Determination of selectivity differences for basic compounds in gradient reverse phase high performance liquid chromatography under high pH conditions by partial least squares modelling

Abstract

The retention behaviour of compounds in a chromatographic system is believed to be multivariate by nature, i.e. many physico-chemical properties of an analyte can influence its retention. Principal component analysis (PCA) and partial least squares (PLS) can therefore be particularly useful tools for visualising, exploring and modelling the complex interactions between solutes and the mobile and stationary phase. PCA allows the relationships between compounds (the observations) and their retention parameters (the variables) to be visualised in usually just two or three dimensions. PLS can be used to model quantitative structure-retention relationships (QSRRs) and may lead to better understanding of retention and selectivity changes in chromatographic systems. The objective of the study was to investigate the chromatographic behaviour of basic compounds under optimised gradient conditions using octadecyl high performance liquid chromatography (HPLC) columns designed for high pH separations. Three pharmaceutical mixtures were analysed by linear gradient reverse phase HPLC (RP-HPLC) at high pH using ammonia as a pH modifier, and methanol and/or acetonitrile as the organic modifier. The separations were carried out on three octadecyl columns: Waters XTerra MS C18, Agilent Zorbax Extend C18 and Thermo Hypersil-Keystone BetaBasic-18. Multivariate PCA and PLS modelling were employed to explore and explain the differences in selectivity between the chromatographic systems studied when the basic compounds were analysed under the high pH conditions. The interactions between the analytes and the mobile–stationary phases were described by relating the compound molecular descriptors with the selectivity of each chromatographic system. The selectivity differences between the chromatographic systems were identified.