Title: Dose finding for new vaccines: the role for immunostimulation/immunodynamic modelling,
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 PK/PD modelling, 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.