Nanoarray Breath Sensor for Differential Disease Diagnosis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current disease diagnosis through breath analysis is limited by the inability to differentiate between various diseases using individual volatile organic compounds (VOCs) and lacks a universal system capable of diagnosing multiple diseases simultaneously, often resulting in false positives and negatives due to shared VOCs among different conditions.
Innovation Solution
A system utilizing a combination of cross-reactive nanoarray sensors with a pattern recognition analyzer, comprising metal nanoparticles and single-walled carbon nanotubes coated with specific organic coatings, to identify a universal biomarker set in exhaled breath, allowing for the differential diagnosis of multiple diseases by comparing response patterns to a database of disease-specific patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If individual VOCs are used for disease detection, then specific well-defined VOCs can be detected with high selectivity, but only a narrow spectrum of diseases can be identified and differentiation between diseases is not achieved
Solution Approach 1:
The patent applies universality by developing a multi-functional sensor array where each sensor can detect multiple VOCs, and the combined array can identify a wide spectrum of diseases. The system transitions from single-purpose detection to multi-purpose diagnostic capability, allowing one system to serve multiple disease detection functions simultaneously.
Solution Approach 2:
The patent segments the complex task of disease diagnosis into multiple sensor components, each with specific sensitivity profiles. By dividing the detection function across multiple sensors with different selectivities, the system achieves both precise individual VOC detection and comprehensive disease spectrum coverage through pattern recognition of combined signals.
2Measurement precision
If highly selective nanomaterial-based recognition methods are used, then specific VOCs can be detected in the presence of interfering species, but this approach is laborious and requires synthesizing highly selective nanomaterials for each VOC
Solution Approach 1:
The patent uses cross-reactive nanomaterials that can detect multiple VOCs rather than requiring separate highly selective nanomaterials for each target compound. This universal approach reduces synthesis complexity while maintaining diagnostic accuracy through pattern recognition of the combined sensor responses.
3Adaptability or versatility
If cross-reactive nanotechnology-based sensor arrays are used, then a wider variety of diseases can be detected through pattern recognition, but individual VOC detection sensitivity is lower than selective sensors
Solution Approach 1:
The patent merges multiple cross-reactive sensors into an array system where the collective pattern recognition compensates for individual sensor limitations. By combining the responses of multiple sensors with similar cross-reactivity profiles, the system achieves both wide disease detection range and sufficient diagnostic precision through statistical pattern analysis.
4Reliability
If binary comparisons between specific disease and healthy controls are performed, then disease detection can be achieved, but differentiation between correlated diseases and classification of disease types is not addressed
Solution Approach 1:
The patent adds a new dimension to disease diagnosis by implementing multi-class classification capabilities alongside traditional binary detection. The system not only detects whether a disease is present but also classifies the specific disease type and differentiates between correlated conditions, providing comprehensive diagnostic information in multiple dimensions simultaneously.
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
The system achieves accurate differentiation between various neurodegenerative, renal, respiratory, and inflammatory bowel diseases with an accuracy of at least 80%, reducing false positives and negatives by using a universal biomarker set that can identify multiple diseases in a single test subject.
Implementation Method 1
chemically sensitive sensors, for detecting volatile organic compounds derived from a breath sample
Data Source
AI summary
The present invention provides a system and method for diagnosing, screening or monitoring a disease by analyzing the breath of a test subject using a selected definitive sensor set in conjunction with a pattern recognition analyzer, wherein the pattern recognition analyzer receives output signals of the sensor set, compares them to disease-specific patterns derived from a database of response patterns of the sensor set to exhaled breath of subjects with known diseases, wherein each of the disease-specific patterns is characteristic of a particular disease, and selects a closest match between the output signals of the sensor set and the disease-specific pattern. The present invention further provides a method of diagnosing, screening or monitoring a disease based on the determination of levels of volatile organic compounds (VOCs) from a universal biomarker set, including 2-ethylhexanol, 3-methylhexane, 5-ethyl-3-methyl-octane, acetone, ethanol, ethyl acetate, ethylbenzene, isononane, isoprene, nonanal, styrene, toluene and undecane.