(299f) Toward Efficient Development and Reliable Scale-up of Agitated Filter Drying Protocol through DEM Modeling and Simulation

Sinha, K., AbbVie Inc.
Nere, N., AbbVie Inc.
Gaertner, J. G., AbbVie Inc.
Mlinar, L., AbbVie Inc.
Ho, R., AbbVie
Mattei, A., AbbVie Inc.
Wei, H., University of Illinois at Chicago
Mukherjee, S., AbbVie Inc.
Sheikh, A., AbbVie Inc.
Bordawekar, S., AbbVie Inc.
Drying of an active pharmaceutical ingredient (API) is an important unit operation in the pharmaceutical industry as it is used to control residual solvent content, in addition to controlling appropriate physical properties. Drying operation is often time consuming, and may turn out to be a bottleneck in the overall process cycle time. Many APIs are potent compounds that require filtration and drying to be done in a single contained vessel, known as an agitated filter dryer (AFD), to minimize operator exposure.

Gradual evolution of powder bed during the drying results in continuously changing physical properties. This poses significant challenges in experimentally driven understanding of the impact of drying process parameters on final physical properties. Agglomeration and attrition, which are governed by the shear, are the major issues encountered during design and scale-up of filter drying operation. The extent of shear and its distribution changes significantly across various scales and is not amenable to experimental measurements. With advancements in computer algorithms and cheaper computational power, more fundamental insights into particle dynamics including the shear stress distribution can be assessed using Discrete Element Methods (DEM).

In this talk, we will present some of the key attributes that govern the particle dynamics calculated using DEM in the context of AFD operation. We will also provide a decision tree to guide efficient design and reliable scale-up of agitated filter drying.