A QSPR model for the prediction of the surface tension of NSAIDs

Interfaces are crucially important in pharmaceutics, biotechnology and biomedicine. There is a growing need for specific interfacial consideration that is using routinely to solve pharmaceutical problems. In order to meet manufacturing challenges and develop new better performing pharmaceutical products with improved qualities, knowledge of surface tension (σ) is of utmost importance. The experimental determination of this property has several limitations, such as the high time invested and the consumption of considerable amounts of sample. In the recent years, constant increase in the performance of hardware and software transformed quantitative structure property relationship (QSPR) into powerful and widely used model for the
prediction of many biological, toxicological and physicochemical properties in the field of medicinal chemistry. The aim of the present work was to find a QSPR model for prediction of surface tension of non-steroidal anti-inflammatory drugs (NSAIDs). To do this, a training series, consisting of 300 compounds, was constructed. By the ACD-Labs and MODESLAB, the simplified representation, surface tension value and molecular descriptors of each
compound in the series were obtained. An initial mathematical model of log σ, obtained using the Multiple Lineal Regression method (MLR) of SPSS, was optimized and validate through BuildQSAR program. The final model showed a good predictive power, results which suggest their use as part of the design and development of NSAIDs.