Granulation is a key step in making particulate products, especially food, household care and pharmaceutical, as the properties of granules determine the effective release rate of active ingredients. Granule microstructure attributes such as primary particle packing, spatial distribution of binder and active ingredients, void volume fraction and its distribution, influence both mechanical and application properties. The understanding of the mechanisms that control microstructure in granules is, however, still relatively limited. In order to rationalise both process and product designs it is important to investigate the granule diagenesis (porous microstructure evolution) process that results from the complex interaction between the ingredients in the formulation and the granulation process conditions.

In order to establish a relationship between dissolution behaviour and granule internal structure and the dependence of the latter on formulation and processing conditions, we are developing an integrated approach that utilises both experimental and computational tools. This approach represents a method of predicting and optimising process and formulation conditions required for a given dissolution rate to be achieved.

This study will complement our earlier work (Ansari and Stepanek, 2005b) by examining the dissolution of granules that are systematically produced by fluid bed granulation. Two model pharmaceutical systems (sugar spheres, mannitol as primary particles and calcium phosphate, sodium chloride as an active ingredients) using both film (aqueous solutions of HPC and PVP) and matrix (PEG) binders will be used in this study. The findings of this work will be compared with recently developed computational models, which correlate effective dissolution rate with granule structure (Stepanek, 2004) and the latter property with particle size, binder spreading and solidification rates (Stepanek and Ansari, 2005). We will also present a novel approach that links physically and computationally realised microstructures with the aid of XMT analysis. In addition of tomographic imaging, SEM along with other conventional methods of analyses (pycnomtery for example) will also be compared and discussed for granule microstructure characterisation

References:

Stepanek, F. (2004). Computer-aided product design: granule dissolution. Chem. Eng. Res. Des., 82, 1458-1466.

Ansari, M.A. and Stepanek, F. (2005a). Computer simulation of granule microstructure formation. Chem. Eng. Sci., 60, 4019-4029.

Ansari, M.A. and Stepanek, F. (2005b). The Effect of Granule Microstructure on Dissolution Rate, presented at ECI Conference: Particulate Processes in the Pharmaceutical Industry, Montreal, Canada, June 26-July 1, 2005.