WO2008109977A1 - Procede de compensation de la courbe de relation dose-effet d'un dosage servant a mesurer la sensibilite a des variables de perturbation - Google Patents

Procede de compensation de la courbe de relation dose-effet d'un dosage servant a mesurer la sensibilite a des variables de perturbation Download PDF

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WO2008109977A1
WO2008109977A1 PCT/CA2007/000398 CA2007000398W WO2008109977A1 WO 2008109977 A1 WO2008109977 A1 WO 2008109977A1 CA 2007000398 W CA2007000398 W CA 2007000398W WO 2008109977 A1 WO2008109977 A1 WO 2008109977A1
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assays
assay
signals
dose
response curve
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PCT/CA2007/000398
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English (en)
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Stephen W. Leonard
Samad Talebpour
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Novx Systems Inc.
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Priority to PCT/CA2007/000398 priority Critical patent/WO2008109977A1/fr
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/27—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands using photo-electric detection ; circuits for computing concentration
    • G01N21/274—Calibration, base line adjustment, drift correction
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/27—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands using photo-electric detection ; circuits for computing concentration
    • G01N21/274—Calibration, base line adjustment, drift correction
    • G01N21/276—Calibration, base line adjustment, drift correction with alternation of sample and standard in optical path
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2201/00—Features of devices classified in G01N21/00
    • G01N2201/12—Circuits of general importance; Signal processing
    • G01N2201/121—Correction signals
    • G01N2201/1211—Correction signals for temperature

Definitions

  • the present invention is related to assays and methods of compensating for changes in the dose-response curve of an assay where such changes are due to variations in a perturbing variable such as temperature.
  • Assays of samples are routinely used to detect and measure the presence and the concentration of analytes such as drugs, pollutants, chemicals, contaminants, or the like. Regardless of the format for the assays, the analyte concentration is inferred from the dose-response curve. This can be done by finding the ordinate on the dose-response curve corresponding to the signal for the unknown concentration of analyte in the sample. The later quantity is given by the value of the abscissa.
  • the dose-response curve is typically non-linear and it can be prepared by assaying standard samples containing known concentrations of the analyte. The number of standard samples and their concentrations are selected in order to determine the analyte concentrations with sufficient accuracy over the expected assay range.
  • a variation in the assay conditions can modify the actual relationship between the measured signal and analyte concentration from that predicted by the initial dose-response curve. It is therefore often necessary for an analyzer to accurately control and maintain variables that affect the dose-response curve.
  • One of the most common variables that produces significant variations in an assay signal is temperature. Changes in temperature lead to assay variations due to the strong thermal dependence of reaction rates and assay kinetics. For example, it is well known that the signal of a homogeneous enzyme assay, in which an enzyme is acting on a substrate to produce a measurable signal, has a thermal dependence of approximately 4% per degree Celsius.
  • US4483823A (Umetsu et al., filed 1982) describes an automated analyzer in which a water bath with precise temperature control is employed to regulate the temperature of a sample vessel.
  • US patent US4933146 A (Meyer and Greene, filed 1986) discloses a thermal subsystem for the accurate thermal regulation of a set of cuvettes in an automated analyzer.
  • An alternative method to avoid degradation in assay performance due to thermal sensitivity is to measure a full set of calibrators and obtain a new dose-response curve each time samples are analyzed. In such a scheme, it is only important to keep the temperature stable during the assay. Unfortunately, this method is not practical since most assays require many separate calibrators for proper calibration.
  • United States Patent No. 5,648,274 (issued to Chandler et al.) describes the use of a single internal calibrator in a comparative dual assay and United States Patent No. 5,387,503 (issued to Selmer et al.) describes the use of an internal calibration by the addition of foreign analytes to samples and detection of both the target and foreign analytes at separate areas on a solid support.
  • United States Patent No. 6,514,770 issued to Sorin.
  • the disadvantage of using an internal calibrator is that insufficient calibration measurements are obtained to properly re-calibrate the initial dose-response curve. Additional disadvantages include the requirement for dedicated reagents, which are not always commercially available, and an analyzer capable of detecting two signals. For these reasons, internal calibrators are not readily integrated into a commercial assay platform.
  • the present invention provides assays and methods of compensating for changes in the dose-response curve of an assay where such changes are due to variations in a perturbing variable such as, but not limited to temperature.
  • this is achieved by using two major steps, the first step of which involves measurements of the dose-response curve, and thus the individual assay parameters, at many different values of the perturbing variable, spanning the expected range of the perturbing variable.
  • the second step unknown samples are assayed simultaneously with a known standard at a chosen analyte concentration.
  • the value of the perturbing variable is unknown and the dose-response curve is therefore also unknown.
  • the different dose-response curves from the first step are used to determine a mathematical relationship between the assay parameters and the assay signal of the known standard.
  • assay parameters that are valid for the unknown value of the perturbing variable can be obtained by substituting the value of the assay signal from the known standard (measured when assaying the unknown samples) into the mathematical relationship and solving for the assay parameters.
