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Model-Guided Development of a Semi-Continuous Drying Process.

Anthony Grelier1, Matej Zadravec2, Johan Remmelgas2

  • 1UCB Pharma S.A, Allée de La Recherche, 60 1070, Brussels, Belgium.

Pharmaceutical Research
|August 16, 2022
PubMed
Summary
This summary is machine-generated.

Variability in drying times within a pharmaceutical continuous manufacturing line was investigated. Computational fluid dynamics (CFD) simulations identified the air inlet design as a key factor impacting temperature distribution and drying performance across different cells.

Keywords:
computational fluid dynamics simulationprocess variability investigationsemi-continuous fluid bed drying

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Area of Science:

  • Pharmaceutical Manufacturing
  • Process Engineering
  • Fluid Dynamics

Background:

  • The ConsiGma® CTL25 wet granulation and tableting line is widely adopted in pharmaceutical continuous manufacturing.
  • The semi-continuous six-segmented fluid bed dryer within this line is crucial for production.
  • Observed repeatable patterns in drying times indicate variability in drying performance across the dryer's cells.

Purpose of the Study:

  • To understand the root cause of drying performance variability in the six-segmented fluid bed dryer.
  • To investigate the factors contributing to uneven drying times between different cells.

Main Methods:

  • Experimental measurements of air temperature and airflow velocity in an empty dryer across its six cells.
  • Interpretation of experimental data using computational fluid dynamics (CFD) simulations.

Main Results:

  • CFD simulations identified the air inlet design as a significant factor influencing temperature distribution within the dryer cells.
  • The simulations correlated with experimental observations regarding temperature differences between cells.

Conclusions:

  • CFD simulations provide valuable insights into equipment performance variability, aiding process development and engineering decisions.
  • While not predicting exact temperatures, simulations accurately reflected observed trends, highlighting their utility in troubleshooting.