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Experiments and numerical modeling to estimate the coating variability in a pan coater
Ekneet Sahni1, Bodhisattwa Chaudhuri
1Department of Pharmaceutical Sciences, University of Connecticut, Storrs, CT 06269, United States.
International Journal of Pharmaceutics
|June 2, 2011
Summary
Optimizing particle coating involves adjusting pan tilt and coating time, which reduces variability. Numerical simulations complement experiments, validating key findings on coating uniformity and process parameters.
Area of Science:
- Pharmaceutical Technology
- Chemical Engineering
- Materials Science
Background:
- Particle coating enhances drug delivery by masking taste, controlling bioavailability, and increasing shelf-life.
- Achieving uniform coating relies on particle flow, mixing dynamics, and controlled spray application within a coater.
- Optimizing coating processes is crucial for consistent product quality and reduced variability.
Purpose of the Study:
- To investigate the impact of coating process parameters on coating performance and variability.
- To determine optimal operating conditions for particle coating processes.
- To validate numerical modeling (DEM) against experimental data for spray coating.
Main Methods:
- Experimental coating of Lactose nonpareils using an aqueous Opadry II solution with varied spray flow rates and concentrations.
- Measurement of particle diameter changes using Vernier Caliper to assess coating thickness.
- Discrete Element Method (DEM) based numerical modeling of spray coating to simulate particle residence time and mass distribution.
Main Results:
- Coating variability decreases with increased pan tilt and coating time, and at an optimal pan speed.
- Spray characteristics had minimal effect on variability, but better mixing (high tilt, pan speed) improved coating.
- DEM simulations showed good agreement with experiments regarding the effect of pan tilt on coating variability.
Conclusions:
- Pan tilt, coating time, and pan speed are critical parameters for reducing coating variability.
- DEM simulations are valuable for understanding and predicting coating uniformity, though speed effects require further experimental refinement.
- The study provides insights into optimizing particle coating processes for improved performance and consistency.
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