Covid19db – An online database of trials of medicinal products to prevent or treat COVID-19, with a specific focus on drug repurposing

  1. Pan Pantziarka
  2. Liese Vandeborne
  3. Lydie Meheus
  4. Gauthier Bouche

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Abstract

Background

The global pandemic caused by SARS-CoV-2 virus has prompted an unprecedented international effort to seek medicines for prevention and treatment of infection. Drug repurposing has played a key part in this response. The rapid increase in trial activity has raised questions about efficiency and lack of coordination. Our objective was to develop a user-friendly, open access database to monitor and rapidly identify trials of medicinal products.

Methods

Using the US clinicaltrials.gov (NCT) registry, the EU Clinical Trials Register (EUCTR) and the WHO International Clinical Trials Registry Platform (WHO ICTRP), we identified all COVID-19 trials of medicinal products. Trials that were out of scope and duplicates were excluded. A manual encoding was performed to ascertain key information (e.g. trial aim, type of intervention etc). The database, Covid19db, is published online at: http://www.redo-project.org/covid19db/ .

Results

Descriptive statistics of the database from April 4th 2020 through to August 18th show an increase from 186 to 1618 trials, or an average of 10.5 new trials registered per day. Over this period, the proportion of trials including a repurposing arm decreased slightly (from a maximum of 75% to 64% at the end of the covered period) as did the proportion of trials aiming to prevent infection (from a maximum of 16% to 13%). The most popular trial intervention is hydroxychloroquine (212 trials), followed by azithromycin (64 trials), tocilizumab, favipiravir and chloroquine (145 trials). Total planned enrolment is 1064556 participants as of 18 th August 2020.

Conclusions

we have developed an open access and regularly updated tool to monitor clinical trials of medicinal products to prevent or treat infection by SARS-CoV-2 globally. Our analysis shows a high number of ‘me-too’ trials, in particular for some repurposed drugs, such as hydroxychloroquine, azithromycin and tocilizumab, substantiating calls for better coordination and better use of trial resources.

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  1. ScreenIT

    SciScore for 10.1101/2020.05.27.20114371: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    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: We detected the following sentences addressing limitations in the study:
    Our tool has some strengths and weaknesses. It is publicly available and the data are easily downloadable. Since we include the WHO ICTRP data, the EUCTR and clinicaltrials.gov, it provides global coverage of clinical trials activity of medicinal products against COVID-19. Our methodology also allows for rapid update as new trials are registered. Manual assessment of each trial has both advantages and shortcomings. Thanks to this manual assessment we have been able to eliminate duplicates and non-interventional trials, and to characterize interventions truly tested in trials (and not listed because of their use in the control group). However, the manual assessment may also lead to rare, though possible, coding errors. In the case of duplicate registrations only one record is used as the reference record and the duplicate entries discarded, therefore the counts for the individual registries, as shown in Figure 2, may not accurately reflect the true number of COVID-19 trials included in them. Our work is however limited by the quality of the information included in the different registries. Common issues include unclear data regarding specific interventions, missing or incomplete data in key fields such as planned enrolment or number and location of trial sites, duplicate entries for some trials within a single registry. Data analysis is also complicated by the lack of API access to some registries – using web spidering technology is inherently brittle and inferior to full prog...

    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

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  2. Version published to 10.1101/2020.05.27.20114371 on medRxiv