Validation of a diffusion-based single droplet drying model for encapsulation of a viral-vectored vaccine using an acoustic levitator

Abstract

Development of thermally stable spray dried viral-vectored vaccine powders is dependent on the selection of a proper excipient or excipient blend for encapsulation, which can be a time and resource intensive process. In this work, a diffusion-based droplet drying model was developed to compute droplet drying time, size, and component distribution. The model predictions were validated using an acoustic levitator to dry droplets containing protein-coated or fluorescently labelled silica nanoparticles (as adenoviral vector analogues) and a range of excipient blends. Surface morphology of the dried particles was characterized by atomic force microscopy and the distribution of silica nanoparticles was quantified by confocal microscopy. The modelled distributions of adenovirus agreed with the microscopy results for three mannitol/dextran excipient blends with varying molecular weight dextrans, verifying the equations and assumptions of the model. Viral vector activity data for adenovirus in a range of (poly)saccharide/sugar alcohol formulations were also compared to the model outputs, suggesting that viral activity decreases when the model predicts increasing adenovirus concentrations near the air-solid interface. Using a validated model with excipient property inputs that are readily available in the literature can facilitate the development of viral-vectored vaccines by identifying promising excipients without the need for experimentation.