FTIR Mucus Analysis for Cystic Fibrosis Alginate Response
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Solution Overview
Problem
Cystic fibrosis patients vary in their response to alginate oligomer therapy, with no current method to predict which patients will benefit from treatment, leading to inconsistent clinical outcomes.
Innovation Solution
A method using Fourier transform infrared spectroscopy (FTIR) to analyze mucus samples from cystic fibrosis patients, identifying specific infrared absorbance or transmittance values at wavenumbers 1395-1405 cm^-1, 1537-1547 cm^-1, and 1578-1588 cm^-1 to determine the likelihood of a positive response to alginate oligomer treatment by comparing test patterns with reference patterns from responders and non-responders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If alginate oligomer therapy is administered to CF patients, then mucus clearance may be improved, but patient response varies significantly with no method to predict who will benefit
Solution Approach 1:
The patent applies preliminary action by performing FTIR analysis on patient sputum samples before initiating alginate oligomer therapy. This pre-screening approach identifies patients likely to respond to treatment based on their mucus biochemical profile, allowing clinicians to predict treatment outcomes in advance and avoid administering ineffective therapy to non-responders.
Solution Approach 2:
The patent implements feedback by using FTIR spectroscopy to analyze the biochemical composition of patient sputum and comparing it against reference profiles from known responders and non-responders. This creates a feedback mechanism where the patient's own mucus characteristics provide information about their likely treatment response, enabling personalized treatment decisions.
2Measurement precision
If FTIR spectroscopy is used to analyze mucus samples, then patient response prediction is enabled, but treatment decision complexity increases
Solution Approach 1:
The patent applies the taking out principle by extracting only the most diagnostically relevant infrared spectral regions from the complete FTIR spectrum. Instead of analyzing the entire spectrum, the method focuses on specific wavenumber ranges that contain the most informative biochemical signatures, simplifying the analysis while maintaining predictive accuracy.
Solution Approach 2:
The patent applies parameter changes by transforming the complex spectral data into simplified predictive parameters. The FTIR spectrum is converted into a predictive score or classification (responder vs. non-responder) based on comparison with reference profiles, changing the data from complex continuous spectral values to discrete clinical decision parameters.
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 the identification of patients likely to respond to alginate oligomer therapy, allowing for targeted treatment and improved clinical outcomes by differentiating between responders and non-responders based on distinct IR spectral features.
Implementation Method 1
The method of the present invention is based therefore on analysing the IR absorbance values and/or transmittance values, in particular a Fourier transform infrared spectroscopy (FTIR) spectrum, of a mucus sample from the respiratory system of a CF patient
Data Source
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AI summary
The present invention provides a diagnostic method which may be used to determine the likelihood that a patient with cystic fibrosis will respond to treatment with an alginate oligomer. The method is based on analysingthe IR absorbance values and/or transmittance values, in particular a Fourier transform infrared spectroscopy (FTIR) spectrum, of a mucus sample from the respiratory system of a CF patient at certain specific wavenumbers.