Frontiers in Immunology (Sep 2019)

Application of Modeling Approaches to Explore Vaccine Adjuvant Mode-of-Action

  • Paul R. Buckley,
  • Paul R. Buckley,
  • Kieran Alden,
  • Margherita Coccia,
  • Aurélie Chalon,
  • Catherine Collignon,
  • Stéphane T. Temmerman,
  • Arnaud M. Didierlaurent,
  • Robbert van der Most,
  • Jon Timmis,
  • Jon Timmis,
  • Claus A. Andersen,
  • Mark C. Coles

DOI
https://doi.org/10.3389/fimmu.2019.02150
Journal volume & issue
Vol. 10

Abstract

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Novel adjuvant technologies have a key role in the development of next-generation vaccines, due to their capacity to modulate the duration, strength and quality of the immune response. The AS01 adjuvant is used in the malaria vaccine RTS,S/AS01 and in the licensed herpes-zoster vaccine (Shingrix) where the vaccine has proven its ability to generate protective responses with both robust humoral and T-cell responses. For many years, animal models have provided insights into adjuvant mode-of-action (MoA), generally through investigating individual genes or proteins. Furthermore, modeling and simulation techniques can be utilized to integrate a variety of different data types; ranging from serum biomarkers to large scale “omics” datasets. In this perspective we present a framework to create a holistic integration of pre-clinical datasets and immunological literature in order to develop an evidence-based hypothesis of AS01 adjuvant MoA, creating a unified view of multiple experiments. Furthermore, we highlight how holistic systems-knowledge can serve as a basis for the construction of models and simulations supporting exploration of key questions surrounding adjuvant MoA. Using the Systems-Biology-Graphical-Notation, a tool for graphical representation of biological processes, we have captured high-level cellular behaviors and interactions, and cytokine dynamics during the early immune response, which are substantiated by a series of diagrams detailing cellular dynamics. Through explicitly describing AS01 MoA we have built a consensus of understanding across multiple experiments, and so we present a framework to integrate modeling approaches into exploring adjuvant MoA, in order to guide experimental design, interpret results and inform rational design of vaccines.

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