New approach methodologies in human regulatory toxicology - Not if, but how and when!

Standardization and optimization of the hiPSC-based PluriLum assay for detection of embryonic and developmental toxicants

New approach methodologies (NAMs) for predicting embryotoxicity and developmental toxicity are urgently needed for generating human relevant data, while reducing turnover time and costs, and alleviating ethical concerns related to the use of animal models. We have previously developed the PluriLum assay, a NKX2.5-reporter gene 3D model using human-induced pluripotent stem cells (hiPSCs) that are genetically modified to enable the assessment of adverse effects of chemicals on the early-stage embryo. Aiming at improving the predictive value of the PluriLum assay for future screening purposes, we sought to introduce standardization steps to the protocol, improving the overall robustness of the PluriLum assay, as well as a shortening of the assay protocol. First, we showed that the initial size of embryoid bodies (EBs) is crucial for a proper differentiation into cardiomyocytes and overall reproducibility of the assay. When the starting diameter of the EBs exceeds 500 µm, robust differentiation can be anticipated. In terms of reproducibility, exposure to the fungicide epoxiconazole at smaller initial diameters resulted in a larger variation of the derived data, compared to more reliable concentration-response curves obtained using spheroids with larger initial diameters. We further investigated the ideal length of the differentiation protocol, resulting in a shortening of the PluriLum assay by 24 h to 7 days. Following exposure to the teratogens all-trans and 13-cis retinoic acid, both cardiomyocyte contraction and measurement of NKX2.5-derived luminescence were recorded with a similar or increased sensitivity after 6 days of differentiation when compared to the original 7 days. Finally, we have introduced an efficient step for enzymatic dissociation of the EBs at assay termination. This allows for an even splitting of the individual EBs and testing of additional endpoints other than the NKX2.5-luciferase reporter, which was demonstrated in this work by the simultaneous assessment of ATP levels. In conclusion, we have introduced standardizations and streamlined the PluriLum assay protocol to improve its suitability as a NAM for screening of a large number of chemicals for developmental toxicity testing.

Towards characterization of cell culture conditions for reliable proteomic analysis: in vitro studies on A549, differentiated THP-1, and NR8383 cell lines

Proteomic investigations result in high dimensional datasets, but integration or comparison of different studies is hampered by high variances due to different experimental setups. In addition, cell culture conditions can have a huge impact on the outcome. This study systematically investigates the impact of experimental parameters on the proteomic profiles of commonly used cell lines-A549, differentiated THP-1 macrophage-like cells, and NR8383-for toxicity studies. The work focuses on analyzing the influence at the proteome level of cell culture setup involving different vessels, cell passage numbers, and post-differentiation harvesting time, aiming to improve the reliability of proteomic analyses for hazard assessment. Mass-spectrometry-based proteomics was utilized for accurate protein quantification by means of a label-free approach. Our results showed that significant proteome variations occur when cells are cultivated under different setups. Further analysis of these variations revealed their association to specific cellular pathways related to protein misfolding, oxidative stress, and proteasome activity. Conversely, the influence of cell passage numbers on the proteome is minor, suggesting a reliable range for conducting reproducible biological replicates. Notable, substantial proteome alterations occur over-time post-differentiation of dTHP-1 cells, particularly impacting pathways crucial for macrophage function. This finding is key for the interpretation of experimental results. These results highlight the need for standardized culture conditions in proteomic-based evaluations of treatment effects to ensure reliable results, a prerequisite for achieving regulatory acceptance of proteomics data.

In vitro 3D skin culture and its sustainability in toxicology: a narrative review

In current toxicological research, 2D cell cultures and animal models are well- accepted and commonly employed methods. However, these approaches have many drawbacks and are distant from the actual environment in human. To embrace this, great efforts have been made to provide alternative methods for non-animal skin models in toxicology studies with the need for more mechanistically informative methods. This review focuses on the current state of knowledge regarding the in vitro 3D skin model methods, with different functional states that correspond to the sustainability in the field of toxicology testing. We discuss existing toxicology testing methods using in vitro 3D skin models which provide a better understanding of the testing requirements that are needed. The challenges and future landscape in using the in vitro 3D skin models in toxicology testing are also discussed. We are confident that the in vitro 3D skin models application may become an important tool in toxicology in the context of risk assessment.

Leveraging a comprehensive unbiased RNAseq database to characterize human monocyte-derived macrophage gene expression profiles within commonly employed in vitro polarization methods

Macrophages are pivotal innate immune cells which exhibit high phenotypic plasticity and can exist in different polarization states dependent on exposure to external stimuli. Numerous methods have been employed to simulate macrophage polarization states to test their function in vitro. However, limited research has explored whether these polarization methods yield comparable populations beyond key gene, cytokine, and cell surface marker expression. Here, we employ an unbiased comprehensive analysis using data organized through the all RNA-seq and ChIP-seq sample and signature search (ARCHS4) database, which compiles all RNAseq data deposited into the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA). In silico analyses were carried out demonstrating that commonly employed macrophage polarization methods generate distinct gene expression profiles in macrophage subsets that remained poorly described until now. Our analyses confirm existing knowledge on broad macrophage polarization, while expanding nuanced differences between M2a and M2c subsets, suggesting non-interchangeable stimuli for M2a polarization. Furthermore, we characterize divergent gene expression patterns in M1 macrophages following standard polarization protocols, indicating significant subset distinctions. Consequently, equivalence cannot be assumed among polarization regimens for in vitro macrophage studies, particularly in simulating diverse pathogen responses.

Time-course cross-species transcriptomics reveals conserved hepatotoxicity pathways induced by repeated administration of cyclosporine A

Cyclosporine A (CsA) has shown efficacy against immunity-related diseases despite its toxicity in various organs, including the liver, emphasizing the need to elucidate its underlying hepatotoxicity mechanism. This study aimed to capture the alterations in genome-wide expression over time and the subsequent perturbations of corresponding pathways across species. Six data from humans, mice, and rats, including animal liver tissue, human liver microtissues, and two liver cell lines exposed to CsA toxic dose, were used. The microtissue exposed to CsA for 10 d was analyzed to obtain dynamically differentially expressed genes (DEGs). Single-time points data at 1, 3, 5, 7, and 28 d of different species were used to provide additional evidence. Using liver microtissue-based longitudinal design, DEGs that were consistently up- or down-regulated over time were captured, and the well-known mechanism involved in CsA toxicity was elucidated. Thirty DEGs that consistently changed in longitudinal data were also altered in 28-d rat in-house data with concordant expression. Some genes (e.g. TUBB2A, PLIN2, APOB) showed good concordance with identified DEGs in 1-d and 7-d mouse data. Pathway analysis revealed up-regulations of protein processing, asparagine N-linked glycosylation, and cargo concentration in the endoplasmic reticulum. Furthermore, the down-regulations of pathways related to biological oxidations and metabolite and lipid metabolism were elucidated. These pathways were also enriched in single-time-point data and conserved across species, implying their biological significance and generalizability. Overall, the human organoids-based longitudinal design coupled with cross-species validation provides temporal molecular change tracking, aiding mechanistic elucidation and biologically relevant biomarker discovery.

