Within WP4 (Effects and Risks) of RadoNorm, a new publication titled “AOP-helpFinder 3.0: from text mining to network visualization of key event relationships, and knowledge integration from multiple sources” was publishing in the journal Bioinformatics by colleagues at Université Paris-Cité and ASNR.

The Adverse Outcome Pathways (AOP) framework structures toxicological knowledge by linking molecular perturbations to adverse effects on human health and ecosystems. With the rise of large-scale data, text mining techniques—combining natural language processing and graph-based methods—efficient extraction of toxicological relationships is possible. AOP-helpFinder 3.0, a web-based tool, automatically identifies stressor-event and event-event links from the literature. The new version integrates additional data sources, annotates events with toxicology databases, and offers interactive network visualisation. These enhancements support integrative toxicology, as demonstrated in a case study on radon exposure.

AOP-helpFinder v3.0 is available at https://aop-helpfinder-v3.u-paris-sciences.fr.