Media type: E-Article Title: Estimation of granule size distribution for batch fluidized bed granulation process using acoustic emission and N‐way PLS Contributor: Matero, Sanni; Poutiainen, Sami; Leskinen, Jari; Järvinen, Kristiina; Ketolainen, Jarkko; Poso, Antti; Reinikainen, Satu‐Pia Published: Wiley, 2010 Published in: Journal of Chemometrics, 24 (2010) 7-8, Seite 464-471 Language: English DOI: 10.1002/cem.1269 ISSN: 1099-128X; 0886-9383 Origination: Footnote: Description: AbstractFluidized bed wet granulation of a pharmaceutical mixture is an unpredictable and complex process. Batch‐to‐batch variation, i.e. output material inconsistency, is still an unmanaged problem in fluidized bed granulation. The variation in outcome with different size distributions and yield arises from process conditions, which until now have proved difficult to control. The good quality batch is usually one with a high yield of the desired narrow granule size distribution. Thus, for successful granulation the size distribution needs to be controlled throughout the process in order to prevent the heterogeneity of different batch runs and inconsistent batch products. This paper introduces a method for determining end‐product granule size distribution in the early phase of granulation, based on the observation that the quality of the early phase nucleation strongly affects the quality of the end product. In the quantitative model, the information gained from the process stream acquired with an acoustic emission (AE) transducer was combined and modeled using an N‐way PLS method. Reference sieve analysis for the granule size distribution was performed off‐line and was used as the response variable. AE monitoring is a non‐invasive technique for evaluating granulation process performance by detecting the sound of particle impacts. AE caused by the particle–chamber wall interaction is influenced by the size of the granules; thus AE contains information about the granule size distribution. This study shows for the first time that the nucleation phase of granulation can be detected using AE techniques, and thus the possibility of predicting end product granule size distribution by means of AE measurement during the nucleation phase. Copyright © 2009 John Wiley & Sons, Ltd.