ADVANCING THE GROUPING & HARMONIZATION OF SIMILAR KEY EVENTS IN THE AOP WIKI: Ontology-based Key Event Component Combinations as Catalysts for Integration

Poster presented at the 59th Congress of the European Societies of Toxicology (EUROTOX 2025), Athens, Greece Advancing the Grouping and Harmonization of Similar Key Events in the AOP Wiki: Ontology-Based Key Event Component Combinations as Catalysts for Integration J. Filipovska1, K. Audouze2, J. Blum3, L. -A. Clerbaux4, E. Coerek3, E. Demuynck5, S. Edwards6, E. Fritsche3, L. Gerner3, K. Groh7, G. Hench8, N. Jeliazkova9, I. Katsiadaki10, J. Malinowska11, B. Mertens5, M. Martens12, H. Mortensen6, P. Nymark13, I. Sovadinová14, S. Tanabe15, K. E. Tollefsen16, L. Wiklund13, C. Wittwehr11 1 Independent, Ohrid, Macedonia2 Université Paris Cité, HealthFex, Inserm, Paris, France3 SCAHT – Swiss Centre for Applied Human Toxicology, Basel, Switzerland4 UCLouvain, Louvain-la-Neuve, Belgium5 Sciensano, Brussels, Belgium6 US EPA, Office of Research and Development, Research Triangle Park, North Carolina, United States of America7 Eawag, Dübendorf,, Switzerland8 Independent, Durham, North Carolina, United States of America9 Ideaconsult Ltd., Sofia, Bulgaria10 Centre for Environment, Fisheries, and Aquaculture Science (Cefas), Weymouth, United Kingdom11 European Commission, Joint Research Centre, Ispra, Italy12 Maastricht University, Maastricht, Netherlands13 Karolinska Institute, Stockholm, Sweden14 Masaryk University, RECETOX, Brno, Czech Republic15 National Institute of Health Sciences, Kawasaki, Japan16 Norwegian Institute for Water Research (NIVA), Oslo, Norway Abstract: Regulatory toxicology is shifting away from an observational towards predictive discipline increasingly embracing New Approach Methodologies (NAMs) that focus on mechanistic understanding of stressor-induced biological perturbations. Adverse Outcome Pathways (AOPs) provide a structured framework for organizing evidence and knowledge to support this transition, with the AOP Wiki serving as the primary platform for documenting Key Events (KEs) and Key Event Relationships (KERs). The Society for the Advancement of AOPs Knowledgebase Interest Group (SKIG) is a global assembly of scientists, regulators, and policymakers dedicated to advancing AOP development and application. A recurring challenge identified by SKIG is the proliferation of distinct yet similar KEs in the AOP Wiki1. The free-text approach used to define KEs has resulted in inconsistencies, complicating AOP development and hindering the emergence of functional AOP networks (AOPN). Addressing this issue requires improved tools and methodologies. One proposed solution is the use of Ontology-Based Key Event Components (KECs) which utilize structured and predefined terms from 22 biological ontologies currently integrated into the AOP Wiki2. They encode KE descriptions into three machine-readable components: ‘Process,’ ‘Object,’ and ‘Action’ (the type/direction of perturbation). Depending on complexity at higher organizational levels, a KE can be represented using one or more combinations of these components as machine-readable tokens. Selecting appropriate KECs or their combinations is not trivial. A proposed approach involves leveraging (i) measurement methods associated with KEs for more precise identification of the ‘Object’ and ‘Process’ and (ii) Large Language Models (LLMs) to analyze free-text descriptions and suggest the most relevant KEC tokens objectively. Although predefined KECs have been considered in AOPN development3 and network analytics4, they have yet to be systematically applied for defining or grouping similar KEs and integration at higher level of biological organisation. Using two- or three-component tokens to define and search KEs—and sub-events in complex cases—could significantly enhance KE identification, harmonisation and integration of KEs into AOPNs. This approach aims to facilitate more objective, high-throughput, and machine-assisted KE description while preserving the integrity and creativity of human-generated content. It focuses on embracing complexity particularly in the context of KEs and KERs at the higher level of biological organisation. As such, it is complementary to the work of the Omics2AOP1, Methods2AOP5, FAIR_AOP6, Mystery of ROS7, PARC8 and Elixir toxicology9 communities, working towards better use of ontologies and developing optimal programmatic applications of KECs for AOP developers and users. Standing on the shoulders of these giants the authors will explore some practical ways to address the challenges of using KECs in the AOP framework. 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