Predicting powder feedability: A workflow for assessing the risk of flow stagnation and defining the operating space...

Powder feeding is of critical importance for continuous manufacturing (CM) since next to in-process segregation it is the phenomenon primarily responsible for fluctuations in content uniformity and for content deviations in the final drug product. So far, feeding studies have focused on the characterization of specific feeders and the prediction of their performance for various materials. This work presents a more holistic approach, an early general assessment of the "feedability" of raw materials. With that regard, we established a workflow to: i) predict potential feeding issues, such as the flow stagnation in the hopper based on both the material attributes and the feeder's geometry; and ii) predict the feed rate space using various feeder/screw combinations for powders with an acceptable risk of hopper flow stagnation. Statistical models were developed for this twofold approach using a dataset comprising nine powders and four different feeders. In order to include different feeding equipment into the statistical models, novel equipment descriptors (capturing the effect of different geometries) and performance indicators (the end fill level as indicator for the risk of powder flow stagnation) were introduced. The application of the workflow was demonstrated for a simple formulation, and model validation was successfully performed for an additional powder that was not contained in the original dataset. Finally, the most relevant material attributes were identified, and reduced material characterization data sets were investigated in terms of effects on the model's prediction performance. The workflow presents a promising tool for initial process assessment in early-phase development.