Development of a fluid bed granulation process control strategy based on real-time process and product measurements

TALANTA

卷:100

Article

Burggraeve, Anneleen¹  Silva, Ana F. T.¹  Van den Kerkhof, Tom²  Hellings, Mario²  Vervaet, Chris³  Remon, Jean Paul³  Vander Heyden, Yvan⁴  De Beer, Thomas¹ 

[1] Univ Ghent, Fac Pharmaceut Sci, Lab Pharmaceut Proc Analyt Technol, B-9000 Ghent, Belgium

[2] Johnson & Johnson Pharmaceut Res & Dev, Analyt Dev, Beerse, Belgium

[3] Univ Ghent, Fac Pharmaceut Sci, Lab Pharmaceut Technol, Ghent, Belgium

[4] Vrije Univ Brussel, Fac Med & Pharm, Dept Analyt Chem & Pharmaceut Technol, Brussels, Belgium

关键词: Fluid bed granulation;    NIR spectroscopy;    Spatial filter velocimetry (SFV);    Focused beam reflectance measurement (FBRM);    In-line monitoring;    Process control;   

DOI  :  10.1016/j.talanta.2012.07.054

来源: Elsevier

【 摘 要 】

This article describes the results of three case studies conducted consecutively, in order to develop a process control strategy for a top-spray fluid bed granulation process. The use of several real-time particle size (i.e., spatial filter velocimetry and focused beam reflectance measurement) and moisture (i.e., near infrared (MR) and Lighthouse near infrared spectroscopy) analyzers was examined. A feed-forward process control method was developed, where in-line collected granulation information during the process spraying phase was used to determine the optimum drying temperature of the consecutive drying phase. Via real-time monitoring of process (i.e., spraying temperature and spray rate) and product (i.e., granule size distribution and moisture) parameters during the spraying period, the batch bulk density was predicted at the end of the spraying cycle, using a PLS model. When this predicted bulk density was not meeting the desired value, the developed control method allowed the calculation of an adjusted drying temperature leading to the desired batch bulk density at the end of the granulation process. Besides the development of the feed-forward control strategy, a quantitative PIS model for in-line moisture content prediction of the granulated end product was built using the NIR data. (C) 2012 Elsevier B.V. All rights reserved.

【 授权许可】

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