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

• Published in: Environment international Vol. 177; p. 108017
• Main Authors: Jaylet, Thomas, Coustillet, Thibaut, Jornod, Florence, Margaritte-Jeannin, Patricia, Audouze, Karine
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Ltd 01.07.2023; Elsevier
• Subjects: Adverse outcome pathways; AOP; AOP-helpFinder; Artificial intelligence; Computer Science; environment; Life Sciences; prioritization; Text mining; Toxicology; weight-of-evidence; Text mining; AOP-helpFinder; AOP; Toxicology; Artificial intelligence; Adverse outcome pathways; AOP; AOP-helpFinder; Adverse outcome pathways; Artificial intelligence; Text mining; Toxicology
• ISSN: 0160-4120; 1873-6750; 1873-6750
• DOI: 10.1016/j.envint.2023.108017

•Adverse outcome pathways represent structured knowledge of toxicity.•Toxicity information are very dispersed.•Artificial intelligence tools help to identify and compile toxicity knowledge.•AOP-helpFinder support the weight of evidence approach. 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/.