Particle processing is one of the core activity of pharmaceutical products and processes development, manufacturing, and also drug delivery. The powder behavior and processing performance have direct impacts on process robustness, yield, and final product performance (drug delivery).
Product and process development efforts are normally time consuming and expensive by experimental trial-and-error approach. Discrete Element Method (DEM) modeling, and other mechanistic methods, are enabling tools for creating a digital sandbox. Engineering can utilize these tools for equipment characterization, process parameter optimization, target performance tuning, rapid process development and cost saving, and eventually delivering product faster to the market (patients benefits). The applications are diverse, from batch or continuous blending, micronization, tablet making, coating, or using CFD-DEM methods for dry powder inhalers and drug delivery.
In this presentation the applications of DEM and CFD-DEM modeling in pharmaceutical manufacturing will be discussed. Critical aspects of the model development, validation, and implementation in compliance with regulatory criteria will be explained. A new hybrid machine learning-DEM approach will be introduced for extended DEM runs for rapid DEM modeling to a realistic process time (hours) in reduced computational expenses and time.
Presented as part of the virtual ATCx Discrete Element Method in November 2020.
Speaker: Dr. Nima Yazdanpanah, Principal, Procegence
Duration: 24 minutes