Cardiovascular Risk Prediction Using Multi-Biomarker Capture Assays
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Solution Overview
Problem
Current biomarker detection methods for cardiovascular events are limited by low detection sensitivity, irreproducibility, and inability to detect low-abundance proteins, leading to inadequate prediction of cardiovascular risk, which hinders personalized and timely interventions.
Innovation Solution
A method involving a set of capture reagents specific to biomarkers such as sTREM1, MMP-12, N-terminal pro-BNP, and others, used in a single sample, single assay format to detect multiple protein biomarkers associated with cardiovascular disease processes, enabling accurate prediction of cardiovascular events within a defined period.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional biomarker detection methods are used, then the detection process is simple, but the detection sensitivity is low and cannot detect low-abundance proteins
Solution Approach 1:
The patent segments the detection process into multiple stages: sample preparation with depletion of abundant proteins, affinity capture of target biomarkers, and sequential washing/detection steps. This segmentation allows each stage to be optimized independently, achieving high sensitivity for low-abundance proteins while maintaining manageable complexity through systematic process design
Solution Approach 2:
The patent introduces affinity capture reagents (antibodies, aptamers, or ligands) as intermediaries between the complex biological sample and the detection system. These intermediaries specifically bind to target biomarkers, enabling selective enrichment and detection of low-abundance proteins while filtering out interfering substances, thus improving detection sensitivity without proportionally increasing complexity
2Measurement precision
If existing risk factors and biomarkers are used, then the prediction model is simple to implement, but the predictive performance is modest with AUC of only 0.75
Solution Approach 1:
The patent combines multiple independent biomarker detection assays into a single integrated predictive model. By merging data from several biomarkers (including low-abundance proteins that were previously undetectable) with conventional risk factors, the model achieves superior predictive performance (AUC >0.80) while maintaining clinical usability through standardized scoring systems
Solution Approach 2:
The patent creates a composite predictive model that integrates heterogeneous data types: conventional clinical risk factors, multiple protein biomarker levels, and their interactions. This composite approach leverages the complementary strengths of different biomarkers, achieving high predictive accuracy without requiring overly complex computational algorithms, as the model can be implemented using established statistical methods
3Loss of time
If the Framingham equation is used for risk calculation, then the calculation method is straightforward, but it is too long term (10-year risk) and not responsive to near-term interventions
Solution Approach 1:
The patent performs preliminary detection and quantification of multiple biomarkers that reflect current physiological state and immediate risk, rather than relying on long-term historical data. This allows the model to provide near-term risk assessment (1-5 years) that is responsive to recent lifestyle changes and interventions, while maintaining straightforward calculation methods through standardized biomarker panels and scoring systems
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 approach enhances the detection of cardiovascular risk by improving sensitivity and reproducibility, allowing for personalized and timely interventions, thereby improving patient outcomes and resource allocation.
Implementation Method 1
contacting the sample from the subject with a set of capture reagents, wherein each capture reagent specifically binds to a different biomarker protein
Data Source
AI summary
Biomarkers, methods, devices, reagents, systems, and kits used to assess an individual for the prediction of risk of developing a primary or secondary Cardiovascular (CV) event over a 4 year period are provided.