Cytometric bead array analysis
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Solution Overview
Problem
Existing methods for particle analysis in flow cytometry struggle with efficiently processing and visualizing multidimensional data, particularly in identifying and quantifying multiple analytes in cytometric bead array (CBA) assays, leading to challenges in accurately determining sample concentrations and generating comprehensive data representations.
Innovation Solution
A method and computing system for cytometric bead array analysis that utilizes processor-controlled gate determination, regression functions, and user inputs to generate standard curves and concentration plots, enabling precise quantification of analytes based on reporter and clustering fluorescent intensities, and generating tables for sample concentrations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional flow cytometry methods are used to analyze CBA data, then the analysis process becomes complex and time-consuming, but the patent achieves automated processing and visualization of multidimensional data
Solution Approach 1:
The patent segments the complex CBA data analysis into distinct modular steps: receiving event data, determining gates based on clustering fluorescent intensity, selecting regression functions, calculating standard curves, and generating visualizations. This segmentation transforms a monolithic complex process into manageable, automated stages that can be executed systematically by a processor.
Solution Approach 2:
The patent introduces an intermediary computational system that acts as a bridge between raw CBA event data and meaningful analytical results. This intermediary processor automatically performs gate determination, regression analysis, and standard curve generation, eliminating the need for manual complex calculations and reducing both time and operational complexity.
2Measurement precision
If manual gate determination and standard curve generation are performed, then measurement precision may be high, but the analysis time and operational complexity increase significantly
Solution Approach 1:
The system implements self-service automation where the processor automatically determines gates based on clustering fluorescent intensity distributions and autonomously selects appropriate regression functions for standard curve generation. This self-service capability maintains measurement precision by applying consistent algorithmic criteria while eliminating time-consuming manual operations.
Solution Approach 2:
The patent performs preliminary automated actions by pre-determining gates and pre-selecting regression functions before final concentration calculations. This preliminary automation ensures that the foundational analytical framework is established systematically, maintaining precision while reducing the time required for subsequent analysis steps.
3Loss of information
If comprehensive multidimensional data visualization is generated, then data representation quality improves, but the complexity of processing and generating these visualizations increases
Solution Approach 1:
The patent transforms complex multidimensional CBA event data into simplified two-dimensional visual representations by plotting analyte concentrations against sample identifiers. This dimensionality reduction maintains essential information while making the data interpretable and eliminating the need for complex high-dimensional visualization processing.
Solution Approach 2:
The system extracts and visualizes only the most critical analytical results—standard curves and concentration measurements—separating these key information elements from the full multidimensional event data. This extraction approach preserves essential analytical information while avoiding the computational burden of processing and displaying all raw data dimensions.
4Productivity
If automated processor control is implemented for gate determination and concentration calculation, then productivity increases, but the complexity of the analysis system increases
Solution Approach 1:
The patent implements a universal processor-based system that performs multiple analytical functions: receiving event data, determining gates, selecting regression functions, calculating standard curves, and generating visualizations. This multi-functional automation consolidates what would otherwise require multiple separate tools or manual procedures into a single integrated system, increasing productivity while managing complexity through consolidation.
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
Enables accurate and efficient quantification of multiple analytes in CBA assays by determining sample concentrations and generating visual and tabular data representations, improving the analysis and visualization of multidimensional data.
Implementation Method 1
particles are exposed to an excitation light, typically from one or more lasers, and the light scattering and fluorescence properties of the particles are measured
Implementation Method 2
the light scattering and fluorescence properties of the particles are measured
Data Source
AI summary
Disclosed herein include systems, devices, and methods for cytometric bead array (CBA) analysis. After receiving user selections of a reporter fluorescent dye and clustering fluorescent dyes, gates for CBA event data corresponding to analytes in samples and standard curves for the analytes can be determined. Concentrations of the analytes in the samples can be determined using the standard curves.