Bioinformatics and machine learning to support nanomaterial grouping.

Nanomaterials (NMs) offer plenty of novel functionalities. Moreover, their physicochemical properties can be fine-tuned to meet the needs of specific applications, leading to virtually unlimited numbers of NM variants. Hence, efficient hazard and risk assessment strategies building on New Approach Methodologies (NAMs) become indispensable. Indeed, the design, the development and implementation of NAMs has been a major topic in a substantial number of research projects. One of the promising strategies that can help to deal with the high number of NMs variants is grouping and read-across. Based on demonstrated structural and physicochemical similarity, NMs can be grouped and assessed together. Within an established NM group, read-across may be performed to fill in data gaps for data-poor variants using existing data for NMs within the group. Establishing a group requires a sound justification, usually based on a grouping hypothesis that links specific physicochemical properties to well-defined hazard endpoints. However, for NMs these interrelationships are only beginning to be understood. The aim of this review is to demonstrate the power of bioinformatics with a specific focus on Machine Learning (ML) approaches to unravel the NM Modes-of-Action (MoA) and identify the properties that are relevant to specific hazards, in support of grouping strategies. This review emphasizes the following messages: 1) ML supports identification of the most relevant properties contributing to specific hazards; 2) ML supports analysis of large omics datasets and identification of MoA patterns in support of hypothesis formulation in grouping approaches; 3) omics approaches are useful for shifting away from consideration of single endpoints towards a more mechanistic understanding across multiple endpoints gained from one experiment; and 4) approaches from other fields of Artificial Intelligence (AI) like Natural Language Processing or image analysis may support automated extraction and interlinkage of information related to NM toxicity. Here, existing ML models for predicting NM toxicity and for analyzing omics data in support of NM grouping are reviewed. Various challenges related to building robust models in the field of nanotoxicology exist and are also discussed.

E-waste: mechanisms of toxicity and safety testing.

Currently, information on the toxicity profile of the majority of the identified e-waste chemicals, while extensive and growing, is admittedly fragmentary, particularly at the cellular and molecular levels. Furthermore, the toxicity of the chemical mixtures likely to be encountered by humans during and after informal e-waste recycling, as well as their underlying mechanisms of action, is largely unknown. This review paper summarizes state-of-the-art knowledge of the potential underlying toxicity mechanisms associated with e-waste exposures, with a focus on toxic responses connected to specific organs, organ systems, and overall effects on the organism. To overcome the complexities associated with assessing the possible adverse outcomes from exposure to chemicals, a growing number of new approach methodologies have emerged in recent years, with the long-term objective of providing a human-based and animal-free system that is scientifically superior to animal testing, more effective, and acceptable. This encompasses a variety of techniques, typically regarded as alternative approaches for determining chemical-induced toxicities and holds greater promise for a better understanding of key events in the metabolic pathways that mediate known adverse health outcomes in e-waste exposure scenarios. This is crucial to establishing accurate scientific knowledge on mixed e-waste chemical exposures in shorter time frames and with greater efficacy, as well as supporting the need for safe management of hazardous chemicals. The present review paper discusses important gaps in knowledge and shows promising directions for mechanistically anchored effect-based monitoring strategies that will contribute to the advancement of the methods currently used in characterizing and monitoring e-waste-impacted ecosystems.

A roadmap towards safe and sustainable by design nanotechnology: Implementation for nano-silver-based antimicrobial textile coatings production by ASINA project.

This report demonstrates a case study within the ASINA project, aimed at instantiating a roadmap with quantitative metrics for Safe(r) and (more) Sustainable by Design (SSbD) options. We begin with a description of ASINA's methodology across the product lifecycle, outlining the quantitative elements within: Physical-Chemical Features (PCFs), Key Decision Factors (KDFs), and Key Performance Indicators (KPIs). Subsequently, we delve in a proposed decision support tool for implementing the SSbD objectives across various dimensions-functionality, cost, environment, and human health safety-within a broader European context. We then provide an overview of the technical processes involved, including design rationales, experimental procedures, and tools/models developed within ASINA in delivering nano-silver-based antimicrobial textile coatings. The result is pragmatic, actionable metrics intended to be estimated and assessed in future SSbD applications and to be adopted in a common SSbD roadmap aligned with the EU's Green Deal objectives. The methodological approach is transparently and thoroughly described to inform similar projects through the integration of KPIs into SSbD and foster data-driven decision-making. Specific results and project data are beyond this work's scope, which is to demonstrate the ASINA roadmap and thus foster SSbD-oriented innovation in nanotechnology.

