Origin-Adjusted LC-MS Quantification for Endogenous Biomarkers
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for accurately quantifying biomarkers in diagnostics and drug development face challenges due to the need for surrogacy, which complicates procedures and limits reliability, particularly in determining endogenous analyte concentrations.
Innovation Solution
The use of mass spectrometry with an origin-adjusted approach, where a sample is spiked with known concentrations of the analyte of interest, allowing for linear regression calculations that exclude the concentration-intercept, shifting the calibration line to intercept the origin, thereby accurately determining endogenous analyte concentrations without relying on surrogates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If surrogate methods are used to quantify biomarkers, then the measurement can be performed, but the procedure becomes complicated and reliability is limited
Solution Approach 1:
The invention extracts and eliminates the surrogate element from the quantification procedure. By directly measuring endogenous analytes using mass spectrometry with origin-adjusted calibration, the method removes the need for surrogate analytes, parallelism checks, and complex correction factors, thereby simplifying the procedure while maintaining or improving reliability
Solution Approach 2:
The invention introduces mass spectrometry with origin-adjusted calibration as a direct measurement intermediary, replacing the surrogate-based indirect measurement approach. This allows for direct quantification of endogenous analytes without requiring surrogate compounds, eliminating the complexity associated with surrogate method validation and application
2Measurement precision
If standard addition technique is used with linear regression including concentration-intercept, then the calibration can be constructed, but the endogenous concentration cannot be directly determined
Solution Approach 1:
The invention inverts the traditional standard addition approach by forcing the calibration line to pass through the origin (0,0) rather than including an intercept term. This inversion allows the x-intercept of the calibration line to directly represent the endogenous analyte concentration, eliminating the need for separate calculation steps and making the determination more straightforward
Solution Approach 2:
The invention changes the calibration model parameter by excluding the intercept term from the linear regression equation. This parameter modification transforms the calibration approach from y = mx + b to y = mx, where the x-intercept directly provides the endogenous concentration, simplifying both the calculation process and interpretation of results
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
This method provides increased accuracy and reliability in quantifying biomarkers by eliminating the need for surrogates and parallelism checks, ensuring precise interpolation of analyte concentrations, even at lower concentrations.
Implementation Method 1
the MS analyzer may ionize samples using electrospray ionization (ESI) such that molecules are detected in a positive or a negative, fragmentation mode
Implementation Method 2
The separation may be performed using an organic-aqueous solvent gradient and/or a reverse-phase liquid chromatography (LC) column
Implementation Method 3
the MS analyzer may be configured to further provide a chromatogram of absorption to indicate relative concentrations of the analyte of interest plus the spiked concentrations of the analyte of interest
Data Source
AI summary
The field of biomarker detection and drug development is constantly in pursuit of more accurate, reliable, rapid, and inexpensive technology. Methods and systems for quantifying an analyte of interest disclosed herein include steps of obtaining a sample, spiking the sample with the analyte of interest, separating and detecting the sample using LC-MS, and calculating a linear regression of a sample using analytical techniques are described herein. Further, these methods and systems preclude the use and/or calculation of endogenous amounts of analyte present in a sample, yielding to methods and systems that provide increased speed and accuracy for measuring sample analytes.