Profiling the ToxCast Library With a Pluripotent Human (H9) Stem Cell Line-Based Biomarker Assay for Developmental Toxicity

Strengths and limitations of the worm development and activity test (wDAT) as a chemical screening tool for developmental hazards

The worm Development and Activity Test (wDAT) measures C. elegans developmental milestone acquisition timing and stage-specific spontaneous locomotor activity (SLA). Previously, the wDAT identified developmental delays and SLA level changes in C. elegans with mammalian developmental toxicants arsenic, lead, and mercury. 5-fluorouracil (5FU), cyclophosphamide (CP), hydroxyurea (HU), and ribavirin (RV) are teratogens that also induce growth retardation in developing mammals. In at least some studies on each of these chemicals, fetal weight reductions were seen at mammalian exposures below those that had teratogenic effects, suggesting that screening for developmental delay in a small alternative whole-animal model could act as a general toxicity endpoint to identify chemicals for further testing for more specific adverse developmental outcomes. Consistent with mammalian developmental effects, 5FU, HU, and RV were associated with developmental delays with the wDAT. Exposures associated with developmental delay induced hypoactivity with 5FU and HU, but slight hyperactivity with RV. CP is a prodrug that requires bioactivation by cytochrome P450s for both therapeutic and toxic effects. CP tests as a false negative in several in vitro assays, and it was also a false negative with the wDAT. These results suggest that the wDAT has the potential to identify some developmental toxicants, and that a positive wDAT result with an unknown may warrant further testing in mammals. Further assessment with larger panels of positive and negative controls will help qualify the applicability and utility of this C. elegans wDAT assay within toxicity test batteries or weight of evidence approaches for developmental toxicity assessment.

Engineering a computable epiblast for in silico modeling of developmental toxicity

Developmental hazard evaluation is an important part of assessing chemical risks during pregnancy. Toxicological outcomes from prenatal testing in pregnant animals result from complex chemical-biological interactions, and while New Approach Methods (NAMs) based on in vitro bioactivity profiles of human cells offer promising alternatives to animal testing, most of these assays lack cellular positional information, physical constraints, and regional organization of the intact embryo. Here, we engineered a fully computable model of the embryonic disc in the CompuCell3D.org modeling environment to simulate epithelial-mesenchymal transition (EMT) of epiblast cells and self-organization of mesodermal domains (chordamesoderm, paraxial, lateral plate, posterior/extraembryonic). Mesodermal fate is modeled by synthetic activity of the BMP4-NODAL-WNT signaling axis. Cell position in the epiblast determines timing with respect to EMT for 988 computational cells in the computer model. An autonomous homeobox (Hox) clock hidden in the epiblast is driven by WNT-FGF4-CDX signaling. Executing the model renders a quantitative cell-level computation of mesodermal fate and consequences of perturbation based on known biology. For example, synthetic perturbation of the control network rendered altered phenotypes (cybermorphs) mirroring some aspects of experimental mouse embryology, with electronic knockouts, under-activation (hypermorphs) or over-activation (hypermorphs) particularly affecting the size and specification of the posterior mesoderm. This foundational model is trained on embryology but capable of performing a wide variety of toxicological tasks conversing through anatomical simulation to integrate in vitro chemical bioactivity data with known embryology. It is amenable to quantitative simulation for probabilistic prediction of early developmental toxicity.

Community-Engaged Research and the Use of Open Access ToxVal/ToxRef In Vivo Databases and New Approach Methodologies (NAM) to Address Human Health Risks From Environmental Contaminants

BACKGROUND

The paper analyzes opportunities for integrating Open access resources (Abstract Sifter, US EPA and NTP Toxicity Value and Toxicity Reference [ToxVal/ToxRefDB]) and New Approach Methodologies (NAM) integration into Community Engaged Research (CEnR).

METHODS

CompTox Chemicals Dashboard and Integrated Chemical Environment with in vivo ToxVal/ToxRef and NAMs (in vitro) databases are presented in three case studies to show how these resources could be used in Pilot Projects involving Community Engaged Research (CEnR) from the University of California, Davis, Environmental Health Sciences Center.

RESULTS

Case #1 developed a novel assay methodology for testing pesticide toxicity. Case #2 involved detection of water contaminants from wildfire ash and Case #3 involved contaminants on Tribal Lands. Abstract Sifter/ToxVal/ToxRefDB regulatory data and NAMs could be used to screen/prioritize risks from exposure to metals, PAHs and PFAS from wildfire ash leached into water and to investigate activities of environmental toxins (e.g., pesticides) on Tribal lands. Open access NAMs and computational tools can apply to detection of sensitive biological activities in potential or known adverse outcome pathways to predict points of departure (POD) for comparison with regulatory values for hazard identification. Open access Systematic Empirical Evaluation of Models or biomonitoring exposures are available for human subpopulations and can be used to determine bioactivity (POD) to exposure ratio to facilitate mitigation.

CONCLUSIONS

These resources help prioritize chemical toxicity and facilitate regulatory decisions and health protective policies that can aid stakeholders in deciding on needed research. Insights into exposure risks can aid environmental justice and health equity advocates.

Stem cell-based approaches for developmental neurotoxicity testing

Neurotoxicants are substances that can lead to adverse structural or functional effects on the nervous system. These can be chemical, biological, or physical agents that can cross the blood brain barrier to damage neurons or interfere with complex interactions between the nervous system and other organs. With concerns regarding social policy, public health, and medicine, there is a need to ensure rigorous testing for neurotoxicity. While the most common neurotoxicity tests involve using animal models, a shift towards stem cell-based platforms can potentially provide a more biologically accurate alternative in both clinical and pharmaceutical research. With this in mind, the objective of this article is to review both current technologies and recent advancements in evaluating neurotoxicants using stem cell-based approaches, with an emphasis on developmental neurotoxicants (DNTs) as these have the most potential to lead to irreversible critical damage on brain function. In the next section, attempts to develop novel predictive model approaches for the study of both neural cell fate and developmental neurotoxicity are discussed. Finally, this article concludes with a discussion of the future use of in silico methods within developmental neurotoxicity testing, and the role of regulatory bodies in promoting advancements within the space.

