Chromatography Pioneer Unveils Strategies for Cutting-Edge Separations
At the HPLC 2025 conference in Bruges, a leading expert shared insights on enhancing the effectiveness of two-dimensional liquid chromatography. Bob Pirok discussed improved method robustness, the value of retention-time alignment, and the potential of machine learning to revolutionize chromatography workflows.
Method Robustness and Data Interpretation
Pirok emphasized the importance of creating strong 2D chromatography methods. He recommended focusing on strategies that enhance system stability. Careful condition selection is also essential to generate consistent, reproducible results.
In the interview, Pirok discussed the importance of aligning retention times for accurate data interpretation. He shared practical approaches and tools that can maintain consistency across multiple analyses.
The Role of Machine Learning
Pirok explored how machine learning and AI can support peak tracking, pattern recognition, and workflow automation. This is especially important when managing complex data sets, and can improve separation effectiveness.
“What positive impact could AI/machine learning have for the chromatography community?”
—Bob Pirok
According to a 2024 report, the global chromatography market is expected to reach $7.5 billion by 2029, driven by advancements in analytical techniques like those discussed by Pirok (MarketsandMarkets).
Expert Profile
Bob W. J. Pirok is an associate professor of analytical chemistry at the Van ‘t Hoff Institute for Molecular Science (HIMS) at the University of Amsterdam, Netherlands. He is also an active member of LCGC International’s editorial advisory board.
These advancements in 2D chromatography, as highlighted by Pirok, show a path toward more efficient analysis. The impact of AI in this area promises a future where complex samples are handled with even greater precision and speed.
