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

Contributions of the joint FAO/WHO expert committee on food additives to international food safety: celebrating the 100th meeting of the committee

The Joint FAO/WHO Expert Committee on Food Additives (JECFA) is an international scientific committee that carries out safety and risk assessments on substances that are intended to be added to food or may be present in food. It advises the Codex Alimentarius Commission and the member countries of the Food and Agricultural Organization and the World Health Organization. In 2025, JECFA has its 100th meeting. This paper reviews the work of JECFA since its inception in 1956. The Committee has evaluated over 660 food additives, 105 enzymes, 2500 flavourings, 11 groups of natural toxicants, 12 metals, 25 groups of synthetic chemical contaminants, and residues of 115 veterinary drugs. The Committee has made major contributions internationally on risk assessment methodology for food safety, including the setting of health-based guidance values for chemicals in food, the evaluation of genotoxic and carcinogenic contaminants in food, benchmark dose analysis, use of body burden comparisons, and global approaches to dietary exposure assessment. JECFA advice is independent and based on objective, state-of-the-science assessment of the evidence. Its advice and evaluations are a freely available online resource and play a pivotal role in ensuring the protection of consumer health and enabling the international trade of safe food.

Fast unmasking toxicity of safe personal care products

Personal care products are used several times a day and come into contact with the skin for many hours. As hazard-related data on products are rare, an imaging safety screening was developed. For the first time, it detected known and unknown hazardous compounds in 140 personal care products from 20 different product segments, including beauty and lifestyle products. The evidence-based chromatographic-hazard-related profiling detected genotoxic, cytotoxic, and estrogenic compounds, which were assigned to structural groups, and revealed that personal care products are not as safe as stated. Wound-healing and nipple creams in contact with babies as well as lipsticks used by adolescents were shown to contain highly toxic compounds able to enter the bloodstream via wounds, micro-injuries or bleeding gums and contaminate nature when washed off. Dose-response curves pointed to half-maximal genotoxic effect doses (EC50) of around 60 µg of such products which can easily be exceeded by a factor of 100,000 for only 6 g product applied or for an aggregated use of various products increasing genotoxic exposure, as observed in consumer profiles. Simulated metabolization via S9 liver enzymes did not lead to detoxification. The new safety screening not only unmasked quickly the toxicity of personal care products but also provided an understanding of how to produce hazard-free products. It empowers industries to produce future products in compliance with their standards and claims in terms of consumer health, ethics, environmental compatibility, and sustainability, and authorities to control the safety of products on the market and tackle the current underregulation.

Chemical safety screening of products - better proactive

The increasing pressure to ensure product safety in a global market comes up against the current practice of targeting only known hazardous compounds in product safety analysis. However, product safety refers not only to known but also to unknown or hidden hazards that are very important to know and avoid. Shortcomings and limitations of currently used technologies seem to cause an obvious discrepancy between intended and actual consumer protection. Products are not as safe as claimed by stakeholders. An existing but overlooked proactive safety screening with a prioritization strategy is brought into focus as it offers a unique solution. It can handle the complexity of a product with thousands of compounds of unknown identity and unknown toxicity and can figure out the important hazardous compounds, both known and unknown. Using hardly any sample preparation and the effect detection at an early position in the workflow is a game changer not to overlook hazardous compounds. All analytical technologies are needed, but the key is the re-arrangement of the instrument order, i.e. firstly hazard-related screening (effect first) and secondly, focus on identification of prioritized hazardous compounds. Such a proactive safety screening revealed previously unknown hazardous compounds in products on the market claimed to be safe. The highly sustainable, affordable, and all-in-one 2LabsToGo-Eco with easy-to-use planar bioassays empowers stakeholders to implement proactive safety screening and dynamic risk management. The transition to greater efficacy in consumer protection needs incentives and the critical review aims to stimulate a debate.

Taking the 3Rs to a higher level: replacement and reduction of animal testing in life sciences in space research

Human settlements on the Moon, crewed missions to Mars and space tourism will become a reality in the next few decades. Human presence in space, especially for extended periods of time, will therefore steeply increase. However, despite more than 60 years of spaceflight, the mechanisms underlying the effects of the space environment on human physiology are still not fully understood. Animals, ranging in complexity from flies to monkeys, have played a pioneering role in understanding the (patho)physiological outcome of critical environmental factors in space, in particular altered gravity and cosmic radiation. The use of animals in biomedical research is increasingly being criticized because of ethical reasons and limited human relevance. Driven by the 3Rs concept, calling for replacement, reduction and refinement of animal experimentation, major efforts have been focused in the past decades on the development of alternative methods that fully bypass animal testing or so-called new approach methodologies. These new approach methodologies range from simple monolayer cultures of individual primary or stem cells all up to bioprinted 3D organoids and microfluidic chips that recapitulate the complex cellular architecture of organs. Other approaches applied in life sciences in space research contribute to the reduction of animal experimentation. These include methods to mimic space conditions on Earth, such as microgravity and radiation simulators, as well as tools to support the processing, analysis or application of testing results obtained in life sciences in space research, including systems biology, live-cell, high-content and real-time analysis, high-throughput analysis, artificial intelligence and digital twins. The present paper provides an in-depth overview of such methods to replace or reduce animal testing in life sciences in space research.

Long-Term Exposure to Real-Life Polyethylene Terephthalate Nanoplastics Induces Carcinogenesis In Vitro

Micro/nanoplastics (MNPLs) are environmental contaminants originating mainly from plastic waste degradation that pose potential health risks. Inhalation is a major exposure route, as evidenced by their detection in human lungs, with polyethylene terephthalate (PET) among the most abundant particles in respiratory airways. However, the harmful effects of particle bioaccumulation remain unclear, as chronic effects are understudied. To assess long-term effects, specifically carcinogenic effects, BEAS-2B cells were exposed to PET-NPLs for 30 weeks. Genotoxicity, carcinogenic phenotypic hallmarks, and a panel of genes and pathways associated with cell transformation and lung cancer were examined and compared across three exposure durations. No significant effects were observed after 24 h or 15 weeks of exposure. However, a 30-week exposure led to increased genotoxic damage, anchorage-independent growth, and invasive potential. Transcriptomic analysis showed the upregulation of several oncogenes and lung cancer-associated genes at the end of the exposure. Further analysis revealed an increase in differentially expressed genes over time and a temporal gradient of lung cancer-related genes. Altogether, the data suggest PET-NPLs' potential carcinogenicity after extended exposure, highlighting serious long-term health risks of MNPLs. Assessing their carcinogenic risks under chronic scenarios of exposure is crucial to addressing knowledge gaps and eventually developing preventive policies.

