Metabolite Profiling for MS Relapse Detection

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Solution Overview

Problem

Current methods for diagnosing and predicting relapses in multiple sclerosis (MS) are inadequate, as they rely on clinical history and MRI, which can be unreliable due to pseudo-relapses and lack of sensitivity, especially in detecting small lesions, and there is no validated biomarker for relapse prediction.

Innovation Solution

Measuring specific metabolites such as leucine, lysine, asparagine, phenylalanine, glucose, β-hydroxybutyrate, myo-inositol, and lipoproteins in biofluids using NMR spectroscopy to differentiate between relapse and remission, and monitor treatment response.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If clinical history and neurological examination are used to establish relapses, then the diagnosis can be made, but the accuracy is reduced due to pseudo-relapses and lack of sensitivity

Engineering Contradiction:

Improverelapse diagnosis accuracyVSAvoiddetection sensitivity

Core Design Contradiction:

ReliabilityVSMeasurement precision

Solution Approach 1:

The patent introduces metabolite profiling as an intermediary biomarker system that mediates between clinical presentation and actual relapse status. By measuring metabolite concentrations in biofluids, the system provides an objective intermediate measure that distinguishes true relapses from pseudo-relapses, improving both reliability and detection sensitivity simultaneously

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent replaces the mechanical/clinical examination system with a biochemical measurement system. Instead of relying on neurological examination and clinical history (mechanical/observational methods), the system uses metabolite concentration measurements (biochemical analysis) to detect relapses, achieving higher accuracy and sensitivity

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If MRI is used to detect relapses, then new or enlarging T2 lesions can be identified, but sensitivity remains insufficient for small lesions particularly in spinal cord, cortical grey matter and optic nerve

Engineering Contradiction:

Improverelapse confirmation accuracyVSAvoidsmall lesion detection sensitivity

Core Design Contradiction:

ReliabilityVSDifficulty of detecting and measuring

Solution Approach 1:

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent shifts the detection dimension from spatial imaging (MRI anatomy) to biochemical concentration measurement. Instead of trying to visually detect small lesions in specific brain regions through MRI, the system measures metabolite concentrations in biofluids, providing a different dimensional approach that is more sensitive for detecting relapse activity regardless of lesion location or size

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

3Reliability

If no validated biomarker is used, then current practice relies on clinical methods, but there is no suitable prognostic method for predicting relapses

Engineering Contradiction:

Improverelapse detection accuracyVSAvoidprognostic prediction capability

Core Design Contradiction:

ReliabilityVSLoss of information

Solution Approach 1:

The patent applies preliminary action by measuring metabolite concentrations before relapses occur. By establishing baseline metabolite profiles and monitoring changes over time, the system can predict upcoming relapses before they manifest clinically, enabling proactive intervention and improving prognostic accuracy

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent implements feedback by continuously monitoring metabolite concentrations and comparing them against reference values and historical data. This feedback mechanism allows the system to detect deviations from normal patterns that indicate impending relapses, providing both diagnostic and prognostic information

Inventive Principle:

Principle #23Feedback

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

Provides accurate and sensitive confirmation of relapses and prediction of upcoming relapses, enabling better management and treatment decisions by distinguishing between genuine relapses and pseudo-relapses and monitoring patient response to therapy.

Implementation Method 1

Measuring specific metabolites such as leucine, lysine, asparagine, phenylalanine, glucose, β-hydroxybutyrate, myo-inositol, and lipoproteins in biofluids using NMR spectroscopy

Methodology Applied

Scientific EffectNMR spectroscopy:

Data Source

PatentUS20240069040A1Detection of a relapse in a multiple sclerosis patient

Publication Date: 2024.02.29 OXFORD UNIVERSITY INNOVATION LTD

AI summary

The present invention is directed to methods for confirming that a multiple sclerosis (MS) patient is suffering from a relapse. In particular, methods comprising: comparing a concentration of one or more metabolite(s) present in a sample obtained from the patient with the concentration of the same one or more metabolite(s) in a reference standard, wherein the one or more metabolite(s) are selected from: leucine, lysine, asparagine, phenylalanine, glucose, β-hydroxybutyrate, myo-inositol, a lipoprotein having a —CH3 group of an HDL and/or LDL, a lipoprotein having a —CH3 group of a VLDL, a lipoprotein having a —(CH2)n group of an HDL and/or LDL, a lipoprotein having a βCH2 group, and an N-acetylated glycoprotein; and confirming or not that the patient is suffering from a relapse.