Statistical Methods to Leverage Immunologic Biomarkers and Complex Molecular Testing Data for Respiratory Diseases Vaccines Development

/Abstract Vaccine efficacy (VE) trials are the gold standard to determine the VE, relative VE, and VE durability. In addition, VE trials generate rich data for characterizing and comparing vaccine-induced immune responses and correlating immune responses to the clinical outcome. An immune correlate of risk (CoR) is a biomarker predicting clinical endpoint risk within a single treatment arm, while a correlate of protection (CoP) builds on a CoR to reliably predict VE or relative VE. Established CoR/CoP analyses have deepened our understand- ing of the causal mechanism through which vaccine works and accelerate vaccine approval. Our extensive experience emphasizes three key aspects of recent and ongoing VE trials: First, these trials target di- verse populations with varying baseline immunity from prior exposures or vaccinations. Second, emerging variants can evade natural or vaccine-induced immunity, prompting the inclusion of variant-specific inserts in updated vaccines. Third, advanced diagnostic technologies, such as multiplex PCR tests used in the COVE trial, enable simultaneous detection of multiple pathogens triggering illness visits. This project aims to develop analytical tools to address these challenges by leveraging rick immune biomarker and clinical endpoint data. First, we will develop an immunogenicity model that seeks to make the best prediction of an individual’s post-vaccination immune biomarker given their baseline immune biomarker from the same im- munoassay and key demographic variables, and we will use this model to unpack how VE is modulated by baseline immunity. Second, we will develop scalable and efficient statistical tests for a “conditional variant- invariant model” across different vaccine platforms and develop robust estimators of relative VE for updated vaccines compared to approved ones against variant pathogens. Lastly, recognizing that vaccines have a null effect on vaccine-mismatched respiratory disease endpoints, we will create a statistical framework to mitigate bias in VE durability and immune correlates analyses using well-defined off-target endpoints from novel multiplex PCR tests. Successful completion will equip investigators with innovative tools to extract more knowledge from VE trials. Project Number: 1R01AI192632-01 | Fiscal Year: 2025 | NIH Institute/Center: National Institute of Allergy and Infectious Diseases (NIAID) | Principal Investigator: Bo Zhang | Institution: FRED HUTCHINSON CANCER CENTER, SEATTLE, WA | Award Amount: $448,573 | Activity Code: R01 | Study Section: Analytics and Statistics for Population Research Panel B Study Section[ASPB] View on NIH RePORTER: https://reporter.nih.gov/project-details/1R01AI19263201