Comparative case study on NAMs: towards enhancing specific target organ toxicity analysis

Traditional risk assessment methodologies in toxicology have relied upon animal testing, despite concerns regarding interspecies consistency, reproducibility, costs, and ethics. New Approach Methodologies (NAMs), including cell culture and multi-level omics analyses, hold promise by providing mechanistic information rather than assessing organ pathology. However, NAMs face limitations, like lacking a whole organism and restricted toxicokinetic interactions. This is an inherent challenge when it comes to the use of omics data from in vitro studies for the prediction of organ toxicity in vivo. One solution in this context are comparative in vitro-in vivo studies as they allow for a more detailed assessment of the transferability of the respective NAM data. Hence, hepatotoxic and nephrotoxic pesticide active substances were tested in human cell lines and the results subsequently related to the biology underlying established effects in vivo. To this end, substances were tested in HepaRG and RPTEC/tERT1 cells at non-cytotoxic concentrations and analyzed for effects on the transcriptome and parts of the proteome using quantitative real-time PCR arrays and multiplexed microsphere-based sandwich immunoassays, respectively. Transcriptomics data were analyzed using three bioinformatics tools. Where possible, in vitro endpoints were connected to in vivo observations. Targeted protein analysis revealed various affected pathways, with generally fewer effects present in RPTEC/tERT1. The strongest transcriptional impact was observed for Chlorotoluron in HepaRG cells (increased CYP1A1 and CYP1A2 expression). A comprehensive comparison of early cellular responses with data from in vivo studies revealed that transcriptomics outperformed targeted protein analysis, correctly predicting up to 50% of in vivo effects.

Time-course characterization of whole-transcriptome dynamics of HepG2/C3A spheroids and its toxicological implications

Physiologically relevant in vitro models are a priority in predictive toxicology to replace and/or reduce animal experiments. The compromised toxicant metabolism of many immortalized human liver cell lines grown as monolayers as compared to in vivo metabolism limits their physiological relevance. However, recent efforts to culture liver cells in a 3D environment, such as spheroids, to better mimic the in vivo conditions, may enhance the toxicant metabolism of human liver cell lines. In this study, we characterized the dynamic changes in the transcriptome of HepG2/C3A hepatocarcinoma cell spheroids maintained in a clinostat system (CelVivo) to gain insight into the metabolic capacity of this model as a function of spheroid size and culture time. We assessed morphological changes (size, necrotic core), cell health, and proliferation rate from initial spheroid seeding to 35 days of continuous culture in conjunction with a time-course (0, 3, 7, 10, 14, 21, 28 days) of the transcriptome (TempO-Seq, BioSpyder). The phenotypic characteristics of HepG2/C3A growing in spheroids were comparable to monolayer growth until ∼Day 12 (Day 10-14) when a significant decrease in cell doubling rate was noted which was concurrent with down-regulation of cell proliferation and cell cycle pathways over this time period. Principal component analysis of the transcriptome data suggests that the Day 3, 7, and 10 spheroids are pronouncedly different from the Day 14, 21, and 28 spheroids in support of a biological transition time point during the long-term 3D spheroid cultures. The expression of genes encoding cellular components involved in toxicant metabolism and transport rapidly increased during the early time points of spheroids to peak at Day 7 or Day 10 as compared to monolayer cultures with a gradual decrease in expression with further culture, suggesting the most metabolically responsive time window for exposure studies. Overall, we provide baseline information on the cellular and molecular characterization, with a particular focus on toxicant metabolic capacity dynamics and cell growth, of HepG2/C3A 3D spheroid cultures over time.

The new paradigm in animal testing - "3Rs alternatives"

Regulatory studies have revolutionised over time. Today, the focus has shifted from animal toxicity testing to non-animal for regulatory safety testing. This move is in line with the international 3Rs (Replacement, Reduction, and Refinement) principle and has also changed the regulator's perspective. The 3R principle has stimulated changes in policy, regulations, and new approaches to safety assessment in drug development in many countries. The 3Rs approach has led to the discovery and application of new technologies and more human-relevant in vitro approaches that minimise the use of animals including non-human primates, in research and improve animal welfare. In 2016, the European Medicines Agency published the Guidelines on the principles of regulatory acceptance of 3Rs testing approaches, followed by a conceptual paper in 2023 to align with current 3R standards. Additionally, the United States Food and Drug Administration passed new legislation in 2023 that no longer requires all new human drugs to be tested on animals, which will change the current testing paradigm. This review paper provides the adoption of the 3Rs and the current regulatory perspective regarding their implementation.

Bridging the gap: Innovative human-based in vitro approaches for nanomaterials hazard assessment and their role in safe and sustainable by design, risk assessment, and life cycle assessment

The application of nanomaterials in industry and consumer products is growing exponentially, which has pressed the development and use of predictive human in vitro models in pre-clinical analysis to closely extrapolate potential toxic effects in vivo. The conventional cytotoxicity investigation of nanomaterials using cell lines from cancer origin and culturing them two-dimensionally in a monolayer without mimicking the proper pathophysiological microenvironment may affect a precise prediction of in vitro effects at in vivo level. In recent years, complex in vitro models (also belonging to the new approach methodologies, NAMs) have been established in unicellular to multicellular cultures either by using cell lines, primary cells or induced pluripotent stem cells (iPSCs), and reconstituted into relevant biological dimensions mimicking in vivo conditions. These advanced in vitro models retain physiologically reliant exposure scenarios particularly appropriate for oral, dermal, respiratory, and intravenous administration of nanomaterials, which have the potential to improve the in vivo predictability and lead to reliable outcomes. In this perspective, we discuss recent developments and breakthroughs in using advanced human in vitro models for hazard assessment of nanomaterials. We identified fit-for-purpose requirements and remaining challenges for the successful implementation of in vitro data into nanomaterials Safe and Sustainable by Design (SSbD), Risk Assessment (RA), and Life Cycle Assessment (LCA). By addressing the gap between in vitro data generation and the utility of in vitro data for nanomaterial safety assessments, a prerequisite for SSbD approaches, we outlined potential key areas for future development.

Impact of Biotransformation on Internal Concentrations and Specificity Classification of Organic Chemicals in the Zebrafish Embryo (Danio rerio)

Internal concentrations (ICs) are crucial for linking exposure to effects in the development of New Approach Methodologies. ICs of chemicals in aquatic organisms are primarily driven by hydrophobicity and modulated by biotransformation and efflux. Comparing the predicted baseline to observed toxicity enables the estimation of effect specificity, but biological processes can lead to overestimating ICs and bias the specificity assessment. To evaluate the prediction of a mass balance model (MBM) and the impact of biotransformation on ICs, experimental ICs of 63 chemicals in zebrafish embryos were compared to predictions with physicochemical properties as input parameters. Experimental ICs of 79% (50 of 63) of the chemicals deviated less than 10-fold from predictions, and the remaining 13 deviated up to a factor of 90. Using experimental ICs changed the classification for 19 chemicals, with ICs 5 to 90 times lower than predicted, showing the bias of specificity classification. Uptake kinetics of pirinixic acid, genistein, dexamethasone, ethoprophos, atorvastatin, and niflumic acid were studied over a 96 h exposure period, and transformation products (TPs) were elucidated using suspect- and nontarget screening with UPLC-HRMS. 35 TPs (5 to 8 TPs per compound) were tentatively identified and semiquantified based on peak areas, suggesting that biotransformation may partly account for the overpredictions of ICs.

New approach methodologies (NAMs) for the in vitro assessment of cleaning products for respiratory irritation: workshop report

The use of in vitro new approach methodologies (NAMs) to assess respiratory irritation depends on several factors, including the specifics of exposure methods and cell/tissue-based test systems. This topic was examined in the context of human health risk assessment for cleaning products at a 1-day public workshop held on 2 March 2023, organized by the American Cleaning Institute® (ACI). The goals of this workshop were to (1) review in vitro NAMs for evaluation of respiratory irritation, (2) examine different perspectives on current challenges and suggested solutions, and (3) publish a manuscript of the proceedings. Targeted sessions focused on exposure methods, in vitro cell/tissue test systems, and application to human health risk assessment. The importance of characterization of assays and development of reporting standards was noted throughout the workshop. The exposure methods session emphasized that the appropriate exposure system design depends on the purpose of the assessment. This is particularly important given the many dosimetry and technical considerations affecting relevance and translation of results to human exposure scenarios. Discussion in the in vitro cell/tissue test systems session focused on the wide variety of cell systems with varying suitability for evaluating key mechanistic steps, such as molecular initiating events (MIEs) and key events (KEs) likely present in any putative respiratory irritation adverse outcome pathway (AOP). This suggests the opportunity to further develop guidance around in vitro cell/tissue test system endpoint selection, assay design, characterization and validation, and analytics that provide information about a given assay's utility. The session on applications for human health protection emphasized using mechanistic understanding to inform the choice of test systems and integration of NAMs-derived data with other data sources (e.g., physicochemical properties, exposure information, and existing in vivo data) as the basis for in vitro to in vivo extrapolation. In addition, this group noted a need to develop procedures to align NAMs-based points of departure (PODs) and uncertainty factor selection with current human health risk assessment methods, together with consideration of elements unique to in vitro data. Current approaches are described and priorities for future characterization of in vitro NAMs to assess respiratory irritation are noted.

