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Safety Challenges Facing Next Generation Vaccines and the Role for Biomarkers

  • S. Sohail Ahmed
  • Ernesto Oviedo-Orta
  • Jeffrey Ulmer
Chapter

Abstract

This chapter will provide the reader with a framework of how vaccine safety is currently assessed and will review the strengths and limitations of tools utilized preclinically to determine the safety of new vaccines (with a focus on adjuvanted vaccines). The specific safety challenge that has faced vaccines recently and will undoubtedly face the next generation vaccines is that of the infrequent and delayed adverse event of autoimmune disease which shares ingredients of the immune response that are being modulated by next generation vaccines (e.g., T-cells, B-cells, tolerance, TLR, inflammasome). Therefore, the following sections will provide an introduction to the challenges facing preclinical and clinical studies utilizing novel adjuvants. Finally, this chapter will conclude with a “translational” section related to biomarkers and their potential to predict outcome in subjects receiving vaccination. Examples of vaccine-dependent signatures with the potential to predict subject responses, such as immunogenicity, efficacy and safety, as well as subject-specific signatures (e.g., genetic makeup) that may modulate these responses will be provided to emphasize the dual-edge of how increasing the immune response may be favorable for efficacy but potentially detrimental for safety. This is one of the key challenges for the next generation of vaccines and the identification of reliable biomarkers that have the potential to overcome this challenge. The chapter will thus conclude with the huge quantity of information that is likely to result from biomarker research and what will need to be addressed to enable biomarkers to fulfill their promise.

Keywords

Yellow Fever Measle Vaccine System Biology Approach Vaccine Safety Adjuvanted Vaccine 
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 New York 2013

Authors and Affiliations

  • S. Sohail Ahmed
    • 1
  • Ernesto Oviedo-Orta
    • 1
  • Jeffrey Ulmer
    • 1
  1. 1.Vaccines Research, Novartis Vaccines & DiagnosticsSienaItaly

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