Next generation risk assessment and new approach methodologies for safe and sustainable by design chemicals and materials: Perspectives and challenges for occupational health

Europe is facing increasingly challenging threats to health and well-being, including chemical pollution, climate change, and biodiversity loss. To counter such threats, the European Union has developed a series of policy strategies, including the Chemicals Strategy for Sustainability and the Zero Pollution Action Plan that pointed out the need for safe-and-sustainable-by-design (SSbD) chemicals/materials. The SSbD and the "zero pollution" ambition will inevitably lead to a transformation of the conditions of exposure to chemicals both in general living environments and workplaces with the consequent need to adequately anticipate and manage the chemical risk, starting from the assessment of the hazard and risk characterization. Among those, next generation risk assessment (NGRA) is defined as a human-relevant, exposure-led, hypothesis driven risk assessment approach, designed to prevent harm. To date, application of NGRA has been restricted to assessing the use of cosmetics, and it has not been implemented in occupational risk assessment. Occupational safety assessment represents an area that would benefit from increasing application of NGRA to safety decision making. Additionally, the application of new approach methodologies (NAMs) can support the generation of data useful to implement the operationalization of the SSbD framework, favorably impacting the adoption of suitable management strategies. In turn, the historical occupational preventive and protective approach to the health and safety of workers may provide support to adequately implement NGRA in the occupational context. Therefore, this work aims to provide an overview on the principal available NAMs and their possible implications for occupational chemical risk assessment and management.

Dynamic QSAR modeling for predicting in vivo genotoxicity and inflammation induced by nanoparticles and advanced materials: a time-dose-property/response approach

Predicting the health risks of nanoparticles (NPs) and advanced materials (AdMa) is a critical challenge. Due to the complexity and time-consuming nature of experimental testing, there is a reliance on in silico methods such as quantitative structure-activity relationship (QSAR), which, while effective, often fail to capture the dynamic nature of material activity over time-essential for reliable risk assessment. This study develops dynamic QSAR models using machine learning to predict toxicological responses, such as inflammation and genotoxicity, following pulmonary exposure to 39 AdMa across various post-exposure time points and dose levels. By incorporating exposure time, administered dose, and material properties as independent variables, we successfully developed time-dose-property/response models capable of predicting AdMa-induced in vivo genotoxicity in bronchoalveolar lavage fluid cells, lung and liver tissue, and inflammation in terms of neutrophil influx into the lungs of mice. Key factors driving AdMa-induced toxicity were identified, including exposure dose, post-exposure duration time, aspect ratio, surface area, reactive oxygen species generation, and metal ion release. The time-dose-property/response modeling paradigm presented here provides a practical and robust approach for predicting in vivo genotoxicity and inflammation and supports the comprehensive risk assessment of morphologically diverse AdMa.

Next generation risk assessment of hair dye HC yellow no. 13: Ensuring protection from liver steatogenic effects

This study employs animal-free Next Generation Risk Assessment (NGRA) principles to evaluate the safety of repeated dermal exposure to 2.5% (w/w) HC Yellow No. 13 (HCY13) hair dye. As multiple in silico tools consistently flagged hepatotoxic potential, likely due to HCY13's trifluoromethyl group, which is known to interfere with hepatic lipid metabolism, liver steatosis was chosen as the primary mode of action for evaluation. AOP-guided in vitro tests were conducted, exposing human stem cell-derived hepatic cells to varying HCY13 concentrations over 72 h. The expression of 11 lipid metabolism-related marker genes (AHR, PPARA, LXRA, APOB, ACOX1, CPT1A, FASN, SCD1, DGAT2, CD36, and PPARG) and triglyceride accumulation, a phenotypic hallmark of steatosis, were measured. PROAST software was used to calculate in vitro Points of Departure (PoDNAM) for each biomarker. Using GastroPlus 9.9, physiologically-based pharmacokinetic (PBPK) models estimated internal liver concentrations (Cmax liver) of HCY13, ranging from 4 to 20 pM. All PoDNAM values significantly exceeded the predicted Cmax liver, indicating that HCY13 at 2.5% (w/w) is unlikely to induce liver steatosis under the assumed conditions. This research demonstrates the utility of NGRA, integrating AOP-based in vitro assays and computational models to protect human health and support regulatory decision-making without animal testing.

Ethical principles for regulatory risk decision-making

Risk assessors, managers, and decision-makers are responsible for evaluating diverse human, environmental, and animal health risks. Although the critical elements of risk assessment and management are well-described in national and international documents, the ethical issues involved in risk decision-making have received comparatively little attention to date. To address this aspect, this article elaborates fundamental ethical principles designed to support fair, balanced, and equitable risk-based decision-making practices. Experts and global thinkers in risk, health, regulatory, and animal sciences were convened to share their lived experiences in relation to the intersection between risk science and analysis, regulatory science, and public health. Through a participatory and knowledge translation approach, an integrated risk decision-making model, with ethical principles and considerations, was developed and applied using diverse, contemporary risk decision-making and regulatory contexts. The ten principles - autonomy, minimize harm, maintain respect and trust, adaptability, reduce disparities, holistic, fair and just, open and transparent, stakeholder engagement, and One Health lens - demonstrate how public sector values and moral norms (i.e., ethics) are relevant to risk decision-making. We also hope these principles and considerations stimulate further discussion, debate, and an increased awareness of the application of ethics in identifying, assessing, and managing health risks.

Per- and polyfluoroalkyl substances (PFAS): immunotoxicity at the primary sites of exposure

Per- and polyfluoroalkyl substances (PFAS) are persistent synthetic chemicals widely used in industrial and consumer products, leading to environmental contamination and human exposure. This review focuses on perfluoroalkyl acids, a subset of PFAS, which are primarily encountered through diet, including drinking water, and other pathways such as dust ingestion, and dermal contact. Impaired vaccine antibody response has been identified as the most critical effect for risk assessment by the European Food Safety Authority. Furthermore, human epidemiological studies have linked exposure to certain PFAS to various immune-related outcomes, such as asthma, allergies, and inflammatory bowel disease. This review examines potential immunomodulatory effects of perfluoroalkyl acids at the primary sites of exposure: lungs, intestines, and skin, using human epidemiological data as the basis for investigating these impacts. While animal studies are referenced for context, this paper highlights the need for further human-based research to address key questions about PFAS and their immunological impacts. The state of in vitro toxicity testing related to these effects is thoroughly reviewed and critical issues pertaining to this topic are discussed.

