Chromatogram Peak Separation Using 3D Mass Spectrometry Data
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Solution Overview
Problem
Existing methods for separating overlapping peaks in chromatograms require a significant amount of time when multiple component peaks are present, due to the unknown number of peaks and the adjustment of numerous model function variables, especially with functions like BEMG, which increases computation time.
Innovation Solution
A method and system that processes chromatogram data by preparing model functions based on the measured number of component peaks, adjusting peak-width variables, and determining similarity to efficiently separate overlapping peaks, using retention time, mass-to-charge ratio, and signal intensity data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the number of component peaks is assumed to be one initially and model functions are fitted iteratively, then the method can handle unknown peak numbers, but the processing time becomes excessively long when multiple peaks are present
Solution Approach 1:
The patent applies preliminary action by using three-dimensional mass spectrometry data to pre-identify the number of component peaks before performing chromatogram fitting. This preliminary identification step avoids the time-consuming iterative process of assuming peak numbers sequentially, as the mass spec data already provides information about the actual number of components present in the mixture.
Solution Approach 2:
The patent introduces mass spectrometry data as an intermediary to bridge the gap between unknown peak numbers and accurate peak separation. The mass spec information acts as a mediator that provides independent verification of component presence, allowing the chromatogram analysis to proceed with known peak numbers rather than through iterative guessing.
2Measurement precision
If multiple model functions with multiple variables are prepared to account for multiple component peaks, then the accuracy of peak separation improves, but the computation time increases significantly
Solution Approach 1:
The patent performs preliminary identification of the correct number of model functions needed using mass spectrometry data before initiating the fitting process. This eliminates the need to prepare and adjust multiple sets of model functions with different numbers of variables, as the appropriate number is determined in advance by the orthogonal mass spec information.
Solution Approach 2:
The patent uses mass spectrometry data to serve multiple functions: identifying the number of components, verifying their presence, and providing retention time correlations. This multi-functional use of the mass spec data eliminates the need for separate iterative trials with different numbers of model functions, reducing computation time while maintaining accuracy.
Data Source
AI summary
First data includes chromatogram data consisting of the retention time and the signal intensity of transmitted/absorbed light acquired. Second data is three-dimensional data consisting of the retention time, mass-to-charge ratio and signal intensity. A first retention-time range where a target peak is present and the waveform of the target peak are determined in a chromatogram created from the first data. The number of component peaks within a second retention-time range which corresponds to the first retention-time range in a three-dimensional graph created from the second data is acquired as a measured component-peak number. Model functions whose number equals the measured component-peak number are created, each function involving a peak-width variable representing the width of a component peak. The model functions are gradually modified by adjusting their peak-width variables until the degree of similarity in waveform between the target peak and a model peak expressed by those functions exceeds a threshold.