Next generation risk assessment for occupational chemical safety - A real world example with sodium-2-hydroxyethane sulfonate

Next Generation Risk Assessment (NGRA) is an exposure-led approach to safety assessment that uses New Approach Methodologies (NAMs). Application of NGRA has been largely restricted to assessments of consumer use of cosmetics and is not currently implemented in occupational safety assessments, e.g. under EU REACH. By contrast, a large proportion of regulatory worker safety assessments are underpinned by toxicological studies using experimental animals. Consequently, occupational safety assessment represents an area that would benefit from increasing application of NGRA to safety decision making. Here, a workflow for conducting NGRA under an occupational safety context was developed, which is illustrated with a case study chemical; sodium 2-hydroxyethane sulphonate (sodium isethionate or SI). Exposures were estimated using a standard occupational exposure model following a comprehensive life cycle assessment of SI and considering factory-specific data. Outputs of this model were then used to estimate internal exposures using a Physiologically Based Kinetic (PBK) model, which was constructed with SI specific Absorption, Distribution, Metabolism and Excretion (ADME) data. PBK modelling indicated a worst-case plasma maximum concentration (Cmax) of 0.8 μM across the SI life cycle. SI bioactivity was assessed in a battery of NAMs relevant to systemic, reproductive, and developmental toxicity; a cell stress panel, high throughput transcriptomics in three cell lines (HepG2, HepaRG and MCF-7 cells), pharmacological profiling and specific assays relating to developmental toxicity (Reprotracker and devTOX quickPredict). Points of Departure (PoDs) for SI ranged from 104 to 5044 µM. Cmax values obtained from PBK modelling of occupational exposures to SI were compared with PoDs from the bioactivity assays to derive Bioactivity Exposure Ratios (BERs) which demonstrated the safety for workers exposed to SI under current levels of factory specific risk management. In summary, the tiered and iterative workflow developed here represents an opportunity for integrating non animal approaches for a large subset of substances for which systemic worker safety assessment is required. Such an approach could be followed to ensure that animal testing is only conducted as a "last resort" e.g. under EU REACH.

Investigating open access new approach methods (NAM) to assess biological points of departure: A case study with 4 neurotoxic pesticides

Open access new approach methods (NAM) in the US EPA ToxCast program and NTP Integrated Chemical Environment (ICE) were used to investigate activities of four neurotoxic pesticides: endosulfan, fipronil, propyzamide and carbaryl. Concordance of in vivo regulatory points of departure (POD) adjusted for interspecies extrapolation (AdjPOD) to modelled human Administered Equivalent Dose (AEDHuman) was assessed using 3-compartment or Adult/Fetal PBTK in vitro to in vivo extrapolation. Model inputs were from Tier 1 (High throughput transcriptomics: HTTr, high throughput phenotypic profiling: HTPP) and Tier 2 (single target: ToxCast) assays. HTTr identified gene expression signatures associated with potential neurotoxicity for endosulfan, propyzamide and carbaryl in non-neuronal MCF-7 and HepaRG cells. The HTPP assay in U-2 OS cells detected potent effects on DNA endpoints for endosulfan and carbaryl, and mitochondria with fipronil (propyzamide was inactive). The most potent ToxCast assays were concordant with specific components of each chemical mode of action (MOA). Predictive adult IVIVE models produced fold differences (FD) < 10 between the AEDHuman and the measured in vivo AdjPOD. The 3-compartment model was concordant (i.e., smallest FD) for endosulfan, fipronil and carbaryl, and PBTK was concordant for propyzamide. The most potent AEDHuman predictions for each chemical showed HTTr, HTPP and ToxCast were mainly concordant with in vivo AdjPODs but assays were less concordant with MOAs. This was likely due to the cell types used for testing and/or lack of metabolic capabilities and pathways available in vivo. The Fetal PBTK model had larger FDs than adult models and was less predictive overall.

Standardizing Extracted Data Using Automated Application of Controlled Vocabularies

BACKGROUND

Extraction of toxicological end points from primary sources is a central component of systematic reviews and human health risk assessments. To ensure optimal use of these data, consistent language should be used for end point descriptions. However, primary source language describing treatment-related end points can vary greatly, resulting in large labor efforts to manually standardize extractions before data are fit for use.

OBJECTIVES

To minimize these labor efforts, we applied an augmented intelligence approach and developed automated tools to support standardization of extracted information via application of preexisting controlled vocabularies.

METHODS

We created and applied a harmonized controlled vocabulary crosswalk, consisting of Unified Medical Language System (UMLS) codes, German Federal Institute for Risk Assessment (BfR) DevTox harmonized terms, and The Organization for Economic Co-operation and Development (OECD) end point vocabularies, to roughly 34,000 extractions from prenatal developmental toxicology studies conducted by the National Toxicology Program (NTP) and 6,400 extractions from European Chemicals Agency (ECHA) prenatal developmental toxicology studies, all recorded based on the original study report language.

RESULTS

We automatically applied standardized controlled vocabulary terms to 75% of the NTP extracted end points and 57% of the ECHA extracted end points. Of all the standardized extracted end points, about half (51%) required manual review for potential extraneous matches or inaccuracies. Extracted end points that were not mapped to standardized terms tended to be too general or required human logic to find a good match. We estimate that this augmented intelligence approach saved > 350 hours of manual effort and yielded valuable resources including a controlled vocabulary crosswalk, organized related terms lists, code for implementing an automated mapping workflow, and a computationally accessible dataset.

