Deciphering Adverse Outcome Pathway Network Linked to Bisphenol F Using Text Mining and Systems Toxicology Approaches

An integrative data-centric approach to derivation and characterization of an adverse outcome pathway network for cadmium-induced toxicity

Cadmium is a prominent toxic heavy metal that contaminates both terrestrial and aquatic environments. Owing to its high biological half-life and low excretion rates, cadmium causes a variety of adverse biological outcomes. Adverse outcome pathway (AOP) networks were envisioned to systematically capture toxicological information to enable risk assessment and chemical regulation. Here, we leveraged AOP-Wiki and integrated heterogeneous data from four other exposome-relevant resources to build the first AOP network relevant for inorganic cadmium-induced toxicity. From AOP-Wiki, we filtered 309 high confidence AOPs, identified 312 key events (KEs) associated with inorganic cadmium from five exposome-relevant databases using a data-centric approach, and thereafter, curated 30 cadmium relevant AOPs (cadmium-AOPs). By constructing the undirected AOP network, we identified a large connected component of 18 cadmium-AOPs. Further, we analyzed the directed network of 59 KEs and 82 key event relationships (KERs) in the largest component using graph-theoretic approaches. Subsequently, we mined published literature using artificial intelligence-based tools to provide auxiliary evidence of cadmium association for all KEs in the largest component. Finally, we performed case studies to verify the rationality of cadmium-induced toxicity in humans and aquatic species. Overall, cadmium-AOP network constructed in this study will aid ongoing research in systems toxicology and chemical exposome.

Artificial intelligence (AI)-it's the end of the tox as we know it (and I feel fine)

The rapid progress of AI impacts diverse scientific disciplines, including toxicology, and has the potential to transform chemical safety evaluation. Toxicology has evolved from an empirical science focused on observing apical outcomes of chemical exposure, to a data-rich field ripe for AI integration. The volume, variety and velocity of toxicological data from legacy studies, literature, high-throughput assays, sensor technologies and omics approaches create opportunities but also complexities that AI can help address. In particular, machine learning is well suited to handle and integrate large, heterogeneous datasets that are both structured and unstructured-a key challenge in modern toxicology. AI methods like deep neural networks, large language models, and natural language processing have successfully predicted toxicity endpoints, analyzed high-throughput data, extracted facts from literature, and generated synthetic data. Beyond automating data capture, analysis, and prediction, AI techniques show promise for accelerating quantitative risk assessment by providing probabilistic outputs to capture uncertainties. AI also enables explanation methods to unravel mechanisms and increase trust in modeled predictions. However, issues like model interpretability, data biases, and transparency currently limit regulatory endorsement of AI. Multidisciplinary collaboration is needed to ensure development of interpretable, robust, and human-centered AI systems. Rather than just automating human tasks at scale, transformative AI can catalyze innovation in how evidence is gathered, data are generated, hypotheses are formed and tested, and tasks are performed to usher new paradigms in chemical safety assessment. Used judiciously, AI has immense potential to advance toxicology into a more predictive, mechanism-based, and evidence-integrated scientific discipline to better safeguard human and environmental wellbeing across diverse populations.

Elucidating the toxicity mechanisms of organophosphate esters by adverse outcome pathway network

With the widespread use of organophosphate esters (OPEs), the accumulation and toxicity effect of OPEs in biota are attracting more and more concern. In order to clarify the mechanism of toxicity of OPEs to organisms, this study reviewed the OPEs toxicity and systematically identified the mechanism of OPEs toxicity under the framework of adverse outcome pathway (AOP). OPEs were divided into three groups (alkyl-OPEs, aryl-OPEs, and halogenated-OPEs) and biota was divided into aquatic organism and mammals. The results showed that tris(1,3-dichloro-2-propyl) phosphate (TDCIPP) and triphenyl phosphate (TPHP) mainly caused neurotoxicity, reproductive, and hepatotoxicity in different mechanisms. According to the constructed AOP network, the toxicity mechanism of OPEs on aquatic organisms and mammals is different, which is mainly attributed to the different biological metabolic systems of aquatic organisms and mammals. Interestingly, our results indicate that the toxicity effect of the three kinds of OPEs on aquatic organisms is different, while there was no obvious difference in the mechanism of toxicity of OPEs on mammals. This study provides a theoretical basis for OPEs risk assessment in the future.

Editorial trend: adverse outcome pathway (AOP) and computational strategy - towards new perspectives in ecotoxicology

The adverse outcome pathway (AOP) has been conceptualized in 2010 as an analytical construct to describe a sequential chain of causal links between key events, from a molecular initiating event leading to an adverse outcome (AO), considering several levels of biological organization. An AOP aims to identify and organize available knowledge about toxic effects of chemicals and drugs, either in ecotoxicology or toxicology, and it can be helpful in both basic and applied research and serve as a decision-making tool in support of regulatory risk assessment. The AOP concept has evolved since its introduction, and recent research in toxicology, based on integrative systems biology and artificial intelligence, gave it a new dimension. This innovative in silico strategy can help to decipher mechanisms of action and AOP and offers new perspectives in AOP development. However, to date, this strategy has not yet been applied to ecotoxicology. In this context, the main objective of this short article is to discuss the relevance and feasibility of transferring this strategy to ecotoxicology. One of the challenges to be discussed is the level of organisation that is relevant to address for the AO (population/community). This strategy also offers many advantages that could be fruitful in ecotoxicology and overcome the lack of time, such as the rapid identification of data available at a time t, or the identification of "data gaps". Finally, this article proposes a step forward with suggested priority topics in ecotoxicology that could benefit from this strategy.

