Abstract
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.
Highlights
Vaccines are administered to a large population of healthy individuals including children and infants
The lung showed the clearest clustering between the whole virion inactivated influenza vaccine and split influenza vaccine compared to the spleen, Modeling for influenza vaccines and adjuvants profile for safety prediction liver, and blood
To assess vaccine safety and quality in this study, we established a vaccine safety profiling and prediction system using biomarker gene expression profiles identified by ordinal logistic regression analysis as the best predictors
Summary
Vaccines are administered to a large population of healthy individuals including children and infants. Advanced imaging and omics technologies (e.g., genomics, proteomics, and metabolomics) have been applied in toxicological analyses with robotized testing platforms that enable the toxicities of large numbers of substances to be tested in animal models and cell lines or with in silico computational methodologies using high-throughput screening. These techniques have shortened the testing process period and enabled determination of how chemicals interact with biological systems in vivo. It remains difficult to integrate advanced omics technologies into preclinical and post-licensure tests to evaluate vaccine safety
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