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Automated Robotic Liquid Handling Assembly of Modular DNA Devices

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Published on: December 1, 2017

Peak-Tracking Algorithm for Use in Automated Interpretive Method-Development Tools in Liquid Chromatography.

Bob W J Pirok^1,2, Stef R A Molenaar¹, Liana S Roca¹

¹van 't Hoff Institute for Molecular Sciences, Analytical Chemistry Group , University of Amsterdam , Science Park 904 , 1098 XH Amsterdam , The Netherlands.

Analytical Chemistry

|November 7, 2018

Summary

This summary is machine-generated.

A new algorithm tracks chromatographic peaks across different liquid chromatography-mass spectrometry methods. This tool accurately predicts retention parameters, improving data analysis for complex samples like isomers.

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Area of Science:

Analytical Chemistry
Chromatography
Mass Spectrometry

Background:

Accurate peak identification and tracking are crucial for analyzing complex mixtures in chromatography.
Comparing chromatograms from different methods or samples can be challenging due to variations in retention times and peak shapes.

Purpose of the Study:

To develop a robust peak-tracking algorithm for liquid chromatography-mass spectrometry (LC-MS) data.
To enable reliable pairing of chromatographic peaks across diverse analytical conditions and samples.
To create a fast-track version for efficient method development and optimization in chromatography.

Main Methods:

Developed a peak-tracking algorithm utilizing spectrometric information, statistical moments of chromatographic peaks, and relative retention.
Incorporated time-saving preselection protocols for processing similar chromatograms during method optimization.
Applied the algorithm to analyze chromatograms of samples containing isomers under varying gradient conditions.

Main Results:

The algorithm successfully tracked chromatographic peaks across significantly different LC-MS methods and samples.
A prediction error of less than 1% was achieved for retention parameters derived from automatically tracked peaks.
The fast-track version proved effective for processing chromatograms during mobile-phase gradient optimization.

Conclusions:

The developed peak-tracking algorithm provides accurate and reliable retention parameter prediction.
This method enhances the comparability of chromatographic data obtained under different experimental conditions.
The algorithm is a valuable tool for accelerating chromatographic method development and sample analysis, particularly for isomers.