An OpenData portal to share COVID-19 drug repurposing data in real time

  1. Kyle R. Brimacombe
  2. Tongan Zhao
  3. Richard T. Eastman
  4. Xin Hu
  5. Ke Wang
  6. Mark Backus
  7. Bolormaa Baljinnyam
  8. Catherine Z. Chen
  9. Lu Chen
  10. Tara Eicher
  11. Marc Ferrer
  12. Ying Fu
  13. Kirill Gorshkov
  14. Hui Guo
  15. Quinlin M. Hanson
  16. Zina Itkin
  17. Stephen C. Kales
  18. Carleen Klumpp-Thomas
  19. Emily M. Lee
  20. Sam Michael
  21. Tim Mierzwa
  22. Andrew Patt
  23. Manisha Pradhan
  24. Alex Renn
  25. Paul Shinn
  26. Jonathan H. Shrimp
  27. Amit Viraktamath
  28. Kelli M. Wilson
  29. Miao Xu
  30. Alexey V. Zakharov
  31. Wei Zhu
  32. Wei Zheng
  33. Anton Simeonov
  34. Ewy A. Mathé
  35. Donald C. Lo
  36. Matthew D. Hall
  37. Min Shen

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

The National Center for Advancing Translational Sciences (NCATS) has developed an online open science data portal for its COVID-19 drug repurposing campaign – named OpenData – with the goal of making data across a range of SARS-CoV-2 related assays available in real-time. The assays developed cover a wide spectrum of the SARS-CoV-2 life cycle, including both viral and human (host) targets. In total, over 10,000 compounds are being tested in full concentration-response ranges from across multiple annotated small molecule libraries, including approved drug, repurposing candidates and experimental therapeutics designed to modulate a wide range of cellular targets. The goal is to support research scientists, clinical investigators and public health officials through open data sharing and analysis tools to expedite the development of SARS-CoV-2 interventions, and to prioritize promising compounds and repurposed drugs for further development in treating COVID-19.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.06.04.135046: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.06.04.135046v1 on bioRxiv