Applying Adverse Outcome Pathways (AOPs) to support Integrated Approaches to Testing and Assessment (IATA)

Quantitative structure-activity relationships of chemical bioactivity toward proteins associated with molecular initiating events of organ-specific toxicity

The adverse outcome pathway (AOP) concept has gained attention as a way to explore the mechanism of chemical toxicity. In this study, quantitative structure-activity relationship (QSAR) models were developed to predict compound activity toward protein targets relevant to molecular initiating events (MIE) upstream of organ-specific toxicities, namely liver steatosis, cholestasis, nephrotoxicity, neural tube closure defects, and cognitive functional defects. Utilizing bioactivity data from the ChEMBL 33 database, various machine learning algorithms, chemical features and methods to assess prediction reliability were compared and applied to develop robust models to predict compound activity. The results demonstrate high predictive performance across multiple targets, with balanced accuracy exceeding 0.80 for the majority of models. Furthermore, stability checks confirmed the consistency of predictive performance across multiple training-test splits. The results obtained by using QSAR predictions to identify known markers of adversities highlighted the utility of the models for risk assessment and for prioritizing compounds for further experimental evaluation.Scientific contributionThe work describes the development of QSAR models as tools for screening chemicals with potential systemic toxicity, thus contributing to resource savings and providing indications for further better-targeted testing. This study provides advances in the field of computational modeling of MIEs and information from AOP which is still relatively young and unexplored. The comprehensive modeling procedure is highly generalizable, and offers a robust framework for predicting a wide range of toxicological endpoints.

Environmental realism in molecular ecotoxicology: key considerations to transition experimental data to ecologically relevant scenarios

Molecular ecotoxicology facilitates the mechanistic understanding of chemical-organism interactions and the establishment of frameworks to link molecular events to adverse outcomes. However, the foundation of this sub-discipline must remain focused on the necessity to generate insight at levels of biological organization beyond the individual, namely the population, community, and ecosystem levels, and to strive towards ecological relevance. As planet Earth continues to experience unprecedented levels of chemical pollution, causing significant impact to the integrity and functionality of ecosystems, research efforts in molecular ecotoxicology must prioritize experimentation that quantitatively incorporates the influence of non-chemical stressors to enhance the predictability of chemical-driven effects at the population level and beyond. Here, perspectives on the challenge to transition experimental data to environmentally relevant scenarios are offered in an attempt to highlight the critical role of molecular ecotoxicology in protecting and supporting ecosystems threatened by chemical pollution.

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.

Novel strategies to assess cytokine release mediated by chimeric antigen receptor T cells based on the adverse outcome pathway concept

The success of cellular immunotherapies such as chimeric antigen receptor (CAR) T cell therapy has led to their implementation as a revolutionary treatment option for cancer patients. However, the safe translation of such novel immunotherapies, from non-clinical assessment to first-in-human studies is still hampered by the lack of suitable in vitro and in vivo models recapitulating the complexity of the human immune system. Additionally, using cells derived from human healthy volunteers in such test systems may not adequately reflect the altered state of the patient's immune system thus potentially underestimating the risk of life-threatening conditions, such as cytokine release syndrome (CRS) following CAR T cell therapy. The IMI2/EU project imSAVAR (immune safety avatar: non-clinical mimicking of the immune system effects of immunomodulatory therapies) aims at creating a platform for novel tools and models for enhanced non-clinical prediction of possible adverse events associated with immunomodulatory therapies. This platform shall in the future guide early non-clinical safety assessment of novel immune therapeutics thereby also reducing the costs of their development. Therefore, we review current opportunities and challenges associated with non-clinical in vitro and in vivo models for the safety assessment of CAR T cell therapy ranging from organ-on-chip models up to advanced biomarker screening.

Estrogen receptor/androgen receptor transcriptional activation of benzophenone derivatives and integrated approaches to testing and assessment (IATA) for estrogenic effects

Estrogen receptor (ER) and androgen receptor (AR) transactivation assays for the benzophenone compounds (BPs) were performed using hERα-HeLa-9903 cells for ER and MMTV/22Rv1_GR-KO cells for AR. Results showed that some BPs, such as BP-1, BP-2, 4OH-BP, 4DHB, and 4-MBP, showed agonistic activity on ER with a higher RPCmax than 1 nM 17-β estradiol. The other BPs (BP, BP-3, BP-6, BP-7, and BP-8) showed low RPCmax in accordance with the OECD Test guideline (TG) 455 criteria, with BP-4 as the only ER-negative. However, the potency of the BPs was at least 1000 times less than the reference chemical, 17-β-estradiol. None of the BPs exhibited agonistic activity on AR except BP-2 which showed a small increase in activity. For further evaluation of the estrogenic effect of BPs based on the integrated approaches to testing and assessment (IATA) approach, existing data on ER binding, steroidogenesis, MCF-7 cell proliferation, and in vivo uterotrophic assays were collected and evaluated. There seemed to be a close association between the in vitro data on BPs, especially ER transcriptional activity, and the in vivo results of increased uterine weight. This case study implied that integrated approaches using in vitro data can be a useful tool for the prediction of in vivo data for estrogenic effects, without the need for additional animal toxicity tests.

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.

Investigation of Peroxisome Proliferator-Activated Receptor Genes as Requirements for Visual Startle Response Hyperactivity in Larval Zebrafish Exposed to Structurally Similar Per- and Polyfluoroalkyl Substances (PFAS)

BACKGROUND

Per- and polyfluoroalkyl Substances (PFAS) are synthetic chemicals widely detected in humans and the environment. Exposure to perfluorooctanesulfonic acid (PFOS) or perfluorohexanesulfonic acid (PFHxS) was previously shown to cause dark-phase hyperactivity in larval zebrafish.

OBJECTIVES

The objective of this study was to elucidate the mechanism by which PFOS or PFHxS exposure caused hyperactivity in larval zebrafish.

METHODS

Swimming behavior was assessed in 5-d postfertilization (dpf) larvae following developmental (1-4 dpf) or acute (5 dpf) exposure to 0.43 - 7.86 μ M PFOS, 7.87 - 120 μ M PFHxS, or 0.4% dimethyl sulfoxide (DMSO). After developmental exposure and chemical washout at 4 dpf, behavior was also assessed at 5-8 dpf. RNA sequencing was used to identify differences in global gene expression to perform transcriptomic benchmark concentration-response (BMC T ) modeling, and predict upstream regulators in PFOS- or PFHxS-exposed larvae. CRISPR/Cas9-based gene editing was used to knockdown peroxisome proliferator-activated receptors (ppars) pparaa/ab, pparda/db, or pparg at day 0. Knockdown crispants were exposed to 7.86 μ M PFOS or 0.4% DMSO from 1-4 dpf and behavior was assessed at 5 dpf. Coexposure with the ppard antagonist GSK3787 and PFOS was also performed.

RESULTS

Transient dark-phase hyperactivity occurred following developmental or acute exposure to PFOS or PFHxS, relative to the DMSO control. In contrast, visual startle response (VSR) hyperactivity only occurred following developmental exposure and was irreversible up to 8 dpf. Similar global transcriptomic profiles, BMC T estimates, and enriched functions were observed in PFOS- and PFHxS-exposed larvae, and ppars were identified as putative upstream regulators. Knockdown of pparda/db, but not pparaa/ab or pparg, blunted PFOS-dependent VSR hyperactivity to control levels. This finding was confirmed via antagonism of ppard in PFOS-exposed larvae.

DISCUSSION

This work identifies a novel adverse outcome pathway for VSR hyperactivity in larval zebrafish. We demonstrate that developmental, but not acute, exposure to PFOS triggered persistent VSR hyperactivity that required ppard function. https://doi.org/10.1289/EHP13667.

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.

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.

Hybrid non-animal modeling: A mechanistic approach to predict chemical hepatotoxicity

Developing mechanistic non-animal testing methods based on the adverse outcome pathway (AOP) framework must incorporate molecular and cellular key events associated with target toxicity. Using data from an in vitro assay and chemical structures, we aimed to create a hybrid model to predict hepatotoxicants. We first curated a reference dataset of 869 compounds for hepatotoxicity modeling. Then, we profiled them against PubChem for existing in vitro toxicity data. Of the 2560 resulting assays, we selected the mitochondrial membrane potential (MMP) assay, a high-throughput screening (HTS) tool that can test chemical disruptors for mitochondrial function. Machine learning was applied to develop quantitative structure-activity relationship (QSAR) models with 2536 compounds tested in the MMP assay for screening new compounds. The MMP assay results, including QSAR model outputs, yielded hepatotoxicity predictions for reference set compounds with a Correct Classification Ratio (CCR) of 0.59. The predictivity improved by including 37 structural alerts (CCR = 0.8). We validated our model by testing 37 reference set compounds in human HepG2 hepatoma cells, and reliably predicting them for hepatotoxicity (CCR = 0.79). This study introduces a novel AOP modeling strategy that combines public HTS data, computational modeling, and experimental testing to predict chemical hepatotoxicity.

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).

A quantitative weight-of-evidence method for confidence assessment of adverse outcome pathway networks: A case study on chemical-induced liver steatosis

The field of chemical toxicity testing is undergoing a transition to overcome the limitations of in vivo experiments. This evolution involves implementing innovative non-animal approaches to improve predictability and provide a more precise understanding of toxicity mechanisms. Adverse outcome pathway (AOP) networks are pivotal in organizing existing mechanistic knowledge related to toxicological processes. However, these AOP networks are dynamic and require regular updates to incorporate the latest data. Regulatory challenges also persist due to concerns about the reliability of the information they offer. This study introduces a generic Weight-of-Evidence (WoE) scoring method, aligned with the tailored Bradford-Hill criteria, to quantitatively assess the confidence levels in key event relationships (KERs) within AOP networks. We use the previously published AOP network on chemical-induced liver steatosis, a prevalent form of human liver injury, as a case study. Initially, the existing AOP network is optimized with the latest scientific information extracted from PubMed using the free SysRev platform for artificial intelligence (AI)-based abstract inclusion and standardized data collection. The resulting optimized AOP network, constructed using Cytoscape, visually represents confidence levels through node size (key event, KE) and edge thickness (KERs). Additionally, a Shiny application is developed to facilitate user interaction with the dataset, promoting future updates. Our analysis of 173 research papers yielded 100 unique KEs and 221 KERs among which 72 KEs and 170 KERs, respectively, have not been previously documented in the prior AOP network or AOP-wiki. Notably, modifications in de novo lipogenesis, fatty acid uptake and mitochondrial beta-oxidation, leading to lipid accumulation and liver steatosis, garnered the highest KER confidence scores. In conclusion, our study delivers a generic methodology for developing and assessing AOP networks. The quantitative WoE scoring method facilitates in determining the level of support for KERs within the optimized AOP network, offering valuable insights into its utility in both scientific research and regulatory contexts. KERs supported by robust evidence represent promising candidates for inclusion in an in vitro test battery for reliably predicting chemical-induced liver steatosis within regulatory frameworks.

How neurobehavior and brain development in alternative whole-organism models can contribute to prediction of developmental neurotoxicity

Developmental neurotoxicity (DNT) is not routinely evaluated in chemical risk assessment because current test paradigms for DNT require the use of mammalian models which are ethically controversial, expensive, and resource demanding. Consequently, efforts have focused on revolutionizing DNT testing through affordable novel alternative methods for risk assessment. The goal is to develop a DNT in vitro test battery amenable to high-throughput screening (HTS). Currently, the DNT in vitro test battery consists primarily of human cell-based assays because of their immediate relevance to human health. However, such cell-based assays alone are unable to capture the complexity of a developing nervous system. Whole organismal systems that qualify as 3 R (Replace, Reduce and Refine) models are urgently needed to complement cell-based DNT testing. These models can provide the necessary organismal context and be used to explore the impact of chemicals on brain function by linking molecular and/or cellular changes to behavioural readouts. The nematode Caenorhabditis elegans, the planarian Dugesia japonica, and embryos of the zebrafish Danio rerio are all suited to low-cost HTS and each has unique strengths for DNT testing. Here, we review the strengths and the complementarity of these organisms in a novel, integrative context and highlight how they can augment current cell-based assays for more comprehensive and robust DNT screening of chemicals. Considering the limitations of all in vitro test systems, we discuss how a smart combinatory use of these systems will contribute to a better human relevant risk assessment of chemicals that considers the complexity of the developing brain.

Endocrine Disruptors and Metabolic Changes: Impact on Puberty Control

OBJECTIVE

This study aims to explore the significant impact of environmental chemicals on disease development, focusing on their role in developing metabolic and endocrine diseases. The objective is to understand how these chemicals contribute to the increasing prevalence of precocious puberty, considering various factors, including epigenetic changes, lifestyle, and emotional disturbances.

METHODS

The study employs a comprehensive review of descriptive observational studies in both human and animal models to identify a degree of causality between exposure to environmental chemicals and disease development, specifically focusing on endocrine disruption. Due to ethical constraints, direct causation studies in human subjects are not feasible; therefore, the research relies on accumulated observational data.

RESULTS

Puberty is a crucial life period with marked physiological and psychological changes. The age at which sexual characteristics develop is changing in many regions. The findings indicate a correlation between exposure to endocrine-disrupting chemicals and the early onset of puberty. These chemicals have been shown to interfere with normal hormonal processes, particularly during critical developmental stages such as adolescence. The research also highlights the interaction of these chemical exposures with other factors, including nutritional history, social and lifestyle changes, and emotional stress, which together contribute to the prevalence of precocious puberty.

CONCLUSION

Environmental chemicals significantly contribute to the development of certain metabolic and endocrine diseases, particularly in the rising incidence of precocious puberty. Although the evidence is mainly observational, it adequately justifies regulatory actions to reduce exposure risks. Furthermore, these findings highlight the urgent need for more research on the epigenetic effects of these chemicals and their wider impact on human health, especially during vital developmental periods.

Development of an in silico evaluation system that quantitatively predicts skin sensitization using OECD Guideline No. 497 ITSv2 defined approach for skin sensitization classification

The Integrated Testing Strategy version 2 (ITSv2) Defined Approach, which is a reliable skin sensitization hazard and multi-step risk assessment method, does not support quantitative risk assessment such as local lymph node assay EC3 values. In this study, we developed a high-performance in silico evaluation system that quantitatively predicts the EC3 values of chemical substances by combining the ITSv2 Defined Approach for hazard identification (ITSv2 HI) with machine learning models. This system uses in chemico/in vitro test data, molecular descriptors, and distance information based on read-across concepts as explanatory variables. The system achieves an R2 value of 0.617 on external-validation data. Substances misclassified in ITSv2 HI are considered to have properties that do not match the correspondence between tests expressing the adverse outcome pathway assumed in the ITSv2 Defined Approach and skin sensitization. Therefore, ITSv2 HI is assumed to be correct within the applicability domains of this system. When using only substances within the applicability domains to reconstruct CatBoost models, the R2 value reached 0.824 on the external-validation data, representing an improvement in system performance. The results demonstrate the utility of explanatory variables that reflect the read-across concept and the advantages of integrating multiple prediction methods.

