Virtual Prototyping of Wet Granulation processes: Design and Optimisation via Multiscale Modelling and Rapid Prototyping

Wet granulation processes are essential in various industries, such as pharmaceuticals, where they play a critical role in enhancing the flowability, compressibility, and homogeneity of powder blends -- properties essential for high-quality manufacturing. The (bio-)pharmaceutical industry is currently changing paradigms from traditional batch processing to continuous manufacturing, driven by the need for increased efficiency, flexibility, and product consistency. However, process optimisation relies heavily on empirical adjustments and time-consuming experimental prototyping, which can be costly and inefficient. This doctoral thesis presents a comprehensive study on experiments and modelling of wet granulation processes. We aim to advance the field by developing a comprehensive multiscale modelling framework that combines the discrete particle method (DPM), population balance (PB) models, and rapid prototyping, to optimise and predict wet granulation process behaviour, enabling virtual prototyping. The study highlights the significance of geometry and formulation dependencies on wet granulation performance, identifies the limitations of existing models that rely on empirical adjustments and assumptions, and proposes the quadrature method of moments to model wet granulation processes. Finally, MercuryPBM is introduced, an open-source software for PB modelling of granular applications with distributed properties, which is designed to facilitate virtual prototyping of wet granulation processes. This research not only contributes to a deeper understanding of wet granulation, but also provides a valuable tool for industrial applications, paving the way for more efficient and cost-effective wet granulation processes by virtual prototyping.