Agglomeration Tendency in Dry Pharmaceutical Granular Systems During Blending: De-Agglomeration Modeling Approaches

Efficient blending of powders is of critical importance in the manufacture of a wide variety of industrial products, including pharmaceuticals, foods, plastics and agrochemicals [1, 2]. This study determined the influence of geometry of blenders (double cone blender and V-blender), blending speed and time. The blend composed of diclofenac sodium, lactose, magnesium stearate and talc. It was subjected to homogeneity assessment, size analysis, drug-excipient analysis and dissolution studies. Fourier transform infrared spectroscopy (FTIR) analysis of the blend showed that there was no chemical interaction. Then the blend was added separately to the two blenders and tested at 25,50rpm and 75 rpm at 5, 10, 15 and 20mins. For testing the homogeneity (uniform distribution of diclofenac sodium), content of diclofenac sodium was determined and was found that it ranged from 65.2-74.3% at low speed to 85.4-96.7% at high speed. The dissolution profiles showed an unusual flat asymptote indicating incomplete extents of dissolution (54-65%) with blending at low energy rates and short mixing times (5-10 min at 25 rpm) possibly caused by agglomerates that did not readily disperse in the dissolution medium. The study showed that increasing both speed and time of mixing (15-20 min at 75 rpm) enhanced the extent of dissolution (91-96%). Mixing speed and time had much greater influence on the extent of dissolution which was controlled by deagglomeration than on the initial dissolution rate, which in turn was related to the dispersed diclofenac sodium. The V-blender appeared to operate intermittently combining splitting and merging, while the double-cone appeared to operate continuously, with a nearly constant flow of particles in a more uniform surface layer. This resulted in significantly more rapid mixing in the V-blender than in the double cone. Nevertheless, both exhibited reproducible and rapidly occurring segregation patterns. The blending conditions influenced the mixing quality of agglomerate characteristics. The use of particle sizing approaches to construct de-agglomeration profiles and their interpretation using modeling approaches provided parameters representing agglomeration and de-agglomeration rate constants.