Oblique Illumination Particle Characterization System
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Solution Overview
Problem
Current particle analysis systems for protein therapeutics are inefficient and lack a routine method for accurately characterizing particulates in fluid samples at high throughput, particularly for subvisible particles, which are crucial for detecting harmful contamination and ensuring product quality and safety.
Innovation Solution
A system and method that includes a filter with a luminaire for oblique angle illumination and an imaging device for capturing and processing images of particles on the filter, utilizing bright field illumination and machine learning algorithms to identify particle type based on size, shape, texture, and intrinsic fluorescence, enabling rapid and accurate characterization of particles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional particle analysis systems are used, then particle counts and sizes can be obtained, but rapid and accurate identification of particle composition is not achieved
Solution Approach 1:
The system segments particle analysis into two distinct stages: (1) routine particle counting and sizing using standard techniques, and (2) targeted identification of particles of interest using spectroscopy. This segmentation allows high-throughput processing of all particles while applying detailed identification methods only to selected particles, resolving the contradiction between accuracy and throughput.
Solution Approach 2:
The system performs preliminary particle counting and characterization using routine methods before applying spectroscopic identification. By pre-screening particles and identifying candidates for detailed analysis based on size, shape, and other parameters, the system prepares the sample in advance to enable rapid spectroscopic analysis only of relevant particles, thus maintaining high throughput while achieving accurate identification.
2Measurement precision
If spectroscopy is used for definitive particle identification, then accurate composition analysis is achieved, but throughput is reduced and sample preparation becomes complex
Solution Approach 1:
The system segments the analysis population, applying spectroscopy only to particles identified as candidates for detailed analysis rather than to all particles. This selective approach maintains high throughput by limiting spectroscopic analysis to a subset of particles while still achieving accurate composition identification for those particles of interest.
Solution Approach 2:
The system performs preliminary screening of particles using routine counting and characterization methods before applying spectroscopy. Particles are pre-identified as candidates based on their size, shape, or other parameters, allowing spectroscopic analysis to be applied efficiently only to relevant particles, thus maintaining high throughput while achieving accurate composition identification.
3Measurement precision
If electron microscopy is used for particle analysis, then detailed particle characterization is achieved, but sample preparation becomes highly complex and requires specialized conditions
Solution Approach 1:
The system replaces the complex mechanical sample preparation requirements of electron microscopy with optical spectroscopy methods. Spectroscopy requires minimal sample preparation and can be performed on particles in their native state, eliminating the need for vacuum conditions, specialized mounting, and complex preparation procedures while still achieving detailed particle characterization through compositional analysis.
4Measurement precision
If fluorescence microscopy with staining is used, then particle identification is enhanced, but sample integrity is compromised and additional reagents are required
Solution Approach 1:
The system replaces chemical staining methods with optical spectroscopy that detects intrinsic properties of particles. This substitution eliminates the need for additional reagents that could chemically associate with or alter particles, maintaining sample integrity and formulation stability while still achieving enhanced particle identification capability through spectral analysis.
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 allows for high-throughput particle identification and typing within 30 minutes, accelerating clinical development and ensuring higher quality and safety of protein therapeutics by enabling early detection of contamination and improving formulation stability.
Implementation Method 1
a luminaire configured to illuminate the at least one particle at an oblique angle
Implementation Method 2
an imaging device configured to capture and process images of the illuminated at least one particle
Implementation Method 3
machine learning algorithms to identify particle type based on size, shape, texture, and intrinsic fluorescence
Data Source
AI summary
A system for characterizing at least one particle from a fluid sample is disclosed. The system includes a filter disposed upstream of an outlet, and a luminaire configured to illuminate the at least one particle at an oblique angle. An imaging device is configured to capture and process images of the illuminated at least one particle as it rests on the filter for characterizing the at least one particle. A system for characterizing at least one particle using bright field illumination is also disclosed. A method for characterizing particulates in a fluid sample using at least one of oblique angle and bright field illumination is also disclosed.