Cooperative efforts on developing vaccines and therapies for COVID-19 Cooperative efforts for COVID-19

  1. Fernanda Gisele Basso
  2. Alex Fabianne de Paulo
  3. Geciane Silveira Porto
  4. Cristiano Gonçalves Pereira

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Abstract

Health organizations have always sought partnership to join competencies in innovation, even with fierce competition in this sector. In this pandemic moment it is relevant to observe how organizations behave to seek quick and safe answers. The present research analyzes how the cooperation networks were set off considering the clinical trials on therapies and vaccines that were developed specifically to treat or prevent COVID-19. Social Network Analysis technique was used to build cooperation networks and apply metrics that characterize these connections. There was an evaluation of statistics of Strength of cooperation and Unilateral dependence of cooperation that identify the cooperation strength between two organizations, and the dependence of this relations. A total of 415 clinical trial were identified, of which 42% are in cooperation. From organizations that have partnership, firms are the first, followed by universities. We extracted the main categories that concentrate 74% of partnerships in the trials of antibody, and vaccine. Several organizations cooperate in multiple categories of trials, evidencing the efforts to focus on different strategies to treat the disease. We found high strength of cooperation and an assimetryc dependency between partners, which can be assigned to specialized models of partnership and it occurs in competitive enviroments like this pandemic moment. Cooperation were not limited to geographical proximity and the advent of Chinese players can represent a new change in the biotechnological development axis. Finally, the challenge of finding therapeutic or immunological solutions for COVID-19 demonstrates a clear composition of cooperation groups that complement their skills to manage organizational strategies to beat the pandemic. In this new paradigm, there can be partnerships not only in clinical trial but also in pre-competitive technologies development. This experience is expected to change the way of organizations define their R&D strategies and start to adopt more a collaborative innovation model.

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  1. ScreenIT

    SciScore for 10.1101/2020.09.06.282145: (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
    CTs with 2 or more organizations were label standardized and analysed using Gephi for graphical representation and calculation of the network metrics.
    Gephi
    suggested: (Gephi, RRID:SCR_004293)

    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:
    This study has some limitations due to the availability of information. There is a difference between the quality of information provided by universities and industries. These variations can be perceived according to the geographical locations of organizations and clinical studies. In addition, there is the possibility that some groups may not fully report their status for competitive reasons or overreport to attract more funding. In future research, it is intended to analyze more broadly the process of technological development for drugs and vaccines that will result in disruptive technologies protected by patents, complementing the understanding of different aspects of cooperation in this new context such as the current pandemic.

    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.
    • No funding statement was detected.
    • 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 10.1101/2020.09.06.282145v1 on bioRxiv