AOP4EUpest

AOP4EUpest extracts and links pesticide–biological event co-occurrences to Adverse Outcome Pathways (AOPs) to support mechanistic assessment of pesticide-induced health effects.


Key Features:

  • Annotated Database: An annotated repository of pesticide-associated biological events linked to AOP-Wiki entries.
  • Integration with Scientific Literature: Uses the AI-based AOP-helpFinder to identify co-occurrences between specific pesticides and biological events in PubMed abstracts.
  • Structured Pathway Mapping: Organizes and links molecular initiating events (MIEs), key events (KEs), and adverse outcomes (AOs) to represent mechanistic pathways.
  • Support for Regulatory Assessment: Facilitates identification of biomarkers and prioritization of pesticides for further investigation based on mechanistic links.
  • Facilitation of New Studies: Generates mechanistic hypotheses to guide epidemiological and experimental studies on pesticide health impacts.

Scientific Applications:

  • Health Risk Assessment: Maps mechanistic pathways to support assessment of long-term risks including neurodevelopmental disorders, carcinogenicity, and endocrine disruption leading to reproductive and metabolic disorders.
  • Research and Development: Identifies knowledge gaps and mechanistic questions to inform targeted experimental and epidemiological study design.
  • Policy Making: Provides mechanistic evidence to inform regulatory prioritization and policy decisions regarding pesticides.

Methodology:

AOP4EUpest applies the AI-based AOP-helpFinder to mine PubMed abstracts for pesticide–biological event co-occurrences, extracts relevant data, and maps those events to AOP-Wiki entries to link MIEs, KEs, and AOs.

Topics

Details

Tool Type:
web application
Added:
1/18/2021
Last Updated:
1/23/2021

Operations

Publications

Jornod F, Rugard M, Tamisier L, Coumoul X, Andersen HR, Barouki R, Audouze K. AOP4EUpest: mapping of pesticides in adverse outcome pathways using a text mining tool. Bioinformatics. 2020;36(15):4379-4381. doi:10.1093/bioinformatics/btaa545. PMID:32467965. PMCID:PMC7520043.

PMID: 32467965
PMCID: PMC7520043
Funding: - European Union’s Horizon 2020: 733032, HBM4EU