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Analysis and Specification of Starch Granule Size Distributions
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A Multi-variate Mathematical Model for Simulating the Granule Size Distribution in Roller Compaction-Milling Process.

Hossein Amini1, Ilgaz Akseli2

  • 1Integrated Material Science & Technology, Drug Product Development, Bristol-Myers Squibb, 556 Morris Avenue, Summit, New Jersey, 07901, USA.

AAPS Pharmscitech
|March 11, 2021
PubMed
Summary

A new mathematical model predicts granule size distribution during roller compaction milling by analyzing ribbon mechanical properties. This model aids in understanding and controlling granule attributes for pharmaceutical development.

Keywords:
material profilingpharmaceutical process modelingribbon Young’s modulusribbon millingroller compaction process

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Area of Science:

  • Pharmaceutical Engineering
  • Powder Technology
  • Process Modeling

Background:

  • Granule size distribution (GSD) is crucial for roller compaction (RC) quality.
  • Predicting GSD requires understanding ribbon breakage during milling.
  • Limited models exist for RC milling, especially for new compounds.

Purpose of the Study:

  • To develop a multivariate mathematical model for simulating GSD in RC milling.
  • To correlate model parameters with ribbon mechanical properties like Young's modulus.
  • To validate the model's predictive capability on unseen data and a real-scale system.

Main Methods:

  • Generated experimental GSD data using a lab-scale milling apparatus.
  • Developed a multivariate model linking GSD to ribbon properties.
  • Correlated model parameters with ribbon Young's modulus.
  • Validated the model using excluded data and a pilot-scale RC system.

Main Results:

  • The model successfully simulated GSD based on ribbon mechanical properties.
  • Model parameters showed correlation with ribbon Young's modulus.
  • The model accurately predicted GSD for a pharmaceutical excipient on a real-scale RC system.
  • Successful prediction of GSD for roller compacted microcrystalline cellulose (MCC) powder.

Conclusions:

  • The developed model provides quantitative insight into RC milling for GSD prediction.
  • This approach aids in process understanding and control within the Quality-by-Design framework.
  • The model can be integrated with RC models for comprehensive pharmaceutical process development.