A Comparative Analysis of Clinical Stage 3 COVID-19 Vaccines using Knowledge Representation

  1. Javier Burgos-Salcedo

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Abstract

The emergence of a novel SARS-CoV-2 coronavirus at the end of 2019 and its accelerated spread worldwide to become a pandemic has had, from the medical biotechnology point of view, an unprecedented global response, to the point that there are currently 176 vaccine candidates in preclinical stage, 66 in clinical stage, of which 19 are in phase 3, and 5 of these are massively applied worldwide. The purpose of the present work is to elaborate a hierarchical landscape of the current status of phase 3 vaccines, taking into account their attributes of technological platform, safety and efficacy. The methodology used was that of conceptual knowledge representation, resulting in, firstly, an appropriate classification of stage 3 vaccines, The Conceptual Lattice for COVID-19 vaccines, constructed according to how they relate to each other with respect to the set of their attributes. Secondly, the approach used allows proposing rational strategies for the design of heterologous vaccination schemes, which are urgently needed to control the pandemic.

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    SciScore for 10.1101/2021.03.07.21253082: (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 10.1101/2021.03.07.21253082v1 on medRxiv