165
Views
6
CrossRef citations to date
0
Altmetric
Research Article

Bulk Characterization of Pharmaceutical Powders by Low-Pressure Compression

, &
Pages 197-209 | Received 09 Aug 2004, Accepted 31 Oct 2004, Published online: 07 Oct 2008
 

Abstract

Low-pressure compression of pharmaceutical powders using small amounts of sample (50 mg) was evaluated as an alternative to traditional bulk powder characterization by tapping volumetry. Material parameters were extrapolated directly from the compression data and by fitting with the Walker, the Kawakita, and the Log-Exp compression models. The compression-derived material parameters were compared to the poured and tapped density and the Compressibility Index determined by tapping. The repeatability of the compression-derived parameters was generally high, supporting their potential for characterization purposes. Significant correlation was demonstrated between several of the compression and tapping-derived parameters. The discriminative power of the low-pressure compression test was discussed using the compressed density at 0.2 MPa, correlated with the tapped density, and the relative Walker coefficient, correlated with the Compressibility Index, as examples. The compressed density at 0.2 MPa and the relative Walker coefficient demonstrated excellent discriminative power, superior to the discriminative power of the correlated tapping derived parameters. The low-pressure compression test was concluded to provide a cost-effective and sensitive alternative to traditional tapping volumetry.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 65.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 523.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.