TY - JOUR
T1 - Application of Modeling Approaches to Explore Vaccine Adjuvant Mode-of-Action
AU - Buckley, Paul R.
AU - Alden, Kieran
AU - Coccia, Margherita
AU - Chalon, Aurélie
AU - Collignon, Catherine
AU - Temmerman, Stéphane T.
AU - Didierlaurent, Arnaud M.
AU - van der Most, Robbert
AU - Timmis, Jon
AU - Andersen, Claus A.
AU - Coles, Mark C.
N1 - Funding Information:
The authors thank Isabelle Carletti for support regarding the data and analysis, Walthere Dewé, Tej Patel, Nabila Amanchar, Caroline Hervé (GSK), and Jason Cosgrove (Curie) for fruitful discussions. This work was partially funded by GlaxoSmithKline Biologicals SA. Shingrix is a trade marks of the GSK group of companies. Funding. Research was funded through a PHD studentship award from BBSRC.
Publisher Copyright:
© Copyright © 2019 Buckley, Alden, Coccia, Chalon, Collignon, Temmerman, Didierlaurent, van der Most, Timmis, Andersen and Coles.
PY - 2019/9/12
Y1 - 2019/9/12
N2 - 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.
AB - 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.
KW - adjuvants
KW - AS01
KW - computational biology
KW - mathematical modeling
KW - mechanistic modeling
KW - systems biology
KW - vaccines
KW - Humans
KW - Saponins/pharmacology
KW - Vaccines
KW - Adjuvants, Immunologic/pharmacology
KW - Animals
KW - Models, Biological
KW - Lipid A/analogs & derivatives
KW - Drug Combinations
UR - http://www.scopus.com/inward/record.url?scp=85072768380&partnerID=8YFLogxK
U2 - 10.3389/fimmu.2019.02150
DO - 10.3389/fimmu.2019.02150
M3 - Article
C2 - 31572370
AN - SCOPUS:85072768380
SN - 1664-3224
VL - 10
JO - Frontiers in Immunology
JF - Frontiers in Immunology
M1 - 2150
ER -