DISCUSSION

Augmenting manual efforts with automation tools increased the efficiency of producing a findable, accessible, interoperable, and reusable (FAIR) dataset of regulatory guideline studies. This open-source approach can be readily applied to other legacy developmental toxicology datasets, and the code design is customizable for other study types. https://doi.org/10.1289/EHP13215.

Definition of the Neurotoxicity-Associated Metabolic Signature Triggered by Berberine and Other Respiratory Chain Inhibitors

To characterize the hits from a phenotypic neurotoxicity screen, we obtained transcriptomics data for valinomycin, diethylstilbestrol, colchicine, rotenone, 1-methyl-4-phenylpyridinium (MPP), carbaryl and berberine (Ber). For all compounds, the concentration triggering neurite degeneration correlated with the onset of gene expression changes. The mechanistically diverse toxicants caused similar patterns of gene regulation: the responses were dominated by cell de-differentiation and a triggering of canonical stress response pathways driven by ATF4 and NRF2. To obtain more detailed and specific information on the modes-of-action, the effects on energy metabolism (respiration and glycolysis) were measured. Ber, rotenone and MPP inhibited the mitochondrial respiratory chain and they shared complex I as the target. This group of toxicants was further evaluated by metabolomics under experimental conditions that did not deplete ATP. Ber (204 changed metabolites) showed similar effects as MPP and rotenone. The overall metabolic situation was characterized by oxidative stress, an over-abundance of NADH (>1000% increase) and a re-routing of metabolism in order to dispose of the nitrogen resulting from increased amino acid turnover. This unique overall pattern led to the accumulation of metabolites known as biomarkers of neurodegeneration (saccharopine, aminoadipate and branched-chain ketoacids). These findings suggest that neurotoxicity of mitochondrial inhibitors may result from an ensemble of metabolic changes rather than from a simple ATP depletion. The combi-omics approach used here provided richer and more specific MoA data than the more common transcriptomics analysis alone. As Ber, a human drug and food supplement, mimicked closely the mode-of-action of known neurotoxicants, its potential hazard requires further investigation.

Machine Learning-Based Hazard-Driven Prioritization of Features in Nontarget Screening of Environmental High-Resolution Mass Spectrometry Data

Nontarget high-resolution mass spectrometry screening (NTS HRMS/MS) can detect thousands of organic substances in environmental samples. However, new strategies are needed to focus time-intensive identification efforts on features with the highest potential to cause adverse effects instead of the most abundant ones. To address this challenge, we developed MLinvitroTox, a machine learning framework that uses molecular fingerprints derived from fragmentation spectra (MS2) for a rapid classification of thousands of unidentified HRMS/MS features as toxic/nontoxic based on nearly 400 target-specific and over 100 cytotoxic endpoints from ToxCast/Tox21. Model development results demonstrated that using customized molecular fingerprints and models, over a quarter of toxic endpoints and the majority of the associated mechanistic targets could be accurately predicted with sensitivities exceeding 0.95. Notably, SIRIUS molecular fingerprints and xboost (Extreme Gradient Boosting) models with SMOTE (Synthetic Minority Oversampling Technique) for handling data imbalance were a universally successful and robust modeling configuration. Validation of MLinvitroTox on MassBank spectra showed that toxicity could be predicted from molecular fingerprints derived from MS2 with an average balanced accuracy of 0.75. By applying MLinvitroTox to environmental HRMS/MS data, we confirmed the experimental results obtained with target analysis and narrowed the analytical focus from tens of thousands of detected signals to 783 features linked to potential toxicity, including 109 spectral matches and 30 compounds with confirmed toxic activity.

Advancing the use of new approach methodologies for assessing teratogenicity: Building a tiered approach

Many New Approach Methodologies (NAMs) have been developed for the safety assessment of new ingredients. Research into reproductive toxicity and teratogenicity is a particularly high priority, especially given their mechanistic complexity. Forty-six non-teratogenic and 39 teratogenic chemicals were screened for teratogenic potential using the in silico DART model from the OECD QSAR Toolbox; the devTox quickPredict™ (devTox assay) test and the Zebrafish Embryotoxicity Test (ZET). The sensitivity and specificity were 94.7% and 84.1%, respectively, for the DART tree (83 chemicals), 86.1% and 35.6% for the devTox (81 chemicals) and 77.8% and 76.7% for the ZET (57 chemicals). Fifty-three chemicals were tested in all three assays and when results were combined and based on a "2 out of 3 rule", the sensitivity and specificity were 96.0% and 71.4%, respectively. The specificity of the devTox assay for a sub-set of 43 chemicals was increased from 26.1% to 82.6% by incorporating human plasma concentrations into the assay interpretation. When all 85 chemicals were assessed in a decision tree approach, there was an excellent predictivity and assay robustness of 90%. In conclusion, all three models exhibited a good sensitivity and specificity, especially when outcomes from all three were combined or used in "2 out of 3" or a tiered decision tree approach. The latter is an interesting predictive approach for evaluating the teratogenic potential of new chemicals. Future investigations will extend the number of chemicals tested, as well as explore ways to refine the results and obtain a robust Integrated Testing Strategy to evaluate teratogenic potential.

