Solubility parameter prediction for kacip fatimah herb using group contribution-based models

Abstract

This study is focusing on determining the most suitable solubility parameter prediction model for Kacip Fatimah herb based on Group Contribution (GC) approach. Stefanis, Van Krevelen, and Marrero and Gani GC models are used to predict Hansen Solubility Parameters (HSP) property of selected Kacip Fatimah active ingredients extracted using methanol solvent. From the results, solubility parameters predicted using Stefanis and Van Krevelen GC methods show high deviations with the experimental data. On the other hand, the HSP predictions using Marrero and Gani GC method is the best from the three GC Methods because it uses the data from organic compound and take into account the contribution of the third order groups. The variation in solubility parameter concludes that Van Krevelen and Stefanis GC parameter is not suitable for computing the parameter for herbs.