Immunostimulatory/Immunodynamic model of mRNA-1273 to guide pediatric vaccine dose selection

Abstract

COVID-19 vaccines, including mRNA-1273, have been rapidly developed and deployed. Establishing the optimal dose is crucial for developing a safe and effective vaccine. Modeling and simulation have the potential to play a key role in guiding the selection and development of the vaccine dose. In this context, we have developed an immunostimulatory/immunodynamic (IS/ID) model to quantitatively characterize the neutralizing antibody titers elicited by mRNA-1273 obtained from three clinical studies. The developed model was used to predict the optimal vaccine dose for future pediatric trials. A 25-μg primary vaccine series was predicted to meet non-inferiority criteria in young children (aged 2–5 years) and infants (aged 6–23 months). The geometric mean titers and geometric mean ratios for this dose level predicted using the IS/ID model a priori matched those observed in the pediatric clinical study. These findings demonstrate that IS/ID models represent a novel approach to guide data-driven clinical dose selection of vaccines.