Literature DB >> 32454784

Extended Hildebrand Solubility Approach: Prediction and Correlation of the Solubility of Itraconazole in Triacetin: Water Mixtures at 298.15°K.

Sachin Jagdale1, Rajesh B Nawale2.   

Abstract

OBJECTIVES: The aim of the study is to explore the suitability of an empirical approach for the extended Hildebrand solubility approach (EHSA) to predict and correlate the solubility of the crystalline drug itraconazole (ITRA) in triacetin: water mixtures.
MATERIALS AND METHODS: The physicochemical properties of ITRA like fusion enthalpy, solubility parameter, and ideal mole fraction solubility were estimated. The solubilities of ITRA in mixed solvent blends comprising triacetin: water were determined at 298.15°K. Theoretical solubilities were back calculated using a polynomial regression equation of the interaction energy parameter W as a function of the solubility parameter (δ1) of the solvent mixture. Similarly, the solubilities were predicted by direct method based on the use of logarithmic experimental solubilities (logX2 ) against the solubility parameter (δ1) of the solvent mixture. The predictive capabilities of both EHSA and the direct method were compared using mean percent deviations.
RESULTS: The solubility of ITRA was increased in all the triacetin: water blends and was highest in the blend in which the solubility parameter of ITRA equaled that of the solvent mixture. The prediction capacities of the direct method (mean % deviation was -1.89%) were better than those of EHSA (mean % deviation was 9.76%) in the fifth order polynomial.
CONCLUSION: The results indicated that the solubility of any crystalline solute can be adequately predicted and correlated with the mere knowledge of physicochemical properties and EHSA. The information could be of help in process and formulation development. ©Copyright 2020 Turk J Pharm Sci, Published by Galenos Publishing House.

Entities:  

Keywords:  Itraconazole; correlation of solubilities; extended Hildebrand solubility approach; interaction energy; prediction; solubility parameter

Year:  2020        PMID: 32454784      PMCID: PMC7227914          DOI: 10.4274/tjps.galenos.2019.20438

Source DB:  PubMed          Journal:  Turk J Pharm Sci        ISSN: 1304-530X


  14 in total

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