Machine Learning for Toxicity Prediction Using Chemical Structures: Pillars for Success in the Real World

Machine learning (ML) is increasingly valuable for predicting molecular properties and toxicity in drug discovery. However, toxicity-related end points have always been challenging to evaluate experimentally with respect to in vivo translation due to the required resources for human and animal studies; this has impacted data availability in the field. ML can augment or even potentially replace traditional experimental processes depending on the project phase and specific goals of the prediction. For instance, models can be used to select promising compounds for on-target effects or to deselect those with undesirable characteristics (e.g., off-target or ineffective due to unfavorable pharmacokinetics). However, reliance on ML is not without risks, due to biases stemming from nonrepresentative training data, incompatible choice of algorithm to represent the underlying data, or poor model building and validation approaches. This might lead to inaccurate predictions, misinterpretation of the confidence in ML predictions, and ultimately suboptimal decision-making. Hence, understanding the predictive validity of ML models is of utmost importance to enable faster drug development timelines while improving the quality of decisions. This perspective emphasizes the need to enhance the understanding and application of machine learning models in drug discovery, focusing on well-defined data sets for toxicity prediction based on small molecule structures. We focus on five crucial pillars for success with ML-driven molecular property and toxicity prediction: (1) data set selection, (2) structural representations, (3) model algorithm, (4) model validation, and (5) translation of predictions to decision-making. Understanding these key pillars will foster collaboration and coordination between ML researchers and toxicologists, which will help to advance drug discovery and development.

Molecular response of Chironomus riparius to antibiotics

Antibiotics, like other pharmaceuticals, are continuously released into the environment as a result of human activities. Although designed to target harmful bacteria, they can also affect non-target organisms in aquatic ecosystems. Standard toxicological tests often fail to detect the subtle or long term antibiotic-induced effects, but newer methods are providing valuable insights into the molecular pathways and physiological responses they affect. Chironomus riparius, a dipteran with aquatic larvae, is widely used in toxicological testing due to its sensitivity to various toxicants. However, little is known about the molecular effects of antibiotics on this species. This study investigated the gene expression profile of C. riparius in response to antibiotics from three classes - aminoglycosides, fluoroquinolones and penicillin. Fourth instar larvae were exposed to concentrations of 0.001, 0.1 and 10 mg/L for 24 and 72 h. The expression of genes involved in hormonal regulation, detoxification, stress response and DNA repair was analysed. The results showed that all antibiotics altered mRNA levels, with three of the four (amoxicillin, neomycin and levofloxacin) downregulating genes at 24 h and upregulating them at 72 h. Genes affected by gentamicin showed the opposite trend. These transcriptional changes in response to different antibiotics highlight the complexity of the regulatory mechanisms involved in development, detoxification, stress response and DNA repair in aquatic insects. Further research is needed to better understand the molecular effects of antibiotics on this species.

In chemico categorization of magnetite-, hydroxyapatite-, and Ag-derived hybrid nanobiomaterials based on the surface oxidative reactivity: implications of doping and coating

In chemico tests are important tools that complement in silico, in vitro and in vivo approaches to predict the toxicological impact of nanomaterials (NMs). Here, we apply a recently proposed in chemico methodology, based on the evaluation of the number, nature and properties of reactive surface sites of NMs, to a series of magnetite-, hydroxyapatite- and silver-based hybrid nanobiomaterials (NBMs). The properties of the NBMs were examined using methanol chemisorption followed by temperature-programmed surface reaction (MeOH-TPSR), dithiothreitol (DTT) oxidation, cyclic voltammetry in biologically relevant media, and electron paramagnetic resonance (EPR) spectroscopy in a series of relevant media as a spin trap. The resulting data were critically compared and correlated with the available in vitro data of the NBMs' hazard. Our findings reveal significant differences in the oxidative potential of these hybrid NBMs. Iron (Fe) doping in hydroxyapatite (HA) introduced new redox-active surface sites, leading to increased oxidative reactivity via ROS-independent mechanisms, as evidenced by higher DTT depletion and Fenton-like activity compared to HA. Conversely, titanium (Ti) doping modified HA's surface by introducing acidic active sites, reducing its oxidative capacity. Coating Fe3O4 with poly(ethylene glycol)-poly(lactic-co-glycolic) acid (PEG-PLGA) enhanced the oxidative reactivity without ROS generation, suggesting a surface-driven process. In contrast, hydroxyethyl cellulose (HEC) coating significantly reduced the high reactivity of uncoated silver (Ag). This study underscores the importance of determining the NBMs' reactivity profile for safe biomedical use, highlighting how specific coatings and dopants can transform oxidative surface properties.

A refined dose metric for nanotoxicology based on surface site reactivity for oxidative potential of engineered nanomaterials

The increasing production of engineered nanomaterials (ENMs) raises significant concerns about human and environmental exposure, making it essential to understand the mechanisms of their interaction with biological systems to manage the associated risks. To address this, we propose categorizing ENM reactivity using in chemico methodologies. Surface analysis through methanol chemisorption and temperature-programmed surface reaction allows for the determination of reactive surface sites, providing accurate estimates of effective ENM doses in toxicity studies. Additionally, antioxidant consumption assays (dithiothreitol, cysteine, and glutathione) and reactive oxygen species (ROS) generation assays (RNO and DCFH2-DA) are employed to rank the oxidative potential of ENM surface sites in a cell-free environment. Our study confirms the classification of ZnO NM-110, ZnO NM-111, CuO, and carbon black as highly oxidant ENMs, while TiO2 NM-101 and NM-105 exhibit low oxidative potential due to their acidic surface sites. In contrast, CeO2 NM-211 and NM-212 demonstrate redox surface sites. SiO2 nanomaterials (NM-200 and NM-201) are shown to be inert, with low oxidation rates and minimal reactive surface density, despite their high surface area. Quantifying reactive surface sites offers a refined dose metric for assessing ENM toxicity, advancing safe-by-design nanomaterial development.

Multi-behavioral fingerprints can identify potential modes of action for neuroactive environmental chemicals

There is a lack of confidence in the relevance of zebrafish-based behavior data for chemical risk assessment. We extended an automated Visual and Acoustic Motor Response (VAMR) new approach method (NAM) in 5-day post-fertilization (dpf) zebrafish to include 26, behavior-based endpoints that measure visual-motor responses, visual and acoustic startle responses, habituation learning, and memory retention. A correlation analysis from 5159 control larvae revealed that more complex endpoints for learning- and memory-related behavior yielded unique behavior patterns. To build confidence in the VAMR NAM, we established neuroactivity fingerprints using concentration-response profiles derived from 63 reference chemicals targeting neurotransmission, neurodevelopmental signaling, or toxicologically-relevant pathways. Hierarchical clustering revealed diverse toxicity fingerprints. Compounds that targeted the N-Methyl-D-aspartic acid (NMDA) or gamma-aminobutyric acid type A (GABAA) receptors reduced habituation learning. Pathway modulators targeting peroxisome proliferator-activated receptor delta (PPARδ) or gamma (PPARγ), GABAA, dopamine, ryanodine, aryl hydrocarbon (AhR), or G-protein-coupled receptors or the tyrosine kinase SRC inappropriately accelerated habituation learning. Reference chemicals targeting GABAA, NMDA, dopamine, PPARα, PPARδ, epidermal growth factor, bone morphogenetic protein, AhR, retinoid X, or α2-adreno receptors triggered inappropriate hyperactivity. Exposure to GABAA receptor antagonists elicited paradoxical excitation characterized by dark-phase sedation and increased startle responses while exposure to GABAA/B receptor agonists altered the same endpoints with opposite directionality. Relative to reference chemicals, environmental chemicals known to be GABA receptor antagonists (Lindane, Dieldrine) or agonists (Tetrabromobisphenol A (TBBPA)) elicited predicted behavior fingerprints. When paired with the phenotypically rich VAMR NAM, behavior fingerprints are a powerful approach to identify neuroactive chemicals.

Revisiting the approaches to DNA damage detection in genetic toxicology: insights and regulatory implications

Genetic toxicology is crucial for evaluating the potential risks of chemicals and drugs to human health and the environment. The emergence of high-throughput technologies has transformed this field, providing more efficient, cost-effective, and ethically sound methods for genotoxicity testing. It utilizes advanced screening techniques, including automated in vitro assays and computational models to rapidly assess the genotoxic potential of thousands of compounds simultaneously. This review explores the transformation of traditional in vitro and in vivo methods into computational models for genotoxicity assessment. By leveraging advances in machine learning, artificial intelligence, and high-throughput screening, computational approaches are increasingly replacing conventional methods. Coupling conventional screening with artificial intelligence (AI) and machine learning (ML) models has significantly enhanced their predictive capabilities, enabling the identification of genotoxicity signatures tied to molecular structures and biological pathways. Regulatory agencies increasingly support such methodologies as humane alternatives to traditional animal models, provided they are validated and exhibit strong predictive power. Standardization efforts, including the establishment of common endpoints across testing approaches, are pivotal for enhancing comparability and fostering consensus in toxicological assessments. Initiatives like ToxCast exemplify the successful incorporation of HTS data into regulatory decision-making, demonstrating that well-interpreted in vitro results can align with in vivo outcomes. Innovations in testing methodologies, global data sharing, and real-time monitoring continue to refine the precision and personalization of risk assessments, promising a transformative impact on safety evaluations and regulatory frameworks.

Metabolomics identified distinct molecular-level responses in Daphnia magna after exposure to phenanthrene and its oxygen and nitrogen containing analogs

The prevalence of polycyclic aromatic hydrocarbons and their oxygenated and nitrogen containing analogs in freshwater ecosystems are of concern due to their reported toxicity to several aquatic species including Daphnia magna. This study explored the molecular-level responses of phenanthrene (PHEN), 9,10-phenanthrenequinone (PHQ), and phenanthridine (PN) as little is known about the impacts of these pollutants on the metabolic profile of D. magna. For this purpose, D. magna was exposed to three sub-lethal concentrations of these pollutants for 24 h. To assess molecular-level responses, 52 polar metabolites were extracted from individual adult daphnids, and analyzed using a mass spectrometry-based targeted metabolomics approach. Exposure to PN resulted in the most statistically significant changes to the metabolic profile of D. magna followed by PHQ, and then PHEN exposures. After PN exposure, the biochemical pathway analysis showed that all exposure concentrations shared 21 perturbed metabolic pathways. However, the number of disrupted metabolic pathways increased with increasing exposure concentrations for PHEN and PHQ. The results suggest that PN and PHQ exposures are more disruptive due to the presence of reactive functional groups when compared to PHEN exposure. For the tested concentration ranges, the findings indicate that exposure to PN resulted in non-monotonic disruptions across exposure concentrations. In contrast, exposure to PHEN and PHQ elicited perturbations that were concentration-dependent. Although the reported median effective concentration (EC50) for PN is higher than PHEN and PHQ, our data shows that metabolomics captures molecular-level changes that may not be detected by traditional toxicity metrics.

Cell Painting PLUS: expanding the multiplexing capacity of Cell Painting-based phenotypic profiling using iterative staining-elution cycles

Phenotypic changes in the morphology and internal organization of cells can indicate perturbations in cell functions. Therefore, imaging-based high-throughput phenotypic profiling (HTPP) applications such as Cell Painting (CP) play an important role in basic and translational research, drug discovery, and regulatory toxicology. Here we present the Cell Painting PLUS (CPP) assay, an efficient, robust and broadly applicable approach that further expands the versatility of available HTPP methods and offers additional options for addressing mode-of-action specific research questions. An iterative staining-elution cycle allows multiplexing of at least seven fluorescent dyes that label nine different subcellular compartments and organelles including the plasma membrane, actin cytoskeleton, cytoplasmic RNA, nucleoli, lysosomes, nuclear DNA, endoplasmic reticulum, mitochondria, and Golgi apparatus. In this way, CPP significantly expands the flexibility, customizability, and multiplexing capacity of the original CP method and, importantly, also improves the organelle-specificity and diversity of the phenotypic profiles due to the separate imaging and analysis of single dyes in individual channels.

An updated comparison of microarray and RNA-seq for concentration response transcriptomic study: case studies with two cannabinoids, cannabichromene and cannabinol

BACKGROUND

Transcriptomic benchmark concentration (BMC) modeling provides quantitative toxicogenomic information that is increasingly being used in regulatory risk assessment of data poor chemicals. Over the past decade, RNA sequencing (RNA-seq) is gradually replacing microarray as the major platform for transcriptomic applications due to its higher precision, wider dynamic range, and capability of detecting novel transcripts. However, it is unclear whether RNA-seq offers substantial advantages over microarray for concentration response transcriptomic studies.

RESULTS

We provide an updated comparison between microarray and RNA-seq using two cannabinoids, cannabichromene (CBC) and cannabinol (CBN), as case studies. The two platforms revealed similar overall gene expression patterns with regard to concentration for both CBC and CBN. However, in spite of the many varieties of non-coding RNA transcripts and larger numbers of differentially expressed genes (DEGs) with wider dynamic ranges identified by RNA-seq, the two platforms displayed equivalent performance in identifying functions and pathways impacted by compound exposure through gene set enrichment analysis (GSEA). Furthermore, transcriptomic point of departure (tPoD) values derived by the two platforms through BMC modeling were on the same levels for both CBC and CBN.

CONCLUSIONS

Considering the relatively low cost, smaller data size, and better availability of software and public databases for data analysis and interpretation, microarray is still a viable method of choice for traditional transcriptomic applications such as mechanistic pathway identification and concentration response modeling.

A Review of the Applications, Benefits, and Challenges of Generative AI for Sustainable Toxicology

Sustainable toxicology is vital for living species and the environment because it guarantees the safety, efficacy, and regulatory compliance of drugs, treatments, vaccines, and chemicals in living organisms and the environment. Conventional toxicological methods often lack sustainability as they are costly, time-consuming, and sometimes inaccurate. It means delays in producing new drugs, vaccines, and treatments and understanding the adverse effects of the chemicals on the environment. To address these challenges, the healthcare sector must leverage the power of the Generative-AI (GenAI) paradigm. This paper aims to help understand how the healthcare field can be revolutionized in multiple ways by using GenAI to facilitate sustainable toxicological developments. This paper first reviews the present literature and identifies the possible classes of GenAI that can be applied to toxicology. A generalized and holistic visualization of various toxicological processes powered by GenAI is presented in tandem. The paper discussed toxicological risk assessment and management, spotlighting how global agencies and organizations are forming policies to standardize and regulate AI-related development, such as GenAI, in these fields. The paper identifies and discusses the advantages and challenges of GenAI in toxicology. Further, the paper outlines how GenAI empowers Conversational-AI, which will be critical for highly tailored toxicological solutions. This review will help to develop a comprehensive understanding of the impacts and future potential of GenAI in the field of toxicology. The knowledge gained can be applied to create sustainable GenAI applications for various problems in toxicology, ultimately benefiting our societies and the environment.

TPD-seq: A high throughput RNA-seq method to derive transcriptomic points of departure from cell lines

There is growing scientific and regulatory interest in transcriptomic points of departure (tPOD) values from high-throughput in vitro experiments. To further help democratize tPOD research, here we outline 'TPD-seq' which links microplate-based exposure methods involving cell lines for human (Caco-2, Hep G2) and environmental (rainbow trout RTgill-W1) health, with a commercially available RNA-seq kit, with a cloud-based bioinformatics tool (ExpressAnalyst.ca). We applied the TPD-seq workflow to derive tPODs for solvents (dimethyl sulfoxide, DMSO; methanol) and positive controls (3,4-dichloroaniline, DCA; hydrogen peroxide, H2O2) commonly used in toxicity testing. The majority of reads mapped to protein coding genes (∼9 k for fish cells; ∼6 k for human cells), and about 50 % of differentially expressed genes were curve-fitted from which 90 % yielded gene benchmark doses. The most robust transcriptomic responses were caused by DMSO exposure, and tPOD values were 31-155 mM across the cell lines. OECD test guideline 249 (RTgill-W1 cells) recommends the use of DCA and here we calculated a tPOD of ∼5 to 76 μM. Finally, exposure of the two human cell lines to H2O2 resulted in tPOD values that ranged from 0.7 to 1.1 mM in Caco-2 cells and 5-30 μM in Hep G2 cells. The methods outlined here are designed to be performed in laboratories with basic molecular and cell culture facilities, and the performance and scalability of the TPD-seq workflow can be determined with additional case studies.

Toxicity of ACP-105: a substance used as doping in sports: application of in silico methods for prediction of selected toxicological endpoints

ACP-105 is a novel non-steroidal Selective Androgen Receptor Modulator (SARM) used by athletes. Its action aims to increase muscle mass and is one of the options in testosterone replacement therapy. Its safety profile remains insufficiently explored, particularly regarding its toxicity in humans. The lack of information about the studied compound in the World Anti-Doping Agency (WADA) became the purpose of this study. Given the increasing use of such compounds in sports, a deeper understanding of their biological risks is crucial. This study not only fills the gap in available information but also contributes to the growing body of research on SARMs, providing insights into their potential hazards and guiding future investigations into their safety. This work aimed to use various in silico techniques to predict the toxicity of ACP-105, including acute toxicity, effects on internal organs, genotoxicity based on the Ames test, eye and skin irritation, and cardiotoxicity by testing hERG inhibitors. A preliminary safety analysis of the compound was based on its chemical structure and interactions with biological targets using various in silico techniques: qualitative (STopTox, ADMETlab, admetSAR, ProTox 3.0, and Toxtree 3.1.0) and quantitative (TEST 5.1.2, Percepta, VEGA QSAR 1.2.3, and SL-Tox) to ensure that the prediction results are as accurate as possible.

Transcriptomic changes and mitochondrial toxicity in response to acute and repeat dose treatment with brequinar in human liver and kidney in vitro models

The potent dihydroorotate dehydrogenase (DHODH) inhibitor brequinar has been investigated as an anticancer, immunosuppressive, and antiviral pharmaceutical agent. However, its toxicity is still poorly understood. We investigated the cellular responses of primary human hepatocytes (PHH) and telomerase-immortalised human renal proximal tubular epithelial cells (RPTEC/TERT1) after a single 24-h exposure up to 100 μM brequinar. Additionally, RPTEC/TERT1 cells underwent repeated daily exposure for five consecutive days at 0.3, 3, and 20 μM. Transcriptomic analysis revealed that PHH were less sensitive to brequinar treatment than RPTEC/TERT1 cells. Upregulation of various phase I and II drug-metabolising enzymes, particularly Cytochrome P450 (CYP) 1 A and 3 A enzymes, in PHH suggests potential detoxification. Furthermore, brequinar exposure led to a significant upregulation of several stress response pathways in PHH and RPTEC/TERT1 cells, including the unfolded protein response, Nrf2, p53, and inflammatory responses. RPTEC/TERT1 cells exhibited greater sensitivity to brequinar at 0.3 μM with repeated exposure compared to a single exposure. Furthermore, brequinar could impair the mitochondrial respiration of RPTEC/TERT1 cells after 24 h. This study provides new insights into the differential responses of PHH and RPTEC/TERT1 cells in response to brequinar exposure and highlights the biological relevance of implementing repeated dosing regimens in in vitro studies.

Going digital to boost safe and sustainable materials innovation markets. The digital safe-and-sustainability-by-design innovation approach of the PINK project

In this innovation report, we present the vision of the PINK project to foster Safe-and-Sustainable-by-Design (SSbD) advanced materials and chemicals (AdMas&Chems) development by integrating state-of-the-art computational modelling, simulation tools and data resources. PINK proposes a novel approach for the use of the SSbD Framework, whose innovative approach is based on the application of a multi-objective optimisation procedure for the criteria of functionality, safety, sustainability and cost efficiency. At the core is the PINK open innovation platform, a distributed system that integrates all relevant modelling resources enriched with advanced data visualisation and an AI-driven decision support system. Data and modelling tools from the, in large parts, independently developed areas of functional design, safety assessment, life cycle assessment & costing are brought together based on a newly created Interoperability Framework. The PINK In Silico Hub, as the user Interface to the platform, finally guides the user through the complete AdMas&Chems development process from idea creation to market introduction. Guided by two Developmental Case Studies, the process of building of the PINK Platform is iterative, ensuring industry readiness to implement and apply it. Additionally, the Industrial Demonstrator programme will be introduced as part of the final project phase, which allows industry partners and especially small and medium enterprises (SMEs) to become part of the PINK consortium. Feedback from the Demonstrators as well as other stakeholder-engagement activities and collaborations will shape the platform's final look and feel and, even more important, activities to assure long-term technical sustainability.

