DEM based computational model to predict moisture induced cohesion in pharmaceutical powders

Area of Science:

• Pharmaceutical Engineering
• Materials Science
• Computational Modeling

Background:

• Pharmaceutical powder flow is sensitive to humidity, impacting process development.
• Existing computational models for predicting humidity effects on powder flow are lacking.
• Accurate prediction is crucial for process optimization and scale-up.

Purpose of the Study:

• To develop and validate a Discrete Element Model (DEM) for predicting humidity's impact on pharmaceutical powder flow.
• To establish a correlation between humidity, cohesive forces, and powder flow behavior.
• To provide a predictive tool for pharmaceutical process design under varying humidity conditions.

Main Methods:

• A Discrete Element Model (DEM) was developed to simulate powder flow in hopper geometries.
• Cohesive forces in the DEM were adjusted based on granular bond numbers to account for humidity.
• Experimental studies were conducted on three pharmaceutical excipients at 20%, 40%, and 60% relative humidity (RH).

Main Results:

• The DEM simulations showed good agreement with experimental results for powder flow tendencies across different humidity levels.
• Granular bond numbers in the DEM effectively represented the influence of humidity on powder cohesion.
• The model demonstrated its utility in predicting powder flow behavior under varying environmental conditions.

Conclusions:

• The proposed Discrete Element Model is a valuable tool for predicting pharmaceutical powder flow under different humidity conditions.
• This model can assist in optimizing pharmaceutical processes and ensuring consistent scale-up performance.
• Understanding and predicting humidity effects on powder flow is critical for robust pharmaceutical manufacturing.