Predictive population balance model development and validation of the effect of high shear wet granulation process parameters on granule properties

Abstract

In this work, a population balance model has been developed and calibrated with experimental data to be used as a predictive tool to replace or reinforce experimental studies of high shear wet granulation. The system studied also involves dry binder addition necessitating the incorporation of dissolution calculations, viscosity-binder correlations and drop penetration calculations to address some of the heterogeneities arising from the dry addition of binder. To address inhomogeneous liquid distribution in the powder bed, the granulator has been divided into two compartments, one with more liquid, less solid and the other one with the opposite. 27 wet granulation experiments were performed by varying liquid addition amount, liquid addition rate, impeller speed and wet massing time. Geometric mean diameter (GMD) in one case and d10 along with d50 in the other case for the 9 of these experiments were used to estimate the tuning parameters in the model. With the estimated parameters, GMD and d10, d50 were predicted for the remaining 18 experiments using the model and compared with experimental results. The model was able to predict the GMD of 8 experiments with a deviation of <10 μm and 4 more with <20 μm deviation. The model was also able to predict the d10 of 6 batches within 10 μm and 9 more batches within 20 μm. For d50 prediction, the deviation was <10 μm for 12 batches and <20 μm for 4 more batches. The model predicted particle size distribution (PSD) was also compared with the experimental PSD for two of the predicted sets as an example. It was seen that the model was able to replicate the PSD fairly well with the exception of the presence of some big granules seen in the experiments.