Chemical risk assessment in food animals via physiologically based pharmacokinetic modeling - Part I: Veterinary drugs on human food safety assessment

Veterinary drugs and environmental pollutants can enter food animals and remain as residues in food chains threatening human food safety and health. Performing health risk and food safety assessments to derive safety levels of these xenobiotics can protect human health. Physiologically based pharmacokinetic (PBPK) modeling is a mathematical tool to quantitatively describe chemical disposition in humans and animals informing human food safety and health risk assessments. However, few reviews focus on the application of PBPK models in food animals and discuss their relationship to human food safety and health risk assessments in the last five years (2020-2024). In this series of reviews, we introduce the methodology, recent progress and challenges of PBPK modeling in food animals. The present review is Part I of this series of reviews and it focuses on applications of PBPK models of veterinary drugs in food animals, whereas Part II is a companion review focusing on environmental chemicals. Advanced strategies of PBPK modeling in risk and food safety assessment, including population PBPK, interactive PBPK web dashboard, and generic PBPK are also summarized in Part I. Additionally, we share our perspective on the existing challenges and future direction for PBPK modeling of veterinary medicines in food animals.

Accelerating Animal Replacement: How Universities Can Lead - Results of a One-Day Expert Workshop in Zurich, Switzerland

This report is a result of an interdisciplinary workshop held at the Collegium Helveticum in Zurich, Switzerland in February 2024, in which ideas for accelerating NAMs (New Approach Methodologies) in Swiss universities were shared and discussed. Due to regional differences in university organisation and funding structures, not all recommendations will be transferable to all regions worldwide. All participants were qualified to contribute to the discussion, due to their knowledge and experience of the Three Rs, in particular with regard to their implementation. The workshop participants believed that universities, which play a pioneering role in so many other areas, should also exploit their innovative potential in the field of animal-free research. The workshop uncovered four areas that would need to be addressed in order to achieve a significant change in university science culture and do more justice to the Three Rs, namely: language - innovative framing (pro-replacement framing in official university statements); knowledge transfer - communicating innovative findings in teaching (redirecting curriculum); change of values within science faculties; and structured implementation and well-coordinated planning of the transformation (establishment of a 'transition unit'). Specific strategies for implementing these four areas are outlined. In addition, we discuss why the replacement of animal testing should be an essential goal for universities, why this goal has not yet been achieved, and why concerted efforts toward change are required.

Zebrafish as a model organism in One Health Toxicology: Impact of solvents and exposure routes on the toxicity of platinum anticancer drugs

Zebrafish are widely used not only as a model in ecotoxicology but also to study the potential impact of chemicals on human health. Typically, zebrafish are exposed to chemicals dissolved in egg water or other defined media, which is the standard routine for ecotoxicology testing. This straightforward exposure method is usually also employed to monitor adverse effects in zebrafish to predict potential hazards and modes of action in humans. Here, we compared different exposure media and studied the impact of salinity and solvents relevant to ecotoxicity testing. For comparison, toxicants also were directly injected into the bloodstream of zebrafish embryos, as this method better simulates the exposure scenario for assessing the adverse effects of drugs administered intravenously to patients. As model compounds we studied platinum-based anticancer drugs, which are known micropollutants, but also lead to severe side effects in humans. Striking differences in sensitivity and phenotypes, i.e. adverse outcomes, were observed dependent on the exposure route and media. The bioavailability of the platinum compounds was significantly altered in the different media and by the commonly used solvent DMSO. These findings highlight the relevance of the exposure route and media as well as of solvents to be considered when interpreting zebrafish studies in the field of ecotoxicology or in cross-species comparisons to predict effects on human health.

Past, Current and Future Techniques for Monitoring Paralytic Shellfish Toxins in Bivalve Molluscs

Paralytic shellfish poisoning is a threat to human health caused by the consumption of shellfish contaminated with toxins of the saxitoxin class. Human health is protected by the setting of regulatory limits and the analysis of shellfish prior to sale. Both robust toxicity data, generated from experiments fitting into the ethical 3R framework, and appropriate analysis methods are required to ensure the success of this approach. A literature review of in vivo animal bioassays and in vitro and analytical methods showed that in vitro methods are the best option to screen shellfish for non-regulatory purposes. However, since neither the receptor nor antibody binding of paralytic shellfish toxin analogues correlate with toxicity, these assays cannot accurately quantify toxicity in shellfish nor be used to calculate toxicity equivalence factors. Fully replacing animals in testing is rightfully the ultimate goal, but this cannot be at a cost to human health. More modern technology, such as organ-on-a-chip, represent an exciting development, but animal bioassays cannot currently be replaced in the determination of toxicity. Analytical methods that employ toxicity equivalence factors calculated using oral animal toxicity data result in an accurate assessment of the food safety risk posed by paralytic shellfish toxin contamination in bivalve molluscs.

Chemical Space Networks Enhance Toxicity Recognition via Graph Embedding

Chemical space networks (CSNs) are a new effective strategy for detecting latent chemical patterns irrespective of defined coordinate systems based on molecular descriptors and fingerprints. CSNs can be a new powerful option as a new approach method and increase the capacity of assessing potential adverse impacts of chemicals on human health. Here, CSNs are shown to effectively characterize the toxicity of chemicals toward several human health end points, namely chromosomal aberrations, mutagenicity, carcinogenicity, developmental toxicity, skin irritation, estrogenicity, androgenicity, and hepatoxicity. In this work, we report how the content from CSNs structure can be embedded through graph neural networks into a metric space, which, for eight different toxicological human health end points, allows better discrimination of toxic and nontoxic chemicals. In fact, using embeddings returns, on average, an increase in predictive performances. In fact, embedding employment enhances the learning, leading to an increment of the classification performance of +12% in terms of the area under the ROC curve. Moreover, through a dedicated eXplainable Artificial Intelligence framework, a straight interpretation of results is provided through the detection of putative structural alerts related to a given toxicity. Hence, the proposed approach represents a step forward in the area of alternative methods and could lead to breakthrough innovations in the design of safer chemicals and drugs.

Novel flame retardants (NFRs) in e-waste: Environmental burdens, health implications, and recommendations for safety assessment and sustainable management

Novel flame retardants (NFRs) have emerged as chemicals of environmental health concern due to their widespread use as an alternative to polybrominated diphenyl ethers (PBDE) in electrical and electronic devices. Humans and ecosystems are under threat because of e-waste recycling procedures that may emit NFRs and other anthropogenic chemicals into the e-waste workplace and the surrounding environment. The individual toxicity of NFRs including novel brominated flame retardants (NBFRs), their combined effects and the underlying mechanisms of toxicity have remained poorly understood. Exposure assessment as well as chemical safety testing should focus on prioritizing N(B)FRs for regulation and management. Here, the occurrence of N(B)FRs in the vicinity and surroundings of e-waste recycling sites are presented. Important knowledge gaps and prospects for a more integrated, harmonized, and mechanistically positioned risk assessment strategy for N(B)FRs as well as possible economically feasible and environmentally sustainable approaches for removing them from complex matrices are highlighted. Overall, data in the ng to µg-ranges of N(B)FR in soil, dust, sediment, water and fish were found. Dust and soil sample concentrations ranged from the low ng to low µg/g range while water concentrations were always in the low ng/L range (∼0.5 to ∼4 ng/L). Concentration in fish was usually in the range of 3- ∼300 ng/g with two substances in the low to medium-high µg/g range (DBDPE, BTBPE). From the 20 N(B)FR analysed in sediment samples only 10 were above detection limit. Most chemicals were found in a low ng/g range.

