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Development of an Image-based Method for Tablet Microstructure Description and Its Correlation with API Release Rate.

Simona Römerová1, Ondřej Dammer2, Petr Zámostný3

  • 1Department of Organic Technology, University of Chemistry and Technology Prague, Technická 5, 166 28, Prague 6, Czech Republic. simona.romerova@vscht.cz.

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Summary
This summary is machine-generated.

A new image-based method describes pharmaceutical tablet microstructure. This method correlates microstructural parameters with drug release rates, aiding in the prediction of tablet performance for solid dosage forms.

Keywords:
SEM image analysisUSP4 dissolutiondeformabilityflow-through dissolutiontablet microstructure

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Area of Science:

  • Pharmaceutical Sciences
  • Materials Science
  • Chemical Engineering

Background:

  • Tablet performance, including drug release, depends on formulation properties and compression parameters.
  • Predicting tablet performance solely from input parameters can be unreliable, necessitating microstructure analysis.
  • Current microstructure analysis techniques are often costly or toxic, limiting pharmaceutical industry adoption.

Purpose of the Study:

  • To develop a fast, accessible, image-based method for describing tablet microstructure.
  • To correlate microstructural parameters with tablet composition, compression pressure, and drug release.
  • To establish a model system for understanding compressed solid dosage forms with varying excipient deformability.

Main Methods:

  • Developed an image-based method for microstructure description.
  • Applied the method to a model system of ibuprofen (API) and calcium phosphate dihydrate (excipient).
  • Correlated the quadratic mean of the equivalent diameter of the excipient with tablet properties and drug release.

Main Results:

  • Successfully developed an image-based microstructure description tool.
  • Established a correlation between the excipient's microstructural parameter and tablet composition, compression pressure, and API release rate.
  • Demonstrated the potential to predict tablet dissolution performance using microstructural data.

Conclusions:

  • An image-based method can effectively describe tablet microstructure.
  • Microstructural parameters can be used to predict drug release performance in specific model systems.
  • This approach offers a viable alternative for microstructure analysis in pharmaceutical development.