An integrative systems biology strategy to support the development of adverse outcome pathways (AOPs): a case study on radiation-induced microcephaly

Adverse Outcome Pathways (AOPs) are useful tools for assessing the potential risks associated with exposure to various stressors, including chemicals and environmental contaminants. They provide a framework for understanding the causal relationships between different biological events that can lead to adverse outcomes (AO). However, developing an AOP is a challenging task, particularly in identifying the molecular initiating events (MIEs) and key events (KEs) that constitute it. Here, we propose a systems biology strategy that can assist in the development of AOPs by screening publicly available databases, literature with the text mining tool AOP-helpFinder, and pathway/network analyses. This approach is straightforward to use, requiring only the name of the stressor and adverse outcome to be studied. From this, it quickly identifies potential KEs and literature providing mechanistic information on the links between the KEs. The proposed approach was applied to the recently developed AOP 441 on radiation-induced microcephaly, resulting in the confirmation of the KEs that were already present and identification of new relevant KEs, thereby validating the strategy. In conclusion, our systems biology approach represents a valuable tool to simplify the development and enrichment of Adverse Outcome Pathways (AOPs), thus supporting alternative methods in toxicology.

AOP-helpFinder 2.0: Integration of an event-event searches module

To support the use of alternative methods in regulatory assessment of chemical risks, the concept of adverse outcome pathway (AOP) constitutes an important toxicological tool. AOP represents a structured representation of existing knowledge, linking molecular initiating event (MIE) initiated by a prototypical stressor that leads to a cascade of biological key event (KE) to an adverse outcome (AO). Biological information to develop such AOP is very dispersed in various data sources. To increase the chance of capturing relevant existing data to develop a new AOP, the AOP-helpFinder tool was recently implemented to assist researchers to design new AOP. Here, an updated version of AOP-helpFinder proposes novel functionalities. The main one being the implementation of an automatic screening of the abstracts from the PubMed database to identify and extract event-event associations. In addition, a new scoring system was created to classify the identified co-occurred terms (stressor-event or event-event (which represent key event relationships) to help prioritization and support the weight of evidence approach, allowing a global assessment of the strength and reliability of the AOP. Moreover, to facilitate interpretation of the results, visualization options are also proposed. The AOP-helpFinder source code are fully accessible via GitHub, and searches can be performed via a web interface at http://aop-helpfinder-v2.u-paris-sciences.fr/.

From old pollutants to the regulation of bisphenol A: Lessons learned for health promotion and disease prevention

Citizens deserve regulatory changes and policies more sensitive to the current needs of humans, the climate, and nature. In this work we draw on prior experiences of preventable human suffering and economic losses caused by delayed regulation of legacy and emerging pollutants. Heightened awareness of environmental health problems is necessary among health professionals, the media, and citizens' organizations. Improved translation from research to the clinical world and to policy is critical to reduce the population burden of diseases caused by exposure to endocrine disruptors and other environmental chemicals. Numerous lessons can be learned from science-to-policy processes built for "old pollutants" (as persistent organic pollutants, heavy metals, tributyltin), as well as from current trends regarding the regulation of non-persistent chemicals, such as the prototypical endocrine disruptor bisphenol A. We end discussing relevant pieces of the puzzle to tackle the environmental and regulatory challenges faced by our societies.

Conducting bioinformatics analysis to predict sulforaphane-triggered adverse outcome pathways in healthy human cells

Sulforaphane (SFN) is a naturally occurring molecule present in plants from Brassica family. It becomes bioactive after hydrolytic reaction mediated by myrosinase or human gastrointestinal microbiota. Sulforaphane gained scientific popularity due to its antioxidant and anti-cancer properties. However, its toxicity profile and potential to cause adverse effects remain largely unidentified. Thus, this study aimed to generate SFN-triggered adverse outcome pathway (AOP) by looking at the relationship between SFN-chemical structure and its toxicity, as well as SFN-gene interactions. Quantitative structure-activity relationship (QSAR) analysis identified 2 toxophores (Derek Nexus software) that have the potential to cause chromosomal damage and skin sensitization in mammals or mutagenicity in bacteria. Data extracted from Comparative Toxicogenomics Database (CTD) linked SFN with previously proposed outcomes via gene interactions. The total of 11 and 146 genes connected SFN with chromosomal damage and skin diseases, respectively. However, network analysis (NetworkAnalyst tool) revealed that these genes function in wider networks containing 490 and 1986 nodes, respectively. The over-representation analysis (ExpressAnalyst tool) pointed out crucial biological pathways regulated by SFN-interfering genes. These pathways are uploaded to AOP-helpFinder tool which found the 2321 connections between 19 enriched pathways and SFN which were further considered as key events. Two major, interconnected AOPs were generated: first starting from disruption of biological pathways involved in cell cycle and cell proliferation leading to increased apoptosis, and the second one connecting activated immune system signaling pathways to inflammation and apoptosis. In both cases, chromosomal damage and/or skin diseases such as dermatitis or psoriasis appear as adverse outcomes.

HBM4EU results support the Chemicals' Strategy for Sustainability and the Zero-Pollution Action Plan

One of the major goals of the European Human Biomonitoring Initiative (HBM4EU) was to bridge the gap between science and policy by consulting both policy makers and national scientists and generating evidence of the actual exposure of residents to chemicals and whether that exposure would be suggest a potential health risk. Residents' perspectives on chemical exposure and risk were also investigated. HBM4EU's research was designed to answer specific short-term and long-term policy questions at national and European levels, and for its results to directly support regulatory action on chemicals. A strategy was established to prioritise chemicals for analysis in human matrices, with a total of 18 substances/substance groups chosen to be investigated throughout the five-and a -half-year project. HBM4EU produced new evidence of human exposure levels, developed reference values for exposure, investigated determinants of exposure and derived health-based guidance values for those substances. In addition, HBM4EU promoted the use of human biomonitoring data in chemical risk assessment and developed innovative tools and methods linking chemicals to possible health impacts, such as effect biomarkers. Furthermore, HBM4EU advanced understand of effects from combined exposures and methods to identify emerging chemicals. With the aim of supporting policy implementation, science-to-policy workshops were organised, providing opportunities for joint reflection and dialogue on research results. I, and indicators were developed to assess temporal and spatial patterns in the exposure of European population. A sustainable human biomonitoring monitoring framework, producing comparable quality assured data would allow: the evaluation of time trends; the exploration of spatial trends: the evaluation of the influence of socio-economic conditions on chemical exposure. Therefore, such a framework should be included in the European Chemicals' Strategy for Sustainability and the data would support the Zero Pollution Action Plan.

