Comparative Computational Modeling of Immune Responses to Vaccines.
Abstract
The goal of this project is to assess the ability of computational immunological methods as predictors of the multifaceted immune responses to vaccines by humans and by animal models. Computer models which accurately predict immune responses and which can bridge both animal and human responses can facilitate and accelerate vaccine design. This can be a particular advantage for development of vaccines to WMD agents that depend on the Animal Rule. Considerable time and cost savings, as well as improved safety and efficacy, can be achieved if more dependence can be placed on reliable computational immunologic modeling of vaccines. A growing database of immunological metrics and sequencing technology combined with considerable advances in computational tools now enable computational predictions to be made across a broad range of human immunogenetics, whereas a limited number of animal trials may not predict all outcomes in a diverse human population. In some cases, no animal model is available that accurately represents pathogenesis or the immune responses in humans, limiting their utility as predictors of risk. To accomplish the goal of this project, we will prepare computational predictions of outcomes of vaccination, and then conduct a detailed study of actual temporal and epitope specific outcomes of vaccination with FDA approved vaccines in human volunteers and in mice. This will determine if the computational analysis can be applied in development of the novel vaccines that may be needed to meet global and WMD threats
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 23, 2018
- Source ID
- HDTRA11710052
Entities
People
- Robert Bremel
Organizations
- Defense Threat Reduction Agency
- ioGenetics (United States)