Rapid and noninvasive estimation of human arsenic exposure based on 4-photo-set of the hand and foot photos through artificial intelligence

Chronic exposure to arsenic is linked to the development of cancers in the skin, lungs, and bladder. Arsenic exposure manifests as variegated pigmentation and characteristic pitted keratosis on the hands and feet, which often precede the onset of internal cancers. Traditionally, human arsenic exposure is estimated through arsenic levels in biological tissues; however, these methods are invasive and time-consuming. This study aims to develop a noninvasive approach to predict arsenic exposure using artificial intelligence (AI) to analyze photographs of hands and feet. By incorporating well water consumption data and arsenic concentration levels, we developed an AI algorithm trained on 9988 hand and foot photographs from 2497 subjects. This algorithm correlates visual features of palmoplantar hyperkeratosis with arsenic exposure levels. Four pictures per patient, capturing both ventral and dorsal aspects of hands and feet, were analyzed. The AI model utilized existing arsenic exposure data, including arsenic concentration (AC) and cumulative arsenic exposure (CAE), to make binary predictions of high and low arsenic exposure. The AI model achieved an optimal area under the curve (AUC) values of 0.813 for AC and 0.779 for CAE. Recall and precision metrics were 0.729 and 0.705 for CAE, and 0.750 and 0.763 for AC, respectively. While biomarkers have traditionally been used to assess arsenic exposure, efficient noninvasive methods are lacking. To our knowledge, this is the first study to leverage deep learning for noninvasive arsenic exposure assessment. Despite challenges with binary classification due to imbalanced and sparse data, this approach demonstrates the potential for noninvasive estimation of arsenic concentration. Future studies should focus on increasing data volume and categorizing arsenic concentration statistics to enhance model accuracy. This rapid estimation method could significantly contribute to epidemiological studies and aid physicians in diagnosis.

New approach methodologies to confirm developmental toxicity of pharmaceuticals based on weight of evidence

The aim of embryo-fetal developmental toxicity assessments for pharmaceuticals is to inform potential risk of adverse pregnancy outcome, which has traditionally relied on studies in pregnant animals. Recent updates to international safety guidelines (ICH S5R3) have incorporated information on how to use weight of evidence and alternative assays to reduce animal use while still informing risk of fetal harm. Uptake of these alternative approaches has been slow due to limitations in understanding how alternative assays translate to in vivo effects and then relevance to human exposure. To understand the predictivity of new approach methodologies for developmental toxicity (DevTox NAMs), we used two pharmaceutical examples (glasdegib and lorlatinib) to illustrate the value of DevTox NAMs to complement weight of evidence (WoE) assessments while considering the relationship of concentration-effect levels in NAMs to in vivo studies. The in vitro results generated in a battery of assays (mEST, rWEC, zebrafish, and human based stem cells) confirmed the WoE based on literature and further confirmed by preliminary embryo-fetal development data. The data generated for these two compounds supports integrating DevTox NAMs into the developmental toxicity assessment for advanced cancer indications.

Intuitive toxicology in the 21st century-Bridging the perspectives of the public and risk assessors in Europe

Three decades ago, several articles on the subjectivity in chemical risk judgments (i.e., labeled "intuitive toxicology") measured the divide between the public and toxicologists with different backgrounds regarding the validity of predicting health effects based on in vivo studies. Similar divides with impacts on societal discourse and chemical risk assessment practices might exist concerning alternative toxicity testing methods (i.e., in vitro and in silico). However, studies to date have focused either on the public's views of in vivo or stem cell testing or on experts' views of in vivo testing and potential alternatives (i.e., toxicologists and medical students), which do not allow for a direct investigation of potential divides. To fill this knowledge gap, we conducted two online surveys, involving members of the German-speaking public in Switzerland and European human health risk assessors, respectively. This article presents the results of these two surveys regarding the divide in the public's and risk assessors' perspectives on risk assessment based on in vivo, in vitro, and in silico testing. Particularly, the survey with the risk assessors highlights that, beyond scientific and regulatory barriers, alternatives to in vivo testing may encounter individual hurdles, such as higher uncertainty associated with them. Understanding and addressing these hurdles will be crucial to facilitate the integration of new approach methodologies into chemical risk assessment practices as well as a successful transition toward next-generation risk assessment, bringing us closer to a fit-for-purpose and more efficient regulatory landscape.

Can Machine Learning Overcome the 95% Failure Rate and Reality that Only 30% of Approved Cancer Drugs Meaningfully Extend Patient Survival?

Despite implementing hundreds of strategies, cancer drug development suffers from a 95% failure rate over 30 years, with only 30% of approved cancer drugs extending patient survival beyond 2.5 months. Adding more criteria without eliminating nonessential ones is impractical and may fall into the "survivorship bias" trap. Machine learning (ML) models may enhance efficiency by saving time and cost. Yet, they may not improve success rate without identifying the root causes of failure. We propose a "STAR-guided ML system" (structure-tissue/cell selectivity-activity relationship) to enhance success rate and efficiency by addressing three overlooked interdependent factors: potency/specificity to the on/off-targets determining efficacy in tumors at clinical doses, on/off-target-driven tissue/cell selectivity influencing adverse effects in the normal organs at clinical doses, and optimal clinical doses balancing efficacy/safety as determined by potency/specificity and tissue/cell selectivity. STAR-guided ML models can directly predict clinical dose/efficacy/safety from five features to design/select the best drugs, enhancing success and efficiency of cancer drug development.

Differentially Induced Autophagy by Engineered Nanomaterial Treatment Has an Impact on Cellular Homeostasis and Cytotoxicity

Considering the increasing production of engineered nanomaterials (ENMs), new approach methodologies (NAMs) are essential for safe-by-design approaches and risk assessment. Our aim was to enhance screening strategies with a focus on reactivity-triggered toxicities. We applied in vitro tests to 10 selected benchmark ENMs in two cell models, lung epithelial A549 and differentiated THP-1 macrophage-like cells. Previously, we categorized ENMs based on surface reactivity. Here we elucidated their reactivity-triggered cytotoxicity and mode of action using the WST-1 assay (metabolic activity), LDH assay (cell membrane integrity), autophagosome detection, and proteomics. Nonreactive SiO2 NM-200 showed no significant impact on cell viability. Conversely, highly reactive CuO and ZnO (NM-110 and NM-111) disrupted cell homeostasis. Interestingly, moderately reactive TiO2 (NM-101 and NM-105) and CeO2 (NM-211 and NM-212), apparently without an adverse effect, induced autophagosome formation, evidencing autophagy as a defensive mechanism. Our improved in vitro testing strategy, combined with state-of-the-art reactivity information, screens ENMs for potential reactivity-triggered toxicity.

The GeoTox Package: Open-source software for connecting spatiotemporal exposure to individual and population-level risk

Background

Comprehensive environmental risk characterization, encompassing physical, chemical, social, ecological, and lifestyle stressors, necessitates innovative approaches to handle the escalating complexity. This is especially true when considering individual and population-level diversity, where the myriad combinations of real-world exposures magnify the combinatoric challenges. The GeoTox framework offers a tractable solution by integrating geospatial exposure data from source-to-outcome in a series of modular, interconnected steps.

