Flow Cytometer Experiment Composition and Completion Detection
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Solution Overview
Problem
Current flow cytometer systems require users to pre-identify tests and set parameters before experiments, leading to time-consuming processes and potential errors, especially in multiplex experiments where multiple assays are performed simultaneously.
Innovation Solution
A computer-implemented method and system that determines the composition and completion of an experiment by analyzing data characteristics, such as event counts and coefficient of variation, to automatically identify included tests and determine when the experiment is complete, eliminating the need for pre-identification and reducing analysis time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users pre-identify tests and set parameters before experiments, then experiment composition can be controlled, but the process becomes time-consuming and error-prone
Solution Approach 1:
The system automatically determines experiment composition by analyzing data characteristics during the experiment, eliminating the need for manual pre-identification of tests and parameters by users
Solution Approach 2:
The system performs automatic experiment composition determination based on predefined thresholds and data characteristics before final results are generated, streamlining the experimental workflow
2Adaptability or versatility
If users manually identify all tests included in multiplex experiments, then complete coverage is achieved, but the complexity and potential for errors increases
Solution Approach 1:
The system uses feedback from data characteristics and event counts to automatically determine which tests are included in the experiment, adapting to the actual experimental conditions without manual configuration
Solution Approach 2:
The system self-determines the experiment composition by analyzing acquired data characteristics, eliminating the need for users to manually configure complex multiplex test parameters
3Productivity
If fixed total count thresholds are set for all samples, then data acquisition is standardized, but flexibility to accommodate different test requirements is reduced
Solution Approach 1:
The system dynamically determines experiment completion based on actual data characteristics and event counts for each specific test and sample, rather than using fixed thresholds for all cases
Solution Approach 2:
The system applies different completion criteria and thresholds to different tests and samples based on their specific characteristics, allowing optimized data acquisition for each case
Data Source
AI summary
Methods and systems for determining composition and completion of an experiment are provided. One-computer-implemented method for determining composition and completion of an experiment includes determining one or more characteristics of data acquired during the experiment and determining if the experiment is completed based on the one or more characteristics. One system configured to determine composition and completion of an experiment includes a processor configured to determine one or more characteristics of data acquired during the experiment and to determine if the experiment is completed based on the one or more characteristics. Another system configured to perform an experiment includes a measurement subsystem configured to acquire data during the experiment and a processor configured to determine one or more characteristics of the data during the experiment and to determine the composition of the experiment and if the experiment is completed based on the one or more characteristics.