<ul>
<li>🎤 Presenter: Tijmen Bos¹, Jim Boelrijk², Stef Molenaar², Dwight Stoll³, Bob Pirok²´³ (¹Vrije Universiteit Amsterdam, Amsterdam, Netherlands. ²University of Amsterdam, Amsterdam, Netherlands. ³Gustavus Adolphus College, Saint Peter, USA)</li>
</ul>
<blockquote>
💡 Book in your calendar: <a href="https://gcms.labrulez.com/events/436">15th Multidimensional Chromatography Workshop (MDCW) January 2024</a>
</blockquote>
<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/15th_Multidimensional_Chromatography_MDC_Workshop_Main_Banner_45f9ba053d/15th-Multidimensional-Chromatography-(MDC)-Workshop-Main-Banner.jpg" alt="15th Multidimensional Chromatography (MDC) Workshop 2024"/>
<h3>Abstract</h3>
One and <a href="https://lcms.labrulez.com/library?instrumentationItems=39">two-dimensional liquid chromatography</a> (LC) technology is making remarkable advancements, however the number of potential users remains lagging behind for 2D separations. A prime obstacle for large-scale usage is the considerable investment needed for method development and data processing. Automation in any step of the method development reduces the required investment.
Recently a comprehensive, modular, closed-loop and interpretive algorithm for automated LC method development for complex samples of unknown composition was developed. The idea of these computer platforms is that they can directly and iteratively program the LC with new method parameters obtained from previous raw experimental data until convergence of a specified objective function was reached. Using peak tracking, multi-start regression, retention modelling and Bayesian optimization, such algorithms are capable to automate the selection of several method parameters.
This presentation will discuss the current challenges to scale this automated method development technology to heart-cut and comprehensive 2D-LC separations.

Unsupervised optimization of heart-cut and comprehensive 2D-LC separations (Bob Pirok, MDCW 2023)

<ul>
<li>🎤 Presenter: Marie Pardon, Soraya Chapel, Peter de Witte, Deirdre Cabooter (KU Leuven, Leuven, Belgium)</li>
</ul>
<blockquote>
💡 Book in your calendar: <a href="https://gcms.labrulez.com/events/436">15th Multidimensional Chromatography Workshop (MDCW) January 2024</a>
</blockquote>
<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/15th_Multidimensional_Chromatography_MDC_Workshop_Main_Banner_45f9ba053d/15th-Multidimensional-Chromatography-(MDC)-Workshop-Main-Banner.jpg" alt="15th Multidimensional Chromatography (MDC) Workshop 2024"/>
<h3>Abstract</h3>
<a href="https://lcms.labrulez.com/library?instrumentationItems=39">Two-dimensional liquid chromatography (2D-LC)</a> is becoming increasingly popular for the analysis of complex samples, which is partly due to the recent introduction of commercial 2D-LC systems. One of these systems employs active solvent modulation (ASM) to deal with the mobile phase incompatibility between highly orthogonal retention mechanisms, such as <a href="https://lcms.labrulez.com/library?search=HILIC">hydrophilic interaction liquid chromatography (HILIC)</a> and reversed-phase LC (RPLC). However, clear recommendations or guidelines regarding the optimal use of ASM are not available.
Therefore, this study investigates possible configurations for the modulation of HILIC and RPLC using ASM in a selective comprehensive 2D-LC set-up (sHILIC x RPLC) to suggest guidelines for future users.
Using a representative sample, the filling percentage of the sample loops and their loading/unloading configuration, the duration of the ASM phase and the dilution factor (DF) are investigated and optimized. It is observed that maintaining the sample loop filling at maximum 25%, unloading it in backflush mode, and using a DF of 10 with the shortest possible ASM phase results in the best peak shapes, intensities and recoveries for early eluting peaks, while keeping the analysis time minimal.
Based on these results, some general recommendations are made: reduce the sample loop filling, the DF, and the duration of the ASM phase as much as possible, and operate in BF mode, in order to improve peak shapes and save analysis time.
These recommendations could also be applied to other 2D-LC modes, such as LC x LC and LC – LC, and other chromatographic combinations with mobile phase incompatibility issues.

