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.

The skin sensitization adverse outcome pathway: exploring the role of mechanistic understanding for higher tier risk assessment.

For over a decade, the skin sensitization Adverse Outcome Pathway (AOP) has served as a useful framework for development of novel in chemico and in vitro assays for use in skin sensitization hazard and risk assessment. Since its establishment, the AOP framework further fueled the existing efforts in new assay development and stimulated a plethora of activities with particular focus on validation, reproducibility and interpretation of individual assays and combination of assay outputs for use in hazard/risk assessment. In parallel, research efforts have also accelerated in pace, providing new molecular and dynamic insight into key events leading to sensitization. In light of novel hypotheses emerging from over a decade of focused research effort, mechanistic evidence relating to the key events in the skin sensitization AOP may complement the tools currently used in risk assessment. We reviewed the recent advances unraveling the complexity of molecular events in sensitization and signpost the most promising avenues for further exploration and development of useful assays.

Quantitative modeling of in vitro data using an adverse outcome pathway for the risk assessment of decreased lung function in humans.

In the absence of epidemiological data, there is a need to develop computational models that convert in vitro findings to human disease risk predictions following toxicant exposure. In such efforts, in vitro data can be evaluated in the context of adverse outcome pathways (AOPs) that organize mechanistic knowledge based on empirical evidence into a sequence of molecular-, cellular-, tissue-, and organ-level key events that precede an adverse outcome (AO). Here we combined data from advanced in vitro organotypic airway models exposed to combustible cigarette (CC) smoke or Tobacco Heating System (THS) aerosol with an AOP for increased oxidative stress leads to decreased lung function. The mathematical modeling predicted reduced risk of decreased ciliary beating frequency (CBF) based on oxidative stress measurements and reduced risk of decreased mucociliary clearance (MCC) based on CBF measurements in THS aerosol- compared with CC smoke-exposed cultures. To extend the predictions to the AO of decreased lung function, we leveraged human MCC data from current smokers, nonsmokers, former smokers, and users of heated tobacco products. This approach provided a plausible prediction of diminished reduction in lung function in response to THS use compared with continued smoking. The current approach may also present a basis for an integrated approach to testing and assessment of tobacco products for future regulatory decision-making.

Human biomonitoring and toxicokinetics as key building blocks for next generation risk assessment.

Human health risk assessment is historically built upon animal testing, often following Organisation for Economic Co-operation and Development (OECD) test guidelines and exposure assessments. Using combinations of human relevant in vitro models, chemical analysis and computational (in silico) approaches bring advantages compared to animal studies. These include a greater focus on the human species and on molecular mechanisms and kinetics, identification of Adverse Outcome Pathways and downstream Key Events as well as the possibility of addressing susceptible populations and additional endpoints. Much of the advancement and progress made in the Next Generation Risk Assessment (NGRA) have been primarily focused on new approach methodologies (NAMs) and physiologically based kinetic (PBK) modelling without incorporating human biomonitoring (HBM). The integration of toxicokinetics (TK) and PBK modelling is an essential component of NGRA. PBK models are essential for describing in quantitative terms the TK processes with a focus on the effective dose at the expected target site. Furthermore, the need for PBK models is amplified by the increasing scientific and regulatory interest in aggregate and cumulative exposure as well as interactions of chemicals in mixtures. Since incorporating HBM data strengthens approaches and reduces uncertainties in risk assessment, here we elaborate on the integrated use of TK, PBK modelling and HBM in chemical risk assessment highlighting opportunities as well as challenges and limitations. Examples are provided where HBM and TK/PBK modelling can be used in both exposure assessment and hazard characterization shifting from external exposure and animal dose/response assays to animal-free, internal exposure-based NGRA.

Challenges integrating skin sensitization data for assessment of difficult to test substances.

Difficult to test substances, including poorly soluble, mildly irritating, or UVCBs (unknown or variable composition complex reaction products or biological materials), producing weak or borderline in vivo results, face additional challenges in in vitro assays that often necessitate data integration in a weight of evidence (WOE) approach to inform skin sensitization potential. Here we present several case studies on difficult to test substances and highlight the utility of the toxicological priority index (ToxPi) as a data visualization tool to compare skin sensitization biological activity. The case study test substances represent two poorly soluble substances, tetrakis (2-ethylbutyl) orthosilicate and decyl palmitate, and two UVCB substances, alkylated anisole and hydrazinecarboximidamide, 2-[(2-hydroxyphenyl)methylene]-, reaction products with 2 undecanone. Data from key events within the skin sensitization adverse outcome pathway were gathered from publicly available sources or specifically generated. Incorporating the data for these case study test substances as well as data on chemicals of a known sensitization class (sensitizer, irritating non-sensitizer, and non-sensitizer) into ToxPi produced biological activity profiles which were grouped using unsupervised hierarchical clustering. Three of the case study test substances concluded to lack skin sensitization potential by traditional WOE produced biological activity profiles most consistent with non-sensi­tizing substances, whereas the prediction was less definitive for a substance considered positive by traditional WOE. Visualizing the data using bioactivity profiles can provide further support for WOE conclusions in certain circumstances but is unlikely to replace WOE as a stand-alone prediction due to limitations of the method including the impact of missing data points.

