Приказ основних података о документу

dc.creatorGolubović, Jelena
dc.creatorProtić, Ana
dc.creatorZečević, Mira
dc.creatorOtašević, Biljana
dc.date.accessioned2019-09-02T11:47:05Z
dc.date.available2019-09-02T11:47:05Z
dc.date.issued2015
dc.identifier.issn0169-7439
dc.identifier.urihttps://farfar.pharmacy.bg.ac.rs/handle/123456789/2403
dc.description.abstractArtificial neural network (ANN) is a learning system based on a computation technique, which was employed for building of the quantitative structure-retention relationship (QSRR) model for candesartan cilexetil and its degradation products. Candesartan cilexetil has been exposed to forced degradation conditions and degradation products have been subsequently identified with the assistance of HPLC-MS technique. Molecular descriptors have been computed for all compounds and were optimized together with significant chromatographic parameters employing developed QSRR models. In this way, QSRR has been used in development of HPLC stabilityindicating method, optimal conditions toward various outputs have been established and high prediction potential of the created QSRR models has been proved.en
dc.publisherElsevier Science BV, Amsterdam
dc.relationinfo:eu-repo/grantAgreement/MESTD/Basic Research (BR or ON)/172033/RS//
dc.rightsrestrictedAccess
dc.sourceChemometrics and Intelligent Laboratory Systems
dc.subjectQSRRen
dc.subjectArtificial neural networksen
dc.subjectCandesartan cilexetilen
dc.subjectForced degradation studiesen
dc.subjectHPLCen
dc.titleQuantitative structure retention relationship modeling in liquid chromatography method for separation of candesartan cilexetil and its degradation productsen
dc.typearticle
dc.rights.licenseARR
dcterms.abstractПротић, Aна; Зечевић, Мира; Голубовић, Јелена; Оташевић, Биљана;
dc.citation.volume140
dc.citation.spage92
dc.citation.epage101
dc.citation.other140: 92-101
dc.citation.rankaM21
dc.identifier.wos000349062500010
dc.identifier.doi10.1016/j.chemolab.2014.11.005
dc.identifier.scopus2-s2.0-84913553965
dc.type.versionpublishedVersion


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Приказ основних података о документу