  • the method enables an accurate determination of the analyte concentration even when the perturbing variable is changing or fluctuating from one sample measurement to another.
  • the second step can be performed repeatedly to measure unknown samples with accuracy.
  • the method first includes characterizing the dependence of the dose-response curve of one or more assays on the perturbing variable by the steps of: i) measuring assay signals from a suitable set of known standards for the one or more assays at different values of the perturbing variable, and also measuring one or more other signals dependent on the perturbing variable, and whereby the one or more other signals dependent on the perturbing variable are measured for each of the different values of the perturbing variable; ii) fitting the measured assay signals to a suitable functional form to produce a dose-response curve for each of the one or more assays at each of the different values of the perturbing variable and determining assay parameters from the fitting; and iii) establishing a mathematical relationship between each assay parameter of the one or more assays and each of the one or more other signals dependent on the perturbing variable.
  • a dose-response curve is determined that compensates for the effects of changes in the value of the perturbing variable by the steps of: iv) re-measuring the one or more other signals dependent on the perturbing variable; v) obtaining a value of each assay parameter of the one or more assays by substituting one of the one or more re-measured other signals dependent on the perturbing variable into the mathematical relationship between the assay parameter and the one of the one or more other signals dependent on the perturbing variable, and repeating the substitution for each of the one or more other signals dependent on the perturbing variable to obtain one or more values of the assay parameter; and vi) producing a compensated dose-response curve for each of the one or more assays of the unknown samples by averaging the one or more
  • a method of compensating a previously measured dose-response curve of one or more assays for the effects of a perturbing variable to which the one or more assays are sensitive comprising the steps of first characterizing a dependence of a dose-response curve of one or .
  • the dose- response curves of the one or more assays Prior to performing assays on unknown samples, the dose- response curves of the one or more assays are measured. This process can be repeated periodically during routine use of the assays in order to correct for long-term assay variations. Periodic measurements of the dose- response curves of the one or more assays are obtained by measuring assay signals from a suitable set of known standards for the one or more assays and fitting the measured assay signals to a suitable functional form to produce a dose-response curve for each of the one or more assays. When measuring the dose-response curves, the one or more other signals dependent on the perturbing variable are also measured.
  • the previously measured dose-response curves of the one or more assays are compensated for the effect of a change in the perturbing variable by the steps of: iv) re-measuring the one or more other signals dependent on the perturbing variable; v) obtaining a compensated value of each assay parameter of said one or more assays by adding to each assay parameter obtained from said previously measured dose-response curve for said one or more assays a value equal to the difference between an assay parameter calculated by said mathematical relationship by substituting one of said one or more signals dependent on said perturbing variable re-measured with said assays for said unknown samples, and an assay parameter calculated by said mathematical relationship by substituting one of said one or more signals dependent on said perturbing variable measured with said previously measured dose-response curve, and repeating steps iv) and v) for each of said one or more other signals dependent on said perturbing variable to obtain one or more values of said each assay parameter;
  • Figure 1 shows dose-response curves (absorbance vs concentration) for a set of calibrators made at different temperatures
  • Figures 2 to 5 show, respectively, plots of assay parameters ai, a 2 , a 3 and a 4 as a function of signal at a concentration of 2500 ng/ml, for a sigmoidal dose-response curve written as:
  • Figure 6 shows a plot of temperature which is also plotted against S cat in corresponding to the Figures 2 to 5.
  • Figure 7 shows the calibration dose-response curve (at 28 °C) along with both the thermally-compensated curves and measured data points for the three additional temperatures (at 30, 32 and 34 0 C).
  • performing an assay means following a pre-determined set of steps in order to obtain and measure a signal related to an unknown concentration of an analyte present in a sample, and where a known relationship between the signal and the analyte concentration is employed to infer the analyte concentration.
  • dose-response curve means a mathematical function that describes the relationship between an assay signal and an analyte concentration.
  • an assay parameter means a coefficient in the dose-response curve of an assay.
  • the phrase “perturbing variable” means a variable to which an assay signal is sensitive, whereby variations in the perturbing variable produce variations in the assay signal.
  • the phase "assay signal” means a measurable quantity resulting from an assay reaction, such as optical density, luminescence power, fluorescence power, or changes in any of these quantities during a reaction.
  • phase "a signal dependent on a perturbing variable” means any measurable quantity that depends on the value of the perturbing variable, such as optical density, luminescence, fluorescence, or changes in any of these quantities during a reaction.
  • the phase "a signal dependent on a perturbing variable” may also be a direct measurement of the perturbing variable, such as a measurement of temperature if the perturbing variable is temperature.
  • a signal-generating means that produces a signal related to the value of the perturbing variable means a material, transducer or other device that produces a signal that is directly related to the value of the perturbing variable.
  • an outlier test means a statistical test designed to detect the presence of outliers in a dataset.
  • the phrase “compensation function” means a mathematical relationship between an assay parameter and a signal dependent on a perturbing variable.