Non-animal test methods to detect chemicals that cause skin allergies are accepted alternatives to animal testing for this purpose. However, some chemicals are difficult to test using these methods, e.g., substances that cause skin irritation, are not water soluble or are mixtures of different compo­nents. We compiled existing and new data on how four such chemicals activate key elements of the biological pathway leading to allergic skin reactions and compared the resulting patterns with respective patterns of many chemicals confirmed to cause skin allergy, skin irritation or neither. The patterns were visualized and analyzed with a computer software tool. The tool confirmed that three substances were non-sensitizers but did not confirm that the fourth substance was a skin sensitizer as predicted by the standard assessment. This approach, which incorporates all available data types into the assessment of difficult to test chemicals, may further reduce unnecessary animal testing.

Making the Case for Quantum Mechanics in Predictive Toxicology─Nearly 100 Years Too Late?

The use of quantum mechanics (QM) has long been the norm to study covalent-binding phenomena in chemistry and biochemistry. The pharmaceutical industry leverages QM models explicitly in covalent drug discovery and implicitly to characterize short-range interactions in noncovalent binding. Predictive toxicology has resisted widespread adoption of QM, including in the pharmaceutical industry, despite its obvious relevance to the metabolic processes in the upstream of adverse outcome pathways and advances in both QM methods and computational resources, which support fit-for-purpose applications in reasonable timeframes. Here, we make the case for embracing QM as an indispensable part of a toxicologist's toolkit. We argue that QM provides the necessary orthogonality to alert-based expert systems and traditional QSARs, consistent with calls for animal-free integrated testing strategies for safety assessments of commercial chemicals. We outline existing roadblocks to this transition, including the need to train model developers in QM and the shift toward service-based toxicity models that utilize high-performance computing clusters. Lastly, we describe recent examples of successful implementations of QM in hazard assessments and propose how in silico toxicology can be further advanced by integrating QM with artificial intelligence.

The hepatotoxicity assessment of micro/nanoplastics: A preliminary study to apply the adverse outcome pathways.

Plastic pollution has become a significant global problem over the years, leading to the continuous decomposition and accumulation of micro/nanoplastics (MNPLs) in the environment. As a result, human exposure to these MNPLs is inevitable. The liver, in particular, is highly susceptible to potential MNPL toxicity. In this study, we systematically reviewed the current literature on MNPLs-induced hepatotoxicity and collected data on toxic events occurring at different biological levels. Then, to better understand the cause-mechanism causality, we developed an Adverse Outcome Pathway (AOP) framework for MNPLs-induced hepatotoxicity. The AOP framework provided insights into the mechanism of MNPL-induced hepatotoxicity and highlighted potential health risks such as liver dysfunction and inflammation, metabolism disorders and liver fibrosis. Moreover, we discussed the potential application of emerging toxicological models in the hepatotoxicity study. Liver organoids and liver-on-chips, which can simulate the structure and function of the liver in vitro, offer a promising alternative platform for toxicity testing and risk assessment. We proposed combining the AOP framework with these emerging toxicological models to improve our understanding of the hepatotoxic effects of MNPLs. Overall, this study performed a preliminary exploration of novel toxicological methodologies to assess the hepatotoxicity of MNPLs, providing a deeper understanding of environmental toxicology.

The need for good practice in the application of mechanistic constructs in hazard and risk assessment.

A series of recent and proposed workshops address the interface between key characteristics and mechanistic pathway descriptions (adverse outcome pathways and mode of action) to identify commonalities and potential for complementary application. Informed by different communities, these constructs have collective potential to increase confidence to support the application of mechanistic data in hazard assessment. This forum article summarizes concepts, introduces evolving understanding, and invites future collaboration to contribute to better common understanding and development of good practice in the use of mechanistic data in hazard assessment.