Effects of petrogenic pollutants on North Atlantic and Arctic Calanus copepods: From molecular mechanisms to population impacts

Oil and gas industries in the Northern Atlantic Ocean have gradually moved closer to the Arctic areas, a process expected to be further facilitated by sea ice withdrawal caused by global warming. Copepods of the genus Calanus hold a key position in these cold-water food webs, providing an important energetic link between primary production and higher trophic levels. Due to their ecological importance, there is a concern about how accidental oil spills and produced water discharges may impact cold-water copepods. In this review, we summarize the current knowledge of the toxicity of petroleum on North Atlantic and Arctic Calanus copepods. We also review how recent development of high-quality transcriptomes from RNA-sequencing of copepods have identified genes regulating key biological processes, like molting, diapause and reproduction in Calanus copepods, to suggest linkages between exposure, molecular mechanisms and effects on higher levels of biological organization. We found that the available ecotoxicity threshold data for these copepods provide valuable information about their sensitivity to acute petrogenic exposures; however, there is still insufficient knowledge regarding underlying mechanisms of toxicity and the potential for long-term implications of relevance for copepod ecology and phenology. Copepod transcriptomics has expanded our understanding of how key biological processes are regulated in cold-water copepods. These advances can improve our understanding of how pollutants affect biological processes, and thus provide the basis for new knowledge frameworks spanning the effect continuum from molecular initiating events to adverse effects of regulatory relevance. Such efforts, guided by concepts such as adverse outcome pathways (AOPs), enable standardized and transparent characterization and evaluation of knowledge and identifies research gaps and priorities. This review suggests enhancing mechanistic understanding of exposure-effect relationships to better understand and link biomarker responses to adverse effects to improve risk assessments assessing ecological effects of pollutant mixtures, like crude oil, in Arctic areas.

Metabolomics in Preclinical Drug Safety Assessment: Current Status and Future Trends

Metabolomics is emerging as a powerful systems biology approach for improving preclinical drug safety assessment. This review discusses current applications and future trends of metabolomics in toxicology and drug development. Metabolomics can elucidate adverse outcome pathways by detecting endogenous biochemical alterations underlying toxicity mechanisms. Furthermore, metabolomics enables better characterization of human environmental exposures and their influence on disease pathogenesis. Metabolomics approaches are being increasingly incorporated into toxicology studies and safety pharmacology evaluations to gain mechanistic insights and identify early biomarkers of toxicity. However, realizing the full potential of metabolomics in regulatory decision making requires a robust demonstration of reliability through quality assurance practices, reference materials, and interlaboratory studies. Overall, metabolomics shows great promise in strengthening the mechanistic understanding of toxicity, enhancing routine safety screening, and transforming exposure and risk assessment paradigms. Integration of metabolomics with computational, in vitro, and personalized medicine innovations will shape future applications in predictive toxicology.

High-Throughput Screening to Advance In Vitro Toxicology: Accomplishments, Challenges, and Future Directions

Traditionally, chemical toxicity is determined by in vivo animal studies, which are low throughput, expensive, and sometimes fail to predict compound toxicity in humans. Due to the increasing number of chemicals in use and the high rate of drug candidate failure due to toxicity, it is imperative to develop in vitro, high-throughput screening methods to determine toxicity. The Tox21 program, a unique research consortium of federal public health agencies, was established to address and identify toxicity concerns in a high-throughput, concentration-responsive manner using a battery of in vitro assays. In this article, we review the advancements in high-throughput robotic screening methodology and informatics processes to enable the generation of toxicological data, and their impact on the field; further, we discuss the future of assessing environmental toxicity utilizing efficient and scalable methods that better represent the corresponding biological and toxicodynamic processes in humans.

Pathogenesis of chemically induced nasal cavity tumors in rodents: contribution to adverse outcome pathway

The pathogenesis of nasal cavity tumors induced in rodents has been critically reviewed. Chemical substances that induce nasal cavity tumors in rats, mice, and hamsters were searched in the National Toxicology Program (NTP), International Agency for Research on Cancer (IARC), and Japan Bioassay Research Center (JBRC) databases, in addition to PubMed. Detailed data such as animal species, administration routes, and histopathological types were extracted for induced nasal cavity tumors. Data on non-neoplastic lesions were also extracted. The relationship between the tumor type and non-neoplastic lesions at equivalent sites was analyzed to evaluate tumor pathogenesis. Genotoxicity data were also analyzed. Squamous cell carcinoma was the most frequent lesion, regardless of the dosing route, and its precursor lesions were squamous metaplasia and/or respiratory epithelial hyperplasia, similar to squamous cell papilloma. The precursor lesions of adenocarcinoma, the second most frequent tumor type, were mainly olfactory epithelial hyperplasia, whereas those of adenoma were respiratory epithelial lesions. These pathways were consistent among species. Our results suggest that the responsible lesions may be commonly linked with chemically-induced cytotoxicity in each tumor type, irrespective of genotoxicity, and that the pathways may largely overlap between genotoxic and non-genotoxic carcinogens. These findings may support the documentation of adverse outcome pathways (AOPs), such as cytotoxicity, leading to nasal cavity tumors and the integrated approaches to testing and assessment (IATA) for non-genotoxic carcinogens.

The utility of ultraviolet beam in advanced oxidation-reduction processes: a review on the mechanism of processes and possible production free radicals

Advanced oxidation processes (AOPs) and advanced reduction processes (ARPs) are a set of chemical treatment procedures designed to eliminate organic (sometimes inorganic) contamination in water and wastewater by producing free reactive radicals (FRR). UV irradiation is one of the factors that are effectively used in oxidation-reduction processes. Not only does the UV beam cause the photolysis of contamination, but it also leads to the product of FRR by affecting oxidants-reductant, and the pollutant decomposition occurs by FRR. UV rays produce active radical species indirectly in an advanced redox process by affecting an oxidant (O3, H2O2), persulfate (PS), or reducer (dithionite, sulfite, sulfide, iodide, ferrous). Produced FRR with high redox potential (including oxidized or reduced radicals) causes detoxification and degradation of target contaminants by attacking them. In this review, it was found that ultraviolet radiation is one of the important and practical parameters in redox processes, which can be used to control a wide range of impurities.

Cross species extrapolation of the disruption of thyroid hormone synthesis by oxyfluorfen using in vitro data, physiologically based pharmacokinetic (PBPK), and thyroid hormone kinetics models

The thyroid hormones play key roles in physiological processes such as regulation of the metabolic and cardiac systems as well as the development of the brain and surrounding sympathetic nervous system. Recent efforts to screen environmental chemicals for their ability to alter thyroid hormone synthesis, transport, metabolism and/or function have identified novel chemicals that target key processes in the thyroid pathway. One newly identified chemical, oxyfluorfen, is a diphenyl-ether herbicide used for control of annual broadleaf and grassy weeds in a variety of tree fruit, nut, vine, and field crops. Using in vitro high-throughput screening (HTS) assays, oxyfluorofen was identified to be a potent inhibitor of the thyroidal sodium-iodide symporter (NIS). To quantitatively assess this inhibition mechanism in vivo, we extrapolated in vitro NIS inhibition data to in vivo disruption of thyroid hormones synthesis in rats using physiologically based pharmacokinetic (PBPK) and thyroid hormone kinetics models. The overall computational model (chemical PBPK and THs kinetic sub-models) was calibrated against in vivo data for the levels of oxyfluorfen in thyroid tissue and serum and against serum levels of thyroid hormones triiodothyronine (T3) and thyroxine (T4) in rats. The rat thyroid model was then extrapolated to humans using human in vitro HTS data for NIS inhibition and the chemical specific hepatic clearance rate in humans. The overall species extrapolated PBPK-thyroid kinetics model can be used to predict dose-response (% drop in thyroid serum levels compared to homeostasis) relationships in humans. These relationships can be used to estimate points of departure for health risks related to a drop in serum levels of TH hormones based on HTS assays in vitro to in vivo extrapolation (IVIVE), toxicokinetics, and physiological principles.

Identification of an adverse outcome pathway (AOP) for chemical-induced craniofacial anomalies using the transgenic zebrafish model

Craniofacial anomalies are one of the most frequent birth defects worldwide and are often caused by genetic and environmental factors such as pharmaceuticals and chemical agents. Although identifying adverse outcome pathways (AOPs) is a central issue for evaluating the teratogenicity, the AOP causing craniofacial anomalies has not been identified. Recently, zebrafish has gained interest as an emerging model for predicting teratogenicity because of high throughput, cost-effectiveness and availability of various tools for examining teratogenic mechanisms. Here, we established zebrafish sox10-EGFP reporter lines to visualize cranial neural crest cells (CNCCs) and have identified the AOPs for craniofacial anomalies. When we exposed the transgenic embryos to teratogens that were reported to cause craniofacial anomalies in mammals, CNCC migration and subsequent morphogenesis of the first pharyngeal arch were impaired at 24 hours post-fertilization. We also found that cell proliferation and apoptosis of the migratory CNCCs were disturbed, which would be key events of the AOP. From these results, we propose that our sox10-EGFP reporter lines serve as a valuable model for detecting craniofacial skeletal abnormalities, from early to late developmental stages. Given that the developmental process of CNCCs around this stage is highly conserved between zebrafish and mammals, our findings can be extrapolated to mammalian craniofacial development and thus help in predicting craniofacial anomalies in human.

Integrating distribution kinetics and toxicodynamics to assess repeat dose neurotoxicity in vitro using human BrainSpheres: a case study on amiodarone

For ethical, economical, and scientific reasons, animal experimentation, used to evaluate the potential neurotoxicity of chemicals before their release in the market, needs to be replaced by new approach methodologies. To illustrate the use of new approach methodologies, the human induced pluripotent stem cell-derived 3D model BrainSpheres was acutely (48 h) or repeatedly (7 days) exposed to amiodarone (0.625-15 µM), a lipophilic antiarrhythmic drug reported to have deleterious effects on the nervous system. Neurotoxicity was assessed using transcriptomics, the immunohistochemistry of cell type-specific markers, and real-time reverse transcription-polymerase chain reaction for various genes involved in the lipid metabolism. By integrating distribution kinetics modeling with neurotoxicity readouts, we show that the observed time- and concentration-dependent increase in the neurotoxic effects of amiodarone is driven by the cellular accumulation of amiodarone after repeated dosing. The development of a compartmental in vitro distribution kinetics model allowed us to predict the change in cell-associated concentrations in BrainSpheres with time and for different exposure scenarios. The results suggest that human cells are intrinsically more sensitive to amiodarone than rodent cells. Amiodarone-induced regulation of lipid metabolism genes was observed in brain cells for the first time. Astrocytes appeared to be the most sensitive human brain cell type in vitro. In conclusion, assessing readouts at different molecular levels after the repeat dosing of human induced pluripotent stem cell-derived BrainSpheres in combination with the compartmental modeling of in vitro kinetics provides a mechanistic means to assess neurotoxicity pathways and refine chemical safety assessment for humans.

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

The predominantly animal-centric approach of chemical safety assessment has increasingly come under pressure. Society is questioning overall performance, sustainability, continued relevance for human health risk assessment and ethics of this system, demanding a change of paradigm. At the same time, the scientific toolbox used for risk assessment is continuously enriched by the development of "New Approach Methodologies" (NAMs). While this term does not define the age or the state of readiness of the innovation, it covers a wide range of methods, including quantitative structure-activity relationship (QSAR) predictions, high-throughput screening (HTS) bioassays, omics applications, cell cultures, organoids, microphysiological systems (MPS), machine learning models and artificial intelligence (AI). In addition to promising faster and more efficient toxicity testing, NAMs have the potential to fundamentally transform today's regulatory work by allowing more human-relevant decision-making in terms of both hazard and exposure assessment. Yet, several obstacles hamper a broader application of NAMs in current regulatory risk assessment. Constraints in addressing repeated-dose toxicity, with particular reference to the chronic toxicity, and hesitance from relevant stakeholders, are major challenges for the implementation of NAMs in a broader context. Moreover, issues regarding predictivity, reproducibility and quantification need to be addressed and regulatory and legislative frameworks need to be adapted to NAMs. The conceptual perspective presented here has its focus on hazard assessment and is grounded on the main findings and conclusions from a symposium and workshop held in Berlin in November 2021. It intends to provide further insights into how NAMs can be gradually integrated into chemical risk assessment aimed at protection of human health, until eventually the current paradigm is replaced by an animal-free "Next Generation Risk Assessment" (NGRA).

A curated gene and biological system annotation of adverse outcome pathways related to human health

Adverse outcome pathways (AOPs) are emerging as a central framework in modern toxicology and other fields in biomedicine. They serve as an extension of pathway-based concepts by depicting biological mechanisms as causally linked sequences of key events (KEs) from a molecular initiating event (MIE) to an adverse outcome. AOPs guide the use and development of new approach methodologies (NAMs) aimed at reducing animal experimentation. While AOPs model the systemic mechanisms at various levels of biological organisation, toxicogenomics provides the means to study the molecular mechanisms of chemical exposures. Systematic integration of these two concepts would improve the application of AOP-based knowledge while also supporting the interpretation of complex omics data. Hence, we established this link through rigorous curation of molecular annotations for the KEs of human relevant AOPs. We further expanded and consolidated the annotations of the biological context of KEs. These curated annotations pave the way to embed AOPs in molecular data interpretation, facilitating the emergence of new knowledge in biomedicine.

Integrative Data Mining Approach: Case Study with Adverse Outcome Pathway Network Leading to Pulmonary Fibrosis

An adverse outcome pathway (AOP) framework can be applied as an efficient tool for the rapid screening of environmental chemicals. For the development of an AOP, a database mining approach can support an expert derivation approach by gathering a wider range of evidence than in a literature review. In this study, data from various databases were integrated and analyzed to supplement the AOP leading to pulmonary fibrosis by analyzing additional evidence using a data mining approach and establishing an application domain for chemicals. First, we collected chemicals, genes, and phenotypes that were studied and related to pulmonary fibrosis through the Comparative Toxicogenomics Database (CTD). CGPD-tetramers constructed by linking each related chemical, gene, phenotype, and disease can provide the basic components for the assembly of putative AOPs. Next, an AOP network was established by connecting eight existing AOPs for pulmonary fibrosis developed by expert derivation from the AOP Wiki. Finally, the pulmonary fibrosis AOP network was proposed by integrating the AOP network from AOP Wiki and the CGPD-tetramers from the CTD. To prioritize potential chemical stressors in the AOP network, 61 chemicals were ranked using the relevance of the chemical to the AOP and chemical exposure information from the CompTox Chemicals Dashboard. The approach proposed in this study can guide the utilization of available evidence from various databases as well as the literature in constructing AOP networks related to specific diseases.

Implementation of effect biomarkers in human biomonitoring studies: A systematic approach synergizing toxicological and epidemiological knowledge

Human biomonitoring (HBM) studies have highlighted widespread daily exposure to environmental chemicals. Some of these are suspected to contribute to adverse health outcomes such as reproductive, neurological, and metabolic disorders, among other developmental and chronic impairments. One of the objectives of the H2020 European Human Biomonitoring Initiative (HBM4EU) was the development of informative effect biomarkers for application in a more systematic and harmonized way in large-scale European HBM studies. The inclusion of effect biomarkers would complement exposure data with mechanistically-based information on early and late adverse effects. For this purpose, a stepwise strategy was developed to identify and implement a panel of validated effect biomarkers in European HBM studies. This work offers an overview of the complete procedure followed, from comprehensive literature search strategies, selection of criteria for effect biomarkers and their classification and prioritization, based on toxicological data and adverse outcomes, to pilot studies for their analytical, physiological, and epidemiological validation. We present the example of one study that demonstrated the mediating role of the effect biomarker status of brain-derived neurotrophic factor BDNF in the longitudinal association between infant bisphenol A (BPA) exposure and behavioral function in adolescence. A panel of effect biomarkers has been implemented in the HBM4EU Aligned Studies as main outcomes, including traditional oxidative stress, reproductive, and thyroid hormone biomarkers. Novel biomarkers of effect, such as DNA methylation status of BDNF and kisspeptin (KISS) genes were also evaluated as molecular markers of neurological and reproductive health, respectively. A panel of effect biomarkers has also been applied in HBM4EU occupational studies, such as micronucleus analysis in lymphocytes and reticulocytes, whole blood comet assay, and malondialdehyde, 8-oxo-2'-deoxyguanosine and untargeted metabolomic profile in urine, to investigate, for example, biological changes in response to hexavalent chromium Cr(VI) exposure. The use of effect biomarkers in HBM4EU has demonstrated their ability to detect early biological effects of chemical exposure and to identify subgroups that are at higher risk. The roadmap developed in HBM4EU confirms the utility of effect biomarkers, and support one of the main objectives of HBM research, which is to link exposure biomarkers to mechanistically validated effect and susceptibility biomarkers in order to better understand the public health implications of human exposure to environmental chemicals.

Multiomics Point of Departure (moPOD) Modeling Supports an Adverse Outcome Pathway Network for Ionizing Radiation

While adverse biological effects of acute high-dose ionizing radiation have been extensively investigated, knowledge on chronic low-dose effects is scarce. The aims of the present study were to identify hazards of low-dose ionizing radiation to Daphnia magna using multiomics dose-response modeling and to demonstrate the use of omics data to support an adverse outcome pathway (AOP) network development for ionizing radiation. Neonatal D. magna were exposed to γ radiation for 8 days. Transcriptomic analysis was performed after 4 and 8 days of exposure, whereas metabolomics and confirmative bioassays to support the omics analyses were conducted after 8 days of exposure. Benchmark doses (BMDs, 10% benchmark response) as points of departure (PODs) were estimated for both dose-responsive genes/metabolites and the enriched KEGG pathways. Relevant pathways derived using the BMD modeling and additional functional end points measured by the bioassays were overlaid with a previously published AOP network. The results showed that several molecular pathways were highly relevant to the known modes of action of γ radiation, including oxidative stress, DNA damage, mitochondrial dysfunction, protein degradation, and apoptosis. The functional assays showed increased oxidative stress and decreased mitochondrial membrane potential and ATP pool. Ranking of PODs at the pathway and functional levels showed that oxidative damage related functions had relatively low PODs, followed by DNA damage, energy metabolism, and apoptosis. These were supportive of causal events in the proposed AOP network. This approach yielded promising results and can potentially provide additional empirical evidence to support further AOP development for ionizing radiation.

Application of AOPs to assist regulatory assessment of chemical risks - Case studies, needs and recommendations

While human regulatory risk assessment (RA) still largely relies on animal studies, new approach methodologies (NAMs) based on in vitro, in silico or non-mammalian alternative models are increasingly used to evaluate chemical hazards. Moreover, human epidemiological studies with biomarkers of effect (BoE) also play an invaluable role in identifying health effects associated with chemical exposures. To move towards the next generation risk assessment (NGRA), it is therefore crucial to establish bridges between NAMs and standard approaches, and to establish processes for increasing mechanistically-based biological plausibility in human studies. The Adverse Outcome Pathway (AOP) framework constitutes an important tool to address these needs but, despite a significant increase in knowledge and awareness, the use of AOPs in chemical RA remains limited. The objective of this paper is to address issues related to using AOPs in a regulatory context from various perspectives as it was discussed in a workshop organized within the European Union partnerships HBM4EU and PARC in spring 2022. The paper presents examples where the AOP framework has been proven useful for the human RA process, particularly in hazard prioritization and characterization, in integrated approaches to testing and assessment (IATA), and in the identification and validation of BoE in epidemiological studies. Nevertheless, several limitations were identified that hinder the optimal usability and acceptance of AOPs by the regulatory community including the lack of quantitative information on response-response relationships and of efficient ways to map chemical data (exposure and toxicity) onto AOPs. The paper summarizes suggestions, ongoing initiatives and third-party tools that may help to overcome these obstacles and thus assure better implementation of AOPs in the NGRA.

Toxicogenomics Data for Chemical Safety Assessment and Development of New Approach Methodologies: An Adverse Outcome Pathway-Based Approach

Mechanistic toxicology provides a powerful approach to inform on the safety of chemicals and the development of safe-by-design compounds. Although toxicogenomics supports mechanistic evaluation of chemical exposures, its implementation into the regulatory framework is hindered by uncertainties in the analysis and interpretation of such data. The use of mechanistic evidence through the adverse outcome pathway (AOP) concept is promoted for the development of new approach methodologies (NAMs) that can reduce animal experimentation. However, to unleash the full potential of AOPs and build confidence into toxicogenomics, robust associations between AOPs and patterns of molecular alteration need to be established. Systematic curation of molecular events to AOPs will create the much-needed link between toxicogenomics and systemic mechanisms depicted by the AOPs. This, in turn, will introduce novel ways of benefitting from the AOPs, including predictive models and targeted assays, while also reducing the need for multiple testing strategies. Hence, a multi-step strategy to annotate AOPs is developed, and the resulting associations are applied to successfully highlight relevant adverse outcomes for chemical exposures with strong in vitro and in vivo convergence, supporting chemical grouping and other data-driven approaches. Finally, a panel of AOP-derived in vitro biomarkers for pulmonary fibrosis (PF) is identified and experimentally validated.

Mechanistic Understanding of the Olfactory Neuroepithelium Involvement Leading to Short-Term Anosmia in COVID-19 Using the Adverse Outcome Pathway Framework

Loss of the sense of smell (anosmia) has been included as a COVID-19 symptom by the World Health Organization. The majority of patients recover the sense of smell within a few weeks postinfection (short-term anosmia), while others report persistent anosmia. Several studies have investigated the mechanisms leading to anosmia in COVID-19; however, the evidence is scattered, and the mechanisms remain poorly understood. Based on a comprehensive review of the literature, we aim here to evaluate the current knowledge and uncertainties regarding the mechanisms leading to short-term anosmia following SARS-CoV-2 infection. We applied an adverse outcome pathway (AOP) framework, well established in toxicology, to propose a sequence of measurable key events (KEs) leading to short-term anosmia in COVID-19. Those KEs are (1) SARS-CoV-2 Spike proteins binding to ACE-2 expressed by the sustentacular (SUS) cells in the olfactory epithelium (OE); (2) viral entry into SUS cells; (3) viral replication in the SUS cells; (4) SUS cell death; (5) damage to the olfactory sensory neurons and the olfactory epithelium (OE). This AOP-aligned approach allows for the identification of gaps where more research should be conducted and where therapeutic intervention could act. Finally, this AOP gives a frame to explain several disease features and can be linked to specific factors that lead to interindividual differences in response to SARS-CoV-2 infection.

Prediction of serious eye damage or eye irritation potential of compounds via consensus labelling models and active learning models based on uncertainty strategies

Serious eye damage and eye irritation have been authenticated to be significant human health issues in various fields such as ophthalmic pharmaceuticals. Due to the shortcomings of traditional animal testing methods, in silico methods have advanced to study eye toxicity. The models for predicting serious eye damage and eye irritation potential of compounds were developed using 2299 and 5214 compounds, respectively. The 40 global single models and 40 local models were developed by combining 5 molecular description methods and 4 machine learning methods. The 40 active learning models were developed by adopting uncertainty-based active learning strategies and taking local models as initial models. The 110 global consensus models based on 40 global single models were developed using a consensus strategy. Active learning models and global consensus models performed high prediction accuracy. The test accuracy of the best serious eye damage model and eye irritation model reached 0.972 and 0.959, respectively. The applicability domains for all models were calculated to verify the rationality of prediction effect. In addition, 8 structural alerts probably causing serious eye damage or eye irritation were sought out. The prediction models and structural alerts contributed to providing hazard identification and assessing chemical safety.

Advances in computational methods along the exposure to toxicological response paradigm

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

A high-level overview of the Organisation for Economic Co-operation and Development Adverse Outcome Pathway Programme

Background The Organisation for Economic Co-operation and Development (OECD), through its Chemical Safety Programme, is delegated to ensure the safety of humans and wildlife from harmful toxicants. To support these needs, initiatives to increase the efficiency of hazard identification and risk management are under way. Amongst these, the adverse outcome pathway (AOP) approach integrates information on biological knowledge and test methodologies (both established and new) to support regulatory decision making. AOPs collate biological knowledge from different sources, assess lines of evidence through considerations of causality and undergo rigorous peer-review before being subsequently endorsed by the OECD. It is envisioned that the OECD AOP Development Programme will transform the toxicity testing paradigm by leveraging the strengths of mechanistic and modelling based approaches and enhance the utility of high throughput screening assays. Since its launch, in 2012, the AOP Development Programme has matured with a greater number of AOPs endorsed since inception, and the attraction of new scientific disciplines (e.g. the radiation field). Recently, a Radiation and Chemical (Rad/Chem) AOP Joint Topical Group has been formed by the OECD Nuclear Energy Agency High-Level Group on Low-Dose Research (HLG-LDR) under the auspices of the Committee on Radiological Protection and Public Health (CRPPH). The topical group will work to evolve the development and use of the AOP framework in radiation research and regulation. As part of these efforts, the group will bring awareness and understanding on the programme, as it has matured from the chemical perspective. In this context, this paper provides the radiation community with a high-level overview of the OECD AOP Development Programme, including examples of application using knowledge gleaned from the field of chemical toxicology, and their work towards regulatory implementation. Conclusion: Although the drivers for developing AOPs in chemical sector differ from that of the radiation field, the principles and transparency of the approach can benefit both scientific disciplines. By providing perspectives and an understanding of the evolution of the OECD AOP Development Programme including case examples and work towards quantitative AOP development, it may motivate the expansion and implementation of AOPs in the radiation field.

An adverse outcome pathway-based approach to assess aurantio-obtusin-induced hepatotoxicity

Cassiae semen (CS), a traditional Chinese medicine, has various bioactivities in preclinical and clinical practice. Aurantio-obtusin (AO) is a major anthraquinone (AQ) ingredient derived from CS, and has drawn public concerns over its potential hepatotoxicity. We previously found that AO induces hepatic necroinflammation by activating NOD-like receptor protein 3 inflammasome signaling. However, the mechanisms contributing to AO-motivated hepatotoxicity remain unclear. Herein, we evaluated hepatotoxic effects of AO on three liver cell lines by molecular and biochemical analyses. We found that AO caused cell viability inhibition and biochemistry dysfunction in the liver cells. Furthermore, AO elevated reactive oxygen species (ROS), followed by mitochondrial dysfunction (decreases in mitochondrial membrane potential and adenosine triphosphate) and apoptosis (increased Caspase-3, Cleaved caspase-3, Cytochrome c and Bax expression, and decreased Bcl-2 expression). We also found that AO increased the lipid peroxidation (LPO) and enhanced ferroptosis by activating cyclic adenosine monophosphate (cAMP)-protein kinase A (PKA)-cAMP response element-binding (CREB) pathway (increases in PKA, p-CREB, acyl-CoA synthetase long chain family member 4). Based on these results, we used an AOP framework to explore the mechanisms underlying AO's hepatotoxicity. It starts from molecular initiating event (ROS), and follows two critical toxicity pathways (i.e., mitochondrial dysfunction-mediated apoptosis and LPO-enhanced ferroptosis) over a series of key events (KEs) to the adverse outcome of hepatotoxicity. The results of an assessment confidence in the adverse outcome pathway (AOP) framework supported the evidence concordance in dose-response, temporal and incidence relationships between KEs in AO-induced hepatotoxicity. This study's findings offer a novel toxicity pathway network for AO-caused hepatotoxicity.

Decision making in next generation risk assessment for skin allergy: Using historical clinical experience to benchmark risk

Our aim is to develop and apply next generation approaches to skin allergy risk assessment that do not require new animal test data and better quantify uncertainties. Quantitative risk assessment for skin sensitisation uses safety assessment factors to extrapolate from the point-of-departure to an acceptable human exposure level. It is currently unclear whether these safety assessment factors are appropriate when using non-animal test data to derive a point-of departure. Our skin allergy risk assessment model Defined Approach uses Bayesian statistics to infer a human-relevant metric of sensitiser potency with explicit quantification of uncertainty, using any combination of human repeat insult patch test, local lymph node assay, direct peptide reactivity assay, KeratinoSens™, h-CLAT or U-SENS™ data. Here we describe the incorporation of benchmark exposures pertaining to use of consumer products with clinical data supporting a high/low risk categorisation for skin sensitisation. Margins-of-exposure (potency estimate to consumer exposure level ratio) are regressed against the benchmark risk classifications, enabling derivation of a risk metric defined as the probability that an exposure is low risk. This approach circumvents the use of safety assessment factors and provides a simple and transparent mechanism whereby clinical experience can directly feed-back into risk assessment decisions.

Replacement of animal testing by integrated approaches to testing and assessment (IATA): a call for in vivitrosi

Alternative methods to animal use in toxicology are evolving with new advanced tools and multilevel approaches, to answer from one side to 3Rs requirements, and on the other side offering relevant and valid tests for drugs and chemicals, considering also their combination in test strategies, for a proper risk assessment.While stand-alone methods, have demonstrated to be applicable for some specific toxicological predictions with some limitations, the new strategy for the application of New Approach Methods (NAM), to solve complex toxicological endpoints is addressed by Integrated Approaches for Testing and Assessment (IATA), aka Integrated Testing Strategies (ITS) or Defined Approaches for Testing and Assessment (DA). The central challenge of evidence integration is shared with the needs of risk assessment and systematic reviews of an evidence-based Toxicology. Increasingly, machine learning (aka Artificial Intelligence, AI) lends itself to integrate diverse evidence streams.In this article, we give an overview of the state of the art of alternative methods and IATA in toxicology for regulatory use for various hazards, outlining future orientation and perspectives. We call on leveraging the synergies of integrated approaches and evidence integration from in vivo, in vitro and in silico as true in vivitrosi.

Investigation of a derived adverse outcome pathway (AOP) network for endocrine-mediated perturbations

An adverse outcome pathway (AOP) is a compact representation of the available mechanistic information on observed adverse effects upon environmental exposure. Sharing of events across individual AOPs has led to the emergence of AOP networks. Since AOP networks are expected to be functional units of toxicity prediction, there is current interest in their development tailored to specific research question or regulatory problem. To this end, we have developed a detailed workflow to construct an endocrine-relevant AOP (ED-AOP) network based on the existing information available in AOP-Wiki. We propose a cumulative weight of evidence (WoE) score for each ED-AOP based on the WoE scores assigned to key event relationships (KERs) by AOP-Wiki, revealing gaps in AOP development. Connectivity analysis of the ED-AOP network comprising 48 AOPs reveals 7 connected components and 12 isolated AOPs. Subsequently, we apply standard network measures to perform an in-depth analysis of the two largest connected components of the ED-AOP network. Notably, the graph-theoretic analyses led to the identification of important events including points of convergence or divergence in the ED-AOP network. These findings can suggest potential adverse outcomes and facilitate the development of new endpoints or assays for chemical risk assessment. Detailed analysis of the largest component in the ED-AOP network gives insights on the systems-level perturbations caused by endocrine disruption, emergent paths, and stressor-event associations. In sum, the derived ED-AOP network can provide a broader view of the biological events disrupted by endocrine disruption, as well as facilitate better risk assessment of environmental chemicals.

Mapping Adverse Outcome Pathways for Kidney Injury as a Basis for the Development of Mechanism-Based Animal-Sparing Approaches to Assessment of Nephrotoxicity

In line with recent OECD activities on the use of AOPs in developing Integrated Approaches to Testing and Assessment (IATAs), it is expected that systematic mapping of AOPs leading to systemic toxicity may provide a mechanistic framework for the development and implementation of mechanism-based in vitro endpoints. These may form part of an integrated testing strategy to reduce the need for repeated dose toxicity studies. Focusing on kidney and in particular the proximal tubule epithelium as a key target site of chemical-induced injury, the overall aim of this work is to contribute to building a network of AOPs leading to nephrotoxicity. Current mechanistic understanding of kidney injury initiated by 1) inhibition of mitochondrial DNA polymerase γ (mtDNA Polγ), 2) receptor mediated endocytosis and lysosomal overload, and 3) covalent protein binding, which all present fairly well established, common mechanisms by which certain chemicals or drugs may cause nephrotoxicity, is presented and systematically captured in a formal description of AOPs in line with the OECD AOP development programme and in accordance with the harmonized terminology provided by the Collaborative Adverse Outcome Pathway Wiki. The relative level of confidence in the established AOPs is assessed based on evolved Bradford-Hill weight of evidence considerations of biological plausibility, essentiality and empirical support (temporal and dose-response concordance).

In vitro to in vivo extrapolation to support the development of the next generation risk assessment (NGRA) strategy for nanomaterials

There is growing interest in developing novel strategies to support assessment of human health risks due to chemicals. Regulatory and decision-making agencies have recommended that non-animal-based alternatives should be applied whenever possible instead of experimentation on living animals. These alternative methods are beneficial because they are ethical, inexpensive, and rapid. Herein, we review recent activities aimed at developing in vitro to in vivo extrapolation (IVIVE) models as a part of the Next Generation Risk Assessment (NGRA) of nanomaterials. In this context, we show the adverse outcome pathway (AOP)-based methodology for the identification of mechanistically relevant events serving as biomarkers for the targeted selection of in vitro assays. Considered events need to be biologically plausible, regulatory relevant, and crucial for the examination of occurrence of adverse outcomes. The promising advantages of using high-throughout-based omics data are highlighted. Furthermore, the application of 3D in vitro models and nano genome atlases to study nanoparticle toxicity is briefly summarized. Additionally, the challenges related to the extrapolation of in vitro doses into in vivo-relevant responses are presented. We also discuss the limitations of models applied thus far to study the fate of chemicals in the human body, which exist due to the lack of available knowledge regarding transformations of nanomaterials occurring in biological systems.

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

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

Comparison of toxicological effects and exposure levels between triclosan and its structurally similar chemicals using in vitro tests for read-across case study

Read-across based on structural and biological similarities is expected to be a promising alternative method for assessing systemic toxicity. A concrete strategy for quantitative chemical risk assessment would be to stack read-across case studies and extract key considerations from them. Thus, we developed a read-across case study by comparing the toxicological effects based on adverse outcome pathways and exposure levels of different structurally similar chemicals for a target organ. In this study, we selected the hepatotoxicity of triclosan and its structurally similar chemicals including diclosan and 1-chloro-3-(4-chlorophenoxy)benzene. The results of in vitro toxicogenomics showed that disorders of cholesterol synthesis were commonly detected with both triclosan and diclosan. The decrease in hepatocellular cholesterol levels was similar in the cells treated with triclosan and diclosan. Furthermore, the exposure levels of triclosan and diclosan for the liver were similar. Collectively, these results suggest that triclosan and diclosan show similar toxicological effects and severity of hepatotoxicity. Considering the existing repeated dose toxicity data, our prediction results are reasonable regarding the toxicological effect and its severity. Thus, the present study demonstrated the usability of comparing toxicological effects and exposure levels using read-across for quantitative chemical risk assessment.

Current status and future directions for a neurotoxicity hazard assessment framework that integrates in silico approaches

Neurotoxicology is the study of adverse effects on the structure or function of the developing or mature adult nervous system following exposure to chemical, biological, or physical agents. The development of more informative alternative methods to assess developmental (DNT) and adult (NT) neurotoxicity induced by xenobiotics is critically needed. The use of such alternative methods including in silico approaches that predict DNT or NT from chemical structure (e.g., statistical-based and expert rule-based systems) is ideally based on a comprehensive understanding of the relevant biological mechanisms. This paper discusses known mechanisms alongside the current state of the art in DNT/NT testing. In silico approaches available today that support the assessment of neurotoxicity based on knowledge of chemical structure are reviewed, and a conceptual framework for the integration of in silico methods with experimental information is presented. Establishing this framework is essential for the development of protocols, namely standardized approaches, to ensure that assessments of NT and DNT based on chemical structures are generated in a transparent, consistent, and defendable manner.

Application of an Accessible Interface for Pharmacokinetic Modeling and In Vitro to In Vivo Extrapolation

Regulatory toxicology testing has traditionally relied on in vivo methods to inform decision-making. However, scientific, practical, and ethical considerations have led to an increased interest in the use of in vitro and in silico methods to fill data gaps. While in vitro experiments have the advantage of rapid application across large chemical sets, interpretation of data coming from these non-animal methods can be challenging due to the mechanistic nature of many assays. In vitro to in vivo extrapolation (IVIVE) has emerged as a computational tool to help facilitate this task. Specifically, IVIVE uses physiologically based pharmacokinetic (PBPK) models to estimate tissue-level chemical concentrations based on various dosing parameters. This approach is used to estimate the administered dose needed to achieve in vitro bioactivity concentrations within the body. IVIVE results can be useful to inform on metrics such as margin of exposure or to prioritize potential chemicals of concern, but the PBPK models used in this approach have extensive data requirements. Thus, access to input parameters, as well as the technical requirements of applying and interpreting models, has limited the use of IVIVE as a routine part of in vitro testing. As interest in using non-animal methods for regulatory and research contexts continues to grow, our perspective is that access to computational support tools for PBPK modeling and IVIVE will be essential for facilitating broader application and acceptance of these techniques, as well as for encouraging the most scientifically sound interpretation of in vitro results. We highlight recent developments in two open-access computational support tools for PBPK modeling and IVIVE accessible via the Integrated Chemical Environment (https://ice.ntp.niehs.nih.gov/), demonstrate the types of insights these tools can provide, and discuss how these analyses may inform in vitro-based decision making.

Next generation risk assessment for skin allergy: Decision making using new approach methodologies

Our aim is to develop and apply next generation approaches to skin allergy risk assessment (SARA) that do not require new animal test data and better quantify uncertainties. Significant progress has been made in the development of New Approach Methodologies (NAMs), non-animal test methods, for assessment of skin sensitisation and there is now focus on their application to derive potency information for use in Next Generation Risk Assessment (NGRA). The SARA model utilises a Bayesian statistical approach to infer a human-relevant metric of sensitiser potency and a measure of risk associated with a given consumer exposure based upon any combination of human repeat insult patch test, local lymph node, direct peptide reactivity assay, KeratinoSens™, h-CLAT or U-SENS™ data. Here we have applied the SARA model within our weight of evidence NGRA framework for skin allergy to three case study materials in four consumer products. Highlighting how to structure the risk assessment, apply NAMs to derive a point of departure and conclude on consumer safety risk. NGRA based upon NAMs were, for these exposures, at least as protective as the historical risk assessment approaches. Through such case studies we are building our confidence in using NAMs for skin allergy risk assessment.

