Hazard Assessment Of Chemicals Research Articles

FutureTox IV Workshop Summary: Predictive Toxicology for Healthy Children.

FutureTox IV, a Society of Toxicology Contemporary Concepts in Toxicology workshop, was held in November 2018. Building upon FutureTox I, II, and III, this conference focused on the latest science and technology for in vitro profiling and in silico modeling as it relates to predictive developmental and reproductive toxicity (DART). Publicly available high-throughput screening data sets are now available for broad in vitro profiling of bioactivities across large inventories of chemicals. Coupling this vast amount of mechanistic data with a deeper understanding of molecular embryology and post-natal development lays the groundwork for using new approach methodologies (NAMs) to evaluate chemical toxicity, drug efficacy, and safety assessment for embryo-fetal development. NAM is a term recently adopted in reference to any technology, methodology, approach, or combination thereof that can be used to provide information on chemical hazard and risk assessment to avoid the use of intact animals (U.S. Environmental Protection Agency [EPA], Strategic plan to promote the development and implementation of alternative test methods within the tsca program, 2018, https://www.epa.gov/sites/production/files/2018-06/documents/epa_alt_strat_plan_6-20-18_clean_final.pdf). There are challenges to implementing NAMs to evaluate chemicals for developmental toxicity compared with adult toxicity. This forum article reviews the 2018 workshop activities, highlighting challenges and opportunities for applying NAMs for adverse pregnancy outcomes (eg, preterm labor, malformations, low birth weight) as well as disorders manifesting postnatally (eg, neurodevelopmental impairment, breast cancer, cardiovascular disease, fertility). DART is an important concern for different regulatory statutes and test guidelines. Leveraging advancements in such approaches and the accompanying efficiencies to detecting potential hazards to human development are the unifying concepts toward implementing NAMs in DART testing. Although use of NAMs for higher level regulatory decision making is still on the horizon, the conference highlighted novel testing platforms and computational models that cover multiple levels of biological organization, with the unique temporal dynamics of embryonic development, and novel approaches for estimating toxicokinetic parameters essential in supporting in vitro to in vivo extrapolation.

Epigenetic biomarkers as tools for chemical hazard assessment: Gene expression profiling using the model Danio rerio

Recent reports raise the concern that exposure to several environmental chemicals may induce persistent changes that go beyond the exposed organisms, being transferred to subsequent generations even in the absence of the original chemical insult. These changes in subsequent non-exposed generations have been related to epigenetic changes. Although highly relevant for hazard and risk assessment, biomarkers of epigenetic modifications that can be associated with adversity, are still not integrated into hazard assessment frameworks. Here, in order to validate new biomarkers of epigenetic modifications in a popular animal model, zebrafish embryos were exposed to different concentrations of Bisphenol A (0.01, 0.1, 1 and 10 mg/L) and Valproic Acid (0.8, 4, 20 and 100 mg/L), two chemicals reported to alter the modulation of the epigenome. Morphological abnormalities and epigenetic changes were assessed at 80 hours-post fertilization, including DNA global methylation and gene expression of both DNA and histone epigenetic modifications. Gene expression changes were detected at concentrations below those inducing morphological abnormalities. These results further support the importance of combining epigenetic biomarkers with apical endpoints to improve guidelines for chemical testing and hazard assessment, and favour the integration of new biomarkers of epigenetic modifications into the standardized OECD test guideline 236 with zebrafish embryos.

In silico Predictive Phytotoxicity Modeling of lactuca sativa of Personal Care Product Ingredients

Detection and evaluation of environmental toxicity of emerging contaminants like personal care product (PCP) additives are the thrust area in the recent day risk assessment of chemical hazards. The phytotoxicity assay is usually performed to identify and quantify the environmental impact of pollutants. In this background, the authors have developed in silico predictive phytotoxicity models for 36 PCP ingredients using 2D molecular descriptors using multiple linear regression as a chemometric tool. The statistical validation parameters assured the robustness of the developed models according to OECD guidelines. The mechanistic output of the models indicated the importance of the partition coefficient (CrippenLogP) and molecular hydrophilicity. The applicability domain explicitly defines the reliability of the application of the developed models for the unknown PCP ingredients in a consensus manner. The first reported predictive phytotoxicity models for PCP ingredients can help depict the environmental impacts of these classes of emerging pollutants.

An efficient method for identifying the chemical hazards of exception‐handling tasks and processes derived from abnormal process conditions

AbstractHazards that result from inappropriate exception‐handling tasks and processes performed in response to abnormal process conditions are not easily identified or cannot be identified at all, using only traditional hazard identification methods, such as normal hazard and operability (HAZOP) studies, failure mode and effects analysis, what‐if analysis, procedural HAZOP, and job safety analysis. This study thus proposes an efficient chemical hazard‐based method for identifying such potential hazards. The method comprises a checklist for identifying intrinsic chemical hazards and the exception tasks and processes which may initiate such hazards and a worksheet for performing the chemical hazard assessment of the identified exception tasks and processes. The checklist provides management with a useful tool for identifying the exception tasks and processes which may result in chemical hazards. Meanwhile, the hazard assessment worksheet provides an effective tool for evaluating the potential chemical hazards of the identified exception‐handling tasks and processes, assessing the effectiveness of existing safeguards for preventing and reducing such hazards, and drawing up additional recommendations if required. The operation of the proposed method is demonstrated through two case studies.

Accounting for Precision Uncertainty of Toxicity Testing: Methods to Define Borderline Ranges and Implications for Hazard Assessment of Chemicals

For hazard classifications of chemicals, continuous data from animal‐ or nonanimal testing methods are often dichotomized into binary positive/negative outcomes by defining classification thresholds (CT). Experimental data are, however, subject to biological and technical variability. Each test method's precision is limited resulting in uncertainty of the positive/negative outcome if the experimental result is close to the CT. Borderline ranges (BR) around the CT were suggested, which represent ranges in which the study result is ambiguous, that is, positive or negative results are equally likely. The BR reflects a method's precision uncertainty. This article explores and compares different approaches to quantify the BR. Besides using the pooled standard deviation, we determine the BR by means of the median absolute deviation (MAD), with a sequential combination of both methods, and by using nonparametric bootstrapping. Furthermore, we quantify the BR for different hazardous effects, including nonanimal tests for skin corrosion, eye irritation, skin irritation, and skin sensitization as well as for an animal test on skin sensitization (the local lymph node assay, LLNA). Additionally, for one method (direct peptide reactivity assay) the BR was determined experimentally and compared to calculated BRs. Our results demonstrate that (i) the precision of the methods is determining the size of their BRs, (ii) there is no “perfect” method to derive a BR, alas, (iii) a consensus on BR is needed to account for the limited precision of testing methods.

High-throughput analyses and Bayesian network modeling highlight novel epigenetic Adverse Outcome Pathway networks of DNA methyltransferase inhibitor mediated transgenerational effects

A number of epigenetic modulating chemicals are known to affect multiple generations of a population from a single ancestral exposure, thus posing transgenerational hazards. The present study aimed to establish a high-throughput (HT) analytical workflow for cost-efficient concentration-response analysis of epigenetic and phenotypic effects, and to support the development of novel Adverse Outcome Pathway (AOP) networks for DNA methyltransferase (DNMT) inhibitor-mediated transgenerational effects on aquatic organisms. The model DNMT inhibitor 5-azacytidine (5AC) and the model freshwater crustacean Daphnia magna were used to generate new experimental data and served as prototypes to construct AOPs for aquatic organisms. Targeted HT bioassays (DNMT ELISA, MS-HRM and qPCR) in combination with multigenerational ecotoxicity tests revealed concentration-dependent transgenerational (F0-F3) effects of 5AC on total DNMT activity, DNA promoter methylation, gene body methylation, gene transcription and reproduction. Top sensitive toxicity pathways related to 5AC exposure, such as apoptosis and DNA damage responses were identified in both F0 and F3 using Gaussian Bayesian network modeling. Two novel epigenetic AOP networks on DNMT inhibitor mediated one-generational and transgenerational effects were developed for aquatic organisms and assessed for the weight of evidence. The new HT analytical workflow and AOPs can facilitate future ecological hazard assessment of epigenetic modulating chemicals.

