%0 Journal Article
%T Using vaccine Immunostimulation/Immunodynamic modelling methods to inform vaccine dose decision-making
%J -
%D 2018
%R https://doi.org/10.1038/s41541-018-0075-3
%X Unlike drug dose optimisation, mathematical modelling has not been applied to vaccine dose finding. We applied a novel Immunostimulation/Immunodynamic mathematical modelling framework to translate multi-dose TB vaccine immune responses from mice, to predict most immunogenic dose in humans. Data were previously collected on IFN-¦Ã secreting CD4+ T cells over time for novel TB vaccines H56 and H1 adjuvanted with IC31 in mice (1 dose groups (0.1¨C1.5 and 15£¿¦Ìg H56£¿+£¿IC31), 45 mice) and humans (1 dose (50£¿¦Ìg H56/H1£¿+£¿IC31), 18 humans). A two-compartment mathematical model, describing the dynamics of the post-vaccination IFN-¦Ã T cell response, was fitted to mouse and human data, separately, using nonlinear mixed effects methods. We used these fitted models and a vaccine dose allometric scaling assumption, to predict the most immunogenic human dose. Based on the changes in model parameters by mouse H56£¿+£¿IC31 dose and by varying the H56 dose allometric scaling factor between mouse and humans, we established that, at a late time point (224 days) doses of 0.8¨C8£¿¦Ìg H56£¿+£¿IC31 in humans may be the most immunogenic. A 0.8¨C8£¿¦Ìg of H-series TB vaccines in humans, may be as, or more, immunogenic, as larger doses. The Immunostimulation/Immunodynamic mathematical modelling framework is a novel, and potentially revolutionary tool, to predict most immunogenic vaccine doses, and accelerate vaccine development
%U https://www.nature.com/articles/s41541-018-0075-3