Development of a network of carcinogenicity adverse outcome pathways and its employment as an evidence framework for safety assessment

The traditional paradigm for safety assessment of chemicals for their carcinogenic potential to humans relies heavily on a battery of well-established genotoxicity tests, usually followed up by long-term, high-dose rodent studies. There are a variety of problems with this approach, not least that the rodent may not always be the best model to predict toxicity in humans. Consequently, new approach methodologies (NAMs) are being developed to replace or enhance predictions coming from the existing assays. However, a combination of the data arising from NAMs is likely to be required to improve upon the current paradigm, and consequently a framework is needed to combine evidence in a meaningful way. Adverse outcome pathways (AOPs) represent an ideal construct on which to organize this evidence. In this work, a data structure outlined previously was used to capture AOPs and evidence relating to carcinogenicity. Knowledge held within the predictive system Derek Nexus was extracted, built upon, and arranged into a coherent network containing 37 AOPs. 60 assays and 351 in silico alerts were then associated with KEs in this network, and it was brought to life by associating data and contextualizing evidence and predictions for over 13,400 compounds. Initial investigations into using the network to view knowledge and reason between evidence in different ways were made. Organizing knowledge and evidence in this way provides a flexible framework on which to carry out more consistent and meaningful carcinogenicity safety assessments in many different contexts.

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.

A high-level overview of the OECD AOP Development 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 modeling 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, 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 program, 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 toward 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 toward quantitative AOP development, it may motivate the expansion and implementation of AOPs in the radiation field.

The path via pathway-based approaches towards safety assessment: A concise review.

For decades, chemical safety assessment has been proposed to shift from animal testing to in vitro testing systems in response to the call for the 3R. In Europe, the answer was to combine various information sources in integrated testing strategies (ITS); In the US, it was in 2007 when the landmark report by the National Research Council put forward a vision of in vitro toxicity testing paradigm. Since then, efforts to develop pathway-based assessment framework have been on the track. In 2010, systems biology brought out a conceptual framework called adverse outcome pathway (AOP), which took one step further from toxicity pathway to regulatory toxicology. Computational modeling, high-throughput screening, high-content omics have all been approached to facilitate this progress. This paper briefly reviewed the achievement of pathway-based chemical assessment since 2007, discussed potential pitfalls and challenges that mechanism-driven chemical assessment may undergo, and presented future perspectives of safety assessment that is to be based on computational system biology.

Application of evidence-based methods to construct mechanism-driven chemical assessment frameworks.

The workshop titled "Application of evidence-based methods to construct mechanism-driven chemical assessment frameworks" was co-organized by the Evidence-based Toxicology Collaboration and the European Food Safety Authority (EFSA) and hosted by EFSA at its headquarters in Parma, Italy on October 2 and 3, 2019. The goal was to explore integration of systematic review with mechanistic evidence evaluation. Participants were invited to work on concrete products to advance the exploration of how evidence-based approaches can support the development and application of adverse outcome pathways (AOP) in chemical risk assessment. The workshop discussions were centered around three related themes: 1) assessing certainty in AOPs, 2) literature-based AOP development, and 3) integrating certainty in AOPs and non-animal evidence into decision frameworks. Several challenges, mostly related to methodology, were identified and largely determined the workshop recommendations. The workshop recommendations included the comparison and potential alignment of processes used to develop AOP and systematic review methodology, including the translation of vocabulary of evidence-based methods to AOP and vice versa, the development and improvement of evidence mapping and text mining methods and tools, as well as a call for a fundamental change in chemical risk and uncertainty assessment methodology if to be conducted based on AOPs and new approach methodologies (NAM). The usefulness of evidence-based approaches for mechanism-based chemical risk assessments was stressed, particularly the potential contribution of the rigor and transparency inherent to such approaches in building stakeholders' trust for implementation of NAM evidence and AOPs into chemical risk assessment.

An In vitro dimerization assay for the adverse outcome pathway approach in risk assessment of human estrogen receptor α-mediated endocrine-disrupting chemicals.

