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预测药物粉末复杂混合物的可压缩性。

Prediction of the compressibility of complex mixtures of pharmaceutical powders.

机构信息

Univ Paris-Sud, UFR de Pharmacie, EA 401, Matériaux et Santé, 5 rue Jean-Baptiste Clément, Châtenay-Malabry, F-92296, France.

出版信息

Int J Pharm. 2012 Oct 15;436(1-2):862-8. doi: 10.1016/j.ijpharm.2012.06.051. Epub 2012 Jul 1.

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.

摘要

开发用于药物压缩过程的预测模型不仅对配方步骤具有重要意义,而且在质量源于设计的发展背景下也具有重要意义。本文涉及可压缩性的预测,即在压缩过程中以及在压片后推出压片期间,预测密度和孔隙率的演变以及与压缩压力的关系。为此,使用旋转压片机模拟器研究了由五种不同药物产品组成的四种不同混合物。选择赋形剂和配方尽可能接近实际的工业配方。使用体积作为加和性质,并将 Kawakita 方程重新表示为密度的函数,从而可以高精度地预测压片内(“in-die”)和压片外(“out-of-die”)的密度(残差<3.5%)。在大多数情况下,对于制药行业中使用的压力水平,对孔隙率预测的绝对误差低于 2%。这项研究表明,这种方法非常适合在工业环境中预测实际药物配方的可压缩性。

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