Assessment of spatial heterogeneity in continuous twin screw wet granulation process using three-compartmental population balance model

Abstract

In this study, a novel three-compartmental population balance model (PBM) for a continuous twin screw wet granulation process is developed, combining the techniques of PBM and regression process modeling. The developed model links screw configuration, screw speed, and blend throughput with granule properties to predict the granule size distribution (GSD) and volume-average granule diameter. The granulator screw barrel was divided into three compartments along barrel length: wetting compartment, mixing compartment, and steady growth compartment. Different granulation mechanisms are assumed in each compartment. The proposed model therefore considers spatial heterogeneity, improving model prediction accuracy. An industrial data set containing 14 experiments is applied for model development. Three validation experiments show that the three-compartmental PBM can accurately predict granule diameter and size distribution at randomly selected operating conditions. Sixteen combinations of aggregation and breakage kernels are investigated in predicting the experimental GSD to best judge the granulation mechanism. The three-compartmental model is compared with a one-compartmental model in predicting granule diameter at different experimental conditions to demonstrate its advantage. The influence of the screw configuration, screw speed and blend throughput on the volume-average granule diameter is analyzed based on the developed model.

Keywords:

• Three-compartmental population balance model
• twin screw wet granulation
• granule size distribution
• design of experiment

Acknowledgements

The authors would like to thank Merck and USFDA for funding the project and providing the data set used in the modeling work. A license for gSOLIDS has also been provided by PSE (UK).

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Additional information

Funding

Funding for this publication was made possible, in part, by the Food and Drug Administration through grant [5U01FD005294, USFDA cooperate research project, Process Modeling and Assessment Tools for Simulation, Risk Management and design space development of integrated pharmaceutical manufacturing processes]. The project is partially supported by Merck.