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.

Daphnia as a model organism to probe biological responses to nanomaterials-from individual to population effects via adverse outcome pathways

The importance of the cladoceran Daphnia as a model organism for ecotoxicity testing has been well-established since the 1980s. Daphnia have been increasingly used in standardised testing of chemicals as they are well characterised and show sensitivity to pollutants, making them an essential indicator species for environmental stress. The mapping of the genomes of D. pulex in 2012 and D. magna in 2017 further consolidated their utility for ecotoxicity testing, including demonstrating the responsiveness of the Daphnia genome to environmental stressors. The short lifecycle and parthenogenetic reproduction make Daphnia useful for assessment of developmental toxicity and adaption to stress. The emergence of nanomaterials (NMs) and their safety assessment has introduced some challenges to the use of standard toxicity tests which were developed for soluble chemicals. NMs have enormous reactive surface areas resulting in dynamic interactions with dissolved organic carbon, proteins and other biomolecules in their surroundings leading to a myriad of physical, chemical, biological, and macromolecular transformations of the NMs and thus changes in their bioavailability to, and impacts on, daphnids. However, NM safety assessments are also driving innovations in our approaches to toxicity testing, for both chemicals and other emerging contaminants such as microplastics (MPs). These advances include establishing more realistic environmental exposures via medium composition tuning including pre-conditioning by the organisms to provide relevant biomolecules as background, development of microfluidics approaches to mimic environmental flow conditions typical in streams, utilisation of field daphnids cultured in the lab to assess adaption and impacts of pre-exposure to pollution gradients, and of course development of mechanistic insights to connect the first encounter with NMs or MPs to an adverse outcome, via the key events in an adverse outcome pathway. Insights into these developments are presented below to inspire further advances and utilisation of these important organisms as part of an overall environmental risk assessment of NMs and MPs impacts, including in mixture exposure scenarios.

Potential adverse outcome pathways with hazard identification of organophosphate esters

Data-driven analysis and pathway-based approaches contribute to reasonable arrangements of limited resources and laboratory tests for continuously emerging commercial chemicals, which provides opportunities to save time and effort for toxicity research. With the widespread usage of organophosphate esters (OPEs) on a global scale, the concentrations generally reached up to micromolar range in environmental media and even in organisms. However, potential adverse effects and toxicity pathways of OPEs have not been systematically assessed. Therefore, it is necessary to review the current situation, formulate the future research priorities, and characterize toxicity mechanisms via data-driven analysis. Results showed that the early toxicity studies focused on neurotoxicity, cytotoxicity, and metabolic disorders. Then the main focus shifted to the mechanisms of cardiotoxicity, endocrine disruption, hepatocytes, reproductive and developmental toxicity to vulnerable sub-populations, such as infants and embryos, affected by OPEs. In addition, several novel OPEs have been emerging, such as bis(2-ethylhexyl)-phenyl phosphate (HDEHP) and oxidation derivatives (OPAsO) generated from organophosphite antioxidants (OPAs), leading to multiple potential ecological and human health risks (neurotoxicity, hepatotoxicity, developmental toxicity, etc.). Notably, in-depth statistical analysis was promising in encapsulating toxicological information to develop adverse outcome pathways (AOPs) frameworks. Subsequently, network-centric analysis and quantitative weight-of-evidence (QWOE) approaches were utilized to construct and evaluate the putative AOPs frameworks of OPEs, showing the moderate confidences of the developed AOPs. In addition, frameworks demonstrated that several events, such as nuclear receptor activation, reactive oxygen species (ROS) production, oxidative stress, and DNA damage, were involved in multiple different adverse outcome (AO), and these AOs had certain degree of connectivity. This study brought new insights into facilitating the complement of AOP efficiently, as well as establishing toxicity pathways framework to inform risk assessment of emerging OPEs.

Reduced Birth Weight and Exposure to Per- and Polyfluoroalkyl Substances: A Review of Possible Underlying Mechanisms Using the AOP-HelpFinder

Prenatal exposure to per- and polyfluorinated substances (PFAS) may impair fetal growth. Our knowledge of the underlying mechanisms is incomplete. We used the Adverse Outcome Pathway (AOP)-helpFinder tool to search PubMed for studies published until March 2021 that examined PFAS exposure in relation to birth weight, oxidative stress, hormones/hormone receptors, or growth signaling pathways. Of these 1880 articles, 106 experimental studies remained after abstract screening. One clear finding is that PFAS are associated with oxidative stress in in vivo animal studies and in vitro studies. It appears that PFAS-induced reactive-oxygen species (ROS) generation triggers increased peroxisome proliferator-activated receptor (PPAR)γ expression and activation of growth signaling pathways, leading to hyperdifferentiation of pre-adipocytes. Fewer proliferating pre-adipocytes result in lower adipose tissue weight and in this way may reduce birth weight. PFAS may also impair fetal growth through endocrine effects. Estrogenic effects have been noted in in vivo and in vitro studies. Overall, data suggest thyroid-damaging effects of PFAS affecting thyroid hormones, thyroid hormone gene expression, and histology that are associated in animal studies with decreased body and organ weight. The effects of PFAS on the complex relationships between oxidative stress, endocrine system function, adipogenesis, and fetal growth should be further explored.

Development of an Adverse Outcome Pathway for radiation-induced microcephaly via expert consultation and machine learning

BACKGROUND

Brain development during embryogenesis and in early postnatal life is particularly complex and involves the interplay of many cellular processes and molecular mechanisms, making it extremely vulnerable to exogenous insults, including ionizing radiation (IR). Microcephaly is one of the most frequent neurodevelopmental abnormalities that is characterized by small brain size, and is often associated with intellectual deficiency. Decades of research span from epidemiological data on in utero exposure of the A-bomb survivors, to studies on animal and cellular models that allowed deciphering the most prominent molecular mechanisms leading to microcephaly. The Adverse Outcome Pathway (AOP) framework is used to organize, evaluate and portray the scientific knowledge of toxicological effects spanning different biological levels of organizations, from the initial interaction with molecular targets to the occurrence of a disease or adversity. In the present study, the framework was used in an attempt to organize the current scientific knowledge on microcephaly progression in the context of ionizing radiation (IR) exposure. This work was performed by a group of experts formed during a recent workshop organized jointly by the Multidisciplinary European Low Dose Initiative (MELODI) and the European Radioecology Alliance (ALLIANCE) associations to present the AOP approach and tools. Here we report on the development of a putative AOP for congenital microcephaly resulting from IR exposure based on discussions of the working group and we emphasize the use of a novel machine-learning approach to assist in the screening of the available literature to develop AOPs.

