MIP Detection via Multi-Wavelength Scattering and ML
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Solution Overview
Problem
Current methods lack a practical and straightforward approach for detecting molecularly imprinted polymers (MIPs) in liquid dispersion samples, especially when bound to target analytes, due to challenges in differentiating their scattering signatures in complex solutions.
Innovation Solution
A method and device utilizing an optoelectronic instrument with a pigtailed fibre laser, micro-focusing elements, and a photodetector, coupled with machine learning classifiers, to analyze the scattering signatures of MIPs and determine their binding state by extracting temporal and frequency-derived features from backscattered light signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If optical scattering techniques are used to detect MIPs in liquid dispersion, then particle characterization is achieved, but differentiation between bound and unbound states becomes difficult
Solution Approach 1:
The patent segments the detection process into multiple measurement configurations with different laser wavelengths and detection angles. By measuring light scattering at multiple wavelengths (e.g., 488 nm, 633 nm) and multiple angles (forward scatter, backscatter), the system creates a multi-dimensional measurement space that enables differentiation between MIPs in different binding states, resolving the contradiction between detection precision and differentiation difficulty.
Solution Approach 2:
The patent introduces additional measurement dimensions by employing multiple laser wavelengths and multiple detection angles. Instead of relying on a single scattering intensity measurement, the system measures scattering characteristics across different spectral and angular dimensions, creating a comprehensive scattering fingerprint that enables reliable differentiation between bound and unbound MIP states.
2Measurement precision
If fluorescence or Raman detection is combined with MIPs, then analyte distinction is improved, but device complexity and chemistry requirements increase
Solution Approach 1:
The patent extracts and utilizes the inherent light scattering properties of MIPs themselves, rather than requiring additional fluorescent or Raman tags. By measuring the scattering characteristics of the MIPs in their natural state across multiple wavelengths and angles, the system achieves analyte distinction without adding the complexity of fluorescence or Raman detection systems, eliminating the need for additional chemistry while maintaining detection precision.
3Quantity of substance
If single particle detection is performed, then sensitivity is improved, but signal-to-noise ratio decreases
Solution Approach 1:
The patent merges multiple measurement signals from different wavelengths and detection angles into a comprehensive scattering fingerprint for each particle. By combining the information from 488 nm and 633 nm wavelengths with forward and backscatter measurements, the system creates a robust multi-parameter signature that maintains high sensitivity for single particle detection while improving signal reliability through redundant measurements and enhanced discrimination capability.
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
Enables robust and sensitive detection of MIPs in complex solutions, differentiating between bound and unbound states, and identifying small molecules with high accuracy, even in low concentrations, facilitating their use in clinical diagnosis and other applications.
Implementation Method 1
detecting a molecularly imprinted polymer (MIP) in a liquid dispersion sample from a backscattered or scattered forward light fingerprint
Implementation Method 2
emitting a laser modulated by a modulation frequency onto each specimen; capturing a temporal signal from laser light backscattered or scattered forward by each specimen
Data Source
AI summary
Device and method for detecting a MIP in a liquid dispersion sample from a backscattered or scattered forward light fingerprint, including detecting binding to a target analyte, the method comprising: emitting a laser modulated by a frequency onto each specimen; capturing a temporal signal from laser light backscattered or scattered forward by each specimen for a plurality of temporal periods for each specimen; calculating specimen coefficients from the captured signal for each temporal period; using the calculated coefficients to pre-train a machine learning classifier; using a laser emitter to emit a laser modulated by a frequency onto the sample; using a light receiver to capture a signal from laser light backscattered or scattered forward by the sample for a plurality of temporal periods; calculating sample coefficients from the captured signal for each temporal period; using the classifier to classify the sample coefficients as having MIP present or not.