(451c) Residence Time Distribution Determination and Prediction with Discrete Element Method (DEM) in Continuous Blending Processes

Authors: 
Yazdanpanah, N., U.S. Food and Drug Administration
Krull, S. M., Office of Testing and Research, U.S. Food and Drug Administration
Cruz, C. N., U.S. Food and Drug Administration
O'Connor, T., U.S. Food and Drug Administration
Continuous blending/mixing is a key processing step in continuous drug product manufacturing. The adequate and consistent mixing of API and excipients has a direct impact on product quality. Understanding of the system dynamics provided by measurement of the residence time distribution (RTD) is a crucial knowledge in developing control strategies for continuous processes. Discrete element method (DEM) models could provide insight to the process, and a capability to run multiple case studies and sensitivity analyses in lieu of running lengthy and costly experiments.

In this work, a DEM model was developed to study powder flow/mixing inside a continuous blender based on experimental tracer studies. As a complement to in-line blend uniformity evaluation via near-infrared spectroscopy (NIR), case studies by the DEM model aimed to characterize the powder mixing efficiency. The experimental and DEM simulation studies include screw speed, screw configuration, and powder flowrate. For the DEM models, the materials properties (inputs to the simulation) and process conditions were defined based on experimental data. The DEM model case studies were compared with the experimental results. The extent of the DEM simulation allows the analysis of particle trajectories, mixing behavior, as well as RTD and travel distance distribution to understand the influence of process parameters, such as impeller shape, pitch angle, hold up, mean residence time, as well as material attributes, such as shape, flowability, and size.

Disclaimer: This scientific publication reflects the views of the authors and should not be construed to represent FDA’s views or policies.