CONCLUSION

The expert consultation led to the identification of crucial biological events for the progression of microcephaly upon exposure to IR, and highlighted current knowledge gaps. The machine learning approach was successfully used to screen the existing knowledge and helped to rapidly screen the body of evidence and in particular the epidemiological data. This systematic review approach also ensured that the analysis was sufficiently comprehensive to identify the most relevant data and facilitate rapid and consistent AOP development. We anticipate that as machine learning approaches become more user-friendly through easy-to-use web interface, this would allow AOP development to become more efficient and less time consuming.

Deploying elements of scoping review methods for Adverse Outcome Pathway development: A space travel case example

Purpose Health protection agencies require scientific information for evidence-based decision-making and guideline development. However, vetting and collating large quantities of published research to identify relevant high-quality studies is a challenge. One approach to address this issue is the use of Adverse Outcome Pathways (AOPs) that provide a framework to assemble toxicological knowledge into causally linked chains of key events across levels of biological organization to culminate in an adverse health outcome of significance. Traditionally, AOPs have been constructed using a narrative review approach where the collection of evidence that supports each pathway is based on prior knowledge of influential studies that can also be supplemented by individually selecting and reviewing relevant references. Objectives: We aimed to create a protocol for AOP weight of evidence gathering that harnesses elements of both scoping review methods and artificial intelligence tools to increase transparency while reducing bias and workload of human screeners. Methods: To develop this protocol, an existing space-health AOP in the workplan of the Organisation for Economic Co-operation and Development (OECD) AOP program was used as a case example. To balance the benefits of both scoping review tools and narrative approaches, a study protocol outlining a screening and search strategy was developed, and three reference collection workflows were tested to identify the most efficient method to inform weight of evidence. The workflows differed in their literature search strategies, and combinations of software tools used. Results: Across the three tested workflows, over 59 literature searches were completed, retrieving over 34000 references of which over 3300 were human reviewed. The most effective of the three methods used a search strategy with searches across each component of the AOP network, SWIFT Review as a pre-filtering software, and DistillerSR to create structured screening and data extraction forms. This methodology effectively retrieved relevant studies while balancing efficiency in data retrieval without compromising transparency, leading to a well-synthesized evidence base to support the AOP. Conclusions: The workflow is still exploratory in the context of AOP development, and we anticipate adaptations to the protocol with further experience. To further the systematicity, future iterations of the workflow could include structured quality assessment and risk of bias analysis. Overall, the workflow provides a transparent and unbiased approach to support AOP development, which in turn will support the need for rigorous methods to identify relevant scientific evidence while being practical to allow uptake by the broader community.

Characterization of Potential Adverse Outcome Pathways Related to Metabolic Outcomes and Exposure to Per- and Polyfluoroalkyl Substances Using Artificial Intelligence

Human exposure to per- and polyfluoroalkyl substances (PFAS) has been associated with numerous adverse health effects, depending on various factors such as the conditions of exposure (dose/concentration, duration, route of exposure, etc.) and characteristics associated with the exposed target (e.g., age, sex, ethnicity, health status, and genetic predisposition). The biological mechanisms by which PFAS might affect systems are largely unknown. To support the risk assessment process, AOP-helpFinder, a new artificial intelligence tool, was used to rapidly and systematically explore all available published information in the PubMed database. The aim was to identify existing associations between PFAS and metabolic health outcomes that may be relevant to support building adverse outcome pathways (AOPs). The collected information was manually organized to investigate linkages between PFAS exposures and metabolic health outcomes, including dyslipidemia, hypertension, insulin resistance, and obesity. Links between PFAS exposure and events from the existing metabolic-related AOPs were also retrieved. In conclusion, by analyzing dispersed information from the literature, we could identify some associations between PFAS exposure and components of existing AOPs. Additionally, we identified some linkages between PFAS exposure and metabolic outcomes for which only sparse information is available or which are not yet present in the AOP-wiki database that could be addressed in future research.

A Narrative Literature Review of Natural Language Processing Applied to the Occupational Exposome

The evolution of the Exposome concept revolutionised the research in exposure assessment and epidemiology by introducing the need for a more holistic approach on the exploration of the relationship between the environment and disease. At the same time, further and more dramatic changes have also occurred on the working environment, adding to the already existing dynamic nature of it. Natural Language Processing (NLP) refers to a collection of methods for identifying, reading, extracting and untimely transforming large collections of language. In this work, we aim to give an overview of how NLP has successfully been applied thus far in Exposome research. Methods: We conduct a literature search on PubMed, Scopus and Web of Science for scientific articles published between 2011 and 2021. We use both quantitative and qualitative methods to screen papers and provide insights into the inclusion and exclusion criteria. We outline our approach for article selection and provide an overview of our findings. This is followed by a more detailed insight into selected articles. Results: Overall, 6420 articles were screened for the suitability of this review, where we review 37 articles in depth. Finally, we discuss future avenues of research and outline challenges in existing work. Conclusions: Our results show that (i) there has been an increase in articles published that focus on applying NLP to exposure and epidemiology research, (ii) most work uses existing NLP tools and (iii) traditional machine learning is the most popular approach.

