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Systematic Organization of COVID-19 Data Supported by the Adverse Outcome Pathway Framework

Adverse Outcome Pathways (AOP) provide structured frameworks for the systematic organization of research data and knowledge. The AOP framework follows a set of key principles that allow for broad application across diverse disciplines related to human health, including toxicology, pharmacology, viro...

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Detalles Bibliográficos
Autores principales: Nymark, Penny, Sachana, Magdalini, Leite, Sofia Batista, Sund, Jukka, Krebs, Catharine E., Sullivan, Kristie, Edwards, Stephen, Viviani, Laura, Willett, Catherine, Landesmann, Brigitte, Wittwehr, Clemens
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8170012/
https://www.ncbi.nlm.nih.gov/pubmed/34095051
http://dx.doi.org/10.3389/fpubh.2021.638605
Descripción
Sumario:Adverse Outcome Pathways (AOP) provide structured frameworks for the systematic organization of research data and knowledge. The AOP framework follows a set of key principles that allow for broad application across diverse disciplines related to human health, including toxicology, pharmacology, virology and medical research. The COVID-19 pandemic engages a great number of scientists world-wide and data is increasing with exponential speed. Diligent data management strategies are employed but approaches for systematically organizing the data-derived information and knowledge are lacking. We believe AOPs can play an important role in improving interpretation and efficient application of scientific understanding of COVID-19. Here, we outline a newly initiated effort, the CIAO project (https://www.ciao-covid.net/), to streamline collaboration between scientists across the world toward development of AOPs for COVID-19, and describe the overarching aims of the effort, as well as the expected outcomes and research support that they will provide.