Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2019 Mar 21:465:51-55.
doi: 10.1016/j.jtbi.2019.01.017. Epub 2019 Jan 10.

Dose finding for new vaccines: The role for immunostimulation/immunodynamic modelling

Sophie J Rhodes  1 , Gwenan M Knight  2 , Denise E Kirschner  3 , Richard G White  2 , Thomas G Evans  4
Affiliations

Dose finding for new vaccines: The role for immunostimulation/immunodynamic modelling

Sophie J Rhodes et al. J Theor Biol. .

Abstract

Current methods to optimize vaccine dose are purely empirically based, whereas in the drug development field, dosing determinations use far more advanced quantitative methodology to accelerate decision-making. Applying these established methods in the field of vaccine development may reduce the currently large clinical trial sample sizes, long time frames, high costs, and ultimately have a better potential to save lives. We propose the field of immunostimulation/immunodynamic (IS/ID) modelling, which aims to translate mathematical frameworks used for drug dosing towards optimizing vaccine dose decision-making. Analogous to Pharmacokinetic/Pharmacodynamic (PK/PD) modelling, the mathematical description of drug distribution (PK) and effect (PD) in host, IS/ID modelling approaches apply mathematical models to describe the underlying mechanisms by which the immune response is stimulated by vaccination (IS) and the resulting measured immune response dynamics (ID). To move IS/ID modelling forward, existing datasets and further data on vaccine allometry and dose-dependent dynamics need to be generated and collate, requiring a collaborative environment with input from academia, industry, regulators, governmental and non-governmental agencies to share modelling expertise, and connect modellers to vaccine data.

Keywords: Immune response; Mathematical modelling; Vaccine development; Vaccine dose optimization.

PubMed Disclaimer

Figures

Fig. 1.
Fig. 1.
Schema depicting the steps required to incorporate immunostimulation (IS) /immunodynamic (ID) modeling into vaccine development.
See this image and copyright information in PMC

References

    1. Aagaard C, Hoang T, Dietrich J, Cardona PJ, Izzo A, Dolganov G, Andersen P, 2011. A multistage tuberculosis vaccine that confers efficient protection before and after exposure. Nat. Med. 17 (2), 189–194. doi:10.1038/nm.2285. - DOI - PubMed
    1. Aagaard C, Hoang TT, Izzo A, Billeskov R, Troudt J, Arnett K, Dietrich J, 2009. Protection and polyfunctional T cells induced by Ag85B-TB10.4/IC31 against Mycobacterium tuberculosis is highly dependent on the antigen dose. PLoS One 4 (6), e5930. doi:10.1371/journal.pone.0005930. - DOI - PMC - PubMed
    1. Aarons L, Ogungbenro K, 2010. Optimal design of pharmacokinetic studies. Basic Clin. Pharmacol. Toxicol. 106 (3), 250–255. doi:10.1111/j.1742-7843.2009.00533.x. - DOI - PubMed
    1. Baldi E, Bucherelli C, 2005. The inverted “u-shaped” dose-effect relationships in learning and memory: modulation of arousal and consolidation. Nonlinearity Biol. Toxicol. Med. 3 (1), 9–21. doi:10.2201/nonlin.003.01.002. - DOI - PMC - PubMed
    1. Billeskov R, Lindenstrom T, Woodworth J, Vilaplana C, Cardona PJ, Cassidy JP, Andersen P, 2017. High antigen dose is detrimental to post-exposure vaccine protection against tuberculosis. Front Immunol. 8, 1973. doi:10.3389/fimmu.2017.01973. - DOI - PMC - PubMed

Publication types