LC/MS Peak Picking With AI Chromatogram Preprocessing
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Solution Overview
Problem
Existing AI algorithms struggle to accurately identify and quantify peaks in complex biological samples due to contaminations, impurities, and matrix effects in LC/MS data, leading to reduced performance in peak picking.
Innovation Solution
A method involving pre-processing steps to generate an artificial chromatogram by subtracting median values from zero samples, applying retention time windows, scaling, smoothing, and using AI algorithms like U-net to enhance peak detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If AI algorithms are used for peak picking in complex biological samples, then automation and processing speed are improved, but measurement precision deteriorates due to contaminations, impurities, and matrix effects
Solution Approach 1:
The patent applies preliminary action by performing pre-processing steps before AI-based peak picking. Specifically, median subtraction of zero samples is performed to remove background contaminations and matrix effects before the AI algorithm processes the chromatogram. This preliminary cleaning action improves the precision of subsequent automated peak detection.
2Measurement precision
If pre-processing steps are added to clean up the chromatogram, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent applies parameter changes by modifying the chromatogram data through mathematical operations (median subtraction) rather than adding physical components. The pre-processing step changes the parameter values of the signal by subtracting the median background from zero samples, thereby improving peak detection accuracy without significantly increasing system complexity.
3Device complexity
If traditional peak picking methods are used without pre-processing, then device complexity is reduced, but measurement precision deteriorates in complex samples
Solution Approach 1:
The patent introduces a preliminary action step (median subtraction of zero samples) that can be integrated into existing AI-based peak picking workflows. This addition maintains the automation and simplicity of the overall system while significantly improving measurement precision in complex biological samples by removing background contaminations.
Data Source
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AI summary
The present invention relates to a new method for peak picking by using at least one AI algorithm wherein the presence of at least one compound corresponds to the regions in a Liquid Chromatography/Mass Spectrometry (LC/MS) chromatogram by detecting and identifying peaks with pre-processing steps for cleaning up the chromatogram in order to improve the results of the AI algorithm on complex samples.