Flow rate of some pharmaceutical diluents through die-orifices relevant to mini-tableting

Kyriakos Kachrimanis, Michael Petrides, Stavros Malamataris

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

The effects of cylindrical orifice length and diameter on the flowrate of three commonly used pharmaceutical direct compression
diluents (lactose, dibasic calcium phosphate dihydrate and pregelatinised starch) were investigated, besides the powder particle
characteristics (particle size, aspect ratio, roundness and convexity) and the packing properties (true, bulk and tapped density).
Flowratewas determined for three different sieve fractions through a series of miniature tableting dies of different orifice diameter
(0.4, 0.3 and 0.2 cm) and thickness (1.5, 1.0 and 0.5 cm). Itwas found that flowrate decreased with the increase of the orifice length
for the small diameter (0.2 cm) but for the large diameter (0.4 cm) was increased with the orifice length (die thickness). Flow rate
changes with the orifice length are attributed to the flowregime (transitional arch formation) and possible alterations in the position
of the free flowing zone caused by pressure gradients arising from the flow of self-entrained air, both above the entrance in the die
orifice and across it. Modelling by the conventional Jones–Pilpel non-linear equation and by two machine learning algorithms
(lazy learning, LL, and feed-forward back-propagation, FBP) was applied and predictive performance of the fitted models was
compared. It was found that both FBP and LL algorithms have significantly higher predictive performance than the Jones–Pilpel
non-linear equation, because they account both dimensions of the cylindrical die opening (diameter and length). The automatic
relevance determination for FBP revealed that orifice length is the third most influential variable after the orifice diameter and
particle size, followed by the bulk density, the difference between bulk and tapped densities and the particle convexity.
Original languageEnglish
Pages (from-to)72-80
Number of pages9
JournalInternational Journal of Pharmaceutics
Volume303
DOIs
Publication statusPublished - 19 Aug 2015
Externally publishedYes

Keywords

  • Powder flow rate
  • Mini-tableting
  • Neural networks
  • Lazy learning

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