several drugs to six additional mammalian species (human, beagle, rat, monkey, mouse, and minipig). We used established PBTK models for these species to account for the species-specific physiology. The parameter sensitivity in the resulting 56 PBTK models was systematically assessed to rank the relevance of the parameters on overall model performance. Interestingly, more than 80% of the 609 considered model parameters showed a negligible sensitivity throughout all models. Only approximately 5% of all parameters had a high sensitivity in at least one of the PBTK models. This approach allowed us to rank the relevance of the various parameters on overall model performance. We used this information to formulate a best practice guideline for the efficient development of PBTK models for novel animal species. We believe that the workflow proposed in this study will significantly support the development of PBTK models for new animal species in the future.

Integrating biokinetics and in vitro studies to evaluate developmental neurotoxicity induced by chlorpyrifos in human iPSC-derived neural stem cells undergoing differentiation towards neuronal and glial cells

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Human iPSC-derived NSCs undergoing differentiation possess some metabolic competence.

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CPF entered the cells and was biotrasformed into its two main metabolites (CPFO and TCP).

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After repeated exposure, very limited bioaccumulation of CPF was observed.

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Treatment with CPF decreased neurite outgrowth, synapse number and electrical activity.

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Treatment with CPF increased BDNF levels and the percentage of astrocytes.

For some complex toxicological endpoints, chemical safety assessment has conventionally relied on animal testing. Apart from the ethical issues, also scientific considerations have been raised concerning the traditional approach, highlighting the importance for considering real life exposure scenario. Implementation of flexible testing strategies, integrating multiple sources of information, including in vitro reliable test methods and in vitro biokinetics, would enhance the relevance of the obtained results. Such an approach could be pivotal in the evaluation of developmental neurotoxicity (DNT), especially when applied to human cell-based models, mimicking key neurodevelopmental processes, relevant to human brain development.

Here, we integrated the kinetic behaviour with the toxicodynamic alterations of chlorpyrifos (CPF), such as in vitro endpoints specific for DNT evaluation, after repeated exposure during differentiation of human neural stem cells into a mixed culture of neurons and astrocytes. The upregulation of some cytochrome P450 and glutathione S-transferase genes during neuronal differentiation and the formation of the two major CPF metabolites (due to bioactivation and detoxification) supported the metabolic competence of the used in vitro model. The alterations in the number of synapses, neurite outgrowth, brain derived neurotrophic factor, the proportion of neurons and astrocytes, as well as spontaneous electrical activity correlated well with the CPF ability to enter the cells and be bioactivated to CPF-oxon. Overall, our results confirm that combining in vitro biokinetics and assays to evaluate effects on neurodevelopmental endpoints in human cells should be regarded as a key strategy for a quantitative characterization of DNT effects.

Development and evaluation of a high throughput inhalation model for organic chemicals

Currently it is difficult to prospectively estimate human toxicokinetics (particularly for novel chemicals) in a high-throughput manner. The R software package httk has been developed, in part, to address this deficiency, and the aim of this investigation was to develop a generalized inhalation model for httk. The structure of the inhalation model was developed from two previously published physiologically based models from Jongeneelen and Berge (Ann Occup Hyg 55:841-864, 2011) and Clewell et al. (Toxicol Sci 63:160-172, 2001), while calculated physicochemical data was obtained from EPA's CompTox Chemicals Dashboard. In total, 142 exposure scenarios across 41 volatile organic chemicals were modeled and compared to published data. The slope of the regression line of best fit between log-transformed simulated and observed blood and exhaled breath concentrations was 0.46 with an r2 = 0.45 and a root mean square error (RMSE) of direct comparison between the log-transformed simulated and observed values of 1.11. Approximately 5.1% (n = 108) of the data points analyzed were >2 orders of magnitude different than expected. The volatile organic chemicals examined in this investigation represent small, generally lipophilic molecules. Ultimately this paper details a generalized inhalation component that integrates with the httk physiologically based toxicokinetic model to provide high-throughput estimates of inhalation chemical exposures.

