Population Data-Driven Formulation of a COVID-19 Therapeutic

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Abstract

This study is designed to utilize computer modeling of the US population through NHANES to reduce the need for preclinical formulation and toxicology studies of an Ebola anti-viral (BSN389) being repurposed for COVID-19, and to thereby speed the candidate therapeutic to the clinic.

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  1. SciScore for 10.1101/2020.07.24.20161547: (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

    Software and Algorithms
    SentencesResources
    The NHANES database can be analyzed to determine the distribution of exposures to a food ingredient, and preliminary human formulation experiments conducted at exposures less than those to which the US population is normally exposed through food.
    NHANES
    suggested: (NHANES, RRID:SCR_013201)
    Consumption data from individual dietary records, detailing food items ingested by each survey participant, were collated by computer in Matlab and used to generate estimates for the intake of BCD by the U.S. population as previously described (Lodder, 2017).
    Matlab
    suggested: (MATLAB, RRID:SCR_001622)

    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: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT00005154CompletedNational Health and Nutrition Examination Survey IV (NHANES …


    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.