Prediction of inotropic effect based on calcium transients in human iPSC-derived cardiomyocytes and machine learning

Functional changes to cardiomyocytes are undesirable during drug discovery and identifying the inotropic effects of compounds is hence necessary to decrease the risk of cardiovascular adverse effects in the clinic. Recently, approaches leveraging calcium transients in human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have been developed to detect contractility changes, induced by a variety of mechanisms early during drug discovery projects. Although these approaches have been able to provide some predictive ability, we hypothesised that using additional waveform parameters could offer improved insights, as well as predictivity. In this study, we derived 25 parameters from each calcium transient waveform and developed a modified Random Forest method to predict the inotropic effects of the compounds. In total annotated data for 48 compounds were available for modelling, out of which 31 were inotropes. The results show that the Random Forest model with a modified purity criterion performed slightly better than an unmodified algorithm in terms of the Area Under the Curve, giving values of 0.84 vs 0.81 in a cross-validation, and outperformed the ToxCast Pipeline model, for which the highest value was 0.76 when using the best-performing parameter, PW10. Our study hence demonstrates that more advanced parameters derived from waveforms, in combination with additional machine learning methods, provide improved predictivity of cardiovascular risk associated with inotropic effects.

High-throughput screening paradigms in ecotoxicity testing: Emerging prospects and ongoing challenges

The rapidly increasing number of new production chemicals coupled with stringent implementation of global chemical management programs necessities a paradigm shift towards boarder uses of low-cost and high-throughput ecotoxicity testing strategies as well as deeper understanding of cellular and sub-cellular mechanisms of ecotoxicity that can be used in effective risk assessment. The latter will require automated acquisition of biological data, new capabilities for big data analysis as well as computational simulations capable of translating new data into in vivo relevance. However, very few efforts have been so far devoted into the development of automated bioanalytical systems in ecotoxicology. This is in stark contrast to standardized and high-throughput chemical screening and prioritization routines found in modern drug discovery pipelines. As a result, the high-throughput and high-content data acquisition in ecotoxicology is still in its infancy with limited examples focused on cell-free and cell-based assays. In this work we outline recent developments and emerging prospects of high-throughput bioanalytical approaches in ecotoxicology that reach beyond in vitro biotests. We discuss future importance of automated quantitative data acquisition for cell-free, cell-based as well as developments in phytotoxicity and in vivo biotests utilizing small aquatic model organisms. We also discuss recent innovations such as organs-on-a-chip technologies and existing challenges for emerging high-throughput ecotoxicity testing strategies. Lastly, we provide seminal examples of the small number of successful high-throughput implementations that have been employed in prioritization of chemicals and accelerated environmental risk assessment.

Quantitative in vitro to in vivo extrapolation for developmental toxicity potency of valproic acid analogues

BACKGROUND

The developmental toxicity potential (dTP) concentration from the devTOX quickPredict (devTOX^qP ) assay, a metabolomics-based human induced pluripotent stem cell assay, predicts a chemical's developmental toxicity potency. Here, in vitro to in vivo extrapolation (IVIVE) approaches were applied to address whether the devTOX^qP assay could quantitatively predict in vivo developmental toxicity lowest effect levels (LELs) for the prototypical teratogen valproic acid (VPA) and a group of structural analogues.

METHODS

VPA and a series of structural analogues were tested with the devTOX^qP assay to determine dTP concentration and we estimated the equivalent administered doses (EADs) that would lead to plasma concentrations equivalent to the in vitro dTP concentrations. The EADs were compared to the LELs in rat developmental toxicity studies, human clinical doses, and EADs reported using other in vitro assays. To evaluate the impact of different pharmacokinetic (PK) models on IVIVE outcomes, we compared EADs predicted using various open-source and commercially available PK and physiologically based PK (PBPK) models. To evaluate the effect of in vitro kinetics, an equilibrium distribution model was applied to translate dTP concentrations to free medium concentrations before subsequent IVIVE analyses.

RESULTS

The EAD estimates for the VPA analogues based on different PK/PBPK models were quantitatively similar to in vivo data from both rats and humans, where available, and the derived rank order of the chemicals was consistent with observed in vivo developmental toxicity. Different models were identified that provided accurate predictions for rat prenatal LELs and conservative estimates of human safe exposure. The impact of in vitro kinetics on EAD estimates is chemical-dependent. EADs from this study were within range of predicted doses from other in vitro and model organism data.

CONCLUSIONS

This study highlights the importance of pharmacokinetic considerations when using in vitro assays and demonstrates the utility of the devTOX^qP human stem cell-based platform to quantitatively assess a chemical's developmental toxicity potency.

Toxicity by descent: A comparative approach for chemical hazard assessment

Toxicology is traditionally divided between human and eco-toxicology. In the shared pursuit of environmental health, this separation does not account for discoveries made in the comparative studies of animal genomes. Here, we provide evidence on the feasibility of understanding the health impact of chemicals on all animals, including ecological keystone species and humans, based on a significant number of conserved genes and their functional associations to health-related outcomes across much of animal diversity. We test four conditions to understand the value of comparative genomics data to inform mechanism-based human and environmental hazard assessment: (1) genes that are most fundamental for health evolved early during animal evolution; (2) the molecular functions of pathways are better conserved among distantly related species than the individual genes that are members of these pathways; (3) the most conserved pathways among animals are those that cause adverse health outcomes when disrupted; (4) gene sets that serve as molecular signatures of biological processes or disease-states are largely enriched by evolutionarily conserved genes across the animal phylogeny. The concept of homology is applied in a comparative analysis of gene families and pathways among invertebrate and vertebrate species compared with humans. Results show that over 70% of gene families associated with disease are shared among the greatest variety of animal species through evolution. Pathway conservation between invertebrates and humans is based on the degree of conservation within vertebrates and the number of interacting genes within the human network. Human gene sets that already serve as biomarkers are enriched by evolutionarily conserved genes across the animal phylogeny. By implementing a comparative method for chemical hazard assessment, human and eco-toxicology converge towards a more holistic and mechanistic understanding of toxicity disrupting biological processes that are important for health and shared among animals (including humans).

