CoVPN Cross-Protocol Analyses

  • Funded by National Institutes of Health (NIH)
  • Total publications:0 publications

Grant number: 3UM1AI068635-16S3

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Key facts

  • Disease

    COVID-19
  • Start & end year

    2022
    2022
  • Known Financial Commitments (USD)

    $1,334,886
  • Funder

    National Institutes of Health (NIH)
  • Principal Investigator

    Peter Gilbert
  • Research Location

    United States of America
  • Lead Research Institution

    FRED HUTCHINSON CANCER RESEARCH CENTER
  • Research Priority Alignment

    N/A
  • Research Category

    Vaccines research, development and implementation

  • Research Subcategory

    N/A

  • Special Interest Tags

    N/A

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable

Abstract

Project Abstract This proposal outlines the scientific agenda for the COVID-19 Prevention Network (CoVPN) Vaccines Statistical and Data Management Center (SDMC) for implementation of cross-protocol work in support of COVID-19 phase 3 efficacy trials. With the global COVID-19 pandemic, we recognize a significant need for vaccines that modify COVID-19 in SARS-CoV-2 infected individuals. Addressing this gap, the HVTN SDMC has joined 4 other National Institute of Health (NIH) clinical trial networks to form the CoVPN, an enhanced network dedicated to developing globally effective vaccines for SARS-CoV-2. The innovation of the CoVPN SDMC and advantages to this work include the collective experience of our group- leader in statistical methods in vaccine evaluation, especially immune correlates assessment, and the long-standing relationships we have with the clinical and lab groups in the CoVPN lead Adapting and leveraging statistical methods for evaluating vaccines against other pathogens to SARS-CoV-2. E.g. causal inference methods for evaluating multiple types of formally defined correlates of protection including correlates of vaccine efficacy, mediators of vaccine efficacy, and stochastic-intervention effects on vaccine efficacy.