Pathogen Detection via Magnetic Separation and Infrared Spectroscopy
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Solution Overview
Problem
Current methods for detecting pathogens, such as SARS-CoV2, are not reliable or rapid enough, and existing technologies like lateral flow rapid tests and PCR tests have limitations in sensitivity and specificity, particularly in handling multiple pathogens or mutations.
Innovation Solution
A method using selective receptors bound to microparticles that are separated from test samples using magnetic fields, followed by optical infrared spectroscopy to detect pathogens through characteristic measurement spectra, allowing for rapid and reliable detection of viruses, bacteria, or virus groups without the need for specific binding sites.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If lateral flow rapid tests are used for pathogen detection, then detection speed is improved, but reliability and sensitivity are worsened
Solution Approach 1:
The patent replaces the mechanical/chemical color-based detection system of lateral flow tests with an optical measurement system that records spectral characteristics. This substitution enables more reliable and sensitive detection while maintaining rapid results, as the optical system can detect pathogen-specific spectral signatures with higher precision than colorimetric methods.
Solution Approach 2:
The invention changes the detection parameter from color intensity (subjective visual assessment) to spectral characteristics (objective numerical data). By measuring multiple spectral parameters across different wavelengths, the system achieves higher reliability and sensitivity while maintaining rapid detection capability.
2Reliability
If PCR tests are used for pathogen detection, then reliability is improved, but detection speed is worsened
Solution Approach 1:
The patent extracts the detection function from the complex PCR amplification process. Instead of requiring viral RNA/DNA amplification followed by detection, the system directly measures spectral characteristics of the pathogen or its components in the original sample, eliminating the time-consuming amplification steps while maintaining reliable detection.
Solution Approach 2:
The invention skips the intermediate amplification step of PCR testing. By using optical spectroscopy to directly detect pathogen-specific spectral signatures in the original sample, the system rushes through the detection process in minutes rather than hours, while maintaining reliability through sensitive spectral analysis.
3Measurement precision
If selective binding methods are used, then specificity is improved, but adaptability to new pathogens is worsened
Solution Approach 1:
The patent creates a universal detection system that can identify multiple pathogens through their spectral characteristics. Instead of requiring pathogen-specific binding reagents for each pathogen, the optical measurement system can detect various viruses and bacteria by their unique spectral fingerprints, enabling rapid adaptation to new pathogens without developing new selective binders.
Solution Approach 2:
The invention changes from relying on biological specificity of selective binders to using spectral parameter diversity for pathogen identification. By analyzing multiple spectral parameters across different wavelengths, the system achieves high specificity for known pathogens and can rapidly adapt to new pathogens by learning their spectral signatures without requiring new selective binding molecules.
4Measurement precision
If complex sample processing is performed to improve detection accuracy, then measurement precision is improved, but device complexity and cost are worsened
Solution Approach 1:
The patent replaces complex mechanical sample processing steps (centrifugation, filtration, extraction) with a simpler optical measurement approach. The system can analyze crude samples directly by recording their spectral characteristics, achieving high detection accuracy through sophisticated spectral analysis algorithms rather than through complex physical processing steps.
Solution Approach 2:
The invention enables the sample to provide its own identification information through its intrinsic spectral characteristics. Instead of requiring external processing to isolate or label the pathogen, the pathogen's molecular structure itself provides the detection signal through its unique spectral fingerprint, eliminating the need for complex processing equipment and reagents.
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 enables high-throughput, cost-effective, and accurate detection of pathogens with reduced false positives/negatives, capable of adapting to new pathogens and mutations, and can handle complex samples with high sensitivity and specificity.
Implementation Method 1
a selective receptor binds a pathogen to be detected
Implementation Method 2
separated from test samples using magnetic fields
Implementation Method 3
optical infrared spectroscopy to detect pathogens through characteristic measurement spectra
Data Source
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AI summary
The invention relates to a method (1) for detecting pathogens (2). A sampled test sample (10) is purified, wherein microparticles (24) with a functionalized surface and with at least one selective receptor (22) are added to the test sample (10) during purification (S200). The selective receptor binds the pathogen (2) present to be detected. In a separation process (S240), the selective receptor (22) and the pathogens (2) present and coupled to the selective receptor (22) are separated from the test sample (10). A purified test sample (20) is used as the measurement sample (30). This sample comprises the selective receptor (22) separated from the test sample (10) and the pathogens (2) present and coupled to the selective receptor (22). In an optical method (S300) in the form of laser-based infrared spectroscopy (S320), the pathogens (2) present in the measurement sample (30) to be detected are identified.The invention further relates to an analysis device, a use of the analysis device and a use of a self-learning network.