Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Modelling and understanding powder flow properties and compactability of selected active pharmaceutical ingredients, excipients and physical mixtures from critical material properties
Show others and affiliations
2017 (English)In: International Journal of Pharmaceutics, ISSN 0378-5173, E-ISSN 1873-3476, Vol. 531, no 1, p. 191-204Article in journal (Refereed) Published
Abstract [en]

The development of solid dosage forms and manufacturing processes are governed by complex physical properties of the powder and the type of pharmaceutical unit operation the manufacturing processes employs. Suitable powder flow properties and compactability are crucial bulk level properties for tablet manufacturing by direct compression. It is also generally agreed that small scale powder flow measurements can be useful to predict large scale production failure. In this study, predictive multilinear regression models were effectively developed from critical material properties to estimate static powder flow parameters from particle size distribution data for a single component and for binary systems. A multilinear regression model, which was successfully developed for ibuprofen, also efficiently predicted the powder flow properties for a range of batches of two other active pharmaceutical ingredients processed by the same manufacturing route. The particle size distribution also affected the compactability of ibuprofen, and the scope of this work will be extended to the development of predictive multivariate models for compactability, in a similar manner to the approach successfully applied to flow properties.

Place, publisher, year, edition, pages
Elsevier, 2017. Vol. 531, no 1, p. 191-204
Keywords [en]
Powder flow, surface chemistry, particle size descriptors, multilinear regression model, crystallisation, milling, compactability
National Category
Chemical Sciences Pharmaceutical Sciences Biological Sciences
Identifiers
URN: urn:nbn:se:kth:diva-260104DOI: 10.1016/j.ijpharm.2017.08.063ISI: 000410648200018PubMedID: 28801109Scopus ID: 2-s2.0-85028383083OAI: oai:DiVA.org:kth-260104DiVA, id: diva2:1355934
Note

Cited By :6; Export Date: 25 September 2019

QC 20191030

Available from: 2019-09-30 Created: 2019-09-30 Last updated: 2020-05-11Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textPubMedScopus

Search in DiVA

By author/editor
Rasmuson, Åke Christoffer
In the same journal
International Journal of Pharmaceutics
Chemical SciencesPharmaceutical SciencesBiological Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 9 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf