Flow Cytometer Light Scatter Detector Alignment Automation
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Solution Overview
Problem
Current methods for aligning flow cytometer light scatter detectors are time-intensive, inconsistent, and reliant on manual adjustments by field service engineers, leading to inaccuracies and difficulties in comparing data across different instruments.
Innovation Solution
A method for deriving a quantitative metric for light scatter detector alignment using a Mie light scatter model, allowing for automated adjustment of detector systems, including software and hardware adjustments based on calculated collection angles and data signals from calibrated beads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual alignment adjustment by field service engineers is used, then the detector alignment can be performed, but the process becomes time-intensive and inconsistent
Solution Approach 1:
The system performs self-alignment by automatically calculating collection angles and determining alignment adjustments without requiring manual intervention from field service engineers. The processor computes the alignment metric based on control data and automatically determines the necessary adjustments, enabling the system to service itself and eliminate time-consuming manual operations.
Solution Approach 2:
The patent replaces the manual mechanical adjustment process with an automated computational system. Instead of relying on engineers to physically adjust detectors, the system uses a processor to calculate collection angles, evaluate alignment metrics, and determine optimal alignment adjustments automatically, substituting mechanical manual operations with automated electronic control.
2Measurement precision
If manual alignment adjustment by field service engineers is used, then the detector alignment can be performed, but consistency across different instruments is compromised
Solution Approach 1:
The system implements a feedback mechanism where control data is collected, a quantitative alignment metric is calculated based on this data, and alignment adjustments are determined to optimize the metric. This closed-loop feedback process ensures that each instrument is aligned according to the same quantitative criteria, guaranteeing consistency across different instruments while maintaining high precision.
Solution Approach 2:
The patent introduces a quantitative alignment metric as a new parameter that objectively defines proper detector alignment. By changing from subjective manual judgment to an objective calculated metric, the system ensures that all instruments are aligned to the same quantitative standard, improving both precision and consistency across the instrument fleet.
3Measurement precision
If automated adjustment based on quantitative metric is implemented, then alignment accuracy and consistency are improved, but system complexity increases
Solution Approach 1:
The processor in the system performs multiple functions: it collects control data, calculates collection angles, evaluates alignment metrics, and determines alignment adjustments. By making the processor multi-functional, the patent avoids adding separate dedicated hardware for each function, thereby improving alignment accuracy without proportionally increasing system complexity.
4Reliability
If quantitative metric calculation is used, then data comparison across instruments is facilitated, but measurement and calculation complexity increases
Solution Approach 1:
The quantitative alignment metric serves as an intermediary that bridges different instruments and enables data comparison. Instead of directly comparing complex raw alignment data from multiple instruments, the system calculates a standardized metric that simplifies the comparison process while ensuring reliability and accuracy across the instrument network.
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 enhances the accuracy and consistency of light scatter detector alignment, facilitating data comparison across instruments and optimizing light collection, thereby improving the reliability of flow cytometry results.
Implementation Method 1
irradiating a control bead with the flow cytometer to generate control data
Implementation Method 2
determining a quantitative metric of the alignment for the light scatter detector system based on the control data
Data Source
AI summary
The present disclosure provides methods of determining an alignment adjustment for a light scatter detector system of a flow cytometer. Methods of interest include: generating control data by the flow cytometer; determining a quantitative metric of the alignment for the light scatter detector system based on the control data; and determining the alignment adjustment for the light scatter detector system based on the quantitative alignment metric. In some embodiments, the subject methods further include adjusting the light scatter detector system based at least in part on the alignment adjustment by performing, e.g., a hardware or software alignment adjustment. The subject methods may be implemented automatically via computer. Systems, non-transitory computer-readable storage media, and kits for carrying out the subject methods are also provided.