Characterization of particle sizes in bulk pharmaceutical solids using digital image information

Abstract

The purpose of this study was to demonstrate a novel method of extracting relevant information from undispersed bulk powder surfaces to be used in particle size analysis. A new surface imaging approach for undispersed powders combined with multivariate modeling was used. Digital surface images of various granule batches were captured using an inventive optical setup in controlled illumination conditions. A descriptor, the gray scale difference matrix (GSDM), which describes the particle size of granular material was generated and extracted from the powder surface image information. Partial least squares (PLS) modeling was used to create a model between the GSDM and the particle size distribution of granules measured with sieving. The use of lateral illumination and the combining of information from 2 surface images strengthened the shading effects on the powder surfaces. The shading effects exposed the topography or the visual texture of the powder surfaces. This textural information was efficiently extracted using the GSDM descriptor. The goodness-of-fit (R2) for the created PLS model was 0.91 and the predicted variation (Q2) was 0.87, indicating a good model. The model covered granule sizes in the size range of approximately 20 to 2500 microm. The extracted descriptor was effectively used in particle size measurement. This study confirms that digital images taken from undispersed bulk powder surfaces contain substantial information needed for particle size distribution analysis. The use of the GSDM enabled the utilization of bulk powder surface information and provided a fast method for particle size measurement.