14:30
14:30 - "Borrowing through the evolving vaccine preclinical research plan: Prior elicitation in absence of recurrent designs or controls"
(joint work with Mario Becerra Contreras, Mathias Schmitz, Oluwafemi Daniel Olusoji, all GSK)
Borrowing through the evolving vaccine preclinical research plan: Prior elicitation in absence of recurrent designs or controls
Summary:
The preclinical research plan in vaccine development consists of a project-specific mixture of small sample size (n<10 per group) animal in-vivo experiments and human in-vitro experiments (often with 2 to 3 donors) aimed at identifying one vaccine candidate that demonstrates the best immunogenicity while generating some but limited reactogenicity. These experiments consist of discrete screening designs, dose response designs, challenge studies, and potency tests, just to name a few.
The vaccine candidate formulations evolve largely across the preclinical plan, making it challenging to borrow from previous studies. Additionally, positive controls do not exist in most of the vaccine projects, whereas negative controls are mostly invariant non-measurable responses (lower than the bioassay technical limit) and are discarded in all statistical models. These vaccine specificities make prior elicitation and Bayesian borrowing strategies quite challenging to implement in preclinical studies as compared to clinical phases.
Therefore, we have experimented with borrowing model coefficients rather than group locations and scales, of which we found limited echo in the literature. Using case studies, we will illustrate the borrowing of model effects such as the antigen dose slope or the interaction between vaccine components. Posterior distributions of these parameters from previous studies have been aggregated using meta-analytic-predictive priors and other methods. Sensitivity analysis of those borrowings on model predictions, decision making, and animal use reduction (aligned with GSK 3Rs commitment on animal studies) will be discussed.
Bio:
All authors are statisticians within the Vaccines Research and Translational Statistics team of GSK. They support the development of new vaccines from the first research stages until the vaccine projects are fully transferred to their clinical colleagues. Using Bayesian statistics, they explore disruptive ways to value the data collected and accelerate the development of new vaccines.
Teams:
https://teams.microsoft.com/meet/3848793947750?p=ihUxXPCvvHUmVDP1NH