A generic PBTK model implemented in the MCRA platform: Predictive performance and uses in risk assessment of chemicals

Physiologically-based toxicokinetic (PBTK) models are important tools for in vitro to in vivo or inter-species extrapolations in health risk assessment of foodborne and non-foodborne chemicals. Here we present a generic PBTK model implemented in the EuroMix toolbox, MCRA 9 and predict internal kinetics of nine chemicals (three endocrine disrupters, three liver steatosis inducers, and three developmental toxicants), in data-rich and data-poor conditions, when increasingly complex levels of parametrization are applied. At the first stage, only QSAR models were used to determine substance-specific parameters, then some parameter values were refined by estimates from substance-specific or high-throughput in vitro experiments. At the last stage, elimination or absorption parameters were calibrated based on available in vivo kinetic data. The results illustrate that parametrization plays a capital role in the output of the PBTK model, as it can change how chemicals are prioritized based on internal concentration factors. In data-poor situations, estimates can be far from observed values. In many cases of chronic exposure, the PBTK model can be summarized by an external to internal dose factor, and interspecies concentration factors can be used to perform interspecies extrapolation. We finally discuss the implementation and use of the model in the MCRA risk assessment platform.

Integrative Strategy of Testing Systems for Identification of Endocrine Disruptors Inducing Metabolic Disorders-An Introduction to the OBERON Project

Exposure to chemical substances that can produce endocrine disrupting effects represents one of the most critical public health threats nowadays. In line with the regulatory framework implemented within the European Union (EU) to reduce the levels of endocrine disruptors (EDs) for consumers, new and effective methods for ED testing are needed. The OBERON project will build an integrated testing strategy (ITS) to detect ED-related metabolic disorders by developing, improving and validating a battery of test systems. It will be based on the concept of an integrated approach for testing and assessment (IATA). OBERON will combine (1) experimental methods (in vitro, e.g., using 2D and 3D human-derived cells and tissues, and in vivo, i.e., using zebrafish at different stages), (2) high throughput omics technologies, (3) epidemiology and human biomonitoring studies and (4) advanced computational models (in silico and systems biology) on functional endpoints related to metabolism. Such interdisciplinary framework will help in deciphering EDs based on a mechanistic understanding of toxicity by providing and making available more effective alternative test methods relevant for human health that are in line with regulatory needs. Data generated in OBERON will also allow the development of novel adverse outcome pathways (AOPs). The assays will be pre-validated in order to select the test systems that will show acceptable performance in terms of relevance for the second step of the validation process, i.e., the inter-laboratory validation as ring tests. Therefore, the aim of the OBERON project is to support the organization for economic co-operation and development (OECD) conceptual framework for testing and assessment of single and/or mixture of EDs by developing specific assays not covered by the current tests, and to propose an IATA for ED-related metabolic disorder detection, which will be submitted to the Joint Research Center (JRC) and OECD community.

Adverse outcome pathways for chemical toxicity and their applications to workers' health: a literature review

OBJECTIVE AND METHODS

Various papers related to the application of adverse outcome pathways (AOPs) for the prevention of occupational disease were reviewed. The Internet was used as the primary tool to search for the necessary research data and information, using such online resources as Google Scholar, ScienceDirect, Scopus, NDSL, and PubMed. The key search terms were "adverse outcome pathway," "toxicology," "risk assessment," "human," "worker," "occupational safety and health," and so on.

RESULTS AND CONCLUSION

The aim of this paper is to explain the use of AOP for the understanding of chemical toxicity as a conceptual means and to predict the toxic mechanism. The tools of AOP have emerged as a forward-looking alternative to the existing chemical risk assessment paradigm. AOP is being applied to the assessment of acute toxicity and to chronic toxic chemicals in the workplace. Not only can it lead to breakthroughs in occupational and environmental cancer prevention, it is also widely used in chemical risk assessment and has led to breakthroughs in the prevention of occupational disease in the workplace.

Prediction of toxicity of secondary metabolites

The prediction of toxicological endpoints has gained broad acceptance; it is widely applied in early stages of drug discovery as well as for impurities obtained in the production of generic or equivalent products. In this work, we describe methodologies for the prediction of toxicological endpoints compounds, with a particular focus on secondary metabolites. Case studies include toxicity prediction of natural compound databases with anti-diabetic, anti-malaria and anti-HIV properties.

Validation of in vitro methods for human cytochrome P450 enzyme induction: Outcome of a multi-laboratory study

CYP enzyme induction is a sensitive biomarker for phenotypic metabolic competence of in vitro test systems; it is a key event associated with thyroid disruption, and a biomarker for toxicologically relevant nuclear receptor-mediated pathways. This paper summarises the results of a multi-laboratory validation study of two in vitro methods that assess the potential of chemicals to induce cytochrome P450 (CYP) enzyme activity, in particular CYP1A2, CYP2B6, and CYP3A4. The methods are based on the use of cryopreserved primary human hepatocytes (PHH) and human HepaRG cells. The validation study was coordinated by the European Union Reference Laboratory for Alternatives to Animal Testing of the European Commission's Joint Research Centre and involved a ring trial among six laboratories. The reproducibility was assessed within and between laboratories using a validation set of 13 selected chemicals (known human inducers and non-inducers) tested under blind conditions. The ability of the two methods to predict human CYP induction potential was assessed. Chemical space analysis confirmed that the selected chemicals are broadly representative of a diverse range of chemicals. The two methods were found to be reliable and relevant in vitro tools for the assessment of human CYP induction, with the HepaRG method being better suited for routine testing. Recommendations for the practical application of the two methods are proposed.

Prioritizing anthropogenic chemicals in drinking water and sources through combined use of mass spectrometry and ToxCast toxicity data

Advancements in high-resolution mass spectrometry based methods have enabled a shift from pure target analysis to target, suspect and non-target screening analyses to detect chemicals in water samples. The multitude of suspect chemicals thereby detected needs to be prioritized for further identification, prior to health risk assessment and potential inclusion into monitoring programs. Here, we compare prioritization of chemicals in Dutch water samples based on relative intensities only to prioritization including hazard information based on high-throughput in vitro toxicity data. Over 1000 suspects detected in sewage treatment plant effluent, surface water, groundwater and drinking water samples were ranked based on their relative intensities. Toxicity data availability and density in the ToxCast database were determined and visualized for these suspects, also in regard to water relevant mechanisms of toxicity. More than 500 suspects could be ranked using occurrence/hazard ratios based on more than 1000 different assay endpoints. The comparison showed that different prioritization strategies resulted in significantly different ranking, with only 2 suspects prioritized based on occurrence among the top 20 in the hazard ranking. We therefore propose a novel scheme that integrates both exposure and hazard data, and efficiently prioritizes which features need to be confidently identified first.

Next generation physiologically based kinetic (NG-PBK) models in support of regulatory decision making

The fields of toxicology and chemical risk assessment seek to reduce, and eventually replace, the use of animals for the prediction of toxicity in humans. In this context, physiologically based kinetic (PBK) modelling based on in vitro and in silico kinetic data has the potential to a play significant role in reducing animal testing, by providing a methodology capable of incorporating in vitro human data to facilitate the development of in vitro to in vivo extrapolation of hazard information. In the present article, we discuss the challenges in: 1) applying PBK modelling to support regulatory decision making under the toxicology and risk-assessment paradigm shift towards animal replacement; 2) constructing PBK models without in vivo animal kinetic data, while relying solely on in vitro or in silico methods for model parameterization; and 3) assessing the validity and credibility of PBK models built largely using non-animal data. The strengths, uncertainties, and limitations of PBK models developed using in vitro or in silico data are discussed in an effort to establish a higher degree of confidence in the application of such models in a regulatory context. The article summarises the outcome of an expert workshop hosted by the European Commission Joint Research Centre (EC-JRC) - European Union Reference Laboratory for Alternatives to Animal Testing (EURL ECVAM), on "Physiologically-Based Kinetic modelling in risk assessment - reaching a whole new level in regulatory decision-making" held in Ispra, Italy, in November 2016, along with results from an international survey conducted in 2017 and recently reported activities occurring within the PBK modelling field. The discussions presented herein highlight the potential applications of next generation (NG)-PBK modelling, based on new data streams.