Using targeted fetal rat testis genomic and endocrine alterations to predict the effects of a phthalate mixture on the male reproductive tract.

Administration of phthalates in utero disrupts gene expression and hormone levels in the fetal rat testis, which are key events in an Adverse Outcome Pathway (AOP) for the Phthalate Syndrome. These measures can be used to predict the postnatal adverse effects of phthalate esters (PEs) on male rat sexual differentiation. Here, pregnant rats were exposed to dibutyl (DBP)- and diisononyl (DINP) phthalate on gestational days 14 to 18 individually and as a mixture (DBP,250 mg/kg/d; DINP, 750 mg/kg/d; and DBP 250 mg/kg/d plus DINP 750 mg/kg/d). We found that each PE reduced testosterone production (T Prod) and related gene transcripts by about 50 % and that they acted in a dose additive manner, reducing T Prod and gene expression by 75 % as a mixture. Based upon effects on T Prod, DINP was 0.33 times as potent as DBP and thus the DBP + DINP mixture was predicted to be equivalent to 500 mg DBP/kg/d. Logistic regression models of T Prod predicted that the adverse effects of the DBP + DINP mixture group versus the DBP and DINP individual treatments would reduce anogenital distance (AGD) by 27 % versus 10 %, increase hypospadias in 18 % versus < 1 %, induce epididymal agenesis in 46 % versus 10 %, and increase areolae/nipples in 4.8 % versus < 0.1 % of the, respectively. These predictions were highly consistent with effects from previously published dose response studies on the male reproductive effects of DBP. In summary, these results support the use of this New Approach Method to predict the detrimental effects of PEs and PE mixtures, replacing or reducing the need to run long-term, resource and animal use intensive extended one-generation reproduction studies for this class of chemicals.

Complex In Vitro Model Characterization for Context of Use in Toxicologic Pathology: Use Cases by Collaborative Teams of Biologists, Bioengineers, and Pathologists.

Complex in vitro models (CIVMs) offer the potential to increase the clinical relevance of preclinical efficacy and toxicity assessments and reduce the reliance on animals in drug development. The European Society of Toxicologic Pathology (ESTP) and Society for Toxicologic Pathology (STP) are collaborating to highlight the role of pathologists in the development and use of CIVM. Pathologists are trained in comparative animal medicine which enhances their understanding of mechanisms of human and animal diseases, thus allowing them to bridge between animal models and humans. This skill set is important for CIVM development, validation, and data interpretation. Ideally, diverse teams of scientists, including engineers, biologists, pathologists, and others, should collaboratively develop and characterize novel CIVM, and collectively assess their precise use cases (context of use). Implementing a morphological CIVM evaluation should be essential in this process. This requires robust histological technique workflows, image analysis techniques, and needs correlation with translational biomarkers. In this review, we demonstrate how such tissue technologies and analytics support the development and use of CIVM for drug efficacy and safety evaluations. We encourage the scientific community to explore similar options for their projects and to engage with health authorities on the use of CIVM in benefit-risk assessment.

Applying new approach methodologies to assess next-generation tobacco and nicotine products.

