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

Front Public Health. 2021 May 19:9:638605. doi: 10.3389/fpubh.2021.638605. eCollection 2021.

Abstract

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.

Keywords: COVID-19; adverse outcome pathways; data integration; interdisciplinarity; mechanisms; systematic organization.

MeSH terms

  • Adverse Outcome Pathways*
  • Biomedical Research*
  • COVID-19*
  • Humans
  • Pandemics
  • SARS-CoV-2