Computational Fluid Dynamics-Discrete Element Method Modeling of an Industrial-Scale Wurster Coater

Area of Science:

• Pharmaceutical Engineering
• Computational Fluid Dynamics
• Particle Technology

Background:

• Wurster coaters are widely used in the pharmaceutical industry for large-scale fluid bed coating.
• Current experimental methods often analyze coating thickness for limited particles, hindering batch-wide uniformity prediction.
• Computational techniques offer a path to understand process parameters influencing coating quality attributes.

Purpose of the Study:

• To perform coupled computational fluid dynamics-discrete element method (CFD-DEM) simulations of an industrial-scale Wurster coater.
• To investigate the influence of key process parameters on fluid dynamics and particle behavior within the coater.
• To establish a basis for predicting particle coating uniformity in large batches.

Main Methods:

• Coupled CFD-DEM simulations were employed to model large-scale Wurster coaters with actual particle sizes.
• Simulations analyzed the impact of inlet air flow rate, atomizing air flow rate, bead size distribution, and Wurster gap height.
• The study focused on characterizing internal flow patterns and calculating bead residence time distribution in the Wurster column.

Main Results:

• The inlet air flow rate was identified as the most influential parameter affecting flow behavior within the coater.
• Bead residence time distribution within the Wurster column was quantified, serving as a proxy for coating received per pass.
• Simulation results provide insights into factors governing particle-coating uniformity.

Conclusions:

• Computational fluid dynamics-discrete element method simulations are effective for studying large-scale pharmaceutical coating processes.
• Inlet air flow rate plays a critical role in determining flow dynamics and subsequent coating uniformity.
• Understanding particle residence time is crucial for predicting and optimizing batch coating uniformity.