In vitro toxicology research has accelerated with the use of in silico, computational approaches and human in vitro tissue systems, facilitating major improvements evaluating the safety and health risks of novel consumer products. Innovation in molecular and cellular biology has shifted testing paradigms, with less reliance on low-throughput animal data and greater use of medium- and high-throughput in vitro cellular screening approaches. These new approach methodologies (NAMs) are being implemented in other industry sectors for chemical testing, screening candidate drugs and prototype consumer products, driven by the need for reliable, human-relevant approaches. Routine toxicological methods are largely unchanged since development over 50 years ago, using high-doses and often employing in vivo testing. Several disadvantages are encountered conducting or extrapolating data from animal studies due to differences in metabolism or exposure. The last decade saw considerable advancement in the development of in vitro tools and capabilities, and the challenges of the next decade will be integrating these platforms into applied product testing and acceptance by regulatory bodies. Governmental and validation agencies have launched and applied frameworks and "roadmaps" to support agile validation and acceptance of NAMs. Next-generation tobacco and nicotine products (NGPs) have the potential to offer reduced risks to smokers compared to cigarettes. These include heated tobacco products (HTPs) that heat but do not burn tobacco; vapor products also termed electronic nicotine delivery systems (ENDS), that heat an e-liquid to produce an inhalable aerosol; oral smokeless tobacco products (e.g., Swedish-style snus) and tobacco-free oral nicotine pouches. With the increased availability of NGPs and the requirement of scientific studies to support regulatory approval, NAMs approaches can supplement the assessment of NGPs. This review explores how NAMs can be applied to assess NGPs, highlighting key considerations, including the use of appropriate in vitro model systems, deploying screening approaches for hazard identification, and the importance of test article characterization. The importance and opportunity for fit-for-purpose testing and method standardization are discussed, highlighting the value of industry and cross-industry collaborations. Supporting the development of methods that are accepted by regulatory bodies could lead to the implementation of NAMs for tobacco and nicotine NGP testing.

A zebrafish-based acoustic motor response (AMR) assay to evaluate chemical-induced developmental neurotoxicity.

Behavioral assays using early-developing zebrafish (Danio rerio) offer a valuable supplement to the in vitro battery adopted as new approach methodologies (NAMs) for assessing risk of chemical-induced developmental neurotoxicity. However, the behavioral assays primarily adopted rely on visual stimulation to elicit behavioral responses, known as visual motor response (VMR) assays. Ocular deficits resulting from chemical exposures can, therefore, confound the behavioral responses, independent of effects on the nervous system. This highlights the need for complementary assays employing alternative forms of sensory stimulation. In this study, we investigated the efficacy of acoustic stimuli as triggers of behavioral responses in larval zebrafish, determined the most appropriate data acquisition mode, and evaluated the suitability of an acoustic motor response (AMR) assay as means to assess alterations in brain activity and risk of chemical-induced developmental neurotoxicity. We quantified the motor responses of 120 h post-fertilization (hpf) larvae to acoustic stimuli with varying patterns and frequencies, and determined the optimal time intervals for data acquisition. Following this, we examined changes in acoustic and visual motor responses resulting from exposures to pharmacological agents known to impact brain activity (pentylenetetrazole (PTZ) and tricaine-s (MS-222)). Additionally, we examined the AMR and VMR of larvae following exposure to two environmental contaminants associated with developmental neurotoxicity: arsenic (As) and cadmium (Cd). Our findings indicate that exposure to a 100 Hz sound frequency in 100 ms pulses elicits the strongest behavioral response among the acoustic stimuli tested and data acquisition in 2 s time intervals is suitable for response assessment. Exposure to PTZ exaggerated and depressed both AMR and VMR in a concentration-dependent manner, while exposure to MS-222 only depressed them. Similarly, exposure to As and Cd induced respective hyper- and hypo-activation of both motor responses. This study highlights the efficiency of the proposed zebrafish-based AMR assay in demonstrating risk of chemical-induced developmental neurotoxicity and its suitability as a complement to the widely adopted VMR assay.

Determination of OTNE-induced thyroid effects within an adverse outcome pathway (AOP) network.

Octahydro-tetramethyl-naphthalenyl-ethanone (OTNE) is a synthetic fragrance ingredient. OTNE was evaluated in repeated-dose toxicological studies. Target organs via oral and dermal routes were the liver and skin/liver, respectively. Effects were observed on the thyroid and thyroid hormones, suggesting hypothalamic-pituitary-thyroid axis perturbation. We investigated the molecular initiating event(s) (MIEs), key events (KEs), and adverse outcomes of OTNE-induced thyroid perturbation within an adverse outcome pathway (AOP). Data were generated using new approach methodologies (NAMs) on human, mouse, and/or rat receptors exploring MIEs using in vitro receptor ligand-binding assays for androstane receptor variant 3 (CAR), farnesoid X receptor (FXR), liver X receptor alpha (LXRα), peroxisome proliferator-activated receptors alpha, delta, and gamma (PPARα, δ, and γ), pregnane X receptor (PXR), and aryl hydrocarbon receptor (AhR). These data inform an AOP network where CAR, FXR, and PXR activation serve as MIEs with thyroid perturbation occurring as secondary effects. These data represent a robust evaluation using NAMs for mapping OTNE-induced thyroid effects and identifying activation of receptor-ligand binding as MIEs in lieu of additional in vivo experimentation. These data indicate the observed thyroid effects are secondary to liver effects and the thyroid effects, therefore, should not be the basis for assessing potential OTNE-induced human health hazards.

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.

Enhanced identification of endocrine disruptors through integration of science-based regulatory practices and innovative methodologies: The MERLON Project.

The prevalence of hormone-related health issues caused by exposure to endocrine disrupting chemicals (EDCs) is a significant, and increasing, societal challenge. Declining fertility rates together with rising incidence rates of reproductive disorders and other endocrine-related diseases underscores the urgency in taking more action. Addressing the growing threat of EDCs in our environment demands robust and reliable test methods to assess a broad variety of endpoints relevant for endocrine disruption. EDCs also require effective regulatory frameworks, especially as the current move towards greater reliance on non-animal methods in chemical testing puts to test the current paradigm for EDC identification, which requires that an adverse effect is observed in an intact organism. Although great advances have been made in the field of predictive toxicology, disruption to the endocrine system and subsequent adverse health effects may prove particularly difficult to predict without traditional animal models. The MERLON project seeks to expedite progress by integrating multispecies molecular research, new approach methodologies (NAMs), human clinical epidemiology, and systems biology to furnish mechanistic insights and explore ways forward for NAM-based identification of EDCs. The focus is on sexual development and function, from foetal sex differentiation of the reproductive system through mini-puberty and puberty to sexual maturity. The project aims are geared towards closing existing knowledge gaps in understanding the effects of EDCs on human health to ultimately support effective regulation of EDCs in the European Union and beyond.

Integrated Approach for Testing and Assessment for Developmental Neurotoxicity (DNT) to Prioritize Aromatic Organophosphorus Flame Retardants.

Organophosphorus flame retardants (OPFRs) are abundant and persistent in the environment but have limited toxicity information. Their similarity in structure to organophosphate pesticides presents great concern for developmental neurotoxicity (DNT). However, current in vivo testing is not suitable to provide DNT information on the amount of OPFRs that lack data. Over the past decade, an in vitro battery was developed to enhance DNT assessment, consisting of assays that evaluate cellular processes in neurodevelopment and function. In this study, behavioral data of small model organisms were also included. To assess if these assays provide sufficient mechanistic coverage to prioritize chemicals for further testing and/or identify hazards, an integrated approach to testing and assessment (IATA) was developed with additional information from the Integrated Chemical Environment (ICE) and the literature. Human biomonitoring and exposure data were identified and physiologically-based toxicokinetic models were applied to relate in vitro toxicity data to human exposure based on maximum plasma concentration. Eight OPFRs were evaluated, including aromatic OPFRs (triphenyl phosphate (TPHP), isopropylated phenyl phosphate (IPP), 2-ethylhexyl diphenyl phosphate (EHDP), tricresyl phosphate (TMPP), isodecyl diphenyl phosphate (IDDP), tert-butylphenyl diphenyl phosphate (BPDP)) and halogenated FRs ((Tris(1,3-dichloro-2-propyl) phosphate (TDCIPP), tris(2-chloroethyl) phosphate (TCEP)). Two representative brominated flame retardants (BFRs) (2,2'4,4'-tetrabromodiphenyl ether (BDE-47) and 3,3',5,5'-tetrabromobisphenol A (TBBPA)) with known DNT potential were selected for toxicity benchmarking. Data from the DNT battery indicate that the aromatic OPFRs have activity at similar concentrations as the BFRs and should therefore be evaluated further. However, these assays provide limited information on the mechanism of the compounds. By integrating information from ICE and the literature, endocrine disruption was identified as a potential mechanism. This IATA case study indicates that human exposure to some OPFRs could lead to a plasma concentration similar to those exerting in vitro activities, indicating potential concern for human health.

