Modeling the long-term 2-8 °C stability profiles of a live, rotavirus vaccine candidate (RV3-BB) in various liquid formulations via extrapolations of real-time and accelerated stability data

To accelerate the formulation development of live-virus vaccine (LW) candidates, more rapid approaches to rank-order formulations and estimate their real-time storage stability losses are needed. In this case-study, we utilize new and previously described stability data of a live, rotavirus vaccine candidate (RV3-BB) in three different liquid formulations to model and compare predicted vs. experimental RV3-BB stability profiles. Linear-regression extrapolations of limited real-time (2-8 degrees C) stability data and Arrhenius modeling of accelerated (15, 25, 37 degrees C) stability data provided predictions of RV3-BB real-time stability profiles (2-8 degrees C, 24 months). Good correlations of modeled versus experimental stability data to rank-order the RV3-BB formulations were achieved by employing (1) a high-throughput RT-qPCR assay to measure viral titers, (2) additional assay replicates and stability time-points, and (3) a -80 degrees C control for each formulation to benchmark results at each stability time-point and temperature. Instead of accumulating two-year, 2-8 degrees C storage stability data, the same rank-ordering of the three RV3-BB formulations could have been achieved by modeling 3T, 25 degrees, 15 degrees (and 2-8 degrees C) stability data over 1, 3 and 12 months, respectively. The results of this case-study are discussed in the context of accelerating LW formulation development by expeditiously identifying stable formulations, estimating their shelf-lives, and determining vaccine vial monitoring (VVM) designations.

Automated summary

This study used linear regression and Arrhenius modeling to predict the real-time stability profiles of a live-virus vaccine. The predictions were validated using high-throughput assays and control groups, and the study concluded with a ranking of the vaccine formulations.