Evaluation of a multiplexed, multispecies nuclear receptor assay for chemical hazard assessment

Sensitivity to potential endocrine disrupting chemicals in the environment varies across species and is influenced by sequence conservation of their nuclear receptor targets. Here, we evaluated a multiplexed, in vitro assay testing receptors relevant to endocrine and metabolic disruption from five species. The TRANS-FACTORIAL™ system of human nuclear receptors was modified to include additional species: mouse (Mus musculus), frog (Xenopus laevis), zebrafish (Danio rerio), chicken (Gallus gallus), and turtle (Chrysemys picta). Receptors regulating endocrine function and xenobiotic recognition were included, specifically: ERα, ERβ, AR, TRα, TRβ, PPARγ and PXR. The assay, ECOTOX-FACTORIAL™, was evaluated with 191 chemicals enriched with known receptor ligands. Hierarchical clustering of potency values demonstrated strong coherence of receptor families. Interspecies comparisons of responses within a receptor family showed moderate to high concordance for potencies under 50 μM. PPARγ showed high concordance between mammalian species, 89%, but only 63% between mammalian and zebrafish. For chemicals with potencies below 1 μM, concordances were 89–100% for all receptors except PXR. Concordance showed a strong positive relationship to ligand-binding domain sequence similarity and critical amino acid residues obtained by the Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool. In combination with SeqAPASS, ECOTOX-FACTORIAL may provide efficient screening of important receptors to identify species of high priority for effects monitoring.

Characterization of the Mercapturic Acid Pathway, an Important Phase II Biotransformation Route, in a Zebrafish Embryo Cell Line.

In view of the steadily increasing number of chemical compounds used in various products and applications, high-throughput toxicity screening techniques can help meeting the needs of 21st century risk assessment. Zebrafish (Danio rerio), especially its early life stages, are increasingly used in such screening efforts. In contrast, cell lines derived from this model organism have received less attention so far. A conceivable reason is the limited knowledge about their overall capacity to biotransform chemicals and the spectrum of expressed biotransformation pathways. One important biotransformation route is the mercapturic acid pathway, which protects organisms from harmful electrophilic compounds. The fully functional pathway involves a succession of several enzymatic reactions. To investigate the mercapturic acid pathway performance in the zebrafish embryonic cell line, PAC2, we analyzed the biotransformation products of the reactions comprising this pathway in the cells exposed to a nontoxic concentration of the reference substrate, 1-chloro-2,4-dinitrobenzene (CDNB). Additionally, we used targeted proteomics to measure the expression of cytosolic glutathione S-transferases (GSTs), the enzyme family catalyzing the first reaction in this pathway. Our results reveal that the PAC2 cell line expresses a fully functional mercapturic acid pathway. All but one of the intermediate CDNB biotransformation products were identified. The presence of the active mercapturic acid pathway in this cell line was further supported by the expression of a large palette of GST enzyme classes. Although the enzymes of the class alpha, one of the dominant GST classes in the zebrafish embryo, were not detected, this did not seem to affect the capacity of the PAC2 cells to biotransform CDNB. Our data provide an important contribution toward using zebrafish cell lines, specifically PAC2, for animal-free high- throughput screening in toxicology and chemical hazard assessment.