Preface to the special issue of Food and Chemical Toxicology on "New approach methodologies and machine learning in food safety and chemical risk assessment: Development of reproducible, open-source, and user-friendly tools for exposure, toxicokinetic, and toxicity assessments in the 21st century".

This Special Issue contains articles on applications of various new approach methodologies (NAMs) in the field of toxicology and risk assessment. These NAMs include in vitro high-throughput screening, quantitative structure-activity relationship (QSAR) modeling, physiologically based pharmacokinetic (PBPK) modeling, network toxicology analysis, molecular docking simulation, omics, machine learning, deep learning, and "template-and-anchor" multiscale computational modeling. These in vitro and in silico approaches complement each other and can be integrated together to support different applications of toxicology, including food safety assessment, dietary exposure assessment, chemical toxicity potency screening and ranking, chemical toxicity prediction, chemical toxicokinetic simulation, and to investigate the potential mechanisms of toxicities, as introduced further in selected articles in this Special Issue.

Integrating gene expression and splicing dynamics across dose-response oxidative modulators.

Toxicological risk assessment increasingly utilizes transcriptomics to derive point of departure (POD) and modes of action (MOA) for chemicals. One essential biological process that allows a single gene to generate several different RNA isoforms is called alternative splicing. To comprehensively assess the role of splicing dysregulation in toxicological evaluation and elucidate its potential as a complementary endpoint, we performed RNA-seq on A549 cells treated with five oxidative stress modulators across a wide dose range. Differential gene expression (DGE) showed limited pathway enrichment except at high concentrations. However, alternative splicing analysis revealed variable intron retention events affecting diverse pathways for all chemicals in the absence of significant expression changes. For instance, diazinon elicited negligible gene expression changes but progressive increase in the number of intron retention events, suggesting splicing alterations precede expression responses. Benchmark dose modeling of intron retention data highlighted relevant pathways overlooked by expression analysis. Systematic integration of splicing datasets should be a useful addition to the toxicogenomic toolkit. Combining both modalities paint a more complete picture of transcriptomic dose-responses. Overall, evaluating intron retention dynamics afforded by toxicogenomics may provide biomarkers that can enhance chemical risk assessment and regulatory decision making. This work highlights splicing-aware toxicogenomics as a possible additional tool for examining cellular responses.

Analyzing high-throughput assay data to advance the rapid screening of environmental chemicals for human reproductive toxicity.

While high-throughput (HTP) assays have been proposed as platforms to rapidly assess reproductive toxicity, there is currently a lack of established assays that specifically address germline development/function and fertility. We assessed the applicability domains of yeast (S. cerevisiae) and nematode (C. elegans) HTP assays in toxicity screening of 124 environmental chemicals, determining their agreement in identifying toxicants and their concordance with reproductive toxicity in vivo. We integrated data generated in the two models and compared results using a streamlined, semi-automated benchmark dose (BMD) modeling approach. We then extracted and modeled relevant mammalian in vivo data available for the matching chemicals included in the Toxicological Reference Database (ToxRefDB). We ranked potencies of common compounds using the BMD and evaluated correlation between the datasets using Pearson and Spearman correlation coefficients. We found moderate to good correlation across the three data sets, with r = 0.48 (95% CI: 0.28-1.00, p<0.001) and rs = 0.40 (p=0.002) for the parametric and rank order correlations between the HTP BMDs; r = 0.95 (95% CI: 0.76-1.00, p=0.0005) and rs = 0.89 (p=0.006) between the yeast assay and ToxRefDB BMDs; and r = 0.81 (95% CI: 0.28-1.00, p=0.014) and rs = 0.75 (p=0.033) between the worm assay and ToxRefDB BMDs. Our findings underscore the potential of these HTP assays to identify environmental chemicals that exhibit reproductive toxicity. Integrating these HTP datasets into mammalian in vivo prediction models using machine learning methods could further enhance the predictive value of these assays in future rapid screening efforts.

