Chromatography Mass Spectrometry Data Analyzer
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Solution Overview
Problem
Existing peak detection algorithms for chromatograms require manual parameter setting by skilled operators, making the process time-consuming and dependent on operator expertise, necessitating an automated solution for efficient analysis of mass information in chromatograph mass spectrometry.
Innovation Solution
A data analyzer that performs statistical analysis on mass spectrum and chromatogram data to correlate signal intensity changes, automatically extracting mass-to-charge ratios with high correlation using techniques like partial least squares, reducing operator burden and improving analysis efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual parameter setting by operator is used for peak detection, then measurement precision can be maintained, but productivity decreases and ease of operation worsens
Solution Approach 1:
The system performs self-service by automatically determining peak detection parameters through statistical analysis of the chromatogram data itself. The algorithm calculates parameters such as peak width, height thresholds, and area measurements automatically without requiring operator intervention, thereby maintaining measurement precision while significantly improving productivity.
Solution Approach 2:
The invention changes the approach from fixed manual parameter setting to dynamic parameter calculation. The system automatically adjusts detection parameters based on the actual data characteristics, transforming the analysis process from operator-dependent to automated, thus resolving the contradiction between precision and productivity.
2Measurement precision
If manual parameter setting by operator is used for peak detection, then measurement precision can be maintained, but ease of operation worsens
Solution Approach 1:
The system eliminates the need for operator expertise by implementing self-service parameter determination. The algorithm automatically analyzes the chromatogram data to identify peaks, calculate areas, and determine thresholds, making the system easy to operate for users regardless of their analytical chemistry background while maintaining consistent measurement precision.
Solution Approach 2:
The invention replaces the mechanical system of manual parameter setting with an automated computational system. Instead of requiring operators to visually inspect and manually define peak parameters, the system uses algorithmic processing to automatically identify and measure peaks, thereby improving ease of operation while preserving measurement precision.
3Ease of operation
If automated analysis is implemented, then ease of operation improves, but measurement precision may decrease
Solution Approach 1:
The system incorporates feedback mechanisms where the automated algorithm continuously refines its parameter calculations based on the actual data patterns. The statistical analysis provides feedback loops that adjust detection thresholds and peak identification criteria, ensuring that automated analysis maintains measurement precision comparable to manual methods while significantly improving ease of operation.
Solution Approach 2:
The invention substitutes manual operator judgment with sophisticated computational algorithms that use statistical methods to automatically extract mass information. This replacement maintains precision through rigorous mathematical processing while eliminating the need for operator skill, thereby resolving the contradiction between ease of operation and measurement precision.
Data Source
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AI summary
A multivariate analysis operation unit (43) represents each of chromatogram data at a specific wavelength λ1 in data acquired by a PDA detector (2) and mass spectrum data repeatedly obtained by a mass spectrometer (3) in the form of a matrix, and then calculates a regression coefficient matrix by performing a PLS operation with a two-dimensional matrix based on the mass spectrum data as an explanatory variable and a one-dimensional matrix based on the chromatogram data as an explained variable. A regression coefficient is obtained with respect to each m/z value, and an m/z value having a high regression coefficient indicates an m/z value of which the chromatogram wavelength at a specific wavelength is similar to an extracted ion chromatogram (XIC). Accordingly, an m/z-value extracting unit (44) compares the regression coefficient with a threshold and extracts a significant m/z value, and an XIC creating unit (46) creates an XIC of the extracted m/z value. By specifying the wavelength λ1 that an operator's target partial chemical structure specifically absorbs, an XIC corresponding to a molecular species containing the partial chemical structure can be obtained without waveform processing manually performed by the operator.