The case for model-informed vaccine development
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.
Authors
- Morgan Craig (ORCID: https://orcid.org/0000-0003-4852-4770)
- Jeffrey R. Sachs (ORCID: https://orcid.org/0000-0001-5725-558X)
- Terry Easlick (ORCID: https://orcid.org/0000-0002-2735-0284)
- Rajat Desikan (ORCID: https://orcid.org/0000-0002-0785-8187)
- Pranesh Padmanabhan (ORCID: https://orcid.org/0000-0001-5569-8731)
- Jane P. F. Bai
- Amber M. Smith
- Anna Kirpichnikova
- Jane Heffernan
- Sonia Gazeau
- Mackenzie Dalton
- Anna Sher
- David Skibinski
- Fatemeh Beigmohammadi
Institutions
- University of Stirling (GB)
- Merck & Co., Inc., Rahway, NJ, USA (United States) (US)
- Center for Drug Evaluation and Research (US)
- University of Tennessee Health Science Center (US)
- The University of Queensland (AU)
- Clarkson University (US)
- York University (CA)
- Park Centre for Mental Health (AU)
- Age UK (GB)
- Centre Hospitalier Universitaire Sainte-Justine (CA)
- Université de Montréal (CA)
Publication Details
- Journal
- Vaccine
- Published
- 2026-09-21
- DOI
- https://doi.org/10.1016/j.vaccine.2026.128780
- Primary Topic
- vaccines and immunoinformatics approaches
- Type
- article
- Field-Weighted Citation Impact
- 0.00