The adverse outcome pathway (AOP) has been recently proposed as an effective framework for chemical risk assessment. The AOP framework offers the advantage of effectively integrating individual in vitro studies and in silico prediction models. Thus, the development of an effective testing method to measure key events caused by chemicals is essential for chemical risk assessment through a fully developed AOP framework. We developed a human cell-based estrogen receptor α (ERα) dimerization assay using the bioluminescence resonance energy transfer (BRET) technique and evaluated the ERα dimerization activities of 72 chemicals. Fifty-one chemicals were identified to mediate dimerization of ERα, and the BRET-based ERα dimerization assay could effectively measure the events that mediated dimerization of ERα by the estrogenic chemicals. These results were compared with the results of pre-existing assay to determine whether the BRET-based ERα dimerization assay could be employed as an in vitro test method to provide scientific information for explaining key events as a part of the AOP framework. Consequently, we propose that the BRET-based ERα dimerization assay is suitable for measuring the chemical-mediated dimerization of ERα, a key event in the AOP framework for cellular-level risk assessment of estrogenic chemicals.

The Eco-Exposome Concept: Supporting an Integrated Assessment of Mixtures of Environmental Chemicals.

Organisms are exposed to ever-changing complex mixtures of chemicals over the course of their lifetime. The need to more comprehensively describe this exposure and relate it to adverse health effects has led to formulation of the exposome concept in human toxicology. Whether this concept has utility in the context of environmental hazard and risk assessment has not been discussed in detail. In this Critical Perspective, we propose-by analogy to the human exposome-to define the eco-exposome as the totality of the internal exposure (anthropogenic and natural chemicals, their biotransformation products or adducts, and endogenous signaling molecules that may be sensitive to an anthropogenic chemical exposure) over the lifetime of an ecologically relevant organism. We describe how targeted and nontargeted chemical analyses and bioassays can be employed to characterize this exposure and discuss how the adverse outcome pathway concept could be used to link this exposure to adverse effects. Available methods, their limitations, and/or requirement for improvements for practical application of the eco-exposome concept are discussed. Even though analysis of the eco-exposome can be resource-intensive and challenging, new approaches and technologies make this assessment increasingly feasible. Furthermore, an improved understanding of mechanistic relationships between external chemical exposure(s), internal chemical exposure(s), and biological effects could result in the development of proxies, that is, relatively simple chemical and biological measurements that could be used to complement internal exposure assessment or infer the internal exposure when it is difficult to measure. Environ Toxicol Chem 2022;41:30-45. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Integrate mechanistic evidence from new approach methodologies (NAMs) into a read-across assessment to characterise trends in shared mode of action.

Read-across approaches often remain inconclusive as they do not provide sufficient evidence on a common mode of action across the category members. This read-across case study on thirteen, structurally similar, branched aliphatic carboxylic acids investigates the concept of using human-based new approach methods, such as in vitro and in silico models, to demonstrate biological similarity. Five out of the thirteen analogues have preclinical in vivo studies. Three out of them induced lipid accumulation or hypertrophy in preclinical studies with repeated exposure, which leads to the read-across hypothesis that the analogues can potentially induce hepatic steatosis. To confirm the selection of analogues, the expression patterns of the induced differentially expressed genes (DEGs) were analysed in a human liver model. With increasing dose, the expression pattern within the tested analogues got more similar, which serves as a first indication of a common mode of action and suggests differences in the potency of the analogues. Hepatic steatosis is a well-known adverse outcome, for which over 55 adverse outcome pathways have been identified. The resulting adverse outcome pathway (AOP) network, comprised a total 43 MIEs/KEs and enabled the design of an in vitro testing battery. From the AOP network, ten MIEs, early and late KEs were tested to systematically investigate a common mode of action among the grouped compounds. The targeted testing of AOP specific MIE/KEs shows that biological activity in the category decreases with side chain length. A similar trend was evident in measuring liver alterations in zebra fish embryos. However, activation of single MIEs or early KEs at in vivo relevant doses did not necessarily progress to the late KE "lipid accumulation". KEs not related to the read-across hypothesis, testing for example general mitochondrial stress responses in liver cells, showed no trend or biological similarity. Testing scope is a key issue in the design of in vitro test batteries. The Dempster-Shafer decision theory predicted those analogues with in vivo reference data correctly using one human liver model or the CALUX reporter assays. The case study shows that the read-across hypothesis is the key element to designing the testing strategy. In the case of a good mechanistic understanding, an AOP facilitates the selection of reliable human in vitro models to demonstrate a common mode of action. Testing DEGs, MIEs and early KEs served to show biological similarity, whereas the late KEs become important for confirmation, as progression from MIEs to AO is not always guaranteed.

Employing an adverse outcome pathway framework for weight-of-evidence assessment with application to the ICH S1B guidance addendum.

Across industry, there is a paradigm shift occurring for carcinogenicity testing, with the focus moving from long term animal studies to alternative approaches. Based on the explorative work done in recent years, the International Council for Harmonization (ICH) recently published a draft addendum to the S1B guidance, which allows for a weight-of-evidence (WoE) assessment to be conducted based on data gathered throughout the pharmaceutical development process and literature to mitigate some testing in rodents if the body of evidence clearly shows undertaking an animal lifetime study would not add value to the risk assessment. While several alternative approaches already exist, and other new approach methodologies (NAMs) are being explored, all of which can contribute to this WoE, it is important that all the evidence can be combined in a meaningful and consistent way to reach a conclusion. Adverse outcome pathways have been advocated as a framework for organising evidence in an integrated approach to testing and assessment, which gives context to data and can aid reaching a conclusion as to the adverse outcome (AO). This approach can be combined with a reasoning methodology to give a prediction for an AO and applied to the factors which need to be considered for the ICH S1B WoE to predict for carcinogenicity. Using this approach to the WoE assessment, consistent, scientifically robust, and transparent calls can be made as to whether conducting an animal carcinogenicity study would add value to a human risk assessment and mitigate the need to run animal studies unnecessarily.

The potential of mechanistic information organised within the AOP framework to increase regulatory uptake of the developmental neurotoxicity (DNT) in vitro battery of assays.

A major challenge in regulatory developmental neurotoxicity (DNT) assessment is lack of toxicological information for many compounds. Therefore, the Test Guidelines programme of the Organisation for Economic Cooperation and Development (OECD) took the initiative to coordinate an international collaboration between diverse stakeholders to consider integration of alternative approaches towards improving the current chemical DNT testing. During the past few years, a series of workshops was organized during which a consensus was reached that incorporation of a DNT testing battery that relies on in vitro assays anchored to key neurodevelopmental processes should be developed. These key developmental processes include neural progenitor cell proliferation, neuronal and oligodendrocyte differentiation, neural cell migration, neurite outgrowth, synaptogenesis and neuronal network formation, as well key events identified in the existing Adverse Outcome Pathways (AOPs). AOPs deliver mechanistic information on the causal links between molecular initiating event, intermediate key events and an adverse outcome of regulatory concern, providing the biological context to facilitate development of Integrated Approaches to Testing and Assessment (IATA) for various regulatory purposes. Developing IATA case studies, using mechanistic information derived from AOPs, is expected to increase scientific confidence for the use of in vitro methods within an IATA, thereby facilitating regulatory uptake. This manuscript summarizes the current state of international efforts to enhance DNT testing by using an in vitro battery of assays focusing on the role of AOPs in informing the development of IATA for different regulatory purposes, aiming to deliver an OECD guidance document on use of in vitro DNT battery of assays that include in vitro data interpretation.

Assessment on the adverse effects on different kinds of fish induced by methamphetamine during the natural attenuation process based on adverse outcome pathway.

The adverse effects on model fish induced by methamphetamine (METH) have been revealed. However, the toxicity of METH on different kinds of non-model fish during the natural attenuation remained unclear. Hence, in this study, we for the first time established a static lab-scale aquatic ecosystem spiked with METH (initial levels at 25 µg/L) for 40 days to estimate its metabolism and toxicity in Chinese medaka, rosy bitterling, loach, and mosquito fish. The concentrations of METH in water and fish's brain were detected termly. The physiological functions, histopathology of brain, neurotransmitters contents, and expressions of associated genes of the four kinds of fish were determined at day 0, 20, and 40, respectively. The results indicated METH could be remarkably accumulated in fish brains with the distribution factor vs water (DFw) at 232.5-folds, and attenuated both in water and fish body during the exposure. METH caused physiological functions (i.e., swimming trajectories, locomotion distances, and feeding rates) disorders of the four kinds of fish, and stimulated surfacing behavior of loach. Tissue and macro/micromolecular biomarkers including histopathology, neurotransmitters (i.e., dopamine, serotonin, and norepinephrine), and mRNA, were similarly affected by METH. Mitogen-activated protein kinase (MAPKs) signaling pathway, P53-regulated apoptosis signaling pathway, N-methyl-d-aspartate-dopamine system, and mTOR signaling pathway of different kinds of fish were regulated by METH. Additionally, the impairments of the physiological and macromolecular indicators of fish could be alleviated as the natural attenuation of METH occurred. All the biomarkers, as well as the recovery effects during the exposure were integrated onto an adverse outcome pathway (AOP) framework. The key event was the micromolecular indicators (genes). The adverse outcomes at individual and population levels would result in the ecological consequences, implying the imperative to consider the natural attenuation process while assessing the environmental risk of METH.