TY - JOUR T1 - Prediction of mechanical properties of compacted binary mixtures containing high-dose poorly compressible drug. AU - Patel,Sarsvatkumar, AU - Bansal,Arvind Kumar, Y1 - 2010/10/27/ PY - 2010/06/08/received PY - 2010/10/14/revised PY - 2010/10/19/accepted PY - 2010/11/2/entrez PY - 2010/11/3/pubmed PY - 2011/3/22/medline SP - 109 EP - 14 JF - International journal of pharmaceutics JO - Int J Pharm VL - 403 IS - 1-2 N2 - The aim of the study was to develop, compare and validate predictive model for mechanical property of binary systems. The mechanical properties of binary mixtures of ibuprofen (IBN) a poorly compressible high dose drug, were studied in presence of different excipients. The tensile strength of tablets of individual components viz. IBN, microcrystalline cellulose (MCC), and dicalcium phosphate dihydrate (DCP) and binary mixtures of IBN with excipients was measured at various relative densities. Prediction of the mechanical property of binary mixtures, from that of single components, was attempted using Ryshkewitch-Duckworth (R-D) and Percolation theory, by assuming a linear mixing rule or a power law mixing rule. The models were compared, and the best model was proposed based on the distribution of residuals and the Akaike's information criterion. Good predictions were obtained with the power law combined with linear mixing rule, using R-D and Percolation models. The results indicated that the proposed model can well predict the mechanical properties of binary system containing predominantly poorly compressible drug candidate. The predictions of these models and conclusions can be systematically generalized to other pharmaceutical powders. SN - 1873-3476 UR - https://www.unboundmedicine.com/medline/citation/21034802/Prediction_of_mechanical_properties_of_compacted_binary_mixtures_containing_high_dose_poorly_compressible_drug_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S0378-5173(10)00814-8 DB - PRIME DP - Unbound Medicine ER -