598363 A Semi-Theoretical Model for Simulating the Temporal Evolution of Moisture-Temperature during Industrial Fluidized Bed Granulation

Tuesday, November 17, 2020
Pharmaceutical Discovery, Development and Manufacturing Forum (26) (PreRecorded+)
Hossein Amini1, Xiaorong He2, Yni-Chao Tseng3, Gulsad Kucuk4, Robert Schwabe4, Leon Schultz4, Martin Maus5, Daniela Schröder6, Pavol Rajniak7 and Ecevit Bilgili1, (1)Otto H. York Department of Chemical and Materials Engineering, New Jersey Institute of Technology, Newark, NJ, (2)Material and Analytical Sciences, Boehringer Ingelheim, Ridgefield, CT, (3)Boehringer Ingelheim, Ridgefield, CT, (4)R&D Pharmaceutical Development, Boehringer Ingelheim, Ridgefield, CT, (5)Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany, (6)Boehringer Ingelheim, Bibrach an der Riß, Germany, (7)Slovak University of Technology, Bratislava, Slovakia

Moisture plays a major role in determining the attributes of granules prepared by fluidized bed granulation (FBG). In this talk, we are presenting a semi-theoretical droplet-based evaporation rate model that was developed and incorporated into moisture mass-enthalpy balances to simulate the temporal evolution of bed moisture-temperature. Experimental data from a GPCG30 unit were used to fit the model parameters. With only two fitting parameters, the model demonstrated very good capability to describe the moisture-temperature evolution for a wide range of operating conditions. Then, in a global process model (GPM) approach, the evaporation parameters were fitted to multi-linear functions of inlet air temperature, binder concentration, and spray rate. The GPM was validated successfully by simulating a different data set which was not used in its calibration. As the GPM demonstrated a good predictive capability, it was further used to investigate the impacts of process parameters. Numerical simulations suggest that the proposed GPM predicts the experimentally well-established trends of moisture-temperature profiles in previously published data, proving the applicability of the GPM approach. This study has demonstrated the capabilities of simple process models as a practical approach to predict time-wise evolution of bed moisture-temperature profiles in industrial FBG modeling, while also pointing out their limitations.

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