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Why adverse outcome pathways need to be FAIR.

Authors
  • Wittwehr, Clemens1
  • Clerbaux, Laure-Alix1
  • Edwards, Stephen2
  • Angrish, Michelle3
  • Mortensen, Holly4
  • Carusi, Annamaria5
  • Gromelski, Maciej6
  • Lekka, Eftychia7
  • Virvilis, Vassilis7
  • Martens, Marvin8
  • Bonino da Silva Santos, Luiz Olavo9, 10
  • Nymark, Penny11
  • 1 European Commission, Joint Research Centre (JRC), Ispra, Italy. , (Italy)
  • 2 RTI International, Research Triangle Park, NC, USA.
  • 3 Center for Public Health and Environmental Assessment, Chemical & Pollutant Assessment Division, U.S. Environmental Protection Agency, Washington DC, USA.
  • 4 Center for Public Health and Environmental Assessment, Public Health and Integrated Toxicology Division, U.S. Environmental Protection Agency, Durham, NC, USA.
  • 5 Interchange Research, London, UK.
  • 6 Laboratory of Environmental Chemoinformatics, Faculty of Chemistry, University of Gdańsk, Gdańsk, Poland. , (Poland)
  • 7 Biovista, Athens, Greece. , (Greece)
  • 8 Department of Bioinformatics - BiGCaT, NUTRIM, Maastricht University, Maastricht, The Netherlands. , (Netherlands)
  • 9 GO FAIR Foundation, Leiden, the Netherlands. , (Netherlands)
  • 10 Services and Cybersecurity group, Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente - Enschede, The Netherlands. , (Netherlands)
  • 11 Karolinska Institutet, Institute of Environmental Medicine, Stockholm, Sweden. , (Sweden)
Type
Published Article
Journal
ALTEX
Publication Date
Jan 09, 2024
Volume
41
Issue
1
Pages
50–56
Identifiers
DOI: 10.14573/altex.2307131
PMID: 37528748
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

New approach methodologies (NAMs) can detect biological phenomena that occur before they add up to serious problems like cancer, infertility, death, and others. NAMs detect key events (KE) along well-proven and agreed adverse outcome pathways (AOP). If a substance tests positive in a NAM for an upstream KE, this signals an early warning that actual adversity might follow. However, what if the knowledge about these AOPs is a well-kept secret? And what if decision-makers find AOPs too exotic to apply in risk assessment? This is where FAIR comes in! FAIR stands for making information findable, accessible, interoperable and re-useable. It aims to increase availability, usefulness, and trustworthiness of data. Here, we show that by interpreting the FAIR principles beyond a purely technical level, AOPs can ring in a new era of 3Rs applicability ‒ by increasing their visibility and making their creation process more transparent and reproducible.

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