Immunoinformatics: The Next Step in Vaccine Design

  • Tobias Cohen
  • Lenny Moise
  • William Martin
  • Anne S. De Groot


T cells have come to be recognized as critical mediators of competent and lasting responses elicited by vaccines. This recognition catalyzed the development of computer-driven (immunoinformatics) methods for defining T-cell epitopes directly from protein sequences. Subsequently, investigations into the role of effector and regulatory T cells have leapfrogged directly from genome and protein sequences to the leading edge of immunology and vaccine research. Although immunoinformatics tools have been available for over a decade, recent technological advances have led to significant improvements in the tools, raising their level of accuracy and increasing their utility in the design of effective T-cell epitope-driven vaccines. Additional technical advances in the field of vaccine delivery and adjuvants have led to significant success at the preclinical level of vaccine design. These advances have the potential to reduce the lead time for vaccines to enter the clinic. Epitope-based vaccines have significant advantages in terms of their safety profile since they are composed of antigen specific sequences. The vaccine contains fewer cross-reactive epitopes than the whole pathogen would, which lowers regulatory hurdles and hastens approval by regulatory agencies. In this chapter, we review recent advances that will accelerate T-cell epitope-driven vaccine development, and provide three examples of successful preclinical epitope-driven vaccine studies: (1) a vaccine that eradicates Helicobacter pylori infection, (2) a candidate smallpox vaccine that affords protection against vaccinia, and (3) a vaccine against tularemia. Owing to recent improvements in vaccine design and delivery systems, now few obstacles remain in the path of a new generation of T-cell epitope-driven vaccines.


Infectious Bronchitis Virus Vaccine Design Major Histocompatability Complex Smallpox Vaccine Live Vaccine Strain 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Tobias Cohen
    • 1
  • Lenny Moise
    • 1
  • William Martin
    • 1
  • Anne S. De Groot
    • 1
  1. 1.Brown University, School of MedicineProvidenceUSA

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