Pittcon Report: The 2026 LCGC Lifetime Achievement and Emerging Leader in Chromatography Awards Session

Introduction

Over nearly two decades, the LCGC awards have recognized many of the most influential chromatographers in the field, including pioneers such as Walt Jennings, Georges Guiochon, Lloyd Snyder, Joseph Jack Kirkland, Milton Lee, Barry Karger, and Peter Schoenmakers. The 2026 session continued this tradition with five presentations that span the historical landscape of LC–MS, advances in ultrahigh-throughput mass spectrometry, new tools for LC–MS method development, and the growing role of artificial intelligence in chromatographic optimization.

The Evolution of Today’s LC–MS Techniques

The session opened with the 2026 LCGC Lifetime Achievement Award Lecture, presented by Jack Henion, emeritus professor of toxicology at Cornell University and co-founder of Advion Biosciences. Henion’s lecture traced the remarkable evolution of liquid chromatography–mass spectrometry (LC–MS), one of the most powerful analytical techniques used today across pharmaceutical, environmental, forensic, clinical, and biochemical applications.

Henion began by describing the early challenges faced in the late 1970s when scientists attempted to connect high-performance liquid chromatography to the high-vacuum ion sources required for mass spectrometry. These early efforts were memorably characterized by Patrick Arpino’s famous 1981 cartoon describing LC–MS as a “difficult courtship.” Initial approaches such as direct liquid introduction (DLI), particle beam interfaces, and thermospray ionization attempted to bridge this gap, each offering incremental progress but also practical limitations.

The breakthrough came with the development of atmospheric pressure ionization (API) techniques. Henion explained how atmospheric pressure chemical ionization (APCI) and electrospray ionization (ESI) transformed the field by generating ions at atmospheric pressure and efficiently transferring them into the mass spectrometer. These innovations enabled the widespread adoption of LC–MS across many instrument platforms, from single-quadrupole systems to triple quadrupoles, quadrupole–time-of-flight instruments, and orbitrap high-resolution systems.

Henion concluded by presenting several modern applications of LC–MS technology, including recent research exploring mobile laboratory systems for breath analysis of marijuana impairment using compact LC–MS instrumentation. His lecture provided both a historical perspective and a forward-looking view of LC–MS innovation.

Two High-Speed Separation Alternatives to HPLC for Ultra High Throughput Mass Spectrometry

The second presentation, delivered by Thomas Covey of Sciex, examined emerging technologies designed to meet the extreme throughput demands of modern drug discovery workflows. In many pharmaceutical screening environments, millions of samples must be analyzed rapidly, placing pressure on analytical techniques to operate at unprecedented speeds.

Covey described how acoustic ejection mass spectrometry (AEMS) has become a key solution for such applications. In AEMS systems, nanoliter volumes of liquid samples are acoustically ejected from microtiter plates and delivered directly into a mass spectrometer through an open port interface (OPI). This approach eliminates chromatographic separation and allows analysis rates of one sample per second, with demonstrations showing speeds of up to six samples per second and theoretical feasibility approaching twenty samples per second.

However, the absence of chromatographic separation introduces challenges, particularly ionization suppression and the inability to distinguish structural isomers. Covey addressed these issues by presenting two technologies designed to operate within the extremely short duty cycle of AEMS.

First, he discusses differential ion mobility spectrometry using clustering agents to separate isomeric species based on differences in gas-phase ion–molecule interactions. This method enables separation of compounds such as citrate and isocitrate within approximately 10 milliseconds. Second, he introduced a novel magnetohydrodynamic sample preparation technique using rapidly rotating ferrimagnetic beads driven by magnetic fields. The resulting turbulent flow dramatically accelerates extraction and reaction kinetics, increasing mixing efficiency by roughly tenfold compared to conventional approaches.

Together, these strategies illustrate how separation science is adapting to the demands of ultrahigh-throughput mass spectrometry.

SprayDx—A New Tool for Gradient LC–MS Method Development

In the third talk, Richard King, co-founder of PharmaCadence Analytical Services, presented a new strategy for addressing one of the persistent challenges in LC–MS: ionization variability during electrospray ionization.

Ion suppression and other ionization artifacts frequently complicate LC–MS method development. Analysts must often balance chromatographic separation with ionization efficiency, yet the chromatographic signals associated with interfering compounds are not always visible in the mass spectrometer. This limitation makes optimization of gradient conditions difficult.

King introduced SprayDx, a method that leverages solvent cluster ions naturally produced during atmospheric pressure ionization. As solvent clusters enter the mass spectrometer, they undergo declustering through thermal energy and collisions with background gas molecules. By monitoring the remnants of these clusters rather than analyte signals, SprayDx generates a signal that reflects ionization conditions during gradient runs.

This approach allows analysts to visualize changes in ion formation in real time without the need for post-column additives or tracer compounds in the mobile phase. The resulting “cluster chromatogram” highlights regions where ionization suppression or enhancement occurs.

King demonstrated how SprayDx can accelerate gradient optimization and help analysts design LC–MS methods that minimize ionization interference while preserving chromatographic resolution. The technique ultimately enables faster development of robust quantitative methods for complex trace analysis.

Guiding Machine Learning Algorithms in Automation for LC–MS Method Development

The fourth presentation featured the 2026 Emerging Leader Award lecture delivered by Bob W. J. Pirok, associate professor at the University of Amsterdam. Pirok’s research focuses on applying chemometrics and machine learning (ML) to analytical chemistry, particularly in multidimensional chromatography and automated method development.

His lecture explored how Bayesian optimization (BO) algorithms can automate LC–MS method development. In these systems, the algorithm iteratively selects experimental conditions, analyzes the resulting chromatographic performance, and learns how to propose improved conditions in a closed-loop workflow. Platforms such as AutoLC have demonstrated that fully unsupervised method development is feasible.

Pirok emphasized that a critical component of Bayesian optimization is the kernel, the mathematical function that defines how the algorithm models relationships between experimental parameters and chromatographic responses. Despite its importance, kernel selection is often treated generically.

He examined several kernel families—including default kernels, ANOVA-style kernels, stick-breaking kernels, and entropy-search portfolios—and explains how each influences the algorithm’s learning behavior. Because chromatographic responses follow known physicochemical relationships, incorporating this domain knowledge into kernel design can significantly improve optimization efficiency.

Pirok outlined a framework for evaluating kernel suitability and argued that knowledge-guided kernels represent an important next step in AI-driven chromatography. By embedding chromatographic understanding directly into machine-learning models, automated method development can become more reliable and efficient.

Using Chromatographic Knowledge to Construct Landing Platforms for Efficient Method-Development Strategies

The final talk of the session was delivered by Peter Schoenmakers, professor of analytical chemistry at the University of Amsterdam and recipient of the 2023 LCGC Lifetime Achievement Award. Schoenmakers extended the discussion of AI and automation in chromatography by emphasizing the importance of chromatographic knowledge in guiding these new computational tools.

Schoenmakers explained that the greatest bottleneck in systematic method development is the time required for each chromatographic experiment. Modern approaches address this challenge by extracting the maximum information from each experiment and supplementing experimental data with simulated chromatographic data.

Interpretive strategies based on retention modeling have dramatically accelerated method development, transforming workflows from what Schoenmakers described metaphorically as “bicycle speed” to “car speed.” Hybrid approaches such as Bayesian optimization push performance even further—toward “airplane speed.”

However, he argues that the success of these advanced optimization strategies depends critically on establishing effective starting conditions and targets, which he likened to building “airports” where optimization processes can take off and land. Without thoughtful selection of starting parameters or clear definitions of optimal performance criteria, automated algorithms may converge to suboptimal solutions.

Schoenmakers concluded by encouraging chromatographers to integrate expert knowledge with artificial intelligence, ensuring that the next generation of automated method development systems remains grounded in chemical understanding.

Closing Remarks

The 2026 LCGC International Awards Session highlighted both the historical foundations and the emerging future of separation science. From Jack Henion’s retrospective on the birth of LC–MS to discussions of ultrafast screening technologies, innovative LC–MS diagnostics, and AI-driven optimization strategies, the session demonstrated how chromatography continues to advance at the intersection of instrumentation, computation, and chemical insight.

Together, these presentations celebrated the achievements of Jack Henion and Bob W. J. Pirok, while underscoring the vibrant innovation that continues to shape the field of analytical separations.