Using high throughput screens to predict miscarriages with placental stem cells and long-term stress effects with embryonic stem cells

A problem in developmental toxicology is the massive loss of life from fertilization through gastrulation, and the surprising lack of knowledge of causes of miscarriage. Half to two-thirds of embryos are lost, and environmental and genetic causes are nearly equal. Simply put, it can be inferred that this is a difficult period for normal embryos, but that environmental stresses may cause homeostatic responses that move from adaptive to maladaptive with increasing exposures. At the lower 50% estimate, miscarriage causes greater loss-of-life than all cancers combined or of all cardio- and cerebral-vascular accidents combined. Surprisingly, we do not know if miscarriage rates are increasing or decreasing. Overshadowed by the magnitude of miscarriages, are insufficient data on teratogenic or epigenetic imbalances in surviving embryos and their stem cells. Superimposed on the difficult normal trajectory for peri-gastrulation embryos are added malnutrition, hormonal, and environmental stresses. An overarching hypothesis is that high throughput screens (HTS) using cultured viable reporter embryonic and placental stem cells (e.g., embryonic stem cells [ESC] and trophoblast stem cells [TSC] that report status using fluorescent reporters in living cells) from the pre-gastrulation embryo will most rapidly test a range of hormonal, environmental, nutritional, drug, and diet supplement stresses that decrease stem cell proliferation and imbalance stemness/differentiation. A second hypothesis is that TSC respond with greater sensitivity in magnitude to stress that would cause miscarriage, but ESC are stress-resistant to irreversible stemness loss and are best used to predict long-term health defects. DevTox testing needs more ESC and TSC HTS to model environmental stresses leading to miscarriage or teratogenesis and more research on epidemiology of stress and miscarriage. This endeavor also requires a shift in emphasis on pre- and early gastrulation events during the difficult period of maximum loss by miscarriage.

Prioritization of chemicals in food for risk assessment by integrating exposure estimates and new approach methodologies: A next generation risk assessment case study

Next generation risk assessment is defined as a knowledge-driven system that allows for cost-efficient assessment of human health risk related to chemical exposure, without animal experimentation. One of the key features of next generation risk assessment is to facilitate prioritization of chemical substances that need a more extensive toxicological evaluation, in order to address the need to assess an increasing number of substances. In this case study focusing on chemicals in food, we explored how exposure data combined with the Threshold of Toxicological Concern (TTC) concept could be used to prioritize chemicals, both for existing substances and new substances entering the market. Using a database of existing chemicals relevant for dietary exposure we calculated exposure estimates, followed by application of the TTC concept to identify substances of higher concern. Subsequently, a selected set of these priority substances was screened for toxicological potential using high-throughput screening (HTS) approaches. Remarkably, this approach resulted in alerts for a selection of substances that are already on the market and represent relevant exposure in consumers. Taken together, the case study provides proof-of-principle for the approach taken to identify substances of concern, and this approach can therefore be considered a supportive element to a next generation risk assessment strategy.

Computational model for fetal skeletal defects potentially linked to disruption of retinoic acid signaling

All-trans retinoic acid (ATRA) gradients determine skeletal patterning morphogenesis and can be disrupted by diverse genetic or environmental factors during pregnancy, leading to fetal skeleton defects. Adverse Outcome Pathway (AOP) frameworks for ATRA metabolism, signaling, and homeostasis allow for the development of new approach methods (NAMs) for predictive toxicology with less reliance on animal testing. Here, a data-driven model was constructed to identify chemicals associated with both ATRA pathway bioactivity and prenatal skeletal defects. The phenotype data was culled from ToxRefDB prenatal developmental toxicity studies and produced a list of 363 ToxRefDB chemicals with altered skeletal observations. Defects were classified regionally as cranial, post-cranial axial, appendicular, and other (unspecified) features based on ToxRefDB descriptors. To build a multivariate statistical model, high-throughput screening bioactivity data from >8,070 chemicals in ToxCast/Tox21 across 10 in vitro assays relevant to the retinoid signaling system were evaluated and compared to literature-based candidate reference chemicals in the dataset. There were 48 chemicals identified for effects on both in vivo skeletal defects and in vitro ATRA pathway targets for computational modeling. The list included 28 chemicals with prior evidence of skeletal defects linked to retinoid toxicity and 20 chemicals without prior evidence. The combination of thoracic cage defects and DR5 (direct repeats of 5 nucleotides for RAR/RXR transactivation) disruption was the most frequently occurring phenotypic and target disturbance, respectively. This data model provides valuable AOP elucidation and validates current mechanistic understanding. These findings also shed light on potential avenues for new mechanistic discoveries related to ATRA pathway disruption and associated skeletal dysmorphogenesis due to environmental exposures.

Advances in computational methods along the exposure to toxicological response paradigm

Human health risk assessment is a function of chemical toxicity, bioavailability to reach target biological tissues, and potential environmental exposure. These factors are complicated by many physiological, biochemical, physical and lifestyle factors. Furthermore, chemical health risk assessment is challenging in view of the large, and continually increasing, number of chemicals found in the environment. These challenges highlight the need to prioritize resources for the efficient and timely assessment of those environmental chemicals that pose greatest health risks. Computational methods, either predictive or investigative, are designed to assist in this prioritization in view of the lack of cost prohibitive in vivo experimental data. Computational methods provide specific and focused toxicity information using in vitro high throughput screening (HTS) assays. Information from the HTS assays can be converted to in vivo estimates of chemical levels in blood or target tissue, which in turn are converted to in vivo dose estimates that can be compared to exposure levels of the screened chemicals. This manuscript provides a review for the landscape of computational methods developed and used at the U.S. Environmental Protection Agency (EPA) highlighting their potentials and challenges.

The DevTox Germ Layer Reporter Platform: An Assay Adaptation of the Human Pluripotent Stem Cell Test

Environmental chemical exposures are a contributing factor to birth defects affecting infant morbidity and mortality. The USA EPA is committed to developing new approach methods (NAMs) to detect chemical risks to susceptible populations, including pregnant women. NAM-based coverage for cellular mechanisms associated with early human development could enhance identification of potential developmental toxicants (DevTox) for new and existing data-poor chemicals. The human pluripotent stem cell test (hPST) is an in vitro test method for rapidly identifying potential human developmental toxicants that employs directed differentiation of embryonic stem cells to measure reductions in SOX17 biomarker expression and nuclear localization. The objective of this study was to expand on the hPST principles to develop a model platform (DevTox GLR) that utilizes the transgenic RUES2-GLR cell line expressing fluorescent reporter fusion protein biomarkers for SOX17 (endoderm marker), BRA (mesoderm marker), and SOX2 (ectoderm and pluripotency marker). Initial assay adaption to definitive endoderm (DevTox GLR-Endo) was performed to emulate the hPST SOX17 endpoint and enable comparative evaluation of concordant chemical effects. Assay duration was reduced to two days and screening throughput scaled to 384-well format for enhanced speed and efficiency. Assay performance for 66 chemicals derived from reference and training set data resulted in a balanced accuracy of 72% (79% sensitivity and 65% specificity). The DevTox GLR-Endo assay demonstrates successful adaptation of the hPST concept with increased throughput, shorter assay duration, and minimal endpoint processing. The DevTox GLR model platform expands the in vitro NAM toolbox to rapidly identify potential developmental hazards and mechanistically characterize toxicant effects on pathways and processes associated with early human development.

Pluripotent stem cell assays: Modalities and applications for predictive developmental toxicity

This manuscript provides a review focused on embryonic stem cell-based models and their place within the landscape of alternative developmental toxicity assays. Against the background of the principles of developmental toxicology, the wide diversity of alternative methods using pluripotent stem cells developed in this area over the past half century is reviewed. In order to provide an overview of available models, a systematic scoping review was conducted following a published protocol with inclusion criteria, which were applied to select the assays. Critical aspects including biological domain, readout endpoint, availability of standardized protocols, chemical domain, reproducibility and predictive power of each assay are described in detail, in order to review the applicability and limitations of the platform in general and progress moving forward to implementation. The horizon of innovative routes of promoting regulatory implementation of alternative methods is scanned, and recommendations for further work are given.

Optimization of the TeraTox assay for preclinical teratogenicity assessment

Current animal-free methods to assess teratogenicity of drugs under development still deliver high numbers of false negatives. To improve the sensitivity of human teratogenicity prediction, we characterized the TeraTox test, a newly developed multilineage differentiation assay using 3D human-induced pluripotent stem cells. TeraTox produces primary output concentration-dependent cytotoxicity and altered gene expression induced by each test compound. These data are fed into an interpretable machine-learning model to perform prediction, which relates to the concentration-dependent human teratogenicity potential of drug candidates. We applied TeraTox to profile 33 approved pharmaceuticals and 12 proprietary drug candidates with known in vivo data. Comparing TeraTox predictions with known human or animal toxicity, we report an accuracy of 69% (specificity: 53%, sensitivity: 79%). TeraTox performed better than 2 quantitative structure-activity relationship models and had a higher sensitivity than the murine embryonic stem cell test (accuracy: 58%, specificity: 76%, and sensitivity: 46%) run in the same laboratory. The overall prediction accuracy could be further improved by combining TeraTox and mouse embryonic stem cell test results. Furthermore, patterns of altered gene expression revealed by TeraTox may help grouping toxicologically similar compounds and possibly deducing common modes of action. The TeraTox assay and the dataset described here therefore represent a new tool and a valuable resource for drug teratogenicity assessment.

Beyond AOPs: A Mechanistic Evaluation of NAMs in DART Testing

New Approach Methodologies (NAMs) promise to offer a unique opportunity to enable human-relevant safety decisions to be made without the need for animal testing in the context of exposure-driven Next Generation Risk Assessment (NGRA). Protecting human health against the potential effects a chemical may have on embryo-foetal development and/or aspects of reproductive biology using NGRA is particularly challenging. These are not single endpoint or health effects and risk assessments have traditionally relied on data from Developmental and Reproductive Toxicity (DART) tests in animals. There are numerous Adverse Outcome Pathways (AOPs) that can lead to DART, which means defining and developing strict testing strategies for every AOP, to predict apical outcomes, is neither a tenable goal nor a necessity to ensure NAM-based safety assessments are fit-for-purpose. Instead, a pragmatic approach is needed that uses the available knowledge and data to ensure NAM-based exposure-led safety assessments are sufficiently protective. To this end, the mechanistic and biological coverage of existing NAMs for DART were assessed and gaps to be addressed were identified, allowing the development of an approach that relies on generating data relevant to the overall mechanisms involved in human reproduction and embryo-foetal development. Using the knowledge of cellular processes and signalling pathways underlying the key stages in reproduction and development, we have developed a broad outline of endpoints informative of DART. When the existing NAMs were compared against this outline to determine whether they provide comprehensive coverage when integrated in a framework, we found them to generally cover the reproductive and developmental processes underlying the traditionally evaluated apical endpoint studies. The application of this safety assessment framework is illustrated using an exposure-led case study.