An ontology for developmental processes and toxicities of neural tube closure

In recent years, the development and implementation of animal-free approaches to chemical and pharmaceutical hazard and risk assessment has taken off. Alternative approaches are being developed starting from the perspective of human biology and physiology.Neural tube closure is a vital step that occurs early in human development. Correct closure of the neural tube depends on a complex interplay between proteins along a number of protein concentration gradients. The sensitivity of neural tube closure to chemical disturbance of signalling pathways such as the retinoid pathway, is well known. To map the pathways underlying neural tube closure, literature data on the molecular regulation of neural tube closure were collected. As the process of neural tube closure is highly conserved in vertebrates, the extensive literature available for the mouse was used whilst considering its relevance for humans. Thus, important cell compartments, regulatory pathways, and protein interactions essential for neural tube closure under physiological circumstances were identified and mapped. An understanding of aberrant processes leading to neural tube defects (NTDs) requires detailed maps of neural tube embryology, including the complex genetic signals and responses underlying critical cellular dynamical and biomechanical processes. The retinoid signaling pathway serves as a case study for this ontology because of well-defined crosstalk with the genetic control of neural tube patterning and morphogenesis. It is a known target for mechanistically-diverse chemical structures that disrupt neural tube closureThe data presented in this manuscript will set the stage for constructing mathematical models and computer simulation of neural tube closure for human-relevant AOPs and predictive toxicology.

Optimization of a pre-metabolization procedure using rat liver S9 and cell-extracted S9 in the Ames fluctuation test

Many environmental pollutants pose a toxicological hazard only after metabolic activation. In vitro bioassays using cell lines or bacteria have often no or reduced metabolic activity, which impedes their use in the risk assessment. To improve the predictive capability of in vitro assays, external metabolization systems like the liver S9 fraction are frequently combined with in vitro toxicity assays. While it is typical for S9 fractions that samples and testing systems are combined in the same exposure system, we propose to separate the metabolism step and toxicity measurement. This allows for a modular combination of metabolic activation by enzymes isolated from rat liver (S9) or a biotechnological alternative (ewoS9R) with in vitro bioassays that lack metabolic capacity. Benzo(a)pyrene and 2-aminoanthracene were used as model compounds to optimize the conditions for the S9 metabolic degradation/activation step. The Ames assay with Salmonella typhimurium strains TA98 and TA100 was applied to validate the set-up of decoupling the S9 activation/metabolism from the bioassay system. S9 protein concentration of 0.25 mgprotein/mL, a supplement of 0.13 mM NADPH and a pre-incubation time of 100 min are recommended for activation of samples prior to dosing them to in vitro bioassays using the regular dosing protocols of the respective bioassay. EwoS9R performed equally well as Moltox S9, which is a step forward in developing true animal-free in vitro bioassays. After pre-incubation with S9 fraction, chemicals induced bacteria revertants in both the TA98 and the TA100 assay as efficiently as the standard Ames assay. The pre-incubation of chemicals with S9 fraction could serve for a wide range of cellular in vitro assays to efficiently combine activation and toxicity measurement, which may greatly facilitate the application of these assays for chemical hazard assessment and monitoring of environmental samples.

Development of machine learning based prediction models for hazardous properties of chemical mixtures

Lower flammability limit (LFL), upper flammability limit (UFL), auto-ignition temperature (AIT) and flash point (FP) are crucial hazardous properties for fire and explosion hazards assessment and consequence analysis. In this study, a comprehensive prediction model set was constructed by using expanded chemical mixture databases of chemical mixture hazardous properties. Machine learning based gradient boosting quantitative structure-property relationship (GB-QSPR) method is implemented for the first time to improve the model performance and prediction accuracy. The result shows that all developed models have significantly higher accuracy than other regular QSPR models, with the 5-fold cross-validation RMSE of LFL, UFL, AIT, and FP models being 1.06, 1.14, 1.08, and 1.17, respectively. All developed QSPR models can be used to estimate reliable chemical mixture hazardous properties and provide useful guidance in chemical mixture hazard assessment and consequence analysis.

Yolk Sac of Zebrafish Embryos as Backpack for Chemicals?

