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Lactose monohydrate flow characterization using shear cell method.

Paulo José Salústio1, Mafalda Machado1, Telmo Nunes2

  • 1Faculty of Pharmacy, Research Institute for Medicines and Pharmaceutical Sciences (iMed.UL), University of Lisbon, Lisbon, Portugal.

Pharmaceutical Development and Technology
|February 29, 2020
PubMed
Summary
This summary is machine-generated.

Pharmaceutical powder flow properties are crucial for solid dosage form manufacturing. Particle size significantly impacts powder flow, with larger particles exhibiting better flowability, as measured by the Flow Index (ff).

Keywords:
Flow indexdiluentexcipientflowingshear cell

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Area of Science:

  • Pharmaceutical Sciences
  • Materials Science
  • Chemical Engineering

Background:

  • Powder flow properties are critical for efficient pharmaceutical manufacturing of solid dosage forms.
  • Standardized methods exist in pharmacopeias, but their applicability across different powder characteristics requires validation.

Purpose of the Study:

  • To compare powder flow properties using conventional methods versus a powder flow tester (PFT) with a shear cell.
  • To investigate the influence of particle size on powder flowability and consolidation behavior.

Main Methods:

  • Utilized conventional (Conv) methods and a shear cell with a powder flow tester (PFT) to measure powder flow.
  • Analyzed powder fractions based on particle size (F<63 and FTotal) and measured Flow Index (ff) under varying consolidation stress (σ₁).

Main Results:

  • Differences in flow properties were observed between conventional and PFT methods, particularly for smaller particle sizes (F<63) and bulk powder (FTotal).
  • Flow Index (ff) increased with particle size and major principal consolidation stress (σ₁).
  • The study demonstrated predictive capabilities for other LactMN fractions based on median particle size (Dv50) or σ₁.

Conclusions:

  • Particle size is a key determinant of pharmaceutical powder flow behavior.
  • The PFT shear cell method provides valuable insights into powder flowability and consolidation.
  • The predictive model allows for the estimation of flow properties for untested powder fractions.