Results

Here, we introduce the GeoTox open-source R software package for characterizing the risk of perturbing molecular targets involved in adverse human health outcomes based on exposure to spatially-referenced stressor mixtures. We demonstrate its usage in building computational workflows that incorporate individual and population-level diversity. Our results demonstrate the applicability of GeoTox for individual and population-level risk assessment, highlighting its capacity to capture the complex interplay of environmental stressors on human health.

Conclusions

The GeoTox package represents a significant advancement in environmental risk characterization, providing modular software to facilitate the application and further development of the GeoTox framework for quantifying the relationship between environmental exposures and health outcomes. By integrating geospatial methods with cutting-edge exposure and toxicological frameworks, GeoTox offers a robust tool for assessing individual and population-level risks from environmental stressors. GeoTox is freely available at https://niehs.github.io/GeoTox/.

Synthetic vitreous fibers (SVFs): adverse outcome pathways (AOPs) and considerations for next generation new approach methods (NAMs)

Fiber dimension, durability/dissolution, and biopersistence are critical factors for the risk of fibrogenesis and carcinogenesis. In the modern era, to reduce, refine, and replace animals in toxicology research, the application of in vitro test methods is paramount for hazard evaluation and designing synthetic vitreous fibers (SVFs) for safe use. The objectives of this review are to: (1) summarize the international frameworks and acceptability criteria for implementation of new approach methods (NAMs), (2) evaluate the adverse outcome pathways (AOPs), key events (KEs), and key event relationships (KERs) for fiber-induced fibrogenesis and carcinogenesis in accordance with Organization for Economic Co-operation and Development (OECD) guidelines, (3) consider existing and emerging technologies for in silico and in vitro toxicity testing for the respiratory system and the ability to predict effects in vivo, (4) outline a recommended testing strategy for evaluating the hazard and safety of novel SVFs, and (5) reflect on methods needs for in vitro in vivo correlation (IVIVC) and predictive approaches for safety assessment of new SVFs. AOP frameworks following the conceptual model of the OECD were developed through an evaluation of available molecular and cellular initiating events, which lead to KEs and KERs in the development of fiber-induced fibrogenesis and carcinogenesis. AOP framework development included consideration of fiber physicochemical properties, respiratory deposition and clearance patterns, biosolubility, and biopersistence, as well as cellular, organ, and organism responses. Available data support that fiber AOPs begin with fiber physicochemical characteristics which influence fiber exposure and biosolubility and subsequent key initiating events are dependent on fiber biopersistence and reactivity. Key cellular events of pathogenic fibers include oxidative stress, chronic inflammation, and epithelial/fibroblast proliferation and differentiation, which ultimately lead to hyperplasia, metaplasia, and fibrosis/tumor formation. Available in vitro models (e.g. single-, multi-cellular, organ system) provide promising NAMs tools to evaluate these intermediate KEs. However, data on SVFs demonstrate that in vitro biosolubility is a reasonable predictor for downstream events of in vivo biopersistence and biological effects. In vitro SVF fiber dissolution rates >100 ng/cm2/hr (glass fibers in pH 7 and stone fibers in pH 4.5) and in vivo SVF fiber clearance half-life less than 40 or 50 days were not associated with fibrosis or tumors in animals. Long (fiber lengths >20 µm) biodurable and biopersistent fibers exceeding these fiber dissolution and clearance thresholds may pose a risk of fibrosis and cancer. In vitro fiber dissolution assays provide a promising avenue and potentially powerful tool to predict in vivo SVF fiber biopersistence, hazard, and health risk. NAMs for fibers (including SVFs) may involve a multi-factor in vitro approach leveraging in vitro dissolution data in complement with cellular- and tissue- based in vitro assays to predict health risk.

In chemico methodology for engineered nanomaterial categorization according to number, nature and oxidative potential of reactive surface sites

Methanol probe chemisorption quantifies the number of reactive sites at the surface of engineered nanomaterials, enabling normalization per reactive site in reactivity and toxicity tests, rather than per mass or physical surface area. Subsequent temperature-programmed surface reaction (TPSR) of chemisorbed methanol identifies the reactive nature of surface sites (acidic, basic, redox or combination thereof) and their reactivity. Complementary to the methanol assay, a dithiothreitol (DTT) probe oxidation reaction is used to evaluate the oxidation capacity. These acellular approaches to quantify the number, nature, and reactivity of surface sites constitute a new approach methodology (NAM) for site-specific classification of nanomaterials. As a proof of concept, CuO, CeO2, ZnO, Fe3O4, CuFe2O4, Co3O4 and two TiO2 nanomaterials were probed. A harmonized reactive descriptor for ENMs was obtained: the DTT oxidation rate per reactive surface site, or oxidative turnover frequency (OxTOF). CuO and CuFe2O4 ENMs exhibit the largest reactive site surface density and possess the highest oxidizing ability in the series, as estimated by the DTT probe reaction, followed by CeO2 NM-211 and then titania nanomaterials (DT-51 and NM-101) and Fe3O4. DTT depletion for ZnO NM-110 was associated with dissolved zinc ions rather than the ZnO particles; however, the basic characteristics of the ZnO NM-110 particles were evidenced by methanol TPSR. These acellular assays allow ranking the eight nanomaterials into three categories with statistically different oxidative potentials: CuO, CuFe2O4 and Co3O4 are the most reactive; ceria exhibits a moderate reactivity; and iron oxide and the titanias possess a low oxidative potential.

Identification of Optimal Machine Learning Algorithms and Molecular Fingerprints for Explainable Toxicity Prediction Models Using ToxCast/Tox21 Bioassay Data

Recent studies have primarily focused on introducing novel frameworks to enhance the predictive power of toxicity prediction models by refining molecular representation methods and algorithms. However, these methods are inherently complex and often pose challenges in understanding and explaining, leading to barriers in their regulatory adoption and validation. Therefore, it is necessary to select the optimal model, considering not only model performance but also interpretability. This study aimed to identify the optimal combination of molecular fingerprints (pattern-based versus algorithm-based) and machine learning algorithms (simple versus complex) for developing explainable toxicity prediction models through an comprehensive investigation of the ToxCast/Tox21 bioassay data set. For 1092 ToxCast/Tox21 assays, five molecular fingerprints (MACCS, Morgan, RDKit, Layered, and Patterned) and six algorithms (MLP, GBT, Random Forest, kNN, Logistic Regression, and Naïve Bayes) were used to train the models. Results showed that 35 models revealed acceptable performance (F1 score or accuracy is 0.8 or higher). Among the combinations, either MACCS or Morgan, paired with Random Forest, demonstrated robust performance compared with other molecular fingerprints and algorithms. MACCS and Random Forest are valuable, even when prioritizing interpretability. Consequently, the MACCS-Random Forest combination model based on four assays, targeting G protein-coupled receptor and kinase, were identified and they can be used to discern specific structural features or patterns in chemical compounds, offering explainable insights into toxicity-related chemical structures. This study indicates the importance of not disregarding the utilization of simple models when assessing both predictivity and interpretability within the context of chemical feature-based Tox21 data analysis.

Seminar: Functional Exposomics and Mechanisms of Toxicity-Insights from Model Systems and NAMs

BACKGROUND

Significant progress has been made over the past decade in measuring the chemical components of the exposome, providing transformative population-scale frameworks in probing the etiologic link between environmental factors and disease phenotypes. While the analytical technologies continue to evolve with reams of data being generated, there is an opportunity to complement exposome-wide association studies (ExWAS) with functional analyses to advance etiologic search at organismal, cellular, and molecular levels.

OBJECTIVES

Exposomics is a transdisciplinary field aimed at enabling discovery-based analysis of the nongenetic factors that contribute to disease, including numerous environmental chemical stressors. While advances in exposure assessment are enhancing population-based discovery of exposome-wide effects and chemical exposure agents, functional screening and elucidation of biological effects of exposures represent the next logical step toward precision environmental health and medicine. In this work, we focus on the use, strategies, and prospects of alternative approaches and model systems to enhance the current human exposomics framework in biomarker search and causal understanding, spanning from bench-based nonmammalian organisms and cell culture to computational new approach methods (NAMs).

