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|Title:||Torque rheological parameters to predict pellet quality in extrusion-spheronization||Authors:||Soh, J.L.P.
|Issue Date:||6-Jun-2006||Citation:||Soh, J.L.P., Liew, C.V., Heng, P.W.S. (2006-06-06). Torque rheological parameters to predict pellet quality in extrusion-spheronization. International Journal of Pharmaceutics 315 (1-2) : 99-109. ScholarBank@NUS Repository. https://doi.org/10.1016/j.ijpharm.2006.02.023||Abstract:||This study explored the feasibility of predicting the quality of microcrystalline cellulose (MCC) pellets prepared by extrusion-spheronization using torque rheological characterization. Rheological properties of eleven MCC grades as well as their binary mixtures with lactose (3:7) at various water contents were determined using a mixer torque rheometer (MTR). Derived torque parameters were: maximum torque and cumulative energy of mixing (CEM). CEM values of MCC powders (CEM(MCC)) could be attributed to their physical properties such as crystallinity, Vlow P and Vtotal (volumes of mercury intruded in their pores at low pressure and the total intrusion volume), bulk and tapped densities. For both MCC powders and their binary mixtures, strong correlation was observed between their torque parameters and the properties of their pellets formed with 30 and 35% (w/w) water. Since this relationship was valid over a broad water content range, rheological assessment for pre-formulation purposes need not be performed at optimized water contents. These results demonstrated the usefulness of torque rheometry as an effective means of comparing and evaluating MCC grades especially when substitution of equivalent grades is encountered. In so doing, the tedious and expensive pre-production (pre-formulation and optimization) work can be considerably reduced. © 2006 Elsevier B.V. All rights reserved.||Source Title:||International Journal of Pharmaceutics||URI:||http://scholarbank.nus.edu.sg/handle/10635/106461||ISSN:||03785173||DOI:||10.1016/j.ijpharm.2006.02.023|
|Appears in Collections:||Staff Publications|
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