Far from Their Origins: A Transcriptomic Investigation on How 2,4-Di-tert-butyl-6-(5-chloro-2H-benzotriazol-2-yl) Phenol Affects Rainbow Trout Alevins.

Benzotriazole ultraviolet stabilizers (BUVSs) are a group of widely used chemicals added to a variety of consumer (e.g., plastics) and industrial (e.g., metal coating) goods. Although detected globally as an environmentally persistent pollutant, BUVSs have received relatively little toxicological attention and only recently have been acknowledged to affect development and the endocrine system in vivo. In our previous study, altered behavior, indicative of potential neurotoxicity, was observed among rainbow trout alevins (day 14 posthatching) that were microinjected as embryos with a single environmentally relevant dose of 2,4-di-tert-butyl-6-(5-chloro-2H-benzotriazol-2-yl) phenol (UV-327). In the present follow-up study, we performed whole-transcriptome profiling (RNA sequencing) of newly hatched alevins from the same batch. The primary aim was to identify biomarkers related to behavior and neurology. Dose-specifically, 1 to 176 differentially expressed genes (DEGs) were identified. In the group presenting altered behavior (273.4 ng g-1), 176 DEGs were identified, yet only a fraction was related to neurological functions, including water, calcium, and potassium homeostasis; acetylcholine transmission and signaling; as well insulin and energy metabolism. The second objective was to estimate the transcriptomic point of departure (tPOD) and assess if point estimate(s) are protective of altered behavior. A tPOD was established at 35 to 94 ng UV-327 g-1 egg, making this tPOD protective of behavioral alterations. Holistically, these transcriptomic alterations provide a foundation for future research on how BUVSs can influence rainbow trout alevin development, while providing support to the hypothesis that UV-327 can influence neurogenesis and subsequent behavioral endpoints. The exact structural and functional changes caused by embryonic exposure to UV-327 remain enigmatic and will require extensive investigation before being deciphered and understood toxicologically. Environ Toxicol Chem 2024;00:1-12. © 2024 The Author(s). Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Contractility assessment using aligned human iPSC-derived cardiomyocytes.

INTRODUCTION: Cardiac safety assessment, such as lethal arrhythmias and contractility dysfunction, is critical during drug development. Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have been shown to be useful in predicting drug-induced proarrhythmic risk through international validation studies. Although cardiac contractility is another key function, fit-for-purpose hiPSC-CMs in evaluating drug-induced contractile dysfunction remain poorly understood. In this study, we investigated whether alignment of hiPSC-CMs on nanopatterned culture plates can assess drug-induced contractile changes more efficiently than non-aligned monolayer culture. METHODS: Aligned hiPSC-CMs were obtained by culturing on 96-well culture plates with a ridge-groove-ridge nanopattern on the bottom surface, while non-aligned hiPSC-CMs were cultured on regular 96-well plates. Next-generation sequencing and qPCR experiments were performed for gene expression analysis. Contractility of the hiPSC-CMs was assessed using an imaging-based motion analysis system. RESULTS: When cultured on nanopatterned plates, hiPSC-CMs exhibited an aligned morphology and enhanced expression of genes encoding proteins that regulate contractility, including myosin heavy chain, calcium channel, and ryanodine receptor. Compared to cultures on regular plates, the aligned hiPSC-CMs also showed both enhanced contraction and relaxation velocity. In addition, the aligned hiPSC-CMs showed a more physiological response to positive and negative inotropic agents, such as isoproterenol and verapamil. DISCUSSION: Taken together, the aligned hiPSC-CMs exhibited enhanced structural and functional properties, leading to an improved capacity for contractility assessment compared to the non-aligned cells. These findings suggest that the aligned hiPSC-CMs can be used to evaluate drug-induced cardiac contractile changes.

An automated computational data pipeline to rapidly acquire, score, and rank toxicological data for ecological hazard assessment.

Biological Evaluations support Endangered Species Act (ESA) consultation with the US Fish and Wildlife Service and National Marine Fisheries Service by federal action agencies, such as the USEPA, regarding impacts of federal activities on threatened or endangered species. However, they are often time-consuming and challenging to conduct. The identification of pollutant benchmarks or guidance to protect taxa for states and tribes when USEPA has not yet developed criteria recommendations is also of importance to ensure a streamlined approach to Clean Water Act program implementation. Due to substantial workloads, tight regulatory timelines, and the often-protracted length of ESA consultations, there is a need to streamline the development of biological evaluation toxicity assessments for determining the impact of chemical pollutants on ESA-listed species. Moreover, there is limited availability of species-specific toxicity data for many contaminants, further complicating the consultation process. New approach methodologies are being increasingly used in toxicology and chemical safety assessment to rapidly and cost-effectively provide data that can fill gaps in hazard and/or exposure characterization. Here, we present the development of an automated computational pipeline-RASRTox (Rapidly Acquire, Score, and Rank Toxicological data)-to rapidly extract and categorize ecological toxicity benchmark values from curated data sources (ECOTOX, ToxCast) and well-established quantitative structure-activity relationships (TEST, ECOSAR). As a proof of concept, points-of-departure (PODs) generated in RASRTox for 13 chemicals were compared against benchmark values derived using traditional methods-toxicity reference values (TRVs) and water quality criteria (WQC). The RASRTox PODs were generally within an order of magnitude of corresponding TRVs, though less concordant compared with WQC. The greatest utility of RASRTox, however, lies in its ability to quickly and systematically identify critical studies that may serve as a basis for screening value derivation by toxicologists as part of an ecological hazard assessment. As such, the strategy described in this case study can potentially be adapted for other risk assessment contexts and stakeholder needs. Integr Environ Assess Manag 2024;00:1-15. © 2024 Society of Environmental Toxicology & Chemistry (SETAC). This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Systematic evaluation of high-throughput PBK modelling strategies for the prediction of intravenous and oral pharmacokinetics in humans.

Physiologically based kinetic (PBK) modelling offers a mechanistic basis for predicting the pharmaco-/toxicokinetics of compounds and thereby provides critical information for integrating toxicity and exposure data to replace animal testing with in vitro or in silico methods. However, traditional PBK modelling depends on animal and human data, which limits its usefulness for non-animal methods. To address this limitation, high-throughput PBK modelling aims to rely exclusively on in vitro and in silico data for model generation. Here, we evaluate a variety of in silico tools and different strategies to parameterise PBK models with input values from various sources in a high-throughput manner. We gather 2000 + publicly available human in vivo concentration-time profiles of 200 + compounds (IV and oral administration), as well as in silico, in vitro and in vivo determined compound-specific parameters required for the PBK modelling of these compounds. Then, we systematically evaluate all possible PBK model parametrisation strategies in PK-Sim and quantify their prediction accuracy against the collected in vivo concentration-time profiles. Our results show that even simple, generic high-throughput PBK modelling can provide accurate predictions of the pharmacokinetics of most compounds (87% of Cmax and 84% of AUC within tenfold). Nevertheless, we also observe major differences in prediction accuracies between the different parameterisation strategies, as well as between different compounds. Finally, we outline a strategy for high-throughput PBK modelling that relies exclusively on freely available tools. Our findings contribute to a more robust understanding of the reliability of high-throughput PBK modelling, which is essential to establish the confidence necessary for its utilisation in Next-Generation Risk Assessment.

The evaluation of skin sensitization potential of the UVCB substance diisopentyl phthalate by in silico and in vitro methods.

