Artificial intelligence (AI)-based predictive modeling of the host microbiome to improve vaccine effectiveness
Abstract
The overall objective of these studies is to develop AI/ML-based models to guide rational modification of the host microbiome to improve vaccine efficacy. While we propose to perform these studies using a prototype viral pathogen, Venezuelan Equine Encephalitis Virus (VEEV), the outcomes of this study will have broad spectrum applications that can be translated to multiple bacterial and viral pathogens. Our approach is unique in that it takes advantage of a murine model system with a simplified microbiome that will be amenable both to in silico model building and experimental manipulation, including the ability to control microbiome composition. Importantly, the animals colonized with the “defined microbiome” retain normal immune system development and function, hence data will be generated from a biologically-relevant experimental model. By iterating between experiments with AI/ML modeling we expect to produce increasingly accurate models that predict host immune responses from more highly complex microbiome data.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jun 14, 2022
- Source ID
- HDTRA12110015
Entities
People
- Gregory J. Phillips
Organizations
- Defense Threat Reduction Agency
- Iowa State University