Membrane Filter Imaging for Rapid Particle Composition Detection
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Solution Overview
Problem
Current particle analysis systems for protein therapeutics are inefficient and lack the ability to rapidly and routinely identify the composition of particles, leading to delayed detection of harmful contaminants and compromised product quality and safety.
Innovation Solution
A method utilizing a membrane filter with brightfield and fluorescence imaging to distinguish between different types of particles based on scattered light, DNA and protein fluorescence intensity profiles, and morphology parameters, enabling high-throughput identification of beads, cellular and non-cellular particulates, and protein aggregates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional particle analysis systems are used, then particle counting can be performed, but the ability to identify particle composition is lacking and throughput is low
Solution Approach 1:
The patent combines multiple imaging modalities (brightfield, fluorescence, and scattered light detection) into a single integrated system that simultaneously performs particle counting and composition identification. This merging of detection capabilities allows the system to achieve both high measurement precision for particle identification and high productivity through parallel analysis of multiple particles in the same field of view.
Solution Approach 2:
The imaging system is designed to perform multiple functions: it can detect particles of various compositions (protein aggregates, polysorbate, silicone oil, glass, metal) using the same hardware platform. The system universally analyzes different particle types by detecting their unique optical properties across multiple wavelengths and imaging modes, eliminating the need for separate specialized instruments for each particle type.
2Measurement precision
If spectroscopy and electron microscopy are used for definitive particle identification, then accurate composition analysis is achieved, but the process is time-consuming and complex
Solution Approach 1:
The system performs preliminary optical characterization of particles during the main analysis process by simultaneously capturing brightfield, fluorescence, and scattered light images. This preliminary action provides sufficient compositional information without requiring subsequent time-consuming spectroscopy or electron microscopy, thereby reducing overall analysis time while maintaining identification accuracy.
Solution Approach 2:
The patent replaces mechanical and chemical analysis methods (electron microscopy requiring vacuum and complex prep, spectroscopy requiring sequential measurements) with optical detection methods. By using multiple imaging modalities that can simultaneously characterize particles based on their light interaction properties, the system achieves accurate composition identification much faster than traditional mechanical or chemical analysis techniques.
3Reliability
If particle identification techniques are implemented, then harmful contaminants can be detected, but the complexity of sample preparation and operation increases
Solution Approach 1:
The system performs self-characterization of particles by automatically detecting their optical properties (brightness, fluorescence intensity, scattered light patterns) without requiring external staining, labeling, or complex sample preparation. The particles themselves provide the diagnostic signals through their inherent optical characteristics, eliminating the need for additional reagents or preparation steps that would increase operational complexity.
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 rapid and accurate identification of particles in protein therapeutics, allowing for early detection of contaminants and improving formulation stability and safety by identifying protein aggregates and other particulates within 30 minutes, enhancing product quality and clinical development.
Implementation Method 1
a method utilizing a membrane filter with brightfield and fluorescence imaging to distinguish between different types of particles
Implementation Method 2
distinguish between different types of particles based on scattered light, DNA and protein fluorescence intensity profiles
Implementation Method 3
distinguish between different types of particles based on scattered light, DNA and protein fluorescence intensity profiles
Data Source
AI summary
Methods for distinguishing particles in a fluid sample are disclosed. In one embodiment, the method includes acquiring a background SIMI image and a background brightfield image of a membrane filter while the membrane filter is free of a fluid sample, introducing a fluid sample onto the membrane filter, acquiring a SIMI image and a brightfield image of filtered particles resting on the membrane filter, distinguishing between the filtered particulates and the membrane filter based on the background SIMI image, generating a particle mask based on the SIMI image, and detecting beads via the particle mask. Methods for distinguishing particulates include distinguishing between viable and non-viable cell populations, distinguishing between cellular and non-cellular particulates, distinguishing between biological and non-biological particulates, distinguishing between first and second protein types, determining stability of monoclonal antibody drugs, identifying beads in a cell therapy, and detecting bacteria.