  • the phrase “compensation coefficient” means the slope of a linear relationship between an assay parameter and an assay signal dependent on a perturbing variable.
  • Biological assays are characterized by a dose-response curve that describes the relationship between the measured assay signal and the corresponding analyte concentration.
  • the dose-response curve is usually fitted to a specific functional form, the most common functional forms being the sigmoidal and linear functions.
  • a sigmoidal dose-response curve is written as:
  • Equations (1 ) and (2) are static dose-response curves that are only valid when the assay conditions are stable and constant. In reality, the true dose-response relationship fluctuates in time due to changes in perturbing variables to which the assay signal is sensitive. For example, it is well known that most assays are strongly dependent on changes in temperature. If changes in a perturbing variable produce variations in the dose-response curve, then equations (1 ) and (2) must be modified as follows:
  • S(C,x) F[C; ⁇ i (x), ⁇ 2 (x),..., ⁇ n (x),..., ⁇ N (x)], (3) where x denotes the value of the perturbing variable to which the assay is sensitive. If the perturbing variable is itself changing during the assay (i.e. equilibrium has not been reached), then x can be interpreted, in a first approximation, as the average value of the variable during the assay analytic phase.
  • the assay parameters of an enzymatic assay usually each depend on temperature in a unique way. In general, the dependence of any given assay parameter will be a nonlinear function of x that is best determined experimentally.
  • the inventors have discovered that a novel and effective method can be employed to compensate for the dependence of the dose-response curve of an assay on changes in a known perturbing variable.
  • This is achieved by a two-step method, the first step of which involves measurements of the dose-response curve (and thus the individual assay parameters) at many different values of the perturbing variable (with the values spanning an expected range of the perturbing variable).
  • unknown samples are assayed simultaneously with a known standard at a chosen analyte concentration. During this measurement, the value of the perturbing variable is unknown and the dose-response curve is therefore also unknown.
  • the measurement of the known standard enables the determination of the new dose-response curve.
  • the different dose- response curves from the first step are used to determine a mathematical relationship between the assay parameters and the assay signal of the known standard.
  • assay parameters that are valid for the unknown value of the perturbing variable can be obtained by substituting the value of the assay signal from the known standard (measured when assaying the unknown samples) into the mathematical relationship and solving for the assay parameters.
  • the method therefore enables an accurate determination of the analyte concentration even when the perturbing variable is changing or fluctuating from one sample measurement to another.
  • the second step can be performed repeatedly to measure unknown samples with accuracy.
  • the assay signals from a set of known standards are measured at a number of different values of the perturbing variable over the range of interest of the perturbing variable.
  • Dose-response curves and assay parameters (a n ) are obtained for each different value of the perturbing variable by fitting the measured assay signals from the known standards to a chosen functional form.
  • a sufficient number of standards are included to obtain a good fit over the desired range of analyte concentrations, with the goodness of fit determined by statistically meaningful measures such as the ⁇ 2 or R 2 parameters.
  • a known standard, with a concentration C ca/ is chosen to be assayed when later performing assays on unknown samples.
  • the signal values S ca corresponding to the concentration C ca , at each of the different values of the perturbing variable are then obtained from the measured dose-response curves. This is done by substituting C ca ⁇ into the dose- response equations and solving for S (for the sigmoidal function this would be equation 2 above).
  • the concentration C ca is preferably chosen to give a sufficiently high signal-to-noise ratio in the assay signal (note that the concentration may be chosen to be below the lower limit of quantitation if this criteria is satisfied).
  • a n (S ca i) of each assay parameter on the calibrator signal can then be determined by fitting the observed values of the assay parameters and the calibrator signal to an appropriate mathematical function (e.g. a linear or higher order polynomial function). This function must be single-valued of the expected range of values of the perturbing variable.
  • This preliminary measurement phase characterizes the dependence of the assay on the perturbing variable via the mathematical relationships a n (S ca! ). These relationship, to be henceforth referred to as the compensation functions, can then be used in subsequent assays for samples with unknown analyte concentrations in order to provide an accurate determination of the analyte concentration despite variations in the value of the perturbing variable.
  • at least one known standard having the concentration C ca/ is also measured. It is important to note that in this context, the term "when” implies that the measurement of the known standard are to be performed at a time that is approximately equal to the time of measurement of the unknown samples, so that the value of the perturbing variable is approximately the same for all measurements.
  • the known standard can include multiple analytes, in which case it could be used as a standard for multiple assays that are each compensated via the present method.
  • the value of the measured signal from the standard is denoted as S ca /.
  • the value of the perturbing variable at which the samples and the standard are measured is denoted as x' and is generally unknown, especially if careful provisions have not been made to keep the perturbing variable constant.
  • the compensation functions are used to produce a corrected dose-response curve that is valid and accurate for the present value of the variable x' by substituting S ca ⁇ into the compensation functions:
  • the compensated assay parameters an(x') are used in the dose-response curve to correctly infer the analyte concentrations of the samples. Since the assay parameters have been