(19g) Online Particle Size Monitoring During Roller Compaction

Rhye Hamey, David Good, Dongsheng Bu, Ziyang Su, Chandra Vema-Varapu

Roller compaction can be a challenging process to monitor and control, often relying on offline measurements of ribbon thickness, and ribbon density to determine if the process is running properly. It is well known that granule particle size can significantly influence powder flow (in turn effects tablet weight), compactability, and dissolution. Yet there has been limited work demonstrating the use of online equipment to monitor or control particle size during granulation.

An online particle size measurement via Mettler Toledo focus beam reflectance measurement (FBRM) was incorporated into the process ruggedness design of experiment (DOE) in order to collect data necessary to establish a control strategy based on real-time particle size information. To demonstrate the applicability of online particle size measurements for monitoring and controlling the granulation process, correlations between particle size, ribbon density, and ribbon thickness were evaluated. The sensitivity on the granule particle size and size distribution as a function of varying roller pressures and gap settings was evaluated. The study used offline sieve analysis data of samples taken during the process to validate the online particle size measurements. A correlation of online particle size measurements to product attributes was achieved by relating particle size data to powder flow, tablet compactability, and dissolution data.

This study suggests the use of online particle size monitoring as a process control in place of or in conjunction with ribbon density and ribbon thickness.  The added product information may reduce the amount of time to transfer a product to commercial manufacturing by reducing the number of batches required to demonstrate process control. Particle size data would allow mapping of a design space in real-time by observing the effect of changes in roller compaction process parameters on the particle size distribution. Ultimately, a feedback control utilizing particle size data may reduce product variability due to manufacturing.