Adverse outcome pathway from activation of the AhR to breast cancer-related death

Adverse outcome pathways (AOPs) are formalized and structured linear concepts that connect one molecular initiating event (MIE) to an adverse outcome (AO) via different key events (KE) through key event relationships (KER). They are mainly used in eco-toxicology toxicology, and regulatory health issues. AOPs must respond to specific guidelines from the Organization for Economic Co-operation and Development (OECD) to weight the evidence between each KE. Breast cancer is the deadliest cancer in women with a poor prognosis in case of metastatic breast cancer. The role of the environments in the formation of metastasis has been suggested. We hypothesized that activation of the AhR (MIE), a xenobiotic receptor, could lead to breast cancer related death (AO), through different KEs, constituting a new AOP. An artificial intelligence tool (AOP-helpfinder), which screens the available literature, was used to collect all existing scientific abstracts to build a novel AOP, using a list of key words. Four hundred and seven abstracts were found containing at least a word from our MIE list and either one word from our AO or KE list. A manual curation retained 113 pertinent articles, which were also screened using PubTator. From these analyses, an AOP was created linking the activation of the AhR to breast cancer related death through decreased apoptosis, inflammation, endothelial cell migration, angiogenesis, and invasion. These KEs promote an increased tumor growth, angiogenesis and migration which leads to breast cancer metastasis and breast cancer related death. The evidence of the proposed AOP was weighted using the tailored Bradford Hill criteria and the OECD guidelines. The confidence in our AOP was considered strong. An in vitro validation must be carried out, but our review proposes a strong relationship between AhR activation and breast cancer-related death with an innovative use of an artificial intelligence literature search.

Position paper on management of personal data in environment and health research in Europe

Management of datasets that include health information and other sensitive personal information of European study participants has to be compliant with the General Data Protection Regulation (GDPR, Regulation (EU) 2016/679). Within scientific research, the widely subscribed'FAIR' data principles should apply, meaning that research data should be findable, accessible, interoperable and re-usable. Balancing the aim of open science driven FAIR data management with GDPR compliant personal data protection safeguards is now a common challenge for many research projects dealing with (sensitive) personal data. In December 2020 a workshop was held with representatives of several large EU research consortia and of the European Commission to reflect on how to apply the FAIR data principles for environment and health research (E&H). Several recent data intensive EU funded E&H research projects face this challenge and work intensively towards developing solutions to access, exchange, store, handle, share, process and use such sensitive personal data, with the aim to support European and transnational collaborations. As a result, several recommendations, opportunities and current limitations were formulated. New technical developments such as federated data management and analysis systems, machine learning together with advanced search software, harmonized ontologies and data quality standards should in principle facilitate the FAIRification of data. To address ethical, legal, political and financial obstacles to the wider re-use of data for research purposes, both specific expertise and underpinning infrastructure are needed. There is a need for the E&H research data to find their place in the European Open Science Cloud. Communities using health and population data, environmental data and other publicly available data have to interconnect and synergize. To maximize the use and re-use of environment and health data, a dedicated supporting European infrastructure effort, such as the EIRENE research infrastructure within the ESFRI roadmap 2021, is needed that would interact with existing infrastructures.

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.

Obesity III: Obesogen assays: Limitations, strengths, and new directions

There is increasing evidence of a role for environmental contaminants in disrupting metabolic health in both humans and animals. Despite a growing need for well-understood models for evaluating adipogenic and potential obesogenic contaminants, there has been a reliance on decades-old in vitro models that have not been appropriately managed by cell line providers. There has been a quick rise in available in vitro models in the last ten years, including commercial availability of human mesenchymal stem cell and preadipocyte models; these models require more comprehensive validation but demonstrate real promise in improved translation to human metabolic health. There is also progress in developing three-dimensional and co-culture techniques that allow for the interrogation of a more physiologically relevant state. While diverse rodent models exist for evaluating putative obesogenic and/or adipogenic chemicals in a physiologically relevant context, increasing capabilities have been identified for alternative model organisms such as Drosophila, C. elegans, zebrafish, and medaka in metabolic health testing. These models have several appreciable advantages, including most notably their size, rapid development, large brood sizes, and ease of high-resolution lipid accumulation imaging throughout the organisms. They are anticipated to expand the capabilities of metabolic health research, particularly when coupled with emerging obesogen evaluation techniques as described herein.

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.

Advancing the Adverse Outcome Pathway for PPARγ Inactivation Leading to Pulmonary Fibrosis Using Bradford-Hill Consideration and the Comparative Toxicogenomics Database

Pulmonary fibrosis is regulated by transforming growth factor-β (TGF-β) and peroxisome proliferator-activated receptor-gamma (PPARγ). An adverse outcome pathway (AOP) for PPARγ inactivation leading to pulmonary fibrosis has been previously developed. To advance the development of this AOP, the confidence of the overall AOP was assessed using the Bradford-Hill considerations as per the recommendations from the Organisation for Economic Co-operation and Development (OECD) Users' Handbook. Overall, the essentiality of key events (KEs) and the biological plausibility of key event relationships (KERs) were rated high. In contrast, the empirical support of KERs was found to be moderate. To experimentally evaluate the KERs from the molecular initiating event (MIE) and KE1, PPARγ (MIE) and TGF-β (KE1) inhibitors were used to examine the effects of downstream events following inhibition of their upstream events. PPARγ inhibition (MIE) led to TGF-β activation (KE1), upregulation in vimentin expression (KE3), and an increase in the fibronectin level (KE4). Similarly, activated TGF-β (KE1) led to an increase in vimentin (KE3) and fibronectin expression (KE4). In the database analysis using the Comparative Toxicogenomics Database, 31 genes related to each KE were found to be highly correlated with pulmonary fibrosis, and the top 21 potential stressors were suggested. The AOP for pulmonary fibrosis evaluated in this study will be the basis for the screening of inhaled toxic substances in the environment.

Emerging Bioinformatics Methods and Resources in Drug Toxicology

Assessing the drug safety at an early stage of a drug discovery program is a critical issue. With the recent advances in molecular biology and genomic, massive amounts of generated and accumulated data by advanced experimental technologies such as RNA sequencing or proteomics start to be at the disposal of the scientific community. Innovative and adequate bioinformatic methods, tools, and protocols are required to analyze properly these diverse and extensive data sources with the aim to identify key features that are related to toxicity observations. Furthermore, the assessment of drug safety can be performed across multiple scales of complexity from molecular, cellular to phenotypic levels; therefore, the application of network science contributes to a better interpretation of the drug's exposure effect on human health. Here, we review databases containing toxicogenomics and chemical-phenotype information, as well as appropriated bioinformatics approaches that are currently used to analyze such data. Extension to others methods such as dose-responses, time-dependent processes, and text mining is also presented giving an overview of suitable tools available for a best practice of drug safety analysis.

