Max Besenhard explains how hybrid mechanistic and machine learning models can make HPLC method development quicker, more robust and ready for autonomous digital twins.
News|Articles|June 15, 2026
Rethinking Food Testing with Dried Spot Microsampling
Author(s)Maria Halabalaki, Kate Jones
LCGC International spoke to Maria Halabalaki, an associate professor at the National and Kapodistrian University of Athens, about how dried spot microsampling could transform food testing.
Advertisement
Advertisement
Q. How does the automated DBS extraction system work and what are its advantages over manual methods?
Related to this article
Sebastian Böcker discusses taking retention prediction beyond reversed-phase to HILIC, what changes elution order in method transfer, and sharing data via RepoRT.
Sebastian Böcker discusses how predicting retention order, not time, makes liquid chromatography retention time prediction transferable across laboratories.
How feasible is it to integrate this Bayesian graph-theory methodology into existing commercial chromatography software workflows for semi-automated data curation in routine analytical laboratories?
Gabriel Vivó-Truyols outlines the benefits and challenges of combining graph theory with Bayesian statistics to automate peak assignment and alignment.
Gabriel Vivó-Truyols from the Spanish Council for Scientific Research, Madrid, Spain. discusses his work on using graph theory and Bayesian statistics for peak assignment and chromatographic alignment.
Leon Niezen and Gert Desmet discuss uncertainty-driven LC method development, peak overlap, and moving from in silico to real data.
Advertisement
Advertisement