Cell State Identification via Multi-Parameter Imaging and Machine Learning
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Solution Overview
Problem
Current methods for drug discovery are time-consuming and costly, and there is a lack of efficient methods to accurately and rapidly identify a cell's state, function, and predicted age, which hinders the development of drugs promoting longevity and improving immune function or treating diseases.
Innovation Solution
A method involving contacting in vitro cells with binding reagents that recognize specific markers, determining morphological and functional signatures through signal intensity, and using machine learning techniques to identify cell state, function, and predicted age, enabling the identification of drugs that change these characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional drug discovery methods are used, then comprehensive testing can be performed, but the process becomes time-consuming and costly
Solution Approach 1:
The patent segments the complex task of cell state identification into multiple measurable parameters including morphological features (cell size, shape, texture), functional markers (proteins, organelles), and signaling pathways. This segmentation allows parallel measurement of multiple aspects simultaneously, reducing overall assessment time while maintaining comprehensive evaluation accuracy
Solution Approach 2:
The patent develops a universal cell profiling platform that can identify multiple cell states (age, activation, differentiation, disease states) using the same set of binding reagents and imaging systems. This multi-functional approach eliminates the need for separate assays for each cell state, dramatically reducing drug discovery time while maintaining accurate identification across diverse cell conditions
2Measurement precision
If multiple binding reagents are used to accurately identify cell characteristics, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent combines multiple binding reagents (antibodies, lectins, dyes) into a single multi-color imaging assay that can be performed in one experimental run. By merging the detection of multiple cell markers into a unified platform using spectral imaging and machine learning analysis, the system achieves high measurement precision without proportionally increasing operational complexity
Solution Approach 2:
The patent implements automated image analysis and machine learning algorithms that automatically interpret complex multi-parameter data without requiring manual analysis. The system self-calibrates and identifies cell states through computational patterns, reducing the complexity burden on operators while maintaining high identification accuracy
3Measurement precision
If traditional assays are used, then detailed cell analysis can be performed, but productivity decreases
Solution Approach 1:
The patent transitions from traditional low-throughput sequential assays to a high-dimensional parallel imaging approach. By capturing multiple parameters (morphology, protein expression, organelle distribution) simultaneously across thousands of cells in a single field of view, the system achieves both detailed functional analysis and high screening throughput
Solution Approach 2:
The patent employs parameter changes in the imaging system including variable excitation wavelengths, detection channels, and focal planes to extract multiple layers of information from the same cell population. This multi-parametric approach enables detailed functional signature detection while processing large numbers of cells efficiently, thereby increasing productivity without sacrificing measurement precision
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 rapid and accurate identification of drug effects on cell state and function, facilitating efficient drug discovery and improving immune function and disease treatment.
Implementation Method 1
contacting an in vitro cell with a first binding reagent capable of recognizing and binding a first marker of the in vitro cell
Implementation Method 2
the first binding reagent and/or the at least second binding reagent are each respectively directly or indirectly labeled with a first fluorescent molecule and/or an at least second fluorescent molecule
Data Source
AI summary
Disclosed herein are methods and systems for identifying a drug capable of changing a cell's state, function, and/or predicted age, which is useful in, at least, drug discovery. Further disclosed herein are methods and systems for identifying an in vitro cell's state, function, and/or predicted age.