Concentration assay
Abstract
Systems and methods are disclosed. An example method of determining the concentration of at least one analyte in a plurality of samples by sequentially subjecting each sample to an analysis cycle includes contacting the sample or a sample-derived solution with a sensor surface supporting a species capable of specifically binding the analyte or an analyte-binding species, detecting the amount of binding to the sensor surface, and regenerating the sensor surface to prepare it for the next analytical cycle, and based on the detected binding to the sensor surface determining the concentration of analyte in each sample using virtual calibration data calculated for each analysis cycle from real calibration data obtained by contacting the solid phase with samples containing known concentrations of analyte.
Claims
exact text as granted — not AI-modifiedWhat is claimed is:
1 . A method of determining the concentration of at least one analyte in a plurality of samples by sequentially subjecting each sample to an analysis cycle comprising contacting the sample or a sample-derived solution with a sensor surface supporting a species capable of specifically binding the analyte or an analyte-binding species, detecting the amount of binding to the sensor surface, and regenerating the sensor surface to prepare it for the next analytical cycle, and based on the detected binding to the sensor surface determining the concentration of analyte in each sample using virtual calibration data calculated for each analysis cycle from real calibration data obtained by contacting the solid phase with samples containing known concentrations of analyte.
2 . The method according to claim 1 , wherein the virtual calibration data comprise a specific calibration curve for each cycle.
3 . The method according to claim 2 , wherein the cycle specific calibration curve is calculated from virtual concentrations predicted for each cycle from the real calibration data.
4 . The method according to claim 3 , wherein predicting the virtual concentrations comprise fitting the known calibration data to a model function to determine a sensor response-cycle number relationship for each calibration concentration.
5 . The method according to claim 4 , wherein the model function is a standard type regression curve for ligand binding.
6 . The method according to claim 4 , wherein the model function is an exponential function.
7 . The method according to claim 1 , wherein the virtual calibration data comprise specific calibration coefficients for each cycle.
8 . The method according to claim 7 , wherein calibration equations are calculated from the real calibration data, and virtual calibration coefficients for each cycle are predicted therefrom.
9 . The method according to claim 8 , wherein predicting the virtual calibration coefficients comprise fitting the calibration data to a model function to determine values for coefficients of the model function for each cycle.
10 . The method according to any one of claims 1 to 9 , wherein the real calibration data comprise data from calibrations performed at least two, preferably at least three different times during the analysis of the plurality of samples.
11 . The method according to claim 9 , wherein each calibration is performed with at least two, preferably at least five to eight different concentrations.
12 . The method according to any one of claims 1 to 11 , wherein the analysis cycle is based on an assay format selected from a direct assay, an inhibition assay, a competitive assay, and a sandwich assay.
13 . The method according to claim 12 , wherein the analysis cycle is based on a direct type assay, and an analyte specific ligand is immobilized on the sensor surface.
14 . The method according to claim 12 , wherein the analysis cycle is based on an inhibition type assay, wherein the sample is mixed with a constant amount of detecting molecule, and analyte or an analyte analogue is immobilized on the sensor surface.Join the waitlist — get patent alerts
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