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dc.creatorJančić, Biljana
dc.creatorMedenica, Mirjana
dc.creatorIvanović, Darko
dc.creatorMalenović, Anđelija
dc.creatorPopović, Igor
dc.date.accessioned2019-09-02T11:13:23Z
dc.date.available2019-09-02T11:13:23Z
dc.date.issued2008
dc.identifier.issn0009-5893
dc.identifier.urihttps://farfar.pharmacy.bg.ac.rs/handle/123456789/1070
dc.description.abstractIn this paper, the chromatographic characterization of fosinopril sodium and fosinoprilat is presented. The first stept was pK(a) determination for the active substance and its degradation product using RP-LC. It was followed by optimization employing the combination of experimental design and artificial neural networks. For the definition of input and output variables, the central composite design for three factors was built. Back propagation algorithm was applied to model the system, and then the optimization of the experimental conditions was carried out in the neural network with 3-8-2 structure, which confirmed to be able to provide the maximum performance. From the method optimization, the most appropriate experimental conditions for fosinopril sodium and fosinoprilat analysis were extracted. The optimized method was validated and applied in the quality control of tablets and for forced degradation studies.en
dc.publisherSpringer Heidelberg, Heidelberg
dc.relationinfo:eu-repo/grantAgreement/MESTD/MPN2006-2010/142077/RS//
dc.rightsrestrictedAccess
dc.sourceChromatographia
dc.subjectcolumn liquid chromatographyen
dc.subjectexperimental design-artificial neural networksen
dc.subjectforced degradation studiesen
dc.subjectfosinoprilaten
dc.titleChromatographic behavior of fosinopril sodium and fosinoprilat using neural networksen
dc.typearticle
dc.rights.licenseARR
dcterms.abstractИвановић, Дарко; Меденица, Мирјана; Поповић, Игор; Маленовић, Aнђелија; Јанчић, Биљана;
dc.citation.volume67
dc.citation.other67: -
dc.citation.rankM23
dc.identifier.wos000256533700017
dc.identifier.doi10.1365/s10337-008-0575-9
dc.identifier.scopus2-s2.0-43449139973
dc.type.versionpublishedVersion


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