Nanomaterial Aggregation Analysis via Mass Spectrometry
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Solution Overview
Problem
Current methods for measuring and evaluating the aggregation state and surface state of nanomaterials, such as amyloid β and nanoparticles, face challenges in quantitativeness, simplicity, and sensitivity, particularly in biopharmaceutical production sites, with limitations in detecting low concentrations and particle sizes of single nanometers or less.
Innovation Solution
An analysis system that acquires signal changes over time due to interactions between capture target substances and capture substances using electrical or optical detection methods, allowing for the analysis of aggregation and surface states with high sensitivity through machine learning-based learned models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If conventional methods (gel filtration chromatography, ThT fluorescence, spectrophotometer, DLS, DSC, microscope) are used to detect aggregates, then detection capability is provided, but quantitativeness and convenience for quality control in biopharmaceutical production sites deteriorate
Solution Approach 1:
The patent replaces conventional mechanical and optical detection methods (DLS, microscope, spectrophotometer) with mass spectrometry-based detection. This substitution enables precise quantitative measurement of aggregation states by detecting mass-to-charge ratios, thereby improving measurement precision while maintaining detection capability
Solution Approach 2:
The patent changes the detection parameter from optical properties (fluorescence, light scattering) to mass-to-charge ratio detection. By using mass spectrometry, the system can quantitatively distinguish different aggregation states based on their distinct mass characteristics, achieving both detection and precise quantification
2Difficulty of detecting and measuring
If mass spectrometry is used for detecting organic compounds and nanomaterials, then detection capability is provided, but the aggregation state is dissolved in pretreatment, making it impossible to distinguish monomer from aggregate
Solution Approach 1:
The patent applies preliminary action by performing crosslinking treatment on the capture target substance before mass spectrometry analysis. This crosslinking stabilizes the aggregation state, preventing dissolution during pretreatment and enabling distinction between monomers and aggregates through their different mass-to-charge ratios
Solution Approach 2:
The patent introduces crosslinking agents as intermediaries that bridge subunits within aggregates. These intermediaries stabilize the aggregate structure during sample preparation, allowing the mass spectrometry to detect and differentiate aggregation states without the aggregates dissolving into monomers
3Difficulty of detecting and measuring
If Size Exclusion Chromatography is used for detection, then separation capability is provided, but detection in low concentration range becomes impossible
Solution Approach 1:
The patent replaces Size Exclusion Chromatography (a mechanical separation method) with mass spectrometry detection. This substitution eliminates the need for large sample volumes required by chromatography, enabling detection in the low concentration range while maintaining separation of different aggregation states through mass-to-charge ratio differentiation
4Difficulty of detecting and measuring
If Dynamic Light Scattering is used for detection, then particle size measurement is provided, but detectability of single nanometer order or less deteriorates
Solution Approach 1:
The patent replaces Dynamic Light Scattering (optical method) with mass spectrometry detection. This substitution enables precise measurement of particle sizes in the single nanometer order or less by detecting mass-to-charge ratios, achieving superior measurement precision for ultrafine particles that are undetectable by light scattering methods
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 precise quantification and discrimination of aggregation and surface states of nanomaterials, improving the quality control and drug efficacy evaluation in biopharmaceuticals and industrial applications by detecting low concentrations and particle sizes with high sensitivity.
Implementation Method 1
acquires a signal change over time due to an interaction between a capture target substance and a capture substance by an electrical or optical detection method
Implementation Method 2
acquires a signal change over time due to an interaction between a capture target substance and a capture substance by an electrical or optical detection method
Data Source
AI summary
An analysis system, a learned model generation device, a discrimination system, an analysis method, a learned model generation method, and a discrimination method can sensitively quantify at least one of an aggregation state or a surface state. An analysis system includes an acquisition unit for acquiring a signal change over time due to interaction between a capture target substance and a capture substance by an electrical detection method or optical detection method, and an analysis unit for analyzing at least one of an aggregation state and a surface state of the capture target substance from the signal change over time acquired by the acquisition unit.