DISCUSSION

We visit the definition of the functional exposome and exposomics and discuss a need to leverage alternative models as opposed to mammalian animals for delineating exposome-wide health effects. Under the "three Rs" principle of reduction, replacement, and refinement, model systems such as roundworms, fruit flies, zebrafish, and induced pluripotent stem cells (iPSCs) are advantageous over mammals (e.g., rodents or higher vertebrates). These models are cost-effective, and cell-specific genetic manipulations in these models are easier and faster, compared to mammalian models. Meanwhile, in silico NAMs enhance hazard identification and risk assessment in humans by bridging the translational gaps between toxicology data and etiologic inference, as represented by in vitro to in vivo extrapolation (IVIVE) and integrated approaches to testing and assessment (IATA) under the adverse outcome pathway (AOP) framework. Together, these alternatives offer a strong toolbox to support functional exposomics to study toxicity and causal mediators underpinning exposure-disease links. https://doi.org/10.1289/EHP13120.

Combination of toxicological and epidemiological approaches for estimating the health impact of atmospheric pollutants. A proof of concept for NO2

BACKGROUND

Regular monitoring of the air pollutant nitrogen dioxide (NO2), an indicator for traffic-related emissions, is a priority in urban environments. The health impacts associated with NO2 exposure are the result of a combination of factors, including concentration, duration of exposure, and interactions with other pollutants. WHO has established air quality guidelines based on epidemiological studies.

OBJECTIVE

This study develops a new concept "Health Impact Pathways (HIPs)" using adversity as a probabilistic indicator of health effects. For this purpose, it integrates available toxicological and epidemiological information, using Adverse Outcome Pathways (AOPs), in order to understand chemical-biological interactions and their consequences on health.

METHODS

Literature review and meta-analysis of toxicological data supported by expert judgment were performed to establish: a) adversity pathways, b) quantitative criteria for scoring the observed toxicological effects (adversity indicators), c) NO2 exposure - adversity relationship for both long-term (1-36 months) and shortterm (1-7 days). The NO2 daily concentrations from January 2001 to December 2022, were obtained from Madrid city Air Quality network monitoring database. Adversity levels were compared with relative risk levels for all-cause and respiratory mortality estimated using linear equations from WHO 2021 guidelines.

RESULTS

Non-linear relations were obtained for all long- and short-term NO2 related adversity indicators; for long-term effects, the best fitting was obtained with a modified Haber's law model with an exponential coefficient for the exposure time of 0.25. Estimations are presented for a set of case studies for Madrid city, covering temporal and spatial variability. A clear improvement trend along the two decades was observed, as well as high inter- and intra-station variability; the adversity indicators provided integrated information on the temporal and spatial evolution of population level risk.

DISCUSSION

The proposed HIP conceptual approach offers promising advances for integrating experimental and epidemiological data. The next step is linking the concentration-adversity relationship with population health impacts through probability estimations, the preliminary estimations confirm the need for assessing independently different population groups.

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.

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.

Comparison on the mechanism and potency of hepatotoxicity among hemp extract and its four major constituent cannabinoids

Cannabidiol (CBD) has been reported to induce hepatotoxicity in clinical trials and research studies; however, little is known about the safety of other nonintoxicating cannabinoids. New approach methodologies (NAMs) based on bioinformatic analysis of high-throughput transcriptomic data are gaining increasing importance in risk assessment and regulatory decision-making of data-poor chemicals. In the current study, we conducted a concentration response transcriptomic analysis of hemp extract and its four major constituent cannabinoids [CBD, cannabichromene (CBC), cannabigerol (CBG), and cannabinol (CBN)] in hepatocytes derived from human induced pluripotent stem cells (iPSCs). Each compound impacted a distinctive combination of biological functions and pathways. However, all the cannabinoids impaired liver metabolism and caused oxidative stress in the cells. Benchmark concentration (BMC) analysis showed potencies in transcriptional activity of the cannabinoids were in the order of CBN > CBD > CBC > CBG, consistent with the order of their cytotoxicity IC50 values. Patterns of transcriptomic changes induced by hemp extract and its median overall BMC were very similar to CBD but differed significantly from other cannabinoids, suggesting that potential adverse effects of hemp extract were largely due to its major constituent CBD. Lastly, transcriptomic point-of-departure (tPoD) values were determined for each of the compounds, with the value for CBD (0.106 µM) being concordant with a previously reported one derived from apical endpoints of clinical and animal studies. Taken together, the current study demonstrates the potential utility of transcriptomic BMC analysis as a NAM for hazard assessment of data-poor chemicals, improves our understanding of the possible health effects of hemp extract and its constituent cannabinoids, and provides important tPoD data that could contribute to inform human safety assessment of these cannabinoid compounds.

Application of an in vitro new approach methodology to determine relative cancer potency factors of air pollutants based on whole mixtures

Air pollution is an example of a complex environmental mixture with different biological activities, making risk assessment challenging. Current cancer risk assessment strategies that focus on individual pollutants may overlook interactions among them, potentially underestimating health risks. Therefore, a shift towards the evaluation of whole mixtures is essential for accurate risk assessment. This study presents the application of an in vitro New Approach Methodology (NAM) to estimate relative cancer potency factors of whole mixtures, with a focus on organic pollutants associated with air particulate matter (PM). Using concentration-dependent activation of the DNA damage-signaling protein checkpoint kinase 1 (pChk1) as a readout, we compared two modeling approaches, the Hill equation and the benchmark dose (BMD) method, to derive Mixture Potency Factors (MPFs). MPFs were determined for five PM2.5 samples covering sites with different land uses and our historical pChk1 data for PM10 samples and Standard Reference Materials. Our results showed a concentration-dependent increase in pChk1 by all samples and a higher potency compared to the reference compound benzo[a]pyrene. The MPFs derived from the Hill equation ranged from 128 to 9793, while those from BMD modeling ranged from 70 to 303. Despite the differences in magnitude, a consistency in the relative order of potencies was observed. Notably, PM2.5 samples from sites strongly impacted by biomass burning had the highest MPFs. Although discrepancies were observed between the two modeling approaches for whole mixture samples, relative potency factors for individual PAHs were more consistent. We conclude that differences in the shape of the concentration-response curves and how MPFs are derived explain the observed differences in model agreement for complex mixtures and individual PAHs. This research contributes to the advancement of predictive toxicology and highlights the feasibility of transitioning from assessing individual agents to whole mixture assessment for accurate cancer risk assessment and public health protection.

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.

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.

Fifteen day repeat air: liquid Interface air-only exposures can cause respiratory epithelium injury in MucilAir™ nasal respiratory epithelial cells that parallels chemically induced cytotoxicity

New Approach Methodologies (NAMs) are being widely used to reduce, refine, and replace, animal use in studying toxicology. For respiratory toxicology, this includes in silico and in vitro alternatives using air:liquid interface (ALI) exposures to replace traditional in vivo inhalation studies. In previous studies using 1,3-dichloropropene (1,3-DCP), a 5-day 4 h repeat exposures of MucilAir™ nasal cell culture models caused, dose-dependent cytotoxicity, depletion of GSH, changes in differential gene expression and histopathological transitions in cellular morphology from pseudostratified columnar epithelium to squamous epithelium. In this report we attempted to extend these studies using 15-day 1,3-DCP 4 h exposures to using MucilAir™ nasal cultures as outlined by an US EPA recent task order (US EPA 2023). For the 15-day repeat exposure, there were severe histopathologic changes in the MucilAir™ nasal mock-treatment (air-only) VITROCELL® chamber controls compared to incubator controls preventing any further analysis. The histopathological transitions in cellular morphology from pseudostratified columnar epithelium to squamous epithelium observed in the air only control in this study and previously with 1,3-DCP in MucilAir™ nasal cultures is also a hallmark of chemically induced cytotoxic responses in vivo in the respiratory tract. Histopathology assessments of 3D respiratory tract models used in ALI exposures can provide the linkage between in vitro to in vivo outcomes as part of the validation efforts of ALI use in regulatory toxicology. This report indicates that importance of histopathological assessments of incubator and mock-treatment (air-only) controls from each ALI exposure experiment along with exposed cell based model.