Prediction of the Neurotoxic Potential of Chemicals Based on Modelling of Molecular Initiating Events Upstream of the Adverse Outcome Pathways of (Developmental) Neurotoxicity

Developmental and adult/ageing neurotoxicity is an area needing alternative methods for chemical risk assessment. The formulation of a strategy to screen large numbers of chemicals is highly relevant due to potential exposure to compounds that may have long-term adverse health consequences on the nervous system, leading to neurodegeneration. Adverse Outcome Pathways (AOPs) provide information on relevant molecular initiating events (MIEs) and key events (KEs) that could inform the development of computational alternatives for these complex effects. We propose a screening method integrating multiple Quantitative Structure–Activity Relationship (QSAR) models. The MIEs of existing AOP networks of developmental and adult/ageing neurotoxicity were modelled to predict neurotoxicity. Random Forests were used to model each MIE. Predictions returned by single models were integrated and evaluated for their capability to predict neurotoxicity. Specifically, MIE predictions were used within various types of classifiers and compared with other reference standards (chemical descriptors and structural fingerprints) to benchmark their predictive capability. Overall, classifiers based on MIE predictions returned predictive performances comparable to those based on chemical descriptors and structural fingerprints. The integrated computational approach described here will be beneficial for large-scale screening and prioritisation of chemicals as a function of their potential to cause long-term neurotoxic effects.

Mapping Mechanistic Pathways of Acute Oral Systemic Toxicity Using Chemical Structure and Bioactivity Measurements

Regulatory agencies around the world have committed to reducing or eliminating animal testing for establishing chemical safety. Adverse outcome pathways can facilitate replacement by providing a mechanistic framework for identifying the appropriate non-animal methods and connecting them to apical adverse outcomes. This study separated 11,992 chemicals with curated rat oral acute toxicity information into clusters of structurally similar compounds. Each cluster was then assigned one or more ToxCast/Tox21 assays by looking for the minimum number of assays required to record at least one positive hit call below cytotoxicity for all acutely toxic chemicals in the cluster. When structural information is used to select assays for testing, none of the chemicals required more than four assays and 98% required two assays or less. Both the structure-based clusters and activity from the associated assays were significantly associated with the GHS toxicity classification of the chemicals, which suggests that a combination of bioactivity and structural information could be as reproducible as traditional in vivo studies. Predictivity is improved when the in vitro assay directly corresponds to the mechanism of toxicity, but many indirect assays showed promise as well. Given the lower cost of in vitro testing, a small assay battery including both general cytotoxicity assays and two or more orthogonal assays targeting the toxicological mechanism could be used to improve performance further. This approach illustrates the promise of combining existing in silico approaches, such as the Collaborative Acute Toxicity Modeling Suite (CATMoS), with structure-based bioactivity information as part of an efficient tiered testing strategy that can reduce or eliminate animal testing for acute oral toxicity.

The use of Bayesian methodology in the development and validation of a tiered assessment approach towards prediction of rat acute oral toxicity

There exists consensus that the traditional means by which safety of chemicals is assessed-namely through reliance upon apical outcomes obtained following in vivo testing-is increasingly unfit for purpose. Whilst efforts in development of suitable alternatives continue, few have achieved levels of robustness required for regulatory acceptance. An array of "new approach methodologies" (NAM) for determining toxic effect, spanning in vitro and in silico spheres, have by now emerged. It has been suggested, intuitively, that combining data obtained from across these sources might serve to enhance overall confidence in derived judgment. This concept may be formalised in the "tiered assessment" approach, whereby evidence gathered through a sequential NAM testing strategy is exploited so to infer the properties of a compound of interest. Our intention has been to provide an illustration of how such a scheme might be developed and applied within a practical setting-adopting for this purpose the endpoint of rat acute oral lethality. Bayesian statistical inference is drawn upon to enable quantification of degree of confidence that a substance might ultimately belong to one of five LD50-associated toxicity categories. Informing this is evidence acquired both from existing in silico and in vitro resources, alongside a purposely-constructed random forest model and structural alert set. Results indicate that the combination of in silico methodologies provides moderately conservative estimations of hazard, conducive for application in safety assessment, and for which levels of certainty are defined. Accordingly, scope for potential extension of approach to further toxicological endpoints is demonstrated.

Innovation in regulatory approaches for endocrine disrupting chemicals: The journey to risk assessment modernization in Canada

Globally, regulatory authorities grapple with the challenge of assessing the hazards and risks to human and ecosystem health that may result from exposure to chemicals that disrupt the normal functioning of endocrine systems. Rapidly increasing number of chemicals in commerce, coupled with the reliance on traditional, costly animal experiments for hazard characterization - often with limited sensitivity to many important mechanisms of endocrine disruption -, presents ongoing challenges for chemical regulation. The consequence is a limited number of chemicals for which there is sufficient data to assess if there is endocrine toxicity and hence few chemicals with thorough hazard characterization. To address this challenge, regulatory assessment of endocrine disrupting chemicals (EDCs) is benefiting from a revolution in toxicology that focuses on New Approach Methodologies (NAMs) to more rapidly identify, prioritize, and assess the potential risks from exposure to chemicals using novel, more efficient, and more mechanistically driven methodologies and tools. Incorporated into Integrated Approaches to Testing and Assessment (IATA) and guided by conceptual frameworks such as Adverse Outcome Pathways (AOPs), emerging approaches focus initially on molecular interactions between the test chemical and potentially vulnerable biological systems instead of the need for animal toxicity data. These new toxicity testing methods can be complemented with in silico and computational toxicology approaches, including those that predict chemical kinetics. Coupled with exposure data, these will inform risk-based decision-making approaches. Canada is part of a global network collaborating on building confidence in the use of NAMs for regulatory assessment of EDCs. Herein, we review the current approaches to EDC regulation globally (mainly from the perspective of human health), and provide a perspective on how the advances for regulatory testing and assessment can be applied and discuss the promises and challenges faced in adopting these novel approaches to minimize risks due to EDC exposure in Canada, and our world.

The Exposome and Toxicology: A Win-Win Collaboration

The development of the exposome concept has been one of the hallmarks of environmental and health research for the last decade. The exposome encompasses the life course environmental exposures including lifestyle factors from the prenatal period onwards. It has inspired many research programs and is expected to influence environmental and health research, practices, and policies. Yet, the links bridging toxicology and the exposome concept have not been well developed. In this review, we describe how the exposome framework can interface with and influence the field of toxicology, as well as how the field of toxicology can help advance the exposome field by providing the needed mechanistic understanding of the exposome impacts on health. Indeed, exposome-informed toxicology is expected to emphasize several orientations including (1) developing approaches integrating multiple stressors, in particular chemical mixtures, as well as the interaction of chemicals with other stressors, (2) using mechanistic frameworks such as the adverse outcome pathways to link the different stressors with toxicity outcomes, (3) characterizing the mechanistic basis of long-term effects by distinguishing different patterns of exposures and further exploring the environment-DNA interface through genetic and epigenetic studies, and (4) improving the links between environmental and human health, in particular through a stronger connection between alterations in our ecosystems and human toxicology. The exposome concept provides the linkage between the complex environment and contemporary mechanistic toxicology. What toxicology can bring to exposome characterization is a needed framework for mechanistic understanding and regulatory outcomes in risk assessment.