Preprint
Communication

This version is not peer-reviewed.

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

A peer-reviewed article of this preprint also exists.

Submitted:

26 January 2021

Posted:

27 January 2021

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Abstract
Adverse Outcome Pathways (AOP) provide structured frameworks for 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 to streamline collaboration between scientists across the world towards 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.
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Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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