Optimisation of high-performance liquid chromatography with diode array detection using an automatic peak tracking procedure based on augmented iterative target transformation factor analysis

Abstract

An automated method for the optimisation of high-performance liquid chromatography is developed. First of all, the sample of interest is analysed with various eluent compositions. All obtained data are combined into one augmented data matrix. Subsequently, augmented iterative target transformation factor analysis performs the integrated tasks of curve resolution and peak tracking. Since this type of curve resolution processes all data at once, it can deal with strong peak overlap and reveal the correspondence of compounds between runs, i.e. peak tracking. The retention time and peak width at half height for each component of the sample are determined for every eluent composition. Next, models are built for the retention time and the peak width at half height. These models are used to predict the resolution and the analysis time for each point in factor space. Finally, a multi-criterion decision-making method, Pareto optimality, is used to find the optimum. The method completes all calculations within a few minutes and without user intervention. By means of this procedure, a mixture of three benzodiazepines is successfully separated using a ternary mobile phase. There are two requirements for the automated optimisation method to work correctly. Firstly, all components of the sample must have sufficiently different spectra. Secondly, each compound should have the same spectrum under all experimental conditions.