A large scale mass spectrometry-based histone screening for assessing epigenetic developmental toxicity

Toxicoepigenetics is an emerging field that studies the toxicological impact of compounds on protein expression through heritable, non-genetic mechanisms, such as histone post-translational modifications (hPTMs). Due to substantial progress in the large-scale study of hPTMs, integration into the field of toxicology is promising and offers the opportunity to gain novel insights into toxicological phenomena. Moreover, there is a growing demand for high-throughput human-based in vitro assays for toxicity testing, especially for developmental toxicity. Consequently, we developed a mass spectrometry-based proof-of-concept to assess a histone code screening assay capable of simultaneously detecting multiple hPTM-changes in human embryonic stem cells. We first validated the untargeted workflow with valproic acid (VPA), a histone deacetylase inhibitor. These results demonstrate the capability of mapping the hPTM-dynamics, with a general increase in acetylations as an internal control. To illustrate the scalability, a dose–response study was performed on a proof-of-concept library of ten compounds (1) with a known effect on the hPTMs (BIX-01294, 3-Deazaneplanocin A, Trichostatin A, and VPA), (2) classified as highly embryotoxic by the European Centre for the Validation of Alternative Methods (ECVAM) (Methotrexate, and All-trans retinoic acid), (3) classified as non-embryotoxic by ECVAM (Penicillin G), and (4) compounds of abuse with a presumed developmental toxicity (ethanol, caffeine, and nicotine).

Using Live Imaging and FUCCI Embryonic Stem Cells to Rank DevTox Risks: Adverse Growth Effects of PFOA Compared With DEP Are 26 Times Faster, 1,000 Times More Sensitive, and 13 Times Greater in Magnitude

Fluorescent ubiquitination-based cell cycle indicator (FUCCI) embryonic stem cells (ESCs), which fluoresce green during the S-G2-M phases, generate an S-shaped curve for the accumulation of cells during normal stemness (NS) culture with leukemia-inhibitory factor (LIF). Since it was hypothesized that a culture of ESCs was heterogeneous in the cell cycle, it was expected that increased S-G2-M-phases of the cell cycle would make an S-shaped curve parallel to the accumulation curve. Unexpectedly, it was observed that the fraction of FUCCI ESCs in green decreases over time to a nadir at ∼24 h after previous feeding and then rapidly enters S-G2-M-phases after medium change. G1 delay by infrequent medium change is a mild stress, as it does not affect growth significantly when frequency is increased to 12 h. Perfluoro-octanoic acid (PFOA) and diethyl phthalate (DEP) were used as examples of members of the per- and polyfluoroalkyl substances (PFAS) and phthalate families of chemicals, respectively. Two adverse outcomes were used to compare dose- and time-dependent effects of PFOA and DEP. The first was cell accumulation assay by time-lapse confluence measurements, largely at Tfinal/T74 h. The second was by quantifying dominant toxicant stress shown by the suppression of mild stress that creates a green fed/unfed peak. In terms of speed, PFOA is 26 times faster than DEP for producing a time-dependent LOAEL dose at 100 uM (that is, 2 h for PFOA and 52 h for DEP). PFOA has 1000-fold more sensitive LOAEL doses than DEP for suppressing ESC accumulation (confluence) at day 3 and day 2. There were two means to compare the magnitude of the growth suppression of PFOA and DEP. For the suppression of the accumulation of cells measured by confluence at Tfinal/T74h, there was a 13-fold suppression at the highest dose of PFOA > the highest dose of DEP. For the suppression of entry into the cell cycle after the G1 phase by stress on day 1 and 2, there is 10-fold more suppression by PFOA than DEP. The data presented here suggest that FUCCI ESCs can assay the suppression of accumulated growth or predict the suppression of future growth by the suppression of fed/unfed green fluorescence peaks and that PFOA's adverse effects are faster and larger and can occur at more sensitive lower doses than DEP.

Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology

Omics methodologies are widely used in toxicological research to understand modes and mechanisms of toxicity. Increasingly, these methodologies are being applied to questions of regulatory interest such as molecular point-of-departure derivation and chemical grouping/read-across. Despite its value, widespread regulatory acceptance of omics data has not yet occurred. Barriers to the routine application of omics data in regulatory decision making have been: 1) lack of transparency for data processing methods used to convert raw data into an interpretable list of observations; and 2) lack of standardization in reporting to ensure that omics data, associated metadata and the methodologies used to generate results are available for review by stakeholders, including regulators. Thus, in 2017, the Organisation for Economic Co-operation and Development (OECD) Extended Advisory Group on Molecular Screening and Toxicogenomics (EAGMST) launched a project to develop guidance for the reporting of omics data aimed at fostering further regulatory use. Here, we report on the ongoing development of the first formal reporting framework describing the processing and analysis of both transcriptomic and metabolomic data for regulatory toxicology. We introduce the modular structure, content, harmonization and strategy for trialling this reporting framework prior to its publication by the OECD.

Assessment of the in vitro developmental toxicity of diethylstilbestrol and estradiol in the zebrafish embryotoxicity test

The present study investigated the developmental toxicity of diethylstilbestrol (DES) in the zebrafish embryotoxicity test (ZET). This was done to investigate whether the ZET would better capture the developmental toxicity of DES than the embryonic stem cells test (EST) that was previously shown to underpredict the DES-induced developmental toxicity as compared to in vivo data, potentially because the EST does not capture late events in the developmental process. The ZET results showed DES-induced growth retardation, cumulative mortality and dysmorphisms (i.e. induction of pericardial edema) in zebrafish embryos while the endogenous ERα agonist 17β-estradiol (E2) showed only growth retardation and cumulative mortality with lower potency compared to DES. Furthermore, the DES-induced pericardial edema formation in zebrafish embryos could be counteracted by co-exposure with ERα antagonist fulvestrant, indicating that the ZET captures the role of ERα in the mode of action underlying the developmental toxicity of DES. Altogether, it is concluded that the ZET differentiates DES from E2 with respect to their developmental toxicity effects, while confirming the role of ERα in mediating the developmental toxicity of DES. Furthermore, comparison to in vivo data revealed that, like the EST, in a quantitative way also the ZET did not capture the relatively high in vivo potency of DES as a developmental toxicant.