High-Resolution Mass Spectrometry for Human Exposomics: Expanding Chemical Space Coverage

In the modern "omics" era, measurement of the human exposome is a critical missing link between genetic drivers and disease outcomes. High-resolution mass spectrometry (HRMS), routinely used in proteomics and metabolomics, has emerged as a leading technology to broadly profile chemical exposure agents and related biomolecules for accurate mass measurement, high sensitivity, rapid data acquisition, and increased resolution of chemical space. Non-targeted approaches are increasingly accessible, supporting a shift from conventional hypothesis-driven, quantitation-centric targeted analyses toward data-driven, hypothesis-generating chemical exposome-wide profiling. However, HRMS-based exposomics encounters unique challenges. New analytical and computational infrastructures are needed to expand the analysis coverage through streamlined, scalable, and harmonized workflows and data pipelines that permit longitudinal chemical exposome tracking, retrospective validation, and multi-omics integration for meaningful health-oriented inferences. In this article, we survey the literature on state-of-the-art HRMS-based technologies, review current analytical workflows and informatic pipelines, and provide an up-to-date reference on exposomic approaches for chemists, toxicologists, epidemiologists, care providers, and stakeholders in health sciences and medicine. We propose efforts to benchmark fit-for-purpose platforms for expanding coverage of chemical space, including gas/liquid chromatography-HRMS (GC-HRMS and LC-HRMS), and discuss opportunities, challenges, and strategies to advance the burgeoning field of the exposome.

Mary L, Truong L, McClure R, Martin JK, Leonard SW, Thunga P, Simonich MT, Waters KM, Field JA, Tanguay RL. Diverse PFAS produce unique transcriptomic changes linked to developmental toxicity in zebrafish

Per- and polyfluoroalkyl substances (PFAS) are a widespread and persistent class of contaminants posing significant environmental and human health concerns. Comprehensive understanding of the modes of action underlying toxicity among structurally diverse PFAS is mostly lacking. To address this need, we recently reported on our application of developing zebrafish to evaluate a large library of PFAS for developmental toxicity. In the present study, we prioritized 15 bioactive PFAS that induced significant morphological effects and performed RNA-sequencing to characterize early transcriptional responses at a single timepoint (48 h post fertilization) after early developmental exposures (8 h post fertilization). Internal concentrations of 5 of the 15 PFAS were measured from pooled whole fish samples across multiple timepoints between 24-120 h post fertilization, and additional temporal transcriptomics at several timepoints (48-96 h post fertilization) were conducted for Nafion byproduct 2. A broad range of differentially expressed gene counts were identified across the PFAS exposures. Most PFAS that elicited robust transcriptomic changes affected biological processes of the brain and nervous system development. While PFAS disrupted unique processes, we also found that similarities in some functional head groups of PFAS were associated with the disruption in expression of similar gene sets. Body burdens after early developmental exposures to select sulfonic acid PFAS, including Nafion byproduct 2, increased from the 24-96 h post fertilization sampling timepoints and were greater than those of sulfonamide PFAS of similar chain lengths. In parallel, the Nafion byproduct 2-induced transcriptional responses increased between 48 and 96 h post fertilization. PFAS characteristics based on toxicity, transcriptomic effects, and modes of action will contribute to further prioritization of PFAS structures for testing and informed hazard assessment.

Unleashing the potential of cell painting assays for compound activities and hazards prediction

The cell painting (CP) assay has emerged as a potent imaging-based high-throughput phenotypic profiling (HTPP) tool that provides comprehensive input data for in silico prediction of compound activities and potential hazards in drug discovery and toxicology. CP enables the rapid, multiplexed investigation of various molecular mechanisms for thousands of compounds at the single-cell level. The resulting large volumes of image data provide great opportunities but also pose challenges to image and data analysis routines as well as property prediction models. This review addresses the integration of CP-based phenotypic data together with or in substitute of structural information from compounds into machine (ML) and deep learning (DL) models to predict compound activities for various human-relevant disease endpoints and to identify the underlying modes-of-action (MoA) while avoiding unnecessary animal testing. The successful application of CP in combination with powerful ML/DL models promises further advances in understanding compound responses of cells guiding therapeutic development and risk assessment. Therefore, this review highlights the importance of unlocking the potential of CP assays when combined with molecular fingerprints for compound evaluation and discusses the current challenges that are associated with this approach.

Avoiding a reproducibility crisis in regulatory toxicology-on the fundamental role of ring trials

The ongoing transition from chemical hazard and risk assessment based on animal studies to assessment relying mostly on non-animal data, requires a multitude of novel experimental methods, and this means that guidance on the validation and standardisation of test methods intended for international applicability and acceptance, needs to be updated. These so-called new approach methodologies (NAMs) must be applicable to the chemical regulatory domain and provide reliable data which are relevant to hazard and risk assessment. Confidence in and use of NAMs will depend on their reliability and relevance, and both are thoroughly assessed by validation. Validation is, however, a time- and resource-demanding process. As updates on validation guidance are conducted, the valuable components must be kept: Reliable data are and will remain fundamental. In 2016, the scientific community was made aware of the general crisis in scientific reproducibility-validated methods must not fall into this. In this commentary, we emphasize the central importance of ring trials in the validation of experimental methods. Ring trials are sometimes considered to be a major hold-up with little value added to the validation. Here, we clarify that ring trials are indispensable to demonstrate the robustness and reproducibility of a new method. Further, that methods do fail in method transfer and ring trials due to different stumbling blocks, but these provide learnings to ensure the robustness of new methods. At the same time, we identify what it would take to perform ring trials more efficiently, and how ring trials fit into the much-needed update to the guidance on the validation of NAMs.

Zooplankton-based adverse outcome pathways: A tool for assessing endocrine disrupting compounds in aquatic environments

Endocrine disrupting compounds (EDCs) pose a significant ecological risk, particularly in aquatic ecosystems. EDCs have become a focal point in ecotoxicology, and their identification and regulation have become a priority. Zooplankton have gained global recognition as bioindicators, benefiting from rigorous standardization and regulatory validation processes. This review aims to provide a comprehensive summary of zooplankton-based adverse outcome pathways (AOPs) with a focus on EDCs as toxicants and the utilisation of freshwater zooplankton as bioindicators in ecotoxicological assessments. This review presents case studies in which zooplankton have been used in the development of AOPs, emphasizing the identification of molecular initiating events (MIEs) and key events (KEs) specific to zooplankton exposed to EDCs. Zooplankton-based AOPs may become an important resource for understanding the intricate processes by which EDCs impair the endocrine system. Furthermore, the data sources, experimental approaches, advantages, and challenges associated with zooplankton-based AOPs are discussed. Zooplankton-based AOPs framework can provide vital tools for consolidating toxicological knowledge into a structured toxicity pathway of EDCs, offering a transformative platform for facilitating enhanced risk assessment and chemical regulation.

