Literature DB >> 22759643

Prediction of the compressibility of complex mixtures of pharmaceutical powders.

V Busignies1, V Mazel, H Diarra, P Tchoreloff.   

Abstract

The development of predictive models for the pharmaceutical compaction process is of great interest for not only the formulation step but also in the context of the quality by design development. This paper deals with the prediction of the compressibility, i.e. the prediction of the evolution of the density and the porosity of the compact along with the compaction pressure, both "in-die" (during the compaction) and "out-of-die (after the ejection of the compact). For this purpose, four different mixtures composed of five different pharmaceutical products were studied using a rotative press simulator. The excipients and formulations were chosen to be as near as possible to real industrial formulations. Using the volume as an additive property and a reformulation of the Kawakita equation as a function of the density, it was possible to predict the density of the compact both "in-die" and "out-of-die" with a good accuracy (residuals <3.5%). In most of the cases, for the pressure levels used in the pharmaceutical industry, the absolute error on the prediction of the porosity was below 2%. This study demonstrates that this approach could be well suited to predict the compressibility of real pharmaceutical formulations in the industrial context.
Copyright © 2012 Elsevier B.V. All rights reserved.

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Year:  2012        PMID: 22759643     DOI: 10.1016/j.ijpharm.2012.06.051

Source DB:  PubMed          Journal:  Int J Pharm        ISSN: 0378-5173            Impact factor:   5.875


  2 in total

1.  Scaling Tableting Processes from Compaction Simulator to Rotary Presses-Mind the Sub-Processes.

Authors:  Isabell Wünsch; Irene Friesen; Daniel Puckhaber; Thomas Schlegel; Jan Henrik Finke
Journal:  Pharmaceutics       Date:  2020-03-31       Impact factor: 6.321

2.  Process Modeling and Simulation of Tableting-An Agent-Based Simulation Methodology for Direct Compression.

Authors:  Niels Lasse Martin; Ann Kathrin Schomberg; Jan Henrik Finke; Tim Gyung-Min Abraham; Arno Kwade; Christoph Herrmann
Journal:  Pharmaceutics       Date:  2021-06-30       Impact factor: 6.321

  2 in total

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