Department of Pharmaceutics, National Institute of Pharmaceutical Education and Research, S.A.S. Nagar, Punjab 160062, India.
Int J Pharm. 2011 Jan 17;403(1-2):109-14. doi: 10.1016/j.ijpharm.2010.10.039. Epub 2010 Oct 27.
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.
本研究旨在开发、比较和验证用于二元体系力学性能预测的模型。在不同赋形剂存在的情况下，研究了布洛芬（IBN）这一难压缩高剂量药物的二元混合物的力学性能。分别测量了各成分（即 IBN、微晶纤维素（MCC）和磷酸二氢钙二水合物（DCP））以及 IBN 与赋形剂二元混合物的片剂在不同相对密度下的拉伸强度。通过假设线性混合规则或幂律混合规则，使用 Ryshkewitch-Duckworth（R-D）和渗透理论，尝试从单一组分的力学性能来预测二元混合物的力学性能。对模型进行了比较，并基于残差分布和赤池信息量准则提出了最佳模型。R-D 和渗透模型均采用幂律结合线性混合规则，可得到良好的预测结果。结果表明，该模型可较好地预测主要含有难压缩候选药物的二元体系的力学性能。这些模型的预测和结论可以系统地推广到其他药物粉末。
