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Revisiting column selectivity choices in ultra-high performance liquid chromatography-Using multidimensional analytical Design Spaces to identify column equivalency.
Zöldhegyi, Arnold; Horváth, Krisztián; Kormány, Róbert.
Afiliação
  • Zöldhegyi A; Department of Analytical Chemistry, University of Pannonia, Egyetem u. 10, 8200 Veszprém, Hungary; Molnár-Institute for Applied Chromatography, Schneeglöckchenstrasse 47, 10407 Berlin, Germany.
  • Horváth K; Department of Analytical Chemistry, University of Pannonia, Egyetem u. 10, 8200 Veszprém, Hungary.
  • Kormány R; Egis Pharmaceuticals Plc., Keresztúri út 30-38, Budapest, Hungary. Electronic address: kormany.robert@egis.hu.
J Chromatogr A ; 1719: 464738, 2024 Mar 29.
Article em En | MEDLINE | ID: mdl-38422706
ABSTRACT
Current guides and column selection system (CSS) platforms can provide some helpful insights with regard to the selection of alternative phases. Their practical reliability however, can also turn out to be questionable, especially considering the lack of detailed specifics, such as a clear definition of points of equivalence-appropriate running conditions under which the given analytical mixture can be satisfactorily resolved on various stationary phases. In this context, the use of multivariate modeling tools can be highly beneficial. These tools, when applied systematically, are ideal for uniquely characterizing complex LC-separation systems, a fact supported by numerous peer-reviewed papers. Revisiting our earlier work [1] and the applied systematic workflow [2], we used a Design Space modeling software (DryLab), with the main focus on building and comparing 3-dimensional separation models of amlodipine and its related impurities to identify shared method conditions under which columns are conveniently interchangeable. Our study comprised 5, C18-modified ultra-high performance liquid chromatography (UHPLC) columns in total, in some cases with surprising results. We identified several equivalences between the Design Spaces (DSs) of markedly different columns. Conversely, there were cases where, despite the predicted similarities in column data, the modeled DSs demonstrated clear differences between the selected stationary phases.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Anlodipino Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Anlodipino Idioma: En Ano de publicação: 2024 Tipo de documento: Article