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dc.creatorNikolić, Katarina
dc.creatorPavlović, Marija
dc.creatorSmolinski, Adam
dc.creatorAgbaba, Danica
dc.date.accessioned2019-09-02T11:28:12Z
dc.date.available2019-09-02T11:28:12Z
dc.date.issued2012
dc.identifier.issn1386-2073
dc.identifier.urihttp://farfar.pharmacy.bg.ac.rs/handle/123456789/1670
dc.description.abstractOptimization of the experimental conditions of a novel HPLC method for determination of the impurity levels with ziprasidone (in bulk substance and pharmaceutical dosage forms) was performed with use of Multi-Layer Perceptron (MLP) Artificial Neural Networks (ANN) and Response Surface Plots. The obtained experimental conditions were further used to test a set of 20 reversed-phase columns for their selectivity towards ziprasidone components by use of the principal component analysis (PCA) and hierarchical clustering analysis (HCA). The obtained HPLC retention times of ziprasidone and its impurities (Imp I-V) along with the computed molecular parameters of the examined compounds were further used in the Quantitative Structure Retention Relationship (QSRR) study. The performed QSRR study has selected the LogD(pH) (1.5), LogD(pH 2.5), LogD(pH 4.0), LogP, MS, and SAS parameters as descriptors of the chromatographic behavior of ziprasidone components. The developed QSRR model can be very useful in the t(R) prediction for the ziprasidone derivatives (impurities, degradation products, and metabolites). As the performed LC-MS study of the test solution has confirmed that the unknown impurity (t(R): 11.270 min) in the test solution is the TS1, one from two candidates predicted by QSRR (TS1 and TS5), the high prediction potential of the created QSRR models has been proved.en
dc.publisherBentham Science Publ Ltd, Sharjah
dc.relationinfo:eu-repo/grantAgreement/MESTD/Basic Research (BR or ON)/172033/RS//
dc.rightsrestrictedAccess
dc.sourceCombinatorial Chemistry & High Throughput Screening
dc.subjectANNen
dc.subjectHCAen
dc.subjectHPLCen
dc.subjectPCAen
dc.subjectPLSen
dc.subjectQSRRen
dc.subjectziprasidoneen
dc.titleThe Chemometric Study and Quantitative Structure Retention Relationship Modeling of Liquid Chromatography Separation of Ziprasidone Componentsen
dc.typearticle
dc.rights.licenseARR
dcterms.abstractСмолински, Aдам; Николић, Катарина; Павловић, Марија; Aгбаба, Даница;
dc.citation.volume15
dc.citation.issue9
dc.citation.spage730
dc.citation.epage744
dc.citation.other15(9): 730-744
dc.citation.rankM22
dc.identifier.wos000314821100006
dc.identifier.doi10.2174/138620712803519699
dc.identifier.pmid22934948
dc.identifier.scopus2-s2.0-84870406306
dc.identifier.rcubconv_2775
dc.type.versionpublishedVersion


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