Using vaccine Immunostimulation/Immunodynamic modelling methods to inform vaccine dose decision-making.

ABSTRACT: 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-? secreting CD4+ T cells over time for novel TB vaccines H56 and H1 adjuvanted with IC31 in mice (1 dose groups (0.1-1.5 and 15??g H56?+?IC31), 45 mice) and humans (1 dose (50??g H56/H1?+?IC31), 18 humans). A two-compartment mathematical model, describing the dynamics of the post-vaccination IFN-? 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 0.8-8??g H56?+?IC31 in humans may be the most immunogenic. A 0.8-8??g 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.

SUBMITTER: Rhodes SJ 

PROVIDER: S-EPMC6141590 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature