Combining Microwave Resonance Technology to Multivariate Data Analysis As a Novel PAT Tool to Improve Process Understanding In Fluid Bed Granulation

A set of 192 fluid bed granulation batches at industrial scale was in-line monitored using microwave resonance technology (MRT) to determine moisture, temperature and density of the granules. The gathered data were analysed through multivariate data analysis techniques, such as multiway partial least squares (PLS) and principal component analysis (PCA) and multivariate batch control charts. The combination of all these techniques, along with a few off-line particle size measurements, led to a huge gain on the process knowledge and understanding. A seasonality effect could be put into evidence with its influence on the process ongoing and on the final granules particle size. Moreover it was demonstrated and quantified by means of a PLS regression the relation between the particle size and the MRT measurements, highlighting a potential ability of the MRT sensor to predict the final particle size of the granules.    

This study contributed successfully to the continuous improvement of an industrial fluid bed granulation process, under the Process Analytical Technology (PAT) initiative to meet the Quality by Design (QbD) principles.