Abstract

A new strategy for the computer-assisted methods development in the reversed-phase liquid chromatographic separations of unknown sample mixtures has been developed using the latent spectral information in chromatogram raw data files of appropriately designed experiments, rather than resorting to elemental information functions (e.g., the number of peaks in chromatograms or similar criteria). The strategy developed allows unification of the approach for samples of both known and unknown composition and, thus, provide a general strategy for computer-aided tools in the chromatography laboratory. The operation principle of this strategy departs from extracting the spectra of components in the mixture chromatograms by resorting to multivariate curve resolution-alternating least squares (MCR-ALS). This technique allows the estimation of the true spectra for the individual components except when they have identical spectra or are fully overlapped. Thus, a convenient experimental design will try to perform separations of the sample mixture having at least partial resolution of components in some runs. This will allow estimating the spectra of components and, then, assign these components to the peaks in each run chromatogram. In this way, a retention model can be built for each component so computerized optimization process can be developed to provide the chromatographer with the best possible separation programs. Following this approach, strategies for sample mixtures of known and unknown composition are only different in the need of an initial spectrum discovery process for unknown mixtures and therefore a real general approach for the computer-assisted LC methods development is now available for the first time.

Highlights

  • Computerized method development in high-performance liquid chromatography (HPLC) emerged as soon as the computers entered the analytical laboratory in the past 1970s

  • Because no information is available about the sample components, the maxplot representation is used to show the run chromatograms and to perform the peak picking process in order to avoid false negatives that could take place by an inappropriate selection of the wavelength channel

  • Excluding the false peaks appearing before the broad signal at the beginning of the chromatograms in column A, no more than 7–8 peaks are evident in most runs, in some of them, some shoulders and unresolved peaks clearly indicate that the sample would contain more than 8 components

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Summary

Introduction

Computerized method development in high-performance liquid chromatography (HPLC) emerged as soon as the computers entered the analytical laboratory in the past 1970s. Our approach was based on considering small data sections in chromatograms separated by baseline signals These sections, or peak clusters, may contain one or several components but, in any case, can be processed by the MCR-ALS algorithms described in the literature [20, 21]. This second step in the strategy consists in obtaining the second derivative of the chromatographic signal and extract sections of the chromatogram delimited by baseline points. Data sets used in case studies are publicly available in the repository of the University of Santiago de Compostela under the ChromChem research Group materials storage [35]

Results and discussion
False positive components
Unassigned components
Inconsistent retention data
Alerts on apparently well-fitted data
Conclusions

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