Comparative Computational Modeling of Immune Responses to Vaccines

Abstract

The project assessed the ability of a computational immunology platform as a predictor of multifaceted immune responses in humans and mice. An accurate computational predictor of immune responses in individuals of differing immunogenetics potentially enable the rapid development of vaccines for emerging pathogens with more confidence than depending on animal models, which do not always replicate human disease, nor the immune responses of a diverse human population. The project mapped epitopes in ten FDA approved vaccines and in SARS-CoV-2. B and T cell responses to SARS-CoV-2 were evaluated in convalescent human volunteers in comparison to computational predictions.

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Document Details

Document Type
Technical Report
Publication Date
Jun 21, 2021
Accession Number
AD1147754

Entities

People

  • Jack Gorski
  • Jane E. Homan
  • Robert D. Bremel
  • Weiguo Cui

Tags

DTIC Thesaurus Topics

  • Biological Factors
  • Cells
  • Chemistry
  • Databases
  • Immunomodulation
  • Infectious Diseases
  • Interferon
  • Lymphocytes
  • Medical Personnel
  • Microbiology
  • Microbiomes
  • Pathogenic Bacteria
  • Physical Properties
  • Proteins
  • Proteomics
  • Vaccines
  • Viruses

Fields of Study

  • Biology

Readers

  • Immunology
  • Infectious Disease/Epidemiology
  • Regression Analysis.

Technology Areas

  • Biotechnology