The zebrafish embryo (Danio rerio) has developed into one of the most important nonsentient animal models for the hazard assessments of chemicals, but the processes governing its toxicokinetics (TK) are poorly understood. This study compares the uptake of seven test compounds into the embryonic body and the yolk sac of the zebrafish embryo using TK experiments, a dialysis approach, thermodynamic calculations, and kinetic modeling. Experimental data show that between 95% (4-iodophenol) and 67% (carbamazepine) of the total internal amount in 26 h post fertilization (hpf) embryos and between 80 and 49% in 74 hpf embryos were found in the yolk. Thus, internal concentrations determined for the whole embryo overestimate the internal concentration in the embryonic body: for the compounds of this study, up to a factor of 5. Partition coefficients for the embryonic body and a one-compartment model with diffusive exchange were calculated for the neutral test compounds and agreed reasonably with the experimental data. For prevalently ionic test compounds at exposure pH (bromoxynil, paroxetine), however, the extent and the speed of uptake were low and could not be modeled adequately. A better understanding of the TK of ionizable test compounds is essential to allow assessment of the validity of this organismic test system for ionic test compounds.

Culture Conditions Affect Chemical-Induced Developmental Toxicity In Vitro: The Case of Folic Acid, Methionine and Methotrexate in the Neural Embryonic Stem Cell Test.

In vitro tests are increasingly applied in chemical hazard assessment. Basic culture conditions may affect the outcome of in vitro tests and should be optimised to reduce false predictions. The neural embryonic stem cell test (ESTn) can predict early neurodevelopmental effects of chemicals, as it mimics the differentiation of stem cells towards the neuroectodermal lineage. Normal early neural differentiation depends crucially on folic acid (FA) and methionine (MET), both elements of the one-carbon (1C) cycle. The aim of this study was to assess the concentration-dependent influence of FA and MET on neural differentiation in the ESTn, and its consequences for assay sensitivity to methotrexate (MTX), a compound that interferes with the 1C cycle. Neural differentiation was inhibited below 0.007 mM and above 0.22 mM FA, while both stem cell viability (< 0.097 mM, > 1.52 mM) and neural differentiation (< 0.181 mM, > 1.35 mM) were affected when changing MET concentrations. A 10-day exposure to 13 nM MTX inhibited neural differentiation, especially in FA- and MET-deficient conditions. However, a 24-hour exposure to 39 nM MTX decreased neural cell and neural crest cell differentiation markers only when the concentration of FA in the medium was three times the standard concentration, which was expected to have a protective effect against MTX. These results show the importance of nutrient concentrations, exposure scenarios and timing of read-outs for cell differentiation and compound sensitivity in the ESTn. Caution should be taken when interpreting results from a single in vitro test, especially when extrapolating to effects on complex morphogenetic processes, like neural tube development.

Optimum concentration-response curve metrics for supervised selection of discriminative cellular phenotypic endpoints for chemical hazard assessment.

High-content imaging (HCI) provides quantitative and information-rich measurements of chemical effects on human in vitro cell models. Identification of discriminative phenotypic endpoints from cellular features obtained from HCI is required for accurate assessments of potential chemical hazards. However, the use of suboptimal metrics to quantify the concentration-response curves (CRC) of chemicals based on these features may obscure discriminative features, and lead to non-predictive endpoints and poor chemical classifications or hazard assessments. Here, we present a systematic and data-driven study on the performances of different CRC metrics in identifying image-based phenotypic features that can accurately classify the effects of reference chemicals with known in vivo toxicities. We studied four previous HCI in vitro nephro- or pulmono-toxicity datasets, which contain phenotypic feature measurements from different cell and feature types. Within a feature type, we found that efficacy metrics at higher chemical concentrations tend to give higher classification accuracy, whereas potency metrics do not have obvious trends across different response levels. Across different cell and feature types, efficacy metrics generally gave higher classification accuracy than potency metrics and area under the curve (AUC). Our results suggest that efficacy metrics, especially at higher concentrations, are more likely to help us to identify discriminative phenotypic endpoints. Therefore, HCI experiments for toxicological applications should include measurements at sufficiently high chemical concentrations, and efficacy metrics should always be analyzed. The identified features may be used as specific toxicity endpoints for further chemical hazard assessment.

Application of an occupational health risk assessment method in dioctyl phthalate producing enterprise

Objective: To find the risk assessment model of [di (2-ethylhexyl) phthalate, DEHP] fitting well for producing companies. Methods: The Cluster Sampling method was used in selecting a DEHP producing company in the occupational health and workplace environment monitoring study conducted between July and August in 2017. Data was collected by site evaluating and workplace environment monitoring. According to GBZ/T 298-2017《Technical Guidelines for Occupational Health Risk Assessment of Chemical Hazards in the Workplace》, a qualitative assessment method and a semi-quantitative comprehensive index method were chosen as the models and were compared. Results: The occupational health risk of the two methods rated 4 (high risk) and 2 (negligible risk) . Conclusion: The semi-quantitative comprehensive index method is more comprehensive and accurate when used to assess the occupational health risk caused by DEHP.

Variability in in vivo studies: Defining the upper limit of performance for predictions of systemic effect levels

New approach methodologies (NAMs) for chemical hazard assessment are often evaluated via comparison to animal studies; however, variability in animal study data limits NAM accuracy. The US EPA Toxicity Reference Database (ToxRefDB) enables consideration of variability in effect levels, including the lowest effect level (LEL) for a treatment-related effect and the lowest observable adverse effect level (LOAEL) defined by expert review, from subacute, subchronic, chronic, multi-generation reproductive, and developmental toxicity studies. The objectives of this work were to quantify the variance within systemic LEL and LOAEL values, defined as potency values for effects in adult or parental animals only, and to estimate the upper limit of NAM prediction accuracy. Multiple linear regression (MLR) and augmented cell means (ACM) models were used to quantify the total variance, and the fraction of variance in systemic LEL and LOAEL values explained by available study descriptors (e.g., administration route, study type). The MLR approach considered each study descriptor as an independent contributor to variance, whereas the ACM approach combined categorical descriptors into cells to define replicates. Using these approaches, total variance in systemic LEL and LOAEL values (in log10-mg/kg/day units) ranged from 0.74 to 0.92. Unexplained variance in LEL and LOAEL values, approximated by the residual mean square error (MSE), ranged from 0.20 to 0.39. Considering subchronic, chronic, or developmental study designs separately resulted in similar values. Based on the relationship between MSE and R-squared for goodness-of-fit, the maximal R-squared may approach 55 to 73% for a NAM-based predictive model of systemic toxicity using these data as reference. The root mean square error (RMSE) ranged from 0.47 to 0.63 log10-mg/kg/day, depending on dataset and regression approach, suggesting that a two-sided minimum prediction interval for systemic effect levels may have a width of 58 to 284-fold. These findings suggest quantitative considerations for building scientific confidence in NAM-based systemic toxicity predictions.

Biotransformation Capacity of Zebrafish (Danio rerio) Early Life Stages: Functionality of the Mercapturic Acid Pathway.

Zebrafish (Danio rerio) early life stages offer a versatile model system to study the efficacy and safety of drugs or other chemicals with regard to human and environmental health. This is because, aside from the well-characterized genome of zebrafish and the availability of a broad range of experimental and computational research tools, they are exceptionally well suited for high-throughput approaches. Yet, one important pharmacokinetic aspect is thus far only poorly understood in zebrafish embryo and early larvae: their biotransformation capacity. Especially, biotransformation of electrophilic compounds is a critical pathway because they easily react with nucleophile molecules, such as DNA or proteins, potentially inducing adverse health effects. To combat such adverse effects, conjugation reactions with glutathione and further processing within the mercapturic acid pathway have evolved. We here explore the functionality of this pathway in zebrafish early life stages using a reference substrate (1-chloro-2,4-dinitrobenzene, CDNB). With this work, we show that zebrafish embryos can biotransform CDNB to the respective glutathione conjugate as early as 4 h postfertilization. At all examined life stages, the glutathione conjugate is further biotransformed to the last metabolite of the mercapturic acid pathway, the mercapturate, which is slowly excreted. Being able to biotransform electrophiles within the mercapturic acid pathway shows that zebrafish early life stages possess the potential to process xenobiotic compounds through glutathione conjugation and the formation of mercapturates. The presence of this chemical biotransformation and clearance route in zebrafish early life stages supports the application of this model in toxicology and chemical hazard assessment.

