Cell Sorting Efficiency via Event Statistics Feedback
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing cell sorting technologies face challenges in efficiently navigating the parameter space to achieve optimal sorting conditions, leading to inefficiencies in separating target cell populations from heterogeneous mixtures.
Innovation Solution
A system and method that rapidly acquires event statistics from a fluid stream carrying cells, allowing for automated adjustments to improve sorting efficiency by analyzing deviations from reference statistics and implementing responsive actions such as altering sample or system configurations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional cell sorting methods are used, then cell separation can be achieved, but the process is time-consuming and inefficient in navigating parameter space
Solution Approach 1:
The system continuously monitors event statistics from the fluid stream and compares them against reference statistics to determine sorting efficiency. This feedback mechanism allows real-time assessment of sorting performance and automatic adjustment of parameters, eliminating the need for time-consuming manual parameter navigation while maintaining high sorting efficiency
Solution Approach 2:
The system automatically evaluates its own performance by processing event statistics and making self-diagnostic decisions about parameter adjustments. This self-service capability enables the system to optimize its own sorting efficiency without external intervention, significantly reducing the time required to navigate parameter space
2Productivity
If automated adjustments are implemented, then sorting efficiency improves, but system complexity increases
Solution Approach 1:
The automated adjustment mechanism is built upon a feedback loop that processes event statistics and automatically modifies sorting parameters. This feedback-based automation improves sorting efficiency while keeping the control logic transparent and manageable, avoiding unnecessary system complexity
Solution Approach 2:
The system automatically adjusts sorting parameters based on real-time event statistics analysis. By systematically varying parameters such as flow rate, voltage, or fluid composition based on statistical deviations, the system achieves automated optimization without requiring complex multi-component hardware modifications
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
Enhances the efficiency and accuracy of cell sorting by quickly identifying and correcting deviations, guiding the system towards optimal conditions through automated interventions.
Implementation Method 1
one or more optical detectors configured to convert optical response signals to the probe light received from the fluid stream into electrical signals
Data Source
AI summary
Methods and apparatuses of determining sorting efficiency for sorted particles. One method includes acquiring event statistics based on one or more signals generated from interrogating the particles in a fluid stream. The method also includes determining a degree of deviation of the event statistics from reference statistics and taking an automated responsive action in response to the degree of deviation exceeding a threshold level.