Biomedical subjects

P V van Zomeren

Publications and source records attributed to P V van Zomeren.

3 recordsLinked to original sources

PubMed2005

Simultaneous resolution of overlapping peaks in high-performance liquid chromatography and micellar electrokinetic chromatography with diode array detection using augmented iterative target transformation factor analysis.

In this paper, augmentation has been applied to data matrices, which originate from hyphenated methods that share the same mode of detection, but use different separation methods, HPLC-DAD and MEKC-DAD. A novel method, wavelength shift eigenstructure tracking (WET), has been proposed for the alignment between the wavelength scale of both detectors. WET proves to be suitable for the detection as well as correction of wavelength shift between both detectors. After correction of the wavelength scale, data obtained on both systems have been augmented and submitted to iterative target transformation factor analysis. Augmented curve resolution provides significantly better estimates of the chromatographic and electrophoretic profiles and spectra than the use of non-augmented curve resolution on HPLC and MEKC data separately. It is particularly useful when the pure fraction of a chromatographic peak is less than 0.10. Finally, the relative weight of MEKC versus HPLC in augmentation may be increased using intensity and noise normalisation. However, since noise normalisation and its accompanying decrease in signal-to-noise ratio leads to a loss of information, and, since intensity normalisation may cause a failure of the augmented curve resolution algorithm, benefits and drawbacks of normalisation should be weighed on a case-by-case basis.

Algorithms↗

PubMed2004

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

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.

Benzodiazepines↗

PubMed2000

Resolution optimisation in micellar electrokinetic chromatography using empirical models.

Theoretical and empirical models can be used to model the migration or separation characteristics in micellar electrokinetic chromatography in order to optimise the resolution. In this paper only empirical models were used, because it is easier and more straightforward to obtain these models. Several empirical approaches for the optimisation of the resolution were compared in order to determine which response should be modelled preferably. The use of models of the effective mobility in combination with average plate numbers proved to be the most suitable approach to optimisation of the resolution, because the relative prediction errors of the models of the effective mobility were a factor of 2-4 smaller than the relative prediction errors of the models of the apparent mobility. Moreover for the least separated peak pair the resolutions based on the models of the apparent and effective mobility showed relative prediction errors that were approximately a factor of 2 smaller than the relative prediction errors of the resolutions based on the models of the resolution and separation factor. The predictions of the separation factor based on the different models generally showed lower prediction errors than the predictions of the corresponding resolutions. Although the relative prediction errors were large, particularly for closely migrating compounds, the empirical approach will probably lead to the optimum separation buffer composition.

Chromatography, Micellar Electrokinetic Capillary↗