InterPred: a webtool to predict chemical autofluorescence and luminescence interference.

High-throughput screening (HTS) research programs for drug development or chemical hazard assessment are designed to screen thousands of molecules across hundreds of biological targets or pathways. Most HTS platforms use fluorescence and luminescence technologies, representing more than 70% of the assays in the US Tox21 research consortium. These technologies are subject to interferent signals largely explained by chemicals interacting with light spectrum. This phenomenon results in up to 5-10% of false positive results, depending on the chemical library used. Here, we present the InterPred webserver (version 1.0), a platform to predict such interference chemicals based on the first large-scale chemical screening effort to directly characterize chemical-assay interference, using assays in the Tox21 portfolio specifically designed to measure autofluorescence and luciferase inhibition. InterPred combines 17 quantitative structure activity relationship (QSAR) models built using optimized machine learning techniques and allows users to predict the probability that a new chemical will interfere with different combinations of cellular and technology conditions. InterPred models have been applied to the entire Distributed Structure-Searchable Toxicity (DSSTox) Database (∼800,000 chemicals). The InterPred webserver is available at https://sandbox.ntp.niehs.nih.gov/interferences/.

Evaluation of a Bayesian Network for Strengthening the Weight of Evidence to Predict Acute Fish Toxicity from Fish Embryo Toxicity Data

The use of fish embryo toxicity (FET) data for hazard assessments of chemicals, in place of acute fish toxicity (AFT) data, has long been the goal for many environmental scientists. The FET test was first proposed as a replacement to the standardized AFT test nearly 15 y ago, but as of now, it has still not been accepted as a standalone replacement by regulatory authorities such as the European Chemicals Agency (ECHA). However, the ECHA has indicated that FET data can be used in a weight of evidence (WoE) approach, if enough information is available to support the conclusions related to the hazard assessment. To determine how such a WoE approach could be applied in practice has been challenging. To provide a conclusive WoE for FET data, we have developed a Bayesian network (BN) to incorporate multiple lines of evidence to predict AFT. There are 4 different lines of evidence in this BN model: 1) physicochemical properties, 2) AFT data from chemicals in a similar class or category, 3) ecotoxicity data from other trophic levels of organisms (e.g., daphnids and algae), and 4) measured FET data. The BN model was constructed from data obtained from a curated database and conditional probabilities assigned for the outcomes of each line of evidence. To evaluate the model, 20 data-rich chemicals, containing a minimum of 3 AFT and FET test data points, were selected to ensure a suitable comparison could be performed. The results of the AFT predictions indicated that the BN model could accurately predict the toxicity interval for 80% of the chemicals evaluated. For the remaining chemicals (20%), either daphnids or algae were the most sensitive test species, and for those chemicals, the daphnid or algal hazard data would have driven the environmental classification. Integr Environ Assess Manag 2020;00:1-9. © 2020 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Is there a rationale for direct dosing of chemicals to nursing pups in the EOGRTS (OECD 443)?

In OECD guideline 443 – Extended One Generation Reproductive Toxicity Study (EOGRTS) – to be used for testing industrial and agrochemicals, it has been indicated that careful consideration of benefits and disadvantages should be made prior to conducting direct-dosing studies in nursing pups. Nursing pups will not be directly dosed in dietary and drinking water studies whereas in oral gavage studies this possibility exists. Besides the risk of intubation trauma and overdosing due to direct exposure and exposure via the mother's milk, direct dosing could lead to a different hazard assessment of chemicals depending on the choice of the route of administration. In addition, in case of industrial and agrochemicals used in industrial or professional settings only, there will never be direct exposure of newborns. Moreover, direct dosing of nursing pups is an artificial, non-physiological, route of exposure and as such it would hamper risk assessment. It should therefore only be considered in exceptional cases and justified on a case-by-case approach.