A Modeling Approach for Orthogonality of Comprehensive Two-Dimensional Separations

Method development of comprehensive two-dimensional liquid chromatography: A new metric for preliminary column selection

To elevate the separation performance, two-dimensional liquid chromatography (2D-LC) uses two chromatographic columns with different stationary phases to diversify solute interactions with the resin, hence providing a second "dimension" to solute-specific separation. Developing methods for 2D-LC starts therefore with preliminary column selection. Selecting columns that yield (metaphorically) orthogonal dimensions is of utmost importance, but remains challenging. Although several metrics exist to quantify column orthogonality, currently there is no established methodology, and none of the existing methods accounts for the non-homogeneity of peak band broadening across each separation dimension. In this work, we propose a new approach to select columns a priori. This approach is based on critical resolution distribution statistics and implicitly accounts for local peak crowding and peak band broadening. Furthermore, we assess the importance of preliminary column selection during in-silico method development and multi-objective optimization of comprehensive 2D-LC. The comparison of the multi-objective Pareto fronts revealed that column pairs selected with our approach provide better separation quality and reduce analysis time compared to column selections via the most established metrics in the literature. Our results prove the importance of preliminary column selection for method development and optimization of 2D-LC systems, and they also show that choosing the right orthogonality metric (such as that proposed here) is crucial.

Comprehensive Two-Dimensional Gas Chromatography as a Bioanalytical Platform for Drug Discovery and Analysis

Over the last decades, comprehensive two-dimensional gas chromatography (GC×GC) has emerged as a significant separation tool for high-resolution analysis of disease-associated metabolites and pharmaceutically relevant molecules. This review highlights recent advances of GC×GC with different detection modalities for drug discovery and analysis, which ideally improve the screening and identification of disease biomarkers, as well as monitoring of therapeutic responses to treatment in complex biological matrixes. Selected recent GC×GC applications that focus on such biomarkers and metabolite profiling of the effects of drug administration are covered. In particular, the technical overview of recent GC×GC implementation with hyphenation to the key mass spectrometry (MS) technologies that provide the benefit of enhanced separation dimension analysis with MS domain differentiation is discussed. We conclude by highlighting the challenges in GC×GC for drug discovery and development with perspectives on future trends.

Comprehensive two-dimensional gas chromatography with mass spectrometry: an advanced bioanalytical technique for clinical metabolomics studies

This review highlights the current state of knowledge in the development of GC × GC-MS for the analysis of clinical metabolites. Selected applications are described as well as our perspectives on current challenges and potential future directions.

Techniques and application in comprehensive multidimensional gas chromatography - mass spectrometry

In contrast to the well-known comprehensive two-dimensional gas chromatography (GC×GC) method, it is possible to define comprehensive multidimensional gas chromatography. 'Comprehensiveness' relates to analysis of the whole sample. Two-dimensional and multidimensional here refer to the use of at least two separation stages for analysis, however comprehensive 2DGC now appears to be reserved for the GC×GC method. This may be differentiated from comprehensive MDGC (CMDGC) simply by the analysis time assigned to the second (²D) column, although there does not appear to be a specific definition that relates to this analysis time parameter. A number of different implementation protocols for comprehensive MDGC are described here, that may involve either a single, or multiple, injection(s). In all cases, independent retention must be achieved on each dimension to ensure the probability of enhanced separation. An original application of a crude oil sample is presented to illustrate development of the MDGC approach that incorporates two Deans switches (DS) and a cryogenic trapping approach, performed using a sequential heart-cut (H/C) event method incremented by 0.5 min for each injection; a total of 40 injections is used to analyse the total sample. The higher peak capacity and consequently greater resolution on the long ²D column is illustrated, compared with that expected for conventional GC×GC, with tentative identification in order to classify chemical classes. Incorporating an approach to acquiring retention indices may be implemented, although its utility for petroleum hydrocarbons is limited. Structured groupings of different chemical classes, as exemplified by mono and diaromatics for the crude oil sample, were noted.

Recent applications of chemometrics in one- and two-dimensional chromatography

The proliferation of increasingly more sophisticated analytical separation systems, often incorporating increasingly more powerful detection techniques, such as high-resolution mass spectrometry, causes an urgent need for highly efficient data-analysis and optimization strategies. This is especially true for comprehensive two-dimensional chromatography applied to the separation of very complex samples. In this contribution, the requirement for chemometric tools is explained and the latest developments in approaches for (pre-)processing and analyzing data arising from one- and two-dimensional chromatography systems are reviewed. The final part of this review focuses on the application of chemometrics for method development and optimization.