Abstract

The use of step-down gradient elution profiles to improve separation of sucrose caprate regioisomers was investigated as part of the development of a quantitative RP-HPLC analysis method with charged aerosol detection. The investigation was conducted using design-of-experiments methodology and evaluated by multivariate regression analysis. This approach was proven to be useful for systematic method development in HPLC analysis. The gradient elution profiles were described by four variables – two concentration variables and two duration variables. The regression analysis showed that the concentration variables had the most significant effects on retention times, both as individual terms and as part of variable interactions. All the regioisomers exhibited non-linear relationships between eluent acetonitrile concentration and retention time with similar curvatures. Kendall rank correlation coefficients confirmed that the curvatures of the regioisomer curves were highly dependent on each other. Charged aerosol detection provided a mass-sensitivity of 10–100ng for the sucrose fatty acid ester regioisomers. Resolution deviation (RD) was defined as an aggregate objective function for evaluating the separation of three specific sucrose caprate regioisomers with similar elution properties substituted at positions 6-, 3- and 1′-, respectively. The investigation resulted in the development of elution strategies for separation and quantitative RP-HPLC analysis of regioisomers of sucrose caprate with all eight sucrose caprate regioisomers successfully identified. Thus, resolutions above the level of adequacy for quantification, Rs≥1.0, were achieved for all regioisomers, both with isocratic and gradient elution strategies. For isocratic elutions, the best separation was achieved with eluent acetonitrile concentration 34%. Gradient elution resulted in a similar RD, but decreased the analysis time by 7–28%. For the gradient resulting in the most desirable combination of separation and analysis time, the Rs-values ranged from 1.31 to 6.82, and the analysis time was 24min.

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