Diisopentyl phthalate (DiPeP) is primarily used as a plasticizer or additive within the production of polyvinyl chloride (PVC), and has many additional industrial applications. Its metabolites were recently found in urinary samples of pregnant women; thus, this substance is of concern as relates to human exposure. Depending upon the nature of the alcohol used in its synthesis, DiPeP may exist either as a mixture consisting of several branched positional isomers, or as a single defined structure. This article investigates the skin sensitization potential and immunomodulatory effects of DiPeP CAS No. 84777-06-0, which is currently marketed and classified as a UVCB substance, by in silico and in vitro methods. Our findings showed an immunomodulatory effect for DiPeP in LPS-induced THP-1 activation assay (increased CD54 expression). In silico predictions using QSAR TOOLBOX 4.5, ToxTree, and VEGA did not identify DiPeP, in the form of a discrete compound, as a skin sensitizer. The keratinocyte activation (Key Event 2 (KE2) of the adverse outcome pathway (AOP) for skin sensitization) was evaluated by two different test methods (HaCaT assay and RHE assay), and results were discordant. While the HaCaT assay showed that DiPeP can activate keratinocytes (increased levels of IL-6, IL-8, IL-1α, and ILA gene expression), in the RHE assay, DiPeP slightly increased IL-6 release. Although inconclusive for KE2, the role of DiPeP in KE3 (dendritic cell activation) was demonstrated by the increased levels of CD54 and IL-8 and TNF-α in THP-1 cells (THP-1 activation assay). Altogether, findings were inconclusive regarding the skin sensitization potential of the UVCB DiPeP-disagreeing with the results of DiPeP in the form of discrete compound (skin sensitizer by the LLNA assay). Additional studies are needed to elucidate the differences between DiPeP isomer forms, and to better understand the applicability domains of non-animal methods in identifying skin sensitization hazards of UVCB substances.

Development of a defined approach for eye hazard identification of solid chemicals according to the three UN GHS categories.

Currently there are two OECD-adopted defined approaches (DA) for eye hazard identification of non-surfactant liquids (OECD TG 467). The current study aimed to develop a DA for eye hazard identification of solid chemicals according to the three UN GHS categories (Cat.1, Cat. 2, No Cat.): the DAS. The DAS combines two test methods described in OECD TG 437 and TG 492. The DAS was developed based on in-depth statistical analysis of a database on solids containing in vitro and historically curated in vivo Draize eye test data. The performance of the DAS was assessed by comparing the predictions with the classification based on in vivo Draize eye test data, on the one hand, and with the performance criteria established by the OECD expert group, on the other hand. In a first tier of the DAS, the SkinEthic™ HCE EIT method (TG 492) is used to distinguish No Cat. from classified substances. For classified substances, the BCOP LLBO method (TG 437) is used to identify Cat. 1, and the remaining solids are predicted Cat. 2. In summary, 77.4% Cat. 1 (N=31), 52.3% Cat. 2 (N=18), and 70.0% of No Cat. (N=60) solids were correctly identified compared to the classification based on the Draize eye test. The percentage of correct predictions met the minimum OECD performance values of 75% Cat. 1, 50% Cat. 2, and 70% No Cat., and the percentage of mispredictions was below the established maximum values. Therefore, inclusion of the DAS in OECD TG 467 has been achieved.

Defined approaches combine information from different non-animal testing methods in a specific way and interpret the results according to a fixed procedure. Such defined approaches are already available as full replacements of animal testing to assess the eye hazard of liquid chemicals (OECD Test Guideline 467). This study used two OECD-adopted in vitro methods, based on human cells and corneas from cattle, to create a defined approach that can be used for solid chemicals. The performance of the procedure was assessed against data from previous animal tests for 109 solid chemicals. The results have already led to this defined approach being adopted by the OECD TGs programme for inclusion in TG 467. With the adoption of the new defined approach, non-animal human relevant strategies are now available for eye hazard assessment of liquids and solids, reducing the need for animal testing.