Investigation on the effect of blade patterns on continuous solid mixing performance

Application of Positron Emission Particle Tracking (PEPT) for the evaluation of powder behaviour in an incline linear blender for Continuous Direct Compression (CDC)

Positron Emission Particle Tracking (PEPT) is a non-invasive measurement technique which offers the ability to track the motion of individual particles with high temporal and spatial resolution, and thus build up an understanding of the bulk behaviour of a system from its microscopic (particle level) dynamics. Using this measurement technique, we have developed a series of novel metrics to better understand the behaviours of powders during the steady-state operation of a continuous blender system. Results are presented concerning the response of particle motion to processing parameters (mixing blade configuration and RPM), quantifying the motion in terms of predicted mixing performance. It was found that both increasing rpm and increasing hold-up mass (by selecting fewer transport blades and more mixing blades) provided improved mixing conditions. Interestingly, under specific conditions, there is evidence of convection-like mixing occurring at the interface of the transport and mixing region. This suggests the existence of a potential 'folding region' whereby powder is transported up the barrel (and away from the powder bulk bed) before being reconstituted back into the bulk mass. The results also provide valuable experimental data for the development, calibration and validation of future Discrete Element Method (DEM) simulations.

Hybrid multi-zonal compartment modeling for continuous powder blending processes

To modernize drug manufacturing, the pharmaceutical industry has been moving towards implementing emerging technologies to enhance manufacturing robustness and process reliability for production of regulation compliant drug products. Although different science and risk based technologies, like Quality-by-Design, have been used to illustrate their potential, there still exist some underlying obstacles. Specifically, for the production of oral solid drug products, an in-depth process understanding, and predictive modeling of powder mixing in continuous powder blenders is one such major obstacle and originates from the current limitations of the experimental and modeling approaches. Though first principle based discrete element modeling (DEM) approach can address the above issues, it can get very computationally intensive which limits its applications for predictive modeling. In the proposed work, we aim to address this limitation using a multi-zonal compartment modeling approach, which is constructed from DEM. The approach provides a computationally efficient and mechanistically informed hybrid model. The application of the proposed approach is first demonstrated for a periodic section of the blender, followed by its extension for the entire continuous powder blender and the obtained model predictions are validated. The proposed approach provides an overall assessment of powder mixing along axial and radial directions, which is an important requirement for the quantification of blend uniformity. Given the low computational cost, the developed model can further be integrated within the predictive flowsheet model of the manufacturing line.