A novel approach to determine the granule density of milled ribbons using multi-stage air classification combined with dynamic image analysis

Determination of the granule density as a critical quality attribute during roller compaction/dry granulation provides an important parameter for further successful processing of the compacted materials. In this study, a novel approach was developed to determine the granule density using the principle of multi-stage air classifying.

Highlights

Granule density via air classifying in combination with dynamic image analysis

A material independent prediction model for the granule density was implemented

Air classifying combined with dynamic image analysis can be used as effective PAT

A roller compactor was utilized to produce ribbons and granules, composed of varying amounts of different excipients. The dry granules were separated using an inhouse built multi-stage air classifier and analyzed via dynamic image analysis in terms of particle size distribution and shape, resulting in a material independent prediction model for the density of granules based on their separation behavior. Overall, the present study introduced a novel, continuous, non-destructive, and material independent method that provides the suitability to monitor the granule density with high accuracy, that can be used as potential process analytical technology for implementation into the roller compaction/dry granulation process. Continue reading on A novel approach to determine the granule density of milled ribbons using multi-stage air classification combined with dynamic image analysis