Physics

Quality by Design

Process engineering

Engineering

Particle size

Composite material

Biochemical engineering

Materials science

SCALE-UP

Breakage

Computer science

Critical quality attributes

Granulation

Chemical engineering

Granule (geology)

Classical mechanics

Powder Technology

Wet granulation is a key step in the pharmaceutical manufacturing of solid-dosage forms. Wet granulation is used in pharmaceutical production to enhance formulation qualities such as flowability, compressibility, etc. Different methods are used for wet granulation, including fluidised bed, twin-screw extrusion, and high-shear method, leading to different mechanisms and granule properties. Modelling wet granulation is of great importance for the pharmaceutical industry, which is aspiring to shift from batch mode to a continuous one. Moreover, model-based understanding is critical for implementing the Quality-by-Design (QbD) approach in the pharmaceutical industry. The current critical review represents an overview of current approaches in modelling wet granulation. Three major models, including the population balance model (PBM), discrete element method (DEM), and data-driven models, are evaluated, and the advantages of each approach are outlined. The PBM is the primary approach for modelling granulation in which granule properties are tracked in the process. On the other hand, DEM provides a better understanding of granulation at the particle level. Recent DEM modelling studies have significantly advanced the knowledge for design and scale-up of DEM models, such as capturing the suitable wetting physics and particle scaling and thus mitigating the traditionally known challenges in the application of DEM for wet granulation processes. However, further research is required to include particle level effects, like breakage, attrition, into the DEM model through either built-in approaches or hybrid approaches. Data-driven models are fast and accurate but do not investigate the mechanisms involved in granulation. Data-driven models based on neural networks have been indicated to be adopted for application in continuous granulation with great accuracy compared to other approaches, which can also be implemented for process control. A great joint prospect for first-principles and data-driven modelling approaches is anticipated, which can play an important role in future process design, optimisation, and control of pharmaceutical wet granulation processes.

Challenges and opportunities in modelling wet granulation in pharmaceutical industry – A critical review