Mechanistic Modelling of Fluid Bed Granulation, Part I: Agglomeration in Pilot Scale Process

The present study aims to develop a mechanistic model to predict the performance of a fluid bed granulation process.

Therefore, the behavior of the bed was investigated experimentally for various operating conditions. It was observed that the granule Loss on Drying and granule size are strongly interrelated. In detail, the maximum final granule size was observed at an intermediate final. Consequently, there is an optimum spray rate and inlet temperature with respect to the granule size. Besides, it was demonstrated that the experiments delivering lower results in a more elongated final granule. Aimed at enabling the prediction of the bed performance numerically, a single-compartment, population-balance-based model was developed and validated against experimental data.

The model parameters associated with the growth rate of granule were estimated and mechanistically correlated to the relevant operating conditions. Detailed analysis of the experimental results suggested that these model parameters may be partially connected to the granule. Subsequently, in order to examine the accuracy of the developed model, a simulation was performed for a new set of operating conditions not previously accounted for in the correlations.

The comparison of the simulated bed performance, when compared to the experimental results, proved with reasonable accuracy the reliability of the developed model in predicting the temporal evolution of granule size. Therefore, this study can be a step forward in developing a stand-alone granulation model, via modeling heat and mass transfer, to simulate evaporation and drying in a fluid bed granulator.

More on mechanistic modeling of fluidbed granulation

Maryam Askarishahi, Martin Maus, Daniela Schröder, David Slade, Michael Martinetz, Dalibor Jajcevic,
Mechanistic modelling of fluid bed granulation, Part I: Agglomeration in pilot scale process, International Journal of Pharmaceutics, Volume 573, 2020, 118837, ISSN 0378-5173, https://doi.org/10.1016/j.ijpharm.2019.118837.