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A two-step approach for fluidized bed granulation in pharmaceutical processing: Assessing different models for design

Liangshan Ming1, Zhe Li2, Fei Wu1,2

  • 1Engineering Research Center of Modern Preparation of TCM of Ministry of Education, Shanghai University of Traditional Chinese Medicine, Shanghai, China.

Plos One
|June 30, 2017
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Summary

This study optimized fluidized bed granulation using Plackett-Burman and Box-Behnken designs. Response surface modeling effectively predicted granule properties, aiding pharmaceutical development.

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Area of Science:

  • Pharmaceutical Technology
  • Chemical Engineering
  • Process Modeling

Background:

  • Fluidized bed granulation is crucial for pharmaceutical product development.
  • Optimizing granulation parameters is essential for achieving desired granule properties.
  • Understanding process-property relationships aids in efficient product development.

Purpose of the Study:

  • To identify and optimize critical process parameters in fluidized bed granulation.
  • To investigate the relationship between input variables and granule quality attributes.
  • To compare the efficacy of different modeling techniques for granulation processes.

Main Methods:

  • Utilized a two-step design approach: Plackett-Burman design (PBD) for factor screening and Box-Behnken design (BBD) for optimization.
  • Employed response surface modeling (RSM), partial least squares (PLS), and artificial neural networks (MLP) to model granulation.
  • Investigated granule morphology using scanning electron microscopy.

Main Results:

  • Identified inlet air temperature, binder solution rate, and binder-to-powder ratio as significant factors affecting granule properties.
  • RSM, PLS, and MLP models proved useful for understanding granulation.
  • The RSM model demonstrated superior performance in fitting granule quality attributes compared to PLS and MLP.

Conclusions:

  • The study successfully optimized fluidized bed granulation parameters.
  • RSM is a highly effective tool for predicting and understanding granule properties.
  • This research provides a foundation for modulating granulation parameters to enhance pharmaceutical product performance.