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dc.contributor.authorJouyban-Gharamaleki, A
dc.contributor.authorDastmalchi, S
dc.contributor.authorChan, HK
dc.contributor.authorHanaee, J
dc.contributor.authorJavanmard, A
dc.contributor.authorBarzegar-Jalali, M
dc.date.accessioned2018-08-26T08:31:25Z
dc.date.available2018-08-26T08:31:25Z
dc.date.issued2001
dc.identifier.urihttp://dspace.tbzmed.ac.ir:8080/xmlui/handle/123456789/52148
dc.description.abstractThe mole fraction solubility of a poorly water soluble loop diuretic, furosemide, was determined in aqueous binary mixtures of ethanol, propylene glycol, and glycerol from 0% to 100% cosolvent concentrations at 25 degreesC. Solubility predictions based on the minimum number of experimental data points were performed using the commonly used accurate cosolvency models: the three-suffix excess free energy (3xEFE), the mixture response surface (MRS), the combined nearly ideal binary solvent/Redlich-Kister (CNIBS/R-K), and the general single model (GSM). This prediction method was tested using three sets of solubility data for furosemide generated in this study and I I data sets collected from the literature. The average percentage deviations (APDs) were 8.4 +/- 3.8, 13.6 +/- 7.3, 7.4 +/- 2.8, and 7.6 +/- 2.9, respectively, for 3xEFE, MRS, CNIBS/R-K, and GSM models. Using 3xEFE, CNIBSIR-K, and GSM models, which are theoretically related, a mean predicted solubility, (MPS) approach was also proposed. The APD for this method was 7.3 +/- 2. 3. The mean differences between MRS and the others were statistically significant (p < .001). The results showed that one can employ solubility prediction based on a minimum of five experimental data points, and the expected APD is less than 10%.
dc.language.isoEnglish
dc.relation.ispartofDRUG DEVELOPMENT AND INDUSTRIAL PHARMACY
dc.subjectcosolvency models
dc.subjectfurosemide
dc.subjectsolubility prediction
dc.subjectwater-cosolvent mixture
dc.titleSolubility prediction for furosemide in water-cosolvent mixtures using the minimum number of experiments
dc.typeArticle
dc.citation.volume27
dc.citation.issue6
dc.citation.spage577
dc.citation.epage583
dc.citation.indexWeb of science
dc.identifier.DOIhttps://doi.org/10.1081/DDC-100105183


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