Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/38448
Appears in Collections:Computing Science and Mathematics Journal Articles
Peer Review Status: Refereed
Title: The case for model-informed vaccine development
Author(s): PF Bai, Jane
Beigmohammadi, Fatemeh
Craig, Morgan
Dalton, Mackenzie
Desikan, Rajat
Easlick, Terry
Gazeau, Sonia
Heffernan, Jane
Kirpichnikova, Anna
Padmanabhan, Pranesh
Sachs, Jeffrey R
Sher, Anna
Skibinski, David
Smith, Amber M
Contact Email: sam.dixon@stir.ac.uk
Keywords: Model-informed vaccine development
MIVD
Quantitative systems pharmacology/toxicology
QSP/T
Mathematical models
Issue Date: 24-Oct-2026
Date Deposited: 8-Oct-2026
Citation: PF Bai J, Beigmohammadi F, Craig M, Dalton M, Desikan R, Easlick T, Gazeau S, Heffernan J, Kirpichnikova A, Padmanabhan P, Sachs JR, Sher A, Skibinski D & Smith AM (2026) The case for model-informed vaccine development. <i>Vaccine</i>, 92, Art. No.: 128780. https://doi.org/10.1016/j.vaccine.2026.128780
Abstract: This perspective paper illustrates how model-informed vaccine development (MIVD) impacts vaccine discovery and development decisions, saving time and resources. It discusses the benefits of mechanistic and other mathematical models within MIVD. We outline key applications, opportunities, challenges, and future steps for MIVD as a call for the continued integration of mathematical modelling during vaccine development.
DOI Link: 10.1016/j.vaccine.2026.128780
Rights: PF Bai, J., Beigmohammadi, F., Craig, M., Dalton, M., Desikan, R., Easlick, T., Gazeau, S., Heffernan, J., Kirpichnikova, A., Padmanabhan, P., Sachs, J. R., Sher, A., Skibinski, D., & Smith, A. M. (2026). The case for model-informed vaccine development. Vaccine, 92, 128780. DOI: https://doi.org/10.1016/j.vaccine.2026.128780 © 2026, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Licence URL(s): http://creativecommons.org/licenses/by-nc-nd/4.0/

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