Capturing a Comprehensive Picture of Biological Events From Adverse Outcome Pathways in the Drug Exposome

Background: The chemical part of the exposome, including drugs, may explain the increase of health effects with outcomes such as infertility, allergies, metabolic disorders, which cannot be only explained by the genetic changes. To better understand how drug exposure can impact human health, the concepts of adverse outcome pathways (AOPs) and AOP networks (AONs), which are representations of causally linked events at different biological levels leading to adverse health, could be used for drug safety assessment.

Methods: To explore the action of drugs across multiple scales of the biological organization, we investigated the use of a network-based approach in the known AOP space. Considering the drugs and their associations to biological events, such as molecular initiating event and key event, a bipartite network was developed. This bipartite network was projected into a monopartite network capturing the event–event linkages. Nevertheless, such transformation of a bipartite network to a monopartite network had a huge risk of information loss. A way to solve this problem is to quantify the network reduction. We calculated two scoring systems, one measuring the uncertainty and a second one describing the loss of coverage on the developed event–event network to better investigate events from AOPs linked to drugs.

Results: This AON analysis allowed us to identify biological events that are highly connected to drugs, such as events involving nuclear receptors (ER, AR, and PXR/SXR). Furthermore, we observed that the number of events involved in a linkage pattern with drugs is a key factor that influences information loss during monopartite network projection. Such scores have the potential to quantify the uncertainty of an event involved in an AON, and could be valuable for the weight of evidence assessment of AOPs. A case study related to infertility, more specifically to “decrease, male agenital distance” is presented.

Conclusion: This study highlights that computational approaches based on network science may help to understand the complexity of drug health effects, with the aim to support drug safety assessment.

AOP-helpFinder webserver: a tool for comprehensive analysis of the literature to support adverse outcome pathways development

MOTIVATION

Adverse outcome pathways (AOPs) are a conceptual framework developed to support the use of alternative toxicology approaches in the risk assessment. AOPs are structured linear organizations of existing knowledge illustrating causal pathways from the initial molecular perturbation triggered by various stressors, through key events (KEs) at different levels of biology, to the ultimate health or ecotoxicological adverse outcome.

RESULTS

Artificial intelligence can be used to systematically explore available toxicological data that can be parsed in the scientific literature. Recently, a tool called AOP-helpFinder was developed to identify associations between stressors and KEs supporting thus documentation of AOPs. To facilitate the utilization of this advanced bioinformatics tool by the scientific and the regulatory community, a webserver was created. The proposed AOP-helpFinder webserver uses better performing version of the tool which reduces the need for manual curation of the obtained results. As an example, the server was successfully applied to explore relationships of a set of endocrine disruptors with metabolic-related events. The AOP-helpFinder webserver assists in a rapid evaluation of existing knowledge stored in the PubMed database, a global resource of scientific information, to build AOPs and Adverse Outcome Networks supporting the chemical risk assessment.

AVAILABILITY AND IMPLEMENTATION

AOP-helpFinder is available at http://aop-helpfinder.u-paris-sciences.fr/index.php.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Intestinal toxicity and microbial community disorder induced by bisphenol F and bisphenol S in zebrafish

The intestine is the important bioaccumulation and target organ of Bisphenol F (BPF) and Bisphenol S (BPS). Morphological and functional abnormalities induced by BPS and BPF exposure in zebrafish intestine have been reported. However, the underlying mechanisms are not well understood, and the combined toxicities of BPS and BPF in the intestine have not been studied. Here, the zebrafish were treated by single and combined exposure of BPF and BPS at 1, 10, 100, 1000 μg/L. Oxidative damage, inflammation, and transcriptome profiles in the zebrafish intestine were determined. Changes in microbial community structure in zebrafish intestine were analyzed. Results showed that BPF, BPS, and BPF + BPS exposures significantly increased MDA, 8-OHdG, 1L-1β, and TNF-α levels in the zebrafish intestine, indicating oxidative damage and inflammatory effects. Co-exposure of BPS and BPF did not cause synergistic effects on the above effects but induced more changes in gene expression profiles. The changes in the PPAR signaling pathway might be associated with oxidative damage and inflammation. The amino acid metabolism and steroid biosynthesis were specifically altered by co-exposure of BPF and BPS. Moreover, BPF and/or BPS exposures altered microbial community structure in the zebrafish intestine, which showed different influence patterns. Increased abundance of potentially pathogenic bacteria (such as Flavobacterium, Pseudomonas, and Stenotrophomonas) might indicate one of the potential health hazards in zebrafish intestine. The above results provide basic information for the health risk assessment of BPS and BPF in aquatic organisms.

Trends in the Application of "Omics" to Ecotoxicology and Stress Ecology

Our ability to predict and assess how environmental changes such as pollution and climate change affect components of the Earth's biome is of paramount importance. This need positioned the fields of ecotoxicology and stress ecology at the center of environmental monitoring efforts. Advances in these interdisciplinary fields depend not only on conceptual leaps but also on technological advances and data integration. High-throughput "omics" technologies enabled the measurement of molecular changes at virtually all levels of an organism's biological organization and thus continue to influence how the impacts of stressors are understood. This bibliometric review describes literature trends (2000-2020) that indicate that more different stressors than species are studied each year but that only a few stressors have been studied in more than two phyla. At the same time, the molecular responses of a diverse set of non-model species have been investigated, but cross-species comparisons are still rare. While transcriptomics studies dominated until 2016, a shift towards proteomics and multiomics studies is apparent. There is now a wealth of data at functional omics levels from many phylogenetically diverse species. This review, therefore, addresses the question of how to integrate omics information across species.