Physiologically based mathematical models of nanomaterials for regulatory toxicology: A review

The development of physiologically based (PB) models to support safety assessments in the field of nanotechnology has grown steadily during the last decade. This review reports on the availability of PB models for toxicokinetic (TK) and toxicodynamic (TD) processes, including in vitro and in vivo dosimetry models applied to manufactured nanomaterials (MNs). In addition to reporting on the state-of-the-art in the scientific literature concerning the availability of physiologically based kinetic (PBK) models, we evaluate their relevance for regulatory applications, mainly considering the EU REACH regulation. First, we performed a literature search to identify all available PBK models. Then, we systematically reported the content of the identified papers in a tailored template to build a consistent inventory, thereby supporting model comparison. We also described model availability for physiologically based dynamic (PBD) and in vitro and in vivo dosimetry models according to the same template. For completeness, a number of classical toxicokinetic (CTK) models were also included in the inventory. The review describes the PBK model landscape applied to MNs on the basis of the type of MNs covered by the models, their stated applicability domain, the type of (nano-specific) inputs required, and the type of outputs generated. We identify the main assumptions made during model development that may influence the uncertainty in the final assessment, and we assess the REACH relevance of the available models within each model category. Finally, we compare the state of PB model acceptance for chemicals and for MNs. In general, PB model acceptance is limited by the absence of standardised reporting formats, psychological factors such as the complexity of the models, and technical considerations such as lack of blood:tissue partitioning data for model calibration/validation.

Advancing internal exposure and physiologically-based toxicokinetic modeling for 21st-century risk assessments

Scientifically sound, risk-informed evaluation of chemicals is essential to protecting public health. Systematically leveraging information from exposure, toxicology, and epidemiology studies can provide a holistic understanding of how real-world exposure to chemicals may impact the health of populations, including sensitive and vulnerable individuals and life-stages. Increasingly, public health policy makers are employing toxicokinetic (TK) modeling tools to integrate these data streams and predict potential human health impact. Development of a suite of tools for predicting internal exposure, including physiologically-based toxicokinetic (PBTK) models, is being driven by needs to address large numbers of data-poor chemicals efficiently, translate bioactivity, and mechanistic information from new in vitro test systems, and integrate multiple lines of evidence to enable scientifically sound, risk-informed decisions. New modeling approaches are being designed "fit for purpose" to inform specific decision contexts, with applications ranging from rapid screening of hundreds of chemicals, to improved prediction of risks during sensitive stages of development. New data are being generated experimentally and computationally to support these models. Progress to meet the demand for internal exposure and PBTK modeling tools will require transparent publication of models and data to build credibility in results, as well as opportunities to partner with decision makers to evaluate and build confidence in use of these for improved decisions that promote safe use of chemicals.

A framework for application of quantitative property-property relationships (QPPRs) in physiologically based pharmacokinetic (PBPK) models for high-throughput prediction of internal dose of inhaled organic chemicals