2D-LC with solvent modulation to overcome the mobile phase incompatibility (Marie Pardon, MDCW 2023)

<ul>
<li>🎤 Presenter: Turaj Rahmani, Adriaan Ampe, Frederic Lynen (Ghent University, Gent, Belgium)</li>
</ul>
<blockquote>
💡 Book in your calendar: <a href="https://gcms.labrulez.com/events/436">15th Multidimensional Chromatography Workshop (MDCW) January 2024</a>
</blockquote>
<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/15th_Multidimensional_Chromatography_MDC_Workshop_Main_Banner_45f9ba053d/15th-Multidimensional-Chromatography-(MDC)-Workshop-Main-Banner.jpg" alt="15th Multidimensional Chromatography (MDC) Workshop 2024"/>
<h3>Abstract</h3>
Chirality is a prevalent property found in nature, caused by the presence of a (carbon) chiral center in a molecule. Many molecules with different chirality greatly vary in their chemical properties, therefore the ability for separation and detection of these molecules is of utmost importance in the biomedical and pharmaceutical industries.
However, obtaining effective separation of chiral analytes in complex (biological or synthetic) samples requires high resolving power. Which can be theoretically achieved by <a href="https://lcms.labrulez.com/library?instrumentationItems=39&amp;search=chiral">Comprehensive two-dimensional liquid chromatography (LC x LC)</a>, as this technique would allow for a large increase in peak capacity per unit of time. However finding appropriate solvents for the second dimension might be difficult. The slow speed of chiral separations, on the other hand, has hampered the use of chiral stationary phases as the second dimension in 2D-LC.
In this study, the enantioselective separation of a wide range of medicinal substances (log p: 0.9-4.1) is evaluated using a combination of temperature-responsive and reversed-phase chiral liquid chromatography. Temperature-responsive liquid chromatography (TRLC) in the first dimension enables analysis in purely aqueous conditions, allowing for complete (and more general) focusing of organic solutes prior to second-dimension separation. By combining this with small particle (sub-2 micron) based chiral stationary phases as the second dimension in TRLCxChiral-RPLC, a chiral screening platform may be built, which in principle has a lot of potential for tackling chiral screening challenges.

Temperature-responsive & chiral chromatography for chiral pharmaceuticals (Turaj Rahmani, MDCW 2023)

<ul>
<li>🎤 Presenter: Giorgia Purcaro (Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium)</li>
</ul>
<blockquote>
💡 Book in your calendar: <a href="https://gcms.labrulez.com/events/436">15th Multidimensional Chromatography Workshop (MDCW) January 2024</a>
</blockquote>
<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/15th_Multidimensional_Chromatography_MDC_Workshop_Main_Banner_45f9ba053d/15th-Multidimensional-Chromatography-(MDC)-Workshop-Main-Banner.jpg" alt="15th Multidimensional Chromatography (MDC) Workshop 2024"/>
<h3>Abstract</h3>
The introduction of multidimensional and comprehensive techniques has revealed that complex samples can be hidden behind apparent simple ones. This understanding has pushed many scientists to study possible approaches for further boosting separation power, mainly by adding extra dimensions.
This presentation will focus on the potentialities of a fully integrated and validated <a href="https://gcms.labrulez.com/library?search=LC-GC%C3%97GC">LC-GC×GC</a> platform coupled with a parallel dual detection, i.e., ToFMS and FID. 
The coupling of an LC system with a GC one was first published by Majors in 1980 and the first automated commercial instrument (Dualchrom 3000) was introduced in 1989 by Carlo Erba (Italy). The LC–GC systems were intensively studied in the 1980s and 1990s by Grob and his group, but the system was almost abandoned later. In 1991 Phillips introduced the comprehensive two-dimensional technique (GC×GC), a powerful technique that gained immediate attention and is still growing exponentially. 
The integration of the two two-dimensional techniques provides exponential benefits with an easy, robust and validated setup. The LC-GC×GC platform can provide an enhanced characterization of complex samples reaching efficient sample clean-up and/or a group-type separation of the analytes in the LC dimension and enhanced separation in the <a href="https://labrulez.cz/contact">GC×GC</a> dimension. It has been proved very useful to improve not only the full characterization of complex samples but also to simplify sample pre-treatment and provide more robust and validated routine analysis, particularly in the challenging topic of mineral oil analysis in food.

LC-GC×GC-TOF MS/FID: a multidimensional technique for complex samples (Giorgia Purcaro, MDCW 2023)

<ul>
<li>🎤 Presenter: Arnaud Delobel (R &amp; D and Innovation Director, Quality Assistance SA)</li>
</ul>
<blockquote>
💡 Book in your calendar: <a href="https://gcms.labrulez.com/events/436">15th Multidimensional Chromatography Workshop (MDCW) January 2024</a>
</blockquote>
<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/15th_Multidimensional_Chromatography_MDC_Workshop_Main_Banner_45f9ba053d/15th-Multidimensional-Chromatography-(MDC)-Workshop-Main-Banner.jpg" alt="15th Multidimensional Chromatography (MDC) Workshop 2024"/>
<h3>Table of Content</h3>
<ul>
<li>Quality Assistance sa</li>
<li>2D-LC/MS at Quality Assistance</li>
<li>Multiple Heartcut 2D-LC in practice</li>
<li>Characterisation of ADCs by HIC-RP/MS</li>
<li>Advanced use of 2D-LC/MS with at-column-dilution technology</li>
<li>What’s next?</li>
<li>Take-home messages</li>
</ul>

2D-LC/MS in a regulated biopharma environment: Challenges & applications (Arnaud Delobel, MDCW 2023)

<ul>
<li>🎤 Presenter: Daniel Geschwender¹, Qingping Tao¹, Chase Heble¹, Stephen Reichenbach¹,² (¹GC Image, LLC, Lincoln, USA. ²University of Nebraska, Lincoln, USA)</li>
</ul>
<blockquote>
💡 Book in your calendar: <a href="https://gcms.labrulez.com/events/436">15th Multidimensional Chromatography Workshop (MDCW) January 2024</a>
</blockquote>
<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/15th_Multidimensional_Chromatography_MDC_Workshop_Main_Banner_45f9ba053d/15th-Multidimensional-Chromatography-(MDC)-Workshop-Main-Banner.jpg" alt="15th Multidimensional Chromatography (MDC) Workshop 2024"/>
<h3>Abstract</h3>
Identifying chemical differences among samples is useful for process monitoring, sample classification or identification, correlative determinations, and other important tasks. Multi-dimensional chromatography (including <a href="https://gcms.labrulez.com/library?search=GCxGC">GCxGC</a> and <a href="https://lcms.labrulez.com/library?search=LCxLC">LCxLC</a>) is a powerful technique for highly effective chemical separations of complex mixtures, but it also produces highly complex data that require both interactive and automated comparative analysis methods.
One common case is to compare two types of samples to determine similarities and differences. Our existing side-by-side interactive differencing tool provides both comparative visualization of chromatograms and comprehensive characterization of sample differences down to individual peaks. It allows comparing chemical differences between two samples qualitatively and quantitatively. However, it requires that the analyst specify an initial peak correspondence in order to compute a transform from one retention time space to the other.
We propose a new automated matching algorithm that combines computer vision image registration techniques with the peak matching algorithm utilized in our Investigator framework. Computer vision-based registration provides an intuitive and unsupervised way to identify and match patterns across entire raw chromatograms. This registration computes an initial transform to seed our peak matching algorithm. The <a href="https://gcms.labrulez.com/library?search=peak+matching+algorithm">peak matching algorithm</a> identifies and matches reliable peaks based on several criteria including retention time distance and spectral match scores. This matching is used to compute a refined transform that is then provided to the side-by-side interactive differencing tool in order to compare the chromatograms. We demonstrate the technique to compare across different samples as well as across different detectors using the same sample.

Auto alignment for quantitative pairwise differencing of 2D data (Daniel Geschwender, MDCW 2023)

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