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dc.contributor.authorBarzegarJalali, M
dc.contributor.authorJouybanGharamaleki, A
dc.contributor.authorHanaee, J
dc.contributor.authorChookhachizadehMoghaddam, MH
dc.date.accessioned2018-08-26T08:31:41Z
dc.date.available2018-08-26T08:31:41Z
dc.date.issued1996
dc.identifier.urihttp://dspace.tbzmed.ac.ir:8080/xmlui/handle/123456789/52189
dc.description.abstractThe accuracy and prediction capability of the linear double log-log (LDL-L), mixture response-surface (MR-S) and the combined nearly ideal binary solvent/Redlich-Kister (CNIBS/R-K) solubility equations have been compared using the model parameters calculated from either the whole data or a minimum number of data in an experimental set. The CNIBS/R-K model produced better prediction for some experimental sets than the other two models when the parameters obtained from the whole data in a set were employed, whereas the LDL-L model was superior to the other models when the parameters calculated from a minimum number of data were used, indicating its greatest prediction capability.
dc.language.isoEnglish
dc.relation.ispartofINTERNATIONAL JOURNAL OF PHARMACEUTICS
dc.subjectsolubility prediction cosolvency
dc.subjectbinary solvent systems
dc.subjectlinear double log-log model
dc.subjectmixture response-surface method
dc.subjectcombined nearly ideal binary solvent Redlich-Kister equation
dc.titleComparison of double log-log, mixture response-surface and combined NIBS/Redlich-Kister solubility models
dc.typeArticle
dc.citation.volume144
dc.citation.issue1
dc.citation.spage127
dc.citation.epage130
dc.citation.indexWeb of science
dc.identifier.DOIhttps://doi.org/10.1016/S0378-5173(96)04717-5


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