Artículo
Determination of enantiomeric composition of ibuprofen in pharmaceutical formulations by partial least-squares regression of strongly overlapped chromatographic profiles
Osorio Grisales, Jaiver
; Arancibia, Juan Alberto
; Castells, Cecilia Beatriz Marta
; Olivieri, Alejandro Cesar
Fecha de publicación:
02/2012
Editorial:
Elsevier Science
Revista:
Journal of Chromatography B
ISSN:
0378-4347
e-ISSN:
1570-0232
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
In this report, we demonstrate how chiral liquid chromatography combined with multivariate chemometric techniques, specifically unfolded-partial least-squares regression (U-PLS), provides a powerful analytical methodology. Using U-PLS, strongly overlapped enantiomer profiles in a sample could be successfully processed and enantiomeric purity could be accurately determined without requiring baseline enantioresolution between peaks. The samples were partially enantioseparated with a permethyl-β-cyclodextrin chiral column under reversed-phase conditions. Signals detected with a diode-array detector within a wavelength range from 198 to 241nm were recorded, and the data were processed by a second-order multivariate algorithm to decrease detection limits. The R-(-)-enantiomer of ibuprofen in tablet formulation samples could be determined at the level of 0.5mgL-1 in the presence of 99.9% of the S-(+)-enantiomorph with relative prediction error within ±3%.
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Articulos(CCT - LA PLATA)
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - LA PLATA
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - LA PLATA
Articulos(IQUIR)
Articulos de INST.DE QUIMICA ROSARIO
Articulos de INST.DE QUIMICA ROSARIO
Citación
Osorio Grisales, Jaiver; Arancibia, Juan Alberto; Castells, Cecilia Beatriz Marta; Olivieri, Alejandro Cesar; Determination of enantiomeric composition of ibuprofen in pharmaceutical formulations by partial least-squares regression of strongly overlapped chromatographic profiles; Elsevier Science; Journal of Chromatography B; 910; 2-2012; 78-83
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