Flow Cytometry Panel Builder for Multi-Laser Reagent Selection
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Solution Overview
Problem
Determining the optimal combination of chemicals and reagents for complex flow cytometry experiments with multiple lasers and detectors is challenging, requiring manual effort and separate workflows for preparation, data acquisition, and analysis, which is inefficient and time-consuming.
Innovation Solution
An interactive graphical user interface with a flow cytometer cloud server that automates the selection and assignment of fluorescent tags and cell markers, simplifying the workflow by allowing users to build, edit, and export experiments directly to the cytometer, using a cloud-based system for data management and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual determination of reagents and fluorochromes is used, then simplicity of the system is maintained, but time consumption and complexity of experiment formation increase significantly
Solution Approach 1:
The system automatically determines optimal reagent and fluorochrome combinations based on user-defined experimental parameters. The algorithm self-selects chemicals and their concentrations without manual intervention, allowing the system to serve itself in the complex selection process while reducing user time investment.
Solution Approach 2:
The system transforms manual selection of multiple parameters (reagents, fluorochromes, concentrations) into automated parameter optimization. By changing from manual adjustment to algorithmic optimization based on experimental goals and equipment constraints, the system efficiently determines optimal combinations without manual effort.
2Adaptability or versatility
If multiple lasers and detectors are used, then measurement capability and experimental versatility improve, but difficulty of determining optimal chemical combinations increases
Solution Approach 1:
The system uses feedback from the flow cytometer's detector characteristics and laser configurations to automatically adjust reagent and fluorochrome selections. By continuously referencing the specific instrument setup and optimizing chemical combinations accordingly, the system manages the complexity introduced by multiple lasers and detectors.
Solution Approach 2:
The system introduces a computational intermediary layer between the user's experimental goals and the complex chemical selection process. This intermediary algorithm translates high-level experimental requirements into specific reagent and fluorochrome combinations, shielding users from the underlying complexity of multi-laser, multi-detector optimization.
3Productivity
If separate workflows for preparation, data acquisition, and analysis are used, then system simplicity is maintained, but overall efficiency and time consumption worsen
Solution Approach 1:
The system merges previously separate workflows (preparation, data acquisition, analysis) into an integrated platform. By combining these functions, the system eliminates redundant steps and enables seamless transitions between stages, significantly improving overall efficiency while reducing total time investment despite the added system complexity.
Data Source
AI summary
In one embodiment, a method is disclosed to determine one or more biological cells of interest to identify and count in a mixed biological sample fluid with differing biological cells. The method can include selecting cell markers associated for biological cells to which conjugated antibodies can attach with differing fluorescent dyes; displaying a panel builder graphical user interface window to display a co-expression matrix by biological cell type to assist in selecting cell markers to assign co-expression; and selecting cell markers to assign co-expression with an input device.