Certainty Deduction Model for Multiparametric Biomarker Quality Control
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Solution Overview
Problem
Current quality control procedures for multiparametric biochemical tests are inadequate, as they are often based on singleton test methods, which are overly stringent and do not account for the statistical tolerance of errors in multiparametric tests, leading to inefficient and inaccurate quality assessments.
Innovation Solution
A system and method for certainty estimation in medical conclusions that processes data from multiple biomarkers of control samples to provide a certainty deduction model, incorporating measurement entity performance characteristics and group models to enhance the reliability of multiparametric test results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If singleton quality control procedures are applied to multiparametric tests, then quality control stringency is maintained, but the procedures become overly stringent and inefficient
Solution Approach 1:
The patent changes the parameters of quality control from singleton-based to multiparametric-based approaches. Instead of controlling each biomarker separately with stringent singleton procedures, the system evaluates the combined statistical output of multiple biomarkers, allowing for more efficient quality control that accounts for the statistical tolerance of errors in multiparametric tests.
Solution Approach 2:
The invention creates a universal quality control framework that can handle both singleton and multiparametric tests through a single system. The quality control procedure universally applies statistical evaluation to any number of biomarkers, making it adaptable to different test configurations while maintaining appropriate stringency for each context.
2Productivity
If multiple biomarkers are measured simultaneously in multiplexed assays, then measurement efficiency increases, but the complexity of calibration and quality control procedures increases
Solution Approach 1:
The patent segments the quality control evaluation into separate statistical components for each biomarker while integrating them through the multiparametric statistical model. This allows independent analysis of each biomarker's performance characteristics while maintaining the overall efficiency benefits of multiplexed measurement.
Solution Approach 2:
The invention introduces statistical evaluation models as intermediaries between the multiplexed measurement system and quality control procedures. These statistical models mediate the complexity by providing a framework for evaluating multiple biomarkers simultaneously without requiring proportional increases in calibration complexity for each additional marker.
3Adaptability or versatility
If different laboratories use different analytical instruments for the same assay, then measurement versatility improves, but lab-to-lab and instrument-to-instrument variation increases
Solution Approach 1:
The patent changes the approach to handling measurement variation by shifting from assuming uniform measurement characteristics across laboratories to explicitly modeling and evaluating the statistical parameters of each laboratory's measurements. This allows the system to accommodate different instruments while maintaining result consistency through statistical evaluation of performance characteristics.
Data Source
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AI summary
Methods for providing certainty estimation support and certainty estimations, respectively, in medical conclusions comprises measuring (S10) of quantities related to concentrations of at least three different biomarkers of control samples, sending (S12), receiving (S20) and storing (S22) the same in an archive memory. Stored data is retrieved (S26) as a response to a sending (S14) and receiving (S24) of a request for a certainty deduction model and is processed (S28) into the certainty deduction model. The certainty deduction model is outputted (S30) and received (S17) and a certainty estimate for medical conclusions made from measurements of samples together with the control samples is provided (S19) based on the received certainty deduction model. The certainty deduction model comprises a group model, determined for all control samples, and measurement entity performance characteristics, determined for measurements related to the first measurement entity that are performed less than a predetermined time ago.