Metabolomics in human SGBS cells as new approach method for studying adipogenic effects: Analysis of the effects of DINCH and MINCH on central carbon metabolism

Growing evidence suggests that exposure to certain metabolism-disrupting chemicals (MDCs), such as the phthalate plasticizer DEHP, might promote obesity in humans, contributing to the spread of this global health problem. Due to the restriction on the use of phthalates, there has been a shift to safer declared substitutes, including the plasticizer diisononyl-cyclohexane-1,2-dicarboxylate (DINCH). Notwithstanding, recent studies suggest that the primary metabolite monoisononyl-cyclohexane-1,2-dicarboxylic acid ester (MINCH), induces differentiation of human adipocytes and affects enzyme levels of key metabolic pathways. Given the lack of methods for assessing metabolism-disrupting effects of chemicals on adipose tissue, we used metabolomics to analyze human SGSB cells exposed to DINCH or MINCH. Concentration analysis of DINCH and MINCH revealed that uptake of MINCH in preadipocytes was associated with increased lipid accumulation during adipogenesis. Although we also observed intracellular uptake for DINCH, the solubility of DINCH in cell culture medium was limited, hampering the analysis of possible effects in the μM concentration range. Metabolomics revealed that MINCH induces lipid accumulation similar to peroxisome proliferator-activated receptor gamma (PPARG)-agonist rosiglitazone through upregulation of the pyruvate cycle, which was recently identified as a key driver of de novo lipogenesis. Analysis of the metabolome in the presence of the PPARG-inhibitor GW9662 indicated that the effect of MINCH on metabolism was mediated at least partly by a PPARG-independent mechanism. However, all effects of MINCH were only observed at high concentrations of 10 μM, which are three orders of magnitudes higher than the current concentrations of plasticizers in human serum. Overall, the assessment of the effects of DINCH and MINCH on SGBS cells by metabolomics revealed no adipogenic potential at physiologically relevant concentrations. This finding aligns with previous in vivo studies and supports the potential of our method as a New Approach Method (NAM) for the assessment of adipogenic effects of environmental chemicals.

Next Generation Risk Assessment approaches for advanced nanomaterials: Current status and future perspectives

This manuscript discusses the challenges of applying New Approach Methodologies (NAMs) for safe by design and regulatory risk assessment of advanced nanomaterials (AdNMs). The authors propose a framework for Next Generation Risk Assessment of AdNMs involving NAMs that is aligned to the conventional risk assessment paradigm. This framework is exposure-driven, endpoint-specific, makes best use of pre-existing information, and can be implemented in tiers of increasing specificity and complexity of the adopted NAMs. The tiered structure of the approach, which effectively combines the use of existing data with targeted testing will allow safety to be assessed cost-effectively and as far as possible with even more limited use of vertebrates. The regulatory readiness of state-of-the-art emerging NAMs is assessed in terms of Transparency, Reliability, Accessibility, Applicability, Relevance and Completeness, and their appropriateness for AdNMs is discussed in relation to each step of the risk assessment paradigm along with providing perspectives for future developments in the respective scientific and regulatory areas.

Assessing human carcinogenicity risk of agrochemicals without the rodent cancer bioassay

The rodent cancer bioassays are conducted for agrochemical safety assessment yet they often do not inform regulatory decision-making. As part of a collaborative effort, the Rethinking Carcinogenicity Assessment for Agrochemicals Project (ReCAAP) developed a reporting framework to guide a weight of evidence (WOE)-based carcinogenicity assessment that demonstrates how to fulfill the regulatory requirements for chronic risk estimation without the need to conduct lifetime rodent bioassays. The framework is the result of a multi-stakeholder collaboration that worked through an iterative process of writing case studies (in the form of waivers), technical peer reviews of waivers, and an incorporation of key learnings back into the framework to be tested in subsequent case study development. The example waivers used to develop the framework were written retrospectively for registered agrochemical active substances for which the necessary data and information could be obtained through risk assessment documents or data evaluation records from the US EPA. This exercise was critical to the development of a framework, but it lacked authenticity in that the stakeholders reviewing the waiver already knew the outcome of the rodent cancer bioassay(s). Syngenta expanded the evaluation of the ReCAAP reporting framework by writing waivers for three prospective case studies for new active substances where the data packages had not yet been submitted for registration. The prospective waivers followed the established framework considering ADME, potential exposure, subchronic toxicity, genotoxicity, immunosuppression, hormone perturbation, mode of action (MOA), and all relevant information available for read-across using a WOE assessment. The point of departure was estimated from the available data, excluding the cancer bioassay results, with a proposed use for the chronic dietary risk assessment. The read-across assessments compared data from reliable registered chemical analogues to strengthen the prediction of chronic toxicity and/or tumorigenic potential. The prospective case studies represent a range of scenarios, from a new molecule in a well-established chemical class with a known MOA to a molecule with a new pesticidal MOA (pMOA) and limited read-across to related molecules. This effort represents an important step in establishing criteria for a WOE-based carcinogenicity assessment without the rodent cancer bioassay(s) while ensuring a health protective chronic dietary risk assessment.

Characterization of Organic Anion and Cation Transport in Three Human Renal Proximal Tubular Epithelial Models

The polarised expression of specific transporters in proximal tubular epithelial cells is important for the renal clearance of many endogenous and exogenous compounds. Thus, ideally, the in vitro tools utilised for predictions would have a similar expression of apical and basolateral xenobiotic transporters as in vivo. Here, we assessed the functionality of organic cation and anion transporters in proximal tubular-like cells (PTL) differentiated from human induced pluripotent stem cells (iPSC), primary human proximal tubular epithelial cells (PTEC), and telomerase-immortalised human renal proximal tubular epithelial cells (RPTEC/TERT1). Organic cation and anion transport were studied using the fluorescent substrates 4-(4-(dimethylamino)styryl)-N-methylpyridinium iodide (ASP) and 6-carboxyfluorescein (6-CF), respectively. The level and rate of intracellular ASP accumulation in PTL following basolateral application were slightly lower but within a 3-fold range compared to primary PTEC and RPTEC/TERT1 cells. The basolateral uptake of ASP and its subsequent apical efflux could be inhibited by basolateral exposure to quinidine in all models. Of the three models, only PTL showed a modest preferential basolateral-to-apical 6-CF transfer. These results show that organic cation transport could be demonstrated in all three models, but more research is needed to improve and optimise organic anion transporter expression and functionality.

Toxicological evaluation of microbial secondary metabolites in the context of European active substance approval for plant protection products

Risk assessment (RA) of microbial secondary metabolites (SM) is part of the EU approval process for microbial active substances (AS) used in plant protection products (PPP). As the number of potentially produced microbial SM may be high for a certain microbial strain and existing information on the metabolites often are low, data gaps are frequently identified during the RA. Often, RA cannot conclusively clarify the toxicological relevance of the individual substances. This work presents data and RA conclusions on four metabolites, Beauvericin, 2,3-deepoxy-2,3-didehydro-rhizoxin (DDR), Leucinostatin A and Swainsonin in detail as examples for the challenging process of RA. To overcome the problem of incomplete assessment reports, RA of microbial AS for PPP is in need of new approaches. In view of the Next Generation Risk Assessment (NGRA), the combination of literature data, omic-methods, in vitro and in silico methods combined in adverse outcome pathways (AOPs) can be used for an efficient and targeted identification and assessment of metabolites of concern (MoC).

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.

Risk assessment of feed components of botanical origin - Approaches taken in the European Union

In view of a continuous trend in replacing synthetic feed additives and especially flavouring compounds by botanical preparations, different aspects of the safety evaluations of plants and plant-derived preparations and components in feed are discussed. This includes risk assessment approaches developed by the European Food Safety Authority (EFSA) for phytotoxins regarding unintentional exposure of target animals and of consumers to animal derived food via carry-over from feed. Relevant regulatory frameworks for feed additives and feed contaminants in the European Union are summarised and the essentials of existing guidelines used in the safety evaluation of botanicals and their preparations and components in feed are outlined. The examples presented illustrate how the safety of the botanicals, their preparations and components present in feed is assessed. An outlook on possible future developments in risk assessment by applying new in vitro and in silico methodologies is given.

Public views of animal testing and alternatives in chemical risk assessment

Next-Generation Risk Assessment (NGRA) aims to implement New Approach Methodologies (NAMs) into risk assessment and to rely on new in vivo testing in animals only as a last resort. However, various technical and regulatory hurdles impede their regulatory implementation. Assumptions about the public's expectations could act as barriers to the acceptance of NAMs. This study aimed at investigating public views of animal testing and potential alternatives, namely in vitro and in silico testing. An online survey was conducted (N = 965). The results suggest that people make trade-offs, as they experience negative affect regarding in vivo testing, which partly might explain their openness regarding certain alternatives. In vitro tests were attributed the highest ability to determine harmful effects of chemicals for different endpoints, followed by in vivo and in silico tests. Our results further showed that many people accept chemicals to be only tested with alternatives, with highest acceptance for household consumer products, food contact material or building materials and less accepting for medicines and foods. This article addresses potential challenges that might arise from public perceptions and thus, contributes to the bottom-up initiatives to overcome the hurdles to the implementation of NAMs in regulatory risk assessment.

Essential Guidelines for Manufacturing and Application of Organoids

An organoid is a self-organized three-dimensional structure derived from stem cells that mimics the structure, cell composition, and functional characteristics of specific organs and tissues and is used for evaluating the safety and effectiveness of drugs and the toxicity of industrial chemicals. Organoid technology is a new methodology that could replace testing on animals testing and accelerate development of precision and regenerative medicine. However, large variations in production can occur between laboratories with low reproducibility of the production process and no internationally agreed standards for quality evaluation factors at endpoints. To overcome these barriers that hinder the regulatory acceptance and commercialization of organoids, Korea established the Organoid Standards Initiative in September 2023 with various stakeholders, including industry, academia, regulatory agencies, and standard development experts, through public and private partnerships. This developed general guidelines for organoid manufacturing and quality evaluation and for quality evaluation guidelines for organoid-specific manufacturing for the liver, intestines, and heart through extensive evidence analysis and consensus among experts. This report is based on the common standard guideline v1.0, which is a general organoid manufacturing and quality evaluation to promote the practical use of organoids. This guideline does not focus on specific organoids or specific contexts of use but provides guidance to organoid makers and users on materials, procedures, and essential quality assessment methods at end points that are essential for organoid production applicable at the current technology level.

Advancing Nanomaterial Toxicology Screening Through Efficient and Cost-Effective Quantitative Proteomics

Proteomic investigations yield high-dimensional datasets, yet their application to large-scale toxicological assessments is hindered by reproducibility challenges due to fluctuating measurement conditions. To address these limitations, this study introduces an advanced tandem mass tag (TMT) labeling protocol. Although labeling approaches shorten data acquisition time by multiplexing samples compared to traditional label-free quantification (LFQ) methods in general, the associated costs may surge significantly with large sample sets, for example, in toxicological screenings. However, the introduced advanced protocol offers an efficient, cost-effective alternative, reducing TMT reagent usage (by a factor of ten) and requiring minimal biological material (1 µg), while demonstrating increased reproducibility compared to LFQ. To demonstrate its effectiveness, the advanced protocol is employed to assess the toxicity of nine benchmark nanomaterials (NMs) on A549 lung epithelial cells. While LFQ measurements identify 3300 proteins, they proved inadequate to reveal NM toxicity. Conversely, despite detecting 2600 proteins, the TMT protocol demonstrates superior sensitivity by uncovering alterations induced by NM treatment. In contrast to previous studies, the introduced advanced protocol allows simultaneous and straightforward assessment of multiple test substances, enabling prioritization, ranking, and grouping for hazard evaluation. Additionally, it fosters the development of New Approach Methodologies (NAMs), contributing to innovative methodologies in toxicological research.

Effects of Chemicals in Reporter Gene Bioassays with Different Metabolic Activities Compared to Baseline Toxicity

High-throughput cell-based bioassays are used for chemical screening and risk assessment. Chemical transformation processes caused by abiotic degradation or metabolization can reduce the chemical concentration or, in some cases, lead to the formation of more toxic transformation products. Unaccounted loss processes may falsify the bioassay results. Capturing the formation and effects of transformation products is important for relating the in vitro effects to in vivo. Reporter gene cell lines are believed to have low metabolic activity, but inducibility of cytochrome P450 (CYP) enzymes has been reported. Baseline toxicity is the minimal toxicity a chemical can have and is caused by the incorporation of the chemical into cell membranes. In the present study, we improved an existing baseline toxicity model based on a newly defined critical membrane burden derived from freely dissolved effect concentrations, which are directly related to the membrane concentration. Experimental effect concentrations of 94 chemicals in three bioassays (AREc32, ARE-bla and GR-bla) were compared with baseline toxicity by calculating the toxic ratio (TR). CYP activities of all cell lines were determined by using fluorescence-based assays. Only ARE-bla showed a low basal CYP activity and inducibility and AREc32 showed a low inducibility. Overall cytotoxicity was similar in all three assays despite the different metabolic activities indicating that chemical metabolism is not relevant for the cytotoxicity of the tested chemicals in these assays. Up to 28 chemicals showed specific cytotoxicity with TR > 10 in the bioassays, but baseline toxicity could explain the effects of the majority of the remaining chemicals. Seven chemicals showed TR < 0.1 indicating inaccurate physicochemical properties or experimental artifacts like chemical precipitation, volatilization, degradation, or other loss processes during the in vitro bioassay. The new baseline model can be used not only to identify specific cytotoxicity mechanisms but also to identify potential problems in the experimental performance or evaluation of the bioassay and thus improve the quality of the bioassay data.

New Approach Methodologies (NAMs) for ad hoc human health risk assessment of food and non-food products - Proceedings of a workshop

RIVM convened a workshop on the use of New Approach Methodologies (NAMs) for the ad hoc human health risk assessment of food and non-food products. Central to the workshop were two case studies of marketed products with a potential health concern: the botanical Tabernanthe iboga which is used to facilitate mental or spiritual insight or to (illegally) treat drug addiction and is associated with cardiotoxicity, and dermal creams containing female sex hormones, intended for use by perimenopausal women to reduce menopause symptoms without medical supervision. The workshop participants recognized that data from NAM approaches added valuable information for the ad hoc risk assessment of these products, although the available approaches were inadequate to derive health-based guidance values. Recommendations were provided on how to further enhance and implement NAM approaches in regulatory risk assessment, specifying both scientific and technical aspects as well as stakeholder engagement aspects.

Zebrafish and nematodes as whole organism models to measure developmental neurotoxicity

Despite the growing epidemiological evidence of an association between toxin exposure and developmental neurotoxicity (DNT), systematic testing of DNT is not mandatory in international regulations for admission of pharmaceuticals or industrial chemicals. However, to date around 200 compounds, ranging from pesticides, pharmaceuticals and industrial chemicals, have been tested for DNT in the current OECD test guidelines (TG-443 or TG-426). There are calls for the development of new approach methodologies (NAMs) for DNT, which has resulted in a DNT testing battery using in vitro human cell-based assays. These assays provide a means to elucidate the molecular mechanisms of toxicity in humans which is lacking in animal-based toxicity tests. However, cell-based assays do not represent all steps of the complex process leading to DNT. Validated models with a multi-organ network of pathways that interact at the molecular, cellular and tissue level at very specific timepoints in a life cycle are currently missing. Consequently, whole model organisms are being developed to screen for, and causally link, new molecular targets of DNT compounds and how they affect whole brain development and neurobehavioral endpoints. Given the practical and ethical restraints associated with vertebrate testing, lower animal models that qualify as 3 R (reduce, refine and replace) models, including the nematode (Caenorhabditis elegans) and the zebrafish (Danio rerio) will prove particularly valuable for unravelling toxicity pathways leading to DNT. Although not as complex as the human brain, these 3 R-models develop a complete functioning brain with numerous neurodevelopmental processes overlapping with human brain development. Importantly, the main signalling pathways relating to (neuro)development, metabolism and growth are highly conserved in these models. We propose the use of whole model organisms specifically zebrafish and C. elegans for DNT relevant endpoints.