Retinoid signaling in skeletal development: Scoping the system for predictive toxicology

All-trans retinoic acid (ATRA), the biologically active form of vitamin A, is instrumental in regulating the patterning and specification of the vertebrate embryo. Various animal models demonstrate adverse developmental phenotypes following experimental retinoid depletion or excess during pregnancy. Windows of vulnerability for altered skeletal patterning coincide with early specification of the body plan (gastrulation) and regional specification of precursor cell populations forming the facial skeleton (cranial neural crest), vertebral column (somites), and limbs (lateral plate mesoderm) during organogenesis. A common theme in physiological roles of ATRA signaling is mutual antagonism with FGF signaling. Consequences of genetic errors or environmental disruption of retinoid signaling include stage- and region-specific homeotic transformations to severe deficiencies for various skeletal elements. This review derives from an annex in Detailed Review Paper (DRP) of the OECD Test Guidelines Programme (Project 4.97) to support recommendations regarding assay development for the retinoid system and the use of resulting data in a regulatory context for developmental and reproductive toxicity (DART) testing.

Computational Biology and in silico Toxicodynamics

New approach methodologies (NAMs) refer to any non-animal technology, methodology, approach, or combination thereof that can be used to provide information on chemical hazard and risk assessment that avoids the use of intact animals. A spectrum of in silico models is needed for the integrated analysis of various domains in toxicology to improve predictivity and reduce animal testing. This review focuses on in silico approaches, computer models, and computational intelligence for developmental and reproductive toxicity (predictive DART), providing a means to measure toxicodynamics in simulated systems for quantitative prediction of adverse outcomes phenotypes.

The use of human induced pluripotent stem cells to screen for developmental toxicity potential indicates reduced potential for non-combusted products, when compared to cigarettes

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Effective in vitro strategies are required to predict early developmental toxicity.

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devTOX^qP is a metabolomics biomarker assay using iPSCs.

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Sample smoke/aerosol captured in bPBS, was tested up to 10% concentration.

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Cigarettes & HTP bPBS extracts were predicted as potentially developmentally toxic.

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HYB & EVP aerosols were not predicted as having developmentally toxic potential in devTOX^qP.

devTOX quickPredict (devTOX^qP) is a metabolomics biomarker-based assay that utilises human induced pluripotent stem (iPS) cells to screen for potential early stage embryonic developmental toxicity in vitro. Developmental toxicity potential is assessed based on the assay endpoint of the alteration in the ratio of key unrelated biomarkers, ornithine and cystine (o/c).

This work aimed to compare the developmental toxicity potential of tobacco-containing and tobacco-free non-combustible nicotine products to cigarette smoke. Smoke and aerosol from test articles were produced using a Vitrocell VC10 smoke/aerosol exposure system and bubbled into phosphate buffered saline (bPBS). iPS cells were exposed to concentrations of up to 10% bPBS. Assay sensitivity was assessed through a spiking study with a known developmental toxicant, all-trans-retinoic acid (ATRA), in combination with cigarette smoke extract.

The bPBS extracts of reference cigarettes (1R6F and 3R4F) and a heated tobacco product (HTP) were predicted to have the potential to induce developmental toxicity, in this screening assay. The bPBS concentration at which these extracts exceeded the developmental toxicity threshold was 0.6% (1R6F), 1.3% (3R4F), and 4.3% (HTP) added to the cell media. Effects from cigarette smoke and HTP aerosol were driven largely by cytotoxicity, with the cell viability and o/c ratio dose–response curves crossing the developmental toxicity thresholds at very similar concentrations of added bPBS. The hybrid product and all the electronic cigarette (e-cigarette) aerosols were not predicted to be potential early developmental toxicants, under the conditions of this screening assay.

Use of computational toxicology (CompTox) tools to predict in vivo toxicity for risk assessment

Computational Toxicology tools were used to predict toxicity for three pesticides: propyzamide (PZ), carbaryl (CB) and chlorpyrifos (CPF). The tools used included: a) ToxCast/Tox21 assays (AC₅₀ s μM: concentration 50% maximum activity); b) in vitro-to-in vivo extrapolation (IVIVE) using ToxCast/Tox21 AC₅₀s to predict administered equivalent doses (AED: mg/kg/d) to compare to known in vivo Lowest-Observed-Effect-Level (LOEL)/Benchmark Dose (BMD); c) high throughput toxicokinetics population based (HTTK-Pop) using AC₅₀s for endpoints associated with the mode of action (MOA) to predict age-adjusted AED for comparison with in vivo LOEL/BMDs. ToxCast/Tox21 active-hit-calls for each chemical were predictive of targets associated with each MOA, however, assays directly relevant to the MOAs for each chemical were limited. IVIVE AEDs were predictive of in vivo LOEL/BMD₁₀s for all three pesticides. HTTK-Pop was predictive of in vivo LOEL/BMD₁₀s for PZ and CPF but not for CB after human age adjustments 11-15 (PZ) and 6-10 (CB) or 6-10 and 11-20 (CPF) corresponding to treated rat ages (in vivo endpoints). The predictions of computational tools are useful for risk assessment to identify targets in chemical MOAs and to support in vivo endpoints. Data can also aid is decisions about the need for further studies.

Industry updates from the field of stem cell research and regenerative medicine in February 2020

The latest developments in the field of stem-cell research and regenerative medicine compiled from publicly available information and press releases from nonacademic institutions in February 2020.