New generation of toxicological tests and assessment strategies require validated toxicokinetic data or models that are lacking for most chemicals. This study aimed at developing a quantitative property-property relationship (QPPR)-based human physiologically based pharmacokinetic (PBPK) modeling framework for high-throughput predictions of inhalation toxicokinetics of organic chemicals. A PBPK model was parameterized with QPPR-derived values for hepatic clearance (CL_h) and partition coefficients (P) [blood:air (P_ba) and tissue:air (P_ta) and tissue:blood (P_tb)]. The model was initially applied to an evaluation dataset of 40 organic chemicals in the applicability domain, and then to an expanded dataset of 249 organic chemicals from diverse chemical classes. 'Batch' analyses were performed for rapid assessments of hundreds of chemicals. The simulations of inhalation toxicokinetics following an 8-h exposure to 1 ppm of each chemical were successful. The mean ratios of their predicted-to-experimental values were within a factor of 1.36-2.36 for P_tb and 1.18 for CL_h, for 80% of the chemicals in the evaluation dataset. The predicted 24-h area under the venous blood concentration-time curve (AUC₂₄) values were within the predicted envelopes obtained while using experimental values of P_ba and considering either no or maximal hepatic extraction. The reliability analysis (based on combined sensitivity and uncertainty analyses) indicated that AUC₂₄ predictions for 55% of the expanded dataset were moderately to highly reliable, with 46% exhibiting highly reliable values. Overall, the modeling framework suggests that molecular structure and chemical properties can together be effectively used to obtain first-cut estimates of the toxicokinetics of data-poor organic chemicals for screening and prioritization purposes.

High-throughput screening and environmental risk assessment: State of the science and emerging applications

In 2007 the United States National Research Council (NRC) published a vision for toxicity testing in the 21st century that emphasized the use of in vitro high-throughput screening (HTS) methods and predictive models as an alternative to in vivo animal testing. In the present study we examine the state of the science of HTS and the progress that has been made in implementing and expanding on the NRC vision, as well as challenges to implementation that remain. Overall, significant progress has been made with regard to the availability of HTS data, aggregation of chemical property and toxicity information into online databases, and the development of various models and frameworks to support extrapolation of HTS data. However, HTS data and associated predictive models have not yet been widely applied in risk assessment. Major barriers include the disconnect between the endpoints measured in HTS assays and the assessment endpoints considered in risk assessments as well as the rapid pace at which new tools and models are evolving in contrast with the slow pace at which regulatory structures change. Nonetheless, there are opportunities for environmental scientists and policymakers alike to take an impactful role in the ongoing development and implementation of the NRC vision. Six specific areas for scientific coordination and/or policy engagement are identified. Environ Toxicol Chem 2019;38:12-26. Published 2018 Wiley Periodicals Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.

Capturing the applicability of in vitro-in silico membrane transporter data in chemical risk assessment and biomedical research

Costs, scientific and ethical concerns related to animal tests for regulatory decision-making have stimulated the development of alternative methods. When applying alternative approaches, kinetics have been identified as a key element to consider. Membrane transporters affect the kinetic processes of absorption, distribution, metabolism and excretion (ADME) of various compounds, such as drugs or environmental chemicals. Therefore, pharmaceutical scientists have intensively studied transporters impacting drug efficacy and safety. Besides pharmacokinetics, transporters are considered as major determinant of toxicokinetics, potentially representing an essential piece of information in chemical risk assessment. To capture the applicability of transporter data for kinetic-based risk assessment in non-pharmaceutical sectors, the EU Reference Laboratory for Alternatives to Animal Testing (EURL ECVAM) created a survey with a view of identifying the improvements needed when using in vitro and in silico methods. Seventy-three participants, from different sectors and with various kinds of expertise, completed the survey. The results revealed that transporters are investigated mainly during drug development, but also for risk assessment purposes of food and feed contaminants, industrial chemicals, cosmetics, nanomaterials and in the context of environmental toxicology, by applying both in vitro and in silico tools. However, to rely only on alternative methods for chemical risk assessment, it is critical that the data generated by in vitro and in silico methods are scientific integer, reproducible and of high quality so that they are trusted by decision makers and used by industry. In line, the respondents identified various challenges related to the interpretation and use of transporter data from non-animal methods. Overall, it was determined that a combined mechanistically-anchored in vitro-in silico approach, validated against available human data, would gain confidence in using transporter data within an animal-free risk assessment paradigm. Finally, respondents involved primarily in fundamental research expressed lower confidence in non-animal studies to unravel complex transporter mechanisms.