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Modeling for influenza vaccines and adjuvants profile for safety prediction system using gene expression profiling and statistical tools.

  • Sasaki, Eita1
  • Momose, Haruka1
  • Hiradate, Yuki1
  • Furuhata, Keiko1
  • Takai, Mamiko1
  • Asanuma, Hideki2
  • Ishii, Ken J3, 4
  • Mizukami, Takuo1
  • Hamaguchi, Isao1
  • 1 Department of Safety Research on Blood and Biological Products, National Institute of Infectious Diseases, Musashi-Murayama, Tokyo, Japan. , (Japan)
  • 2 Influenza Virus Research Center, National Institute of Infectious Diseases, Musashi-Murayama, Tokyo, Japan. , (Japan)
  • 3 Laboratory of Adjuvant Innovation, National Institutes of Biomedical Innovation, Health and Nutrition, Ibaraki, Osaka, Japan. , (Japan)
  • 4 Laboratory of Vaccine Science, WPI Immunology Frontier Research Center, Osaka University, Suita, Osaka, Japan. , (Japan)
Published Article
Public Library of Science
Publication Date
Jan 01, 2018
DOI: 10.1371/journal.pone.0191896
PMID: 29408882


Historically, vaccine safety assessments have been conducted by animal testing (e.g., quality control tests and adjuvant development). However, classical evaluation methods do not provide sufficient information to make treatment decisions. We previously identified biomarker genes as novel safety markers. Here, we developed a practical safety assessment system used to evaluate the intramuscular, intraperitoneal, and nasal inoculation routes to provide robust and comprehensive safety data. Influenza vaccines were used as model vaccines. A toxicity reference vaccine (RE) and poly I:C-adjuvanted hemagglutinin split vaccine were used as toxicity controls, while a non-adjuvanted hemagglutinin split vaccine and AddaVax (squalene-based oil-in-water nano-emulsion with a formulation similar to MF59)-adjuvanted hemagglutinin split vaccine were used as safety controls. Body weight changes, number of white blood cells, and lung biomarker gene expression profiles were determined in mice. In addition, vaccines were inoculated into mice by three different administration routes. Logistic regression analyses were carried out to determine the expression changes of each biomarker. The results showed that the regression equations clearly classified each vaccine according to its toxic potential and inoculation amount by biomarker expression levels. Interestingly, lung biomarker expression was nearly equivalent for the various inoculation routes. The results of the present safety evaluation were confirmed by the approximation rate for the toxicity control. This method may contribute to toxicity evaluation such as quality control tests and adjuvant development.

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