Identification of non-validated endocrine disrupting chemical characterization methods by screening of the literature using artificial intelligence and by database exploration

BACKGROUND

Exposure to endocrine disrupting chemicals (EDCs) represents a critical public health threat. Several adverse health outcomes (e.g., cancers, metabolic and neurocognitive/neurodevelopmental disorders, infertility, immune diseases and allergies) are associated with exposure to EDCs. However, the regulatory tests that are currently employed in the EU to identify EDCs do not assess all of the endocrine pathways.

OBJECTIVE

Our objective was to explore the literature, guidelines and databases to identify relevant and reliable test methods which could be used for prioritization and regulatory pre-validation of EDCs in missing and urgent key areas.

METHODS

Abstracts of articles referenced in PubMed were automatically screened using an updated version of the AOP-helpFinder text mining approach. Other available sources were manually explored. Exclusion criteria (computational methods, specific tests for estrogen receptors, tests under validation or already validated, methods accepted by regulatory bodies) were applied according to the priorities of the French Public-privatE Platform for the Pre-validation of Endocrine disRuptors (PEPPER) characterisation methods.

RESULTS

226 unique non-validated methods were identified. These experimental methods (in vitro and in vivo) were developed for 30 species using diverse techniques (e.g., reporter gene assays and radioimmunoassays). We retrieved bioassays mainly for the reproductive system, growth/developmental systems, lipogenesis/adipogenicity, thyroid, steroidogenesis, liver metabolism-mediated toxicity, and more specifically for the androgen-, thyroid hormone-, glucocorticoid- and aryl hydrocarbon receptors.

CONCLUSION

We identified methods to characterize EDCs which could be relevant for regulatory pre-validation and, ultimately for the efficient prevention of EDC-related severe health outcomes. This integrative approach highlights a successful and complementary strategy which combines computational and manual curation approaches.

Deep Dive into Plastic Monomers, Additives, and Processing Aids

A variety of chemical substances used in plastic production may be released throughout the entire life cycle of the plastic, posing risks to human health, the environment, and recycling systems. Only a limited number of these substances have been widely studied. We systematically investigate plastic monomers, additives, and processing aids on the global market based on a review of 63 industrial, scientific, and regulatory data sources. In total, we identify more than 10'000 relevant substances and categorize them based on substance types, use patterns, and hazard classifications wherever possible. Over 2'400 substances are identified as substances of potential concern as they meet one or more of the persistence, bioaccumulation, and toxicity criteria in the European Union. Many of these substances are hardly studied according to SciFinder (266 substances), are not adequately regulated in many parts of the world (1'327 substances), or are even approved for use in food-contact plastics in some jurisdictions (901 substances). Substantial information gaps exist in the public domain, particularly on substance properties and use patterns. To transition to a sustainable circular plastic economy that avoids the use of hazardous chemicals, concerted efforts by all stakeholders are needed, starting by increasing information accessibility.

Development of an adverse outcome pathway for nanoplastic toxicity in Daphnia pulex using proteomics

Nanoplastics are a growing environmental and public health concern. However, the toxic mechanisms of nanoplastics are poorly understood. Here, we evaluated the effects of spherical polystyrene nanoplastics on reproduction of Daphnia pulex and analyzed the proteome of whole animals followed by molecular and biochemical analyses for the development of an adverse outcome pathway (AOP) for these contaminants of emerging concern. Animals were exposed to polystyrene nanoplastics (0, 0.1, 0.5, 1 and 2 mg/L) via water for 21 days. Nanoplastics negatively impacted cumulative offspring production. A total of 327 differentially expressed proteins (DEPs) were identified in response to nanoplastics which were further validated from gene expression and enzyme activity data. Based on these results, we propose an AOP for nanoplastics, including radical oxygen species production and oxidative stress as the molecular initiating event (MIE); followed by changes in specific signaling pathways (Jak-STAT, mTOR and FoxO) and in the metabolism of glutathione, protein, lipids, and molting proteins; with an end result of growth inhibition and decrease reproductive output. This study serves as a foundation for the development of a mechanistic understanding of nanoplastic toxicity in crustaceans and perhaps other aquatic organisms.

Bringing together scientific disciplines for collaborative undertakings: a vision for advancing the adverse outcome pathway framework

BACKGROUND

Decades of research to understand the impacts of various types of environmental occupational and medical stressors on human health have produced a vast amount of data across many scientific disciplines. Organizing these data in a meaningful way to support risk assessment has been a significant challenge. To address this and other challenges in modernizing chemical health risk assessment, the Organisation for Economic Cooperation and Development (OECD) formalized the adverse outcome pathway (AOP) framework, an approach to consolidate knowledge into measurable key events (KEs) at various levels of biological organisation causally linked to disease based on the weight of scientific evidence (http://oe.cd/aops). Currently, AOPs have been considered predominantly in chemical safety but are relevant to radiation. In this context, the Nuclear Energy Agency's (NEA's) High-Level Group on Low Dose Research (HLG-LDR) is working to improve research co-ordination, including radiological research with chemical research, identify synergies between the fields and to avoid duplication of efforts and resource investments. To this end, a virtual workshop was held on 7 and 8 October 2020 with experts from the OECD AOP Programme together with the radiation and chemical research/regulation communities. The workshop was a coordinated effort of Health Canada, the Electric Power Research Institute (EPRI), and the Nuclear Energy Agency (NEA). The AOP approach was discussed including key issues to fully embrace its value and catalyze implementation in areas of radiation risk assessment.

CONCLUSIONS

A joint chemical and radiological expert group was proposed as a means to encourage cooperation between risk assessors and an initial vision was discussed on a path forward. A global survey was suggested as a way to identify priority health outcomes of regulatory interest for AOP development. Multidisciplinary teams are needed to address the challenge of producing the appropriate data for risk assessments. Data management and machine learning tools were highlighted as a way to progress from weight of evidence to computational causal inference.

AOP4EUpest: mapping of pesticides in adverse outcome pathways using a text mining tool

MOTIVATION

Exposure to pesticides may lead to adverse health effects in human populations, in particular vulnerable groups. The main long-term health concerns are neurodevelopmental disorders, carcinogenicity as well as endocrine disruption possibly leading to reproductive and metabolic disorders. Adverse outcome pathways (AOP) consist in linear representations of mechanistic perturbations at different levels of the biological organization. Although AOPs are chemical-agnostic, they can provide a better understanding of the Mode of Action of pesticides and can support a rational identification of effect markers.

RESULTS

With the increasing amount of scientific literature and the development of biological databases, investigation of putative links between pesticides, from various chemical groups and AOPs using the biological events present in the AOP-Wiki database is now feasible. To identify co-occurrence between a specific pesticide and a biological event in scientific abstracts from the PubMed database, we used an updated version of the artificial intelligence-based AOP-helpFinder tool. This allowed us to decipher multiple links between the studied substances and molecular initiating events, key events and adverse outcomes. These results were collected, structured and presented in a web application named AOP4EUpest that can support regulatory assessment of the prioritized pesticides and trigger new epidemiological and experimental studies.

AVAILABILITY AND IMPLEMENTATION

http://www.biomedicale.parisdescartes.fr/aop4EUpest/home.php.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Exposure to New Emerging Bisphenols Among Young Children in Switzerland

Restrictions on the use of bisphenol A (BPA) in consumer products led to its replacement by various bisphenol (BP) analogues, yet young children's exposure to these analogues has been poorly characterized so far. This study aimed to characterize infants' and toddlers' exposure to BPA and 14 emerging BP analogues (i.e., bisphenol AF, bisphenol AP, bisphenol B, bisphenol BP, bisphenol C (BPC), bisphenol E, bisphenol F (BPF), bisphenol G, bisphenol M (BPM), bisphenol P, bisphenol PH, bisphenol S (BPS), bisphenol TMC, and bisphenol Z). We extracted infants' and toddlers' urine from diapers (n = 109) collected in Swiss daycare centers as a practical and noninvasive alternative approach to urinary biomonitoring. Bisphenols were present in 47% of the samples, with BPC and BPM being the most frequently detected (23% and 25% of all samples, respectively). The mean concentrations of urinary BPS and BPF were greater than that of BPA. This contrasts with data reported previously. Furthermore, statistical analysis revealed a significant and negative correlation between urinary BPM concentration and the population's age. Our results provide a first characterization of infants' and toddlers' exposure to bisphenols in Switzerland. This knowledge can be used to support ongoing biomonitoring studies and to prioritize exposure reduction and prevention strategies.

Development of an adverse drug event network to predict drug toxicity

Despite of their therapeutic effects, drug's exposure may have negative effects on human health such as adverse drug reaction (ADR) and side effects (SE). Adverse drug events (ADEs), that correspond to an event occurring during the drug treatment (i.e. ADR and SE), is not necessarily caused by the drug itself, as this is the case with medical errors and social factors. Due to the complexity of the biological systems, not all ADEs are known for marketed drugs. Therefore, new and effective methods are needed to determine potential risks, including the development of computational strategies. We present an ADE association network based on 90,827 drug-ADE associations between 930 unique drug and 6221 unique ADE, on which we implemented a scoring system based on a pull-down approach for prediction of drug-ADE combination. Based on our network, ADEs proposed for three drugs, safinamide, sonidegib, rufinamide are further discussed. The model was able to identify, already known drug-ADE associations that are supported by the literature and FDA reports, and also to predict uncharacterized associations such as dopamine dysregulation syndrome, or nicotinic acid deficiency for the drugs safinamide and sonidegib respectively, illustrating the power of such integrative toxicological approach.

Quantitative adverse outcome pathway (qAOP) models for toxicity prediction

The quantitative adverse outcome pathway (qAOP) concept is gaining interest due to its potential regulatory applications in chemical risk assessment. Even though an increasing number of qAOP models are being proposed as computational predictive tools, there is no framework to guide their development and assessment. As such, the objectives of this review were to: (i) analyse the definitions of qAOPs published in the scientific literature, (ii) define a set of common features of existing qAOP models derived from the published definitions, and (iii) identify and assess the existing published qAOP models and associated software tools. As a result, five probabilistic qAOPs and ten mechanistic qAOPs were evaluated against the common features. The review offers an overview of how the qAOP concept has advanced and how it can aid toxicity assessment in the future. Further efforts are required to achieve validation, harmonisation and regulatory acceptance of qAOP models.

Integrative Strategy of Testing Systems for Identification of Endocrine Disruptors Inducing Metabolic Disorders-An Introduction to the OBERON Project

Exposure to chemical substances that can produce endocrine disrupting effects represents one of the most critical public health threats nowadays. In line with the regulatory framework implemented within the European Union (EU) to reduce the levels of endocrine disruptors (EDs) for consumers, new and effective methods for ED testing are needed. The OBERON project will build an integrated testing strategy (ITS) to detect ED-related metabolic disorders by developing, improving and validating a battery of test systems. It will be based on the concept of an integrated approach for testing and assessment (IATA). OBERON will combine (1) experimental methods (in vitro, e.g., using 2D and 3D human-derived cells and tissues, and in vivo, i.e., using zebrafish at different stages), (2) high throughput omics technologies, (3) epidemiology and human biomonitoring studies and (4) advanced computational models (in silico and systems biology) on functional endpoints related to metabolism. Such interdisciplinary framework will help in deciphering EDs based on a mechanistic understanding of toxicity by providing and making available more effective alternative test methods relevant for human health that are in line with regulatory needs. Data generated in OBERON will also allow the development of novel adverse outcome pathways (AOPs). The assays will be pre-validated in order to select the test systems that will show acceptable performance in terms of relevance for the second step of the validation process, i.e., the inter-laboratory validation as ring tests. Therefore, the aim of the OBERON project is to support the organization for economic co-operation and development (OECD) conceptual framework for testing and assessment of single and/or mixture of EDs by developing specific assays not covered by the current tests, and to propose an IATA for ED-related metabolic disorder detection, which will be submitted to the Joint Research Center (JRC) and OECD community.

Adverse Outcome Pathway Bridge Building from Research to Regulation

The adverse outcome pathway (AOP) framework is a new way of generating knowledge from existing data for hazard assessment. Computational tools will help, especially with further development and adoption of data quality guidance.