New approach methodologies in human health risk assessment across European regulatory frameworks: Status quo, barriers and drivers for regulatory acceptance and use

The traditional approaches to chemical risk assessment for human health are continuously challenged by their limitations, such as validity concerns, societal pressure to use animal-free methods, and resource constraints. New Approach Methodologies (NAMs) are considered a promising avenue toward modernisation of chemical risk assessment practices but their implementation in practice has been slow. This article aims to investigate the perspectives of human health risk assessors on the status quo, barriers and drivers of the acceptance and use of NAMs across different regulatory frameworks. A mixed method design was applied: qualitative interviews (N = 19) and an online survey with human health risk assessors from industry, regulatory agencies/institutions and academia (N = 222). The results show heterogeneity in familiarity and use of specific NAMs (e.g., QSARs as well-known and used vs. -omics approaches that are seldom used), the risk assessors' background (e.g., industry vs. regulatory agencies and institutions vs. academia) and the application context (e.g., screening/prioritisation vs. hazard identification/characterisation). The identified barriers and drivers offer pointers for the future integration and acceptance of NAMs in regulatory risk assessment. For instance, guidance documents can facilitate the use of NAMs, showcasing successful examples that increase trust in the methods and thus, the risk assessors' confidence in using these methods. Among other things, the article highlights the importance of considering human health risk assessors' needs and prerequisites to foster bottom-up coordinated efforts and to ensure the success of top-down legal and institutional change to incorporate NAMs in regulatory risk assessment.

Integrated Computational Analysis Reveals Early Genetic and Epigenetic AML Susceptibility Biomarkers in Benzene-Exposed Workers

Benzene, a well-known carcinogenic airborne pollutant, poses significant health risks, particularly in industries such as petroleum, shoemaking, and painting. Despite strict regulations, chronic occupational exposure persists, contributing to the onset of acute myeloid leukemia (AML) and other malignancies. Benzene's carcinogenicity stems from its metabolic activation, leading to increased oxidative stress, DNA damage, and cancer transformation. While its toxicity is well-documented, the link between genetic and epigenetic alterations and cancer susceptibility in exposed workers remains underexplored. This study aims to identify early biomarkers of benzene exposure and AML risk by analyzing gene expression and DNA methylation datasets from GEO DataSets, integrated with molecular pathway analyses, as well as miRNA-target and protein-protein network evaluations. This multi-approach led to the identification of nine deregulated genes (CRK, CXCR6, GSPT1, KPNA1, MECP2, MELTF, NFKB1, TBC1D7, ZNF331) in workers exposed to benzene, with NFKB1 showing strong discriminatory potential. Also, dose-dependent DNA methylation changes were observed in CXCR6 and MELTF, while selected miRNAs such as let-7d-5p, miR-126-3p, and miR-361-5p emerged as key post-transcriptional regulators. Furthermore, functional enrichment linked these genes to immune response, inflammation, cell proliferation, and apoptosis pathways. While network analyses highlighted NFKB1, CRK, and CXCR6 as central to benzene-associated leukemogenesis. Altogether, these findings provide novel insights into an early biomarker fingerprint for benzene exposure and AML susceptibility, supporting the future development of biomolecular-based targeted occupational health monitoring and personalized preventive strategies for at-risk workers.

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/ .

Computational new approach methods guide focused testing and enhance understanding of chlorantraniliprole toxicity across species

Diamide insecticides, specifically chlorantraniliprole (CHL), have been rising in popularity over the past decade, becoming one of the most widely used insecticide classes globally. These insecticides target the ryanodine receptor (RyR), primarily for control of lepidopteran agricultural pests. Field studies have revealed that some lepidopteran species have developed mutations where a methionine in a particular position (e.g., I4790M) increases resistance to CHL. The toxicity data for CHL across species is limited, as is the case for many chemicals, which creates an opportunity to apply both traditional toxicity test methods and new approach methods (NAMs) to address data gaps. Here, the U.S. Environmental Protection Agency's Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool was used to query the RyR to generate susceptibility predictions for species exposed to CHL to fill those data gaps. These SeqAPASS results generated testable hypotheses that were used to guide focused acute aquatic toxicity studies using Daphnia magna, Daphnia pulex, Pimephales promelas, and Danio rerio. The fish species were not sensitive to CHL, whereas D. magna and D. pulex were found to be sensitive to CHL at environmentally relevant concentrations, despite having the methionine residue in the position of the I4790M resistance mutation. Additional SeqAPASS results showed that many other species, including beneficial pollinators and Lepidoptera, are predicted as likely susceptible to CHL. This study provided multiple lines of evidence toward the unlikelihood for the I4790M mutation to be the primary cause of resistance across species, filled knowledge gaps concerning CHL toxicity across species, and generated predictions of susceptibility for nontarget species that are not generally amenable to toxicity testing. This work presents a case example that demonstrates how NAMs can be used in combination with other types of data to direct targeted testing and build confidence in predictive approaches for their use in risk assessment.

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.

The Critical Role of Commercial Analytical Reference Standards in the Control of Chemical Risks: The Case of PFAS and Ways Forward

BACKGROUND

Various countries have instituted risk governance measures to control and minimize the risks of chemicals at the national and international levels. Activities typically include risk assessment based on a) hazard and exposure assessments; b) setting limits on the production, use, and emissions of chemicals; c) enforcement of regulations; and d) monitoring the effectiveness of the measures taken. These steps largely depend on chemical analysis and access to pure chemical reference standards. However, except for specific highly regulated categories of chemicals, such reference standards often are not commercially available. This raises a critical question: Given the widespread lack of reference standards, is the current approach to governing chemicals adequate to protect humans and the environment from harm? If not, what measures could be taken to improve the situation?

OBJECTIVE

We outline how current chemical risk governance is hampered by the widespread lack of reference standards to produce the required scientific evidence. We also provide a list of recommendations for controlling chemical risks in the absence of reference standards.

DISCUSSION

We use per- and polyfluoroalkyl substances (PFASs), specifically the chemical C6O4 [perfluoro ([5-methoxy-1,3-dioxolan-4-yl]oxy) acetic acid], to illustrate how companies that produce chemicals can prevent access to reference standards. We argue that the very limited availability of reference standards undermines the ability of scientists to produce independent scientific evidence needed for chemical risk governance and, thereby, prevents society from protecting people and the environment against chemical pollution and its harms. Possible ways to improve the situation include a) guaranteeing access to chemical reference standards by creating a reference standards repository, b) redefining the level of confidence sufficient for regulatory action, c) providing alternative options for chemical identification and quantification when reference standards are not available, and d) considering, when no reference standards are available, regulation of chemicals by class rather than individually. https://doi.org/10.1289/EHP12331.

An industry perspective on the FDA Modernization Act 2.0/3.0: potential next steps for sponsors to reduce animal use in drug development

Pharmaceutical developers are encouraged to adopt the best practices of being purposefully thoughtful about the use of animals, seeking alternatives wherever possible. They should engage with health authorities to increase their familiarity with the methods, study designs, data outputs, and the context of use for new approach methodologies (NAMs). Although current state of technology does not yet provide adequate models to fully replace in vivo studies, many models are sufficiently good for an augmented approach that will enhance our understanding of in vitro to in vivo correlations and advance the long-term goal of reducing animal use through innovative NAMs. The goal of future nonclinical safety packages is to advance the utilization of such enabling technologies toward appropriate human risk characterization. Establishing confidence in NAMs is a critical first step. For example, sponsors may include both "traditional" and NAM-based nonclinical safety data in regulatory submissions to establish confidence with health authorities. In addition, regulators should create a "safe harbor" for hybrid nonclinical data packages to facilitate iterative learning, refinement, and implementation of NAM-based safety assessment strategies. Sponsors are urged to contribute to NAMs evolution through consortia participation, peer-reviewed publications, and documenting animal reduction in studies/programs, accelerating the eventual elimination of animal use in pharmaceutical development, as envisioned in the FDA Modernization Act 3.0.

A critical review on the toxicological and epidemiological evidence integration for assessing human health risks to environmental chemical exposures

Toxicology and epidemiology are the two traditional public health scientific disciplines which can contribute to investigate harmful health effects of exposure to toxic substances. Several frameworks for integrating different lines of evidence were proposed since 2011, evolving based of the emergence of new methodologies and approaches. Through the comparison of various theoretical frameworks for evidence integration, we examined similarities, differences, strengths, and weaknesses to provide insights into potential directions for future research. We identified several key challenges of the integration approach to be applied to risk assessment. More specifically, collaboration within a multidisciplinary team of scientists, toxicologists, epidemiologists, and risk assessors, is strongly recommended to be aligned with key regulatory objectives and promote a harmonized approach. Moreover, literature search transparency and systematicity have to be ensured by following validated guidelines, developing parallel protocols for collecting epidemiological and toxicological evidence from various sources, including human, animal, and new approach methodologies (NAMs). Also, the adoption of tailored quality assessment tools is essential to grade the certainty in evidence. Lastly, we recommend the use of the Adverse Outcome Pathway framework to provide a structured understanding of toxicity mechanisms and allow the integration of human, animal, and NAMs data within a single framework.

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.

A tiered toxicity testing strategy for assessing early life stage toxicity in estuarine fish (Mugilogobius chulae): A case study on tris (1-chloro-2-propyl) phosphate ester

The estuarine ecological environment faces significant threats from contaminants of emerging concern (CECs); yet, the risk posed by CECs to resident organisms remains poorly understood. Here, we employed tiered toxicity testing to investigate the adverse effects and potential mechanisms of tris (1-chloro-2-propyl) phosphate (TCPP) on the early life stages of an estuarine fish, Mugilogobius chulae. TCPP affected the development of M. chulae embryos, including survival, morphology, hatching, and behavior. A concentration-dependent transcriptomic analysis showed that TCPP disrupted 12 neurodevelopment-related KEGG pathways in M. chulae embryos, with five of the 30 % top-ranked pathways related to neurotransmitter signaling. Besides the cholinergic synapse signaling pathway, the glutamatergic signaling pathway (including NMDAR and AMPAR subtypes) may also mediate TCPP-induced neurodevelopmental toxicity. The NMDAR subtype GRIN2B was downregulated at high concentrations. Molecular dynamics simulations revealed a strong interaction between TCPP and GRIN2B, with TCPP binding to the residues Ile153 and Ile188. The results suggest that NMDARs play a crucial role in TCPP-induced neurodevelopmental toxicity toward M. chulae. AOP network analysis predicted that TCPP may impact cognitive functions and memory. Our study provides a novel testing strategy for identifying the mechanisms of toxicity of CECs, a crucial component of ecological risk assessment.

Overview of Computational Toxicology Methods Applied in Drug and Green Chemical Discovery

In the field of computational chemistry, computer models are quickly and cheaply constructed to predict toxicology hazards and results, with no need for test material or animals as these computational predictions are often based on physicochemical properties of chemical structures. Multiple methodologies are employed to support in silico assessments based on machine learning (ML) and deep learning (DL). This review introduces the development of computational toxicology, focusing on ML and DL and emphasizing their importance in the field of toxicology. A fine balance between target potency, selectivity, absorption, distribution, metabolism, excretion, toxicity (ADMET) and clinical safety properties should be achieved to discover a potential new drug. It is advantageous to perform virtual predictions as early as possible in drug development processes, even before a molecule is synthesized. Currently, there are numerous commercially available and free web-based programs for toxicity prediction, which can be used to construct various predictive models. The key features of the QSAR method are also outlined, and the selection of appropriate physicochemical descriptors is a prerequisite for robust predictions. In addition, examples of open-source tools applied to toxicity prediction are included, as well as examples of the application of different computational methods for the prediction of toxicity in drug design and environmental toxicology.

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.

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.

Unveiling the interspecies correlation and sensitivity factor analysis of rat and mouse acute oral toxicity of antimicrobial agents: first QSTR and QTTR Modeling report

This study aims to identify toxic potential and environmental hazardousness of antimicrobials. In this regard, the available experimental toxicity data with rat and mouse acute oral toxicity have been gathered from ChemID Plus database (n = 202) and subjected to data curation. Upon the data curation 51 and 68 compounds were left for the rat and mouse respectively for the modeling. The quantitative structure toxicity relationship (QSTR) and interspecies correlation analysis by quantitative toxicity-toxicity relationship (QTTR) modeling was approached in this study. The models were developed from 2D descriptors under OECD guidelines by using multiple linear regressions (MLR) with genetic algorithm (GA) for feature selection as a chemometric tool. The developed models were robust (Q 2 LOO  = 0.600-0.679) and predictive enough (Q 2 F n  = 0.626-0.958, CCC Ext  = 0.840-0.893). The leverage approach of applicability domain (ad) analysis assures the model's reliability. The antimicrobials without experimental toxicity values were classified as high, moderate and low toxic based on prediction and ad. The occurrence of the same classification from QSTR and QTTR models revealed the reliability of QTTR models.Finally, the applied "sensitivity factor analysis" typifies the sensitivity of chemicals toward each species. Overall, the first report will be helpful in the toxicity assessment of upcoming antimicrobials in rodents.

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.

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/.

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.