Biosensor Binding Curve Analysis Without Model Fitting
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Solution Overview
Problem
Existing biosensor systems rely on specific interaction models for evaluating molecular interactions, which are limited to certain types of interactions and often discard valuable data, leading to unreliable results for interactions that do not fit these models.
Innovation Solution
A method and biosensor system that evaluates interactions independently of theoretical models by comparing sample binding curves to a reference binding curve, considering all registered data points, and classifying interactions based on predefined deviation criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If model-based evaluation methods are used to derive interaction parameters from binding curves, then reliable results are obtained for interactions that fit specific models, but the method becomes limited to specific interaction types and cannot provide reliable results for interactions that do not fit the model
Solution Approach 1:
The patent applies universality by creating an evaluation method that works for all interaction types without requiring specific model fitting. The system compares binding curves to reference curves using deviation analysis, making it applicable to diverse analyte-ligand interactions including those that don't fit traditional models like 1:1 binding
Solution Approach 2:
The patent inverts the traditional approach by instead of fitting data to theoretical models, it compares experimental binding curves to reference binding curves and evaluates based on deviation. This inversion allows model-independent evaluation while maintaining reliability
2Ease of operation
If report points at predetermined points in the binding curve are used for evaluation, then the evaluation process is simplified, but only information at specific points is used and a majority of the information in the binding curves is discarded
Solution Approach 1:
The patent applies continuity by utilizing all data points throughout the entire binding curve for evaluation, not just discrete report points. The deviation analysis continuously compares the sample binding curve to the reference binding curve across all measured time points, preserving all information
Solution Approach 2:
The patent changes the evaluation parameter from discrete report point values to continuous deviation metrics. By calculating deviation across the entire binding curve and using this as the evaluation parameter, the system maintains simplicity while utilizing all available information
3Measurement precision
If complex model fitting calculations are performed to derive interaction parameters, then detailed kinetic information is obtained, but the computational complexity and time required for analysis increases
Solution Approach 1:
The patent extracts the essential evaluation information directly from binding curve deviation without performing complex model fitting calculations. By taking out only the necessary deviation metrics rather than deriving full kinetic parameters through iterative fitting, the system reduces computational time while maintaining evaluation precision
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
Provides a more complete and reliable evaluation of analyte-ligand interactions by utilizing all data points, reducing computational complexity, and ensuring accurate results without requiring complex model fitting.
Implementation Method 1
A representative such biosensor system is the BIACORE® instrumentation sold by GE Healthcare, which uses surface plasmon resonance (SPR) for detecting interactions between molecules in a sample and molecular structures immobilized on a sensing surface.
Data Source
AI summary
A method and system for interaction analysis are disclosed. An example method for evaluation of an interaction between an analyte in a fluid sample and a ligand immobilized on a sensor surface of a biosensor includes providing a reference binding curve, representing a reference interaction for a predetermined acquisition cycle, by acquiring, using the biosensor, one or more binding curves for a reference-analyte ligand interaction at the predetermined acquisition conditions, acquiring, using the biosensor, a sample binding curve for the analyte ligand interaction for the predetermined acquisition cycle including at least one association phase wherein the sensor surface is put into contact with a fluid sample including analyte at a predetermined concentration, and generating a graphical user interface, including an upper threshold curve and a lower threshold curve defined with respect to the reference binding curve.