Accelerating model-informed decisions for COVID-19 vaccine candidates using a model-based meta-analysis approach.

ABSTRACT:

Background

The COVID-19 pandemic has increased the need for innovative quantitative decision tools to support rapid development of safe and efficacious vaccines against SARS-CoV-2. To meet that need, we developed and applied a model-based meta-analysis (MBMA) approach integrating non-clinical and clinical immunogenicity and protection data.

Methods

A systematic literature review identified studies of vaccines against SARS-CoV-2 in rhesus macaques (RM) and humans. Summary-level data of 13 RM and 8 clinical trials were used in the analysis. A RM MBMA model was developed to quantify the relationship between serum neutralizing (SN) titres after vaccination and peak viral load (VL) post-challenge in RM. The translation of the RM MBMA model to a clinical protection model was then

SUBMITTER: Kandala B 

PROVIDER: S-EPMC9514977 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature