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Journal of Nanomaterials
Volume 2011 (2011), Article ID 206320, 12 pages
Research Article

Development of Quantitative Structure-Property Relationship Models for Self-Emulsifying Drug Delivery System of 2-Aryl Propionic Acid NSAIDs

1Department of Pharmaceutics, West China School of Pharmacy, Sichuan University, Chengdu, Sichuan 610041, China
2State Key Laboratory of Biotherapy and Cancer Center, West China Medical School, Sichuan University, Chengdu, Sichuan 610041, China
3Department of Pharmacy, Chengdu Family Planning Guidance Institute, Chengdu, Sichuan 610041, China

Received 19 May 2011; Revised 22 July 2011; Accepted 22 July 2011

Academic Editor: Xing J. Liang

Copyright © 2011 Chen-Wen Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


We developed the quantative structure-property relationships (QSPRs) models to correlate the molecular structures of surfactant, cosurfactant, oil, and drug with the solubility of poorly water-soluble 2-aryl propionic acid nonsteroidal anti-inflammatory drugs (2-APA-NSAIDs) in self-emulsifying drug delivery systems (SEDDSs). The compositions were encoded with electronic, geometrical, topological, and quantum chemical descriptors. To obtain reliable predictions, we used multiple linear regression (MLR) and artificial neural network (ANN) methods for model development. The obtained equations were validated using a test set of 42 formulations and showed a great predictive power, and linear models were found to be better than nonlinear ones. The obtained QSPR models would greatly facilitate fast screening for the optimal formulations of SEDDS at the early stage of drug development and minimize experimental effort.