Mass Spectral Vector Comparison for Rapid Sample Similarity
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Mass spectrometry (MS) devices face challenges in quickly and efficiently identifying the similarity of a sample to known compounds, as existing methods require detailed analysis that can be time-consuming and complex, making them impractical for real-time or near-real-time applications.
Innovation Solution
A system that analyzes a sample using mass spectrometry, breaks down the spectrums into bins, compares key peaks from the sample to a library of known compounds by representing them as vectors and calculating similarity based on the angle between these vectors, allowing for rapid identification of similarities without the need for probabilistic analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If detailed analysis methods are used to positively identify samples, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent segments the spectrum comparison task by focusing only on key peaks rather than analyzing the entire spectrum. This selective approach divides the complex identification problem into manageable parts, enabling faster comparison while maintaining sufficient accuracy for similarity determination.
Solution Approach 2:
The patent applies partial action by performing only the necessary comparisons needed to determine similarity - comparing key peaks against library compounds without conducting a complete positive identification analysis. This partial analysis achieves the goal of similarity assessment without the time cost of full identification.
2Measurement precision
If complex analysis methods are used to provide detailed sample information, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent extracts only the essential features needed for similarity comparison - specifically the key peaks from spectra - and compares these against library compounds. This extraction approach simplifies the analysis method by removing unnecessary complexity while retaining the core functionality needed for accurate similarity determination.
Solution Approach 2:
Instead of using complex probabilistic methods to determine identification confidence, the patent inverts the approach by using simple vector angle calculations to directly measure similarity. This inverted methodology achieves accurate results through mathematical simplicity rather than complex statistical analysis.
3Measurement precision
If probabilistic analysis is performed to determine sample identity, then measurement precision is improved, but productivity decreases
Solution Approach 1:
The patent replaces complex probabilistic statistical analysis with a straightforward mechanical calculation - computing the angle between vectors representing the sample and library compounds. This substitution eliminates time-consuming probabilistic computations while maintaining the ability to accurately assess similarity, thereby increasing analysis throughput.
4Measurement precision
If full spectrum comparison is performed, then measurement precision is improved, but productivity decreases
Solution Approach 1:
The patent extracts only the key peaks from the full spectrum for comparison purposes, rather than analyzing every data point in the complete spectrum. This selective extraction maintains comparison accuracy by focusing on the most informative features while dramatically reducing the computational burden, thus improving productivity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables quick and efficient comparison of samples to a library of compounds, providing a binary decision on similarity, which is essential for applications where speed and accuracy are critical, such as in forensic analysis or medical procedures.
Implementation Method 1
Mass spectrometry (MS) and liquid chromatography-mass spectrometry (LC-MS) apparatuses are used to analyze a chemical sample
Implementation Method 2
The sample of interest may be analyzed with the MS device, where the analyzing involves generating a plurality of spectrums for the sample of interest
Data Source
AI summary
Exemplary embodiments provide methods, mediums, and systems for comparing a sample of interest to a library of known compounds to quickly determine how similar the sample is to the compounds in the library. Peaks of interest in the sample data are compared to corresponding peaks in the library compound data. These peaks may be represented as vectors, and an angle between the sample vector and the library vector may be used as a similarity metric. In some embodiments, a cosine similarity may be calculated for the vectors. If the similarity score for a given library compound/sample pair exceed a threshold, then the system determines that the library compound and the sample are similar and takes appropriate action. Various parameters associated with the comparison can be adjusted in order to improve the quality of the results and/or the efficiency of the process.