In this study, a hybrid multi-scale model has been developed for a continuous fluid bed wet granulation process by dynamically coupling computational fluid dynamics (CFD) with a discrete element model (DEM) and population balance model (PBM). In this process, the granules are formed by spraying the liquid binder on the fluidized powder bed. The fluid flow field has been solved implementing CFD principles and the behavior of the solid particles has been modeled using DEM techniques whereas the change in particle size has been quantified with the help of PBM. The liquid binder droplets have been modeled implicitly in DEM. A detailed understanding of the process aids in the development of better design, optimization and control strategies. The model predicts the evolution of important process variables (i.e., average particle diameter, particle size distribution (PSD) and particle liquid content) over time, which have qualitative similarity with experimentally observed trends. The advantage of incorporating the multi-scale approach is that the model can be used to study the distributions of collision frequencies, particle velocity and particle liquid content in different sections of the fluid bed granulator (FBG), in a more mechanistic manner.

In view of growing interest and investment in continuous manufacturing, the development and utilization of mathematical model(s) of the manufacturing line is of prime importance. These models are essential for understanding the complex interplay between process-wide critical process parameters (CPPs) and critical quality attributes (CQAs) beyond the individual process operations. In this work, a flowsheet model that is an approximate representation of the ConsiGma ${}^{\mathrm{TM}}$ -25 line for continuous tablet manufacturing, including wet granulation, is developed. The manufacturing line involves various unit operations, i.e., feeders, blenders, a twin-screw wet granulator, a fluidized bed dryer, a mill, and a tablet press. The unit operations are simulated using various modeling approaches such as data-driven models, semi-empirical models, population balance models, and mechanistic models. Intermediate feeders, blenders, and transfer lines between the units are also simulated. The continuous process is simulated using the flowsheet model thus developed and case studies are provided to demonstrate its application for dynamic simulation. Finally, the flowsheet model is used to systematically identify critical process parameters (CPPs) that affect process responses of interest using global sensitivity analysis methods. Liquid feed rate to the granulator, and air temperature and drying time in the dryer are identified as CPPs affecting the tablet properties.