New perspectives for visual characterization of pharmaceutical solids

The utilization of descriptive image information in pharmaceutical powder technology is rather limited. Consequently, the development of this discipline is a challenge within physical characterization of pharmaceutical solids. The aim of this study was to develop and evaluate an inventive visual characterization approach for monitoring the granule growth in a fluidized-bed granulation process and to use the generated image information in the prediction of tabletting behavior of granules. Surface images of samples from 34 granulations were continuously captured during the spraying and drying phases of the process and particle size distributions were determined. The gray scale difference matrix (GSDM) was derived from two surface images taken in controlled illumination conditions. The particle size calculation from the surface images was based on a multivariate Partial Least Square (PLS) model between the GSDM and sieve analysis measurements. The image information of the end-point samples was also evaluated with respect to tabletting behavior of the granules produced. Principal component analysis (PCA) was used for data visualization. The introduced approach was suitable in particle size measurements of granules during all process phases and in the monitoring of different kinds of granule growth behavior. The visual inspection of the granule samples was powerful, enabling representational batch-to-batch comparisons. The tabletting behavior of the granules could be predicted directly from particle size information generated from the surface images. PCA as a projection method was efficient in data visualization. Development of process analytical technologies (PAT) aims at improving the efficiency of processes. The presented visual characterization approach can be an effective process analytical tool in particle size analysis also enabling the evaluation of the further product quality in the end of the granulation process. The idea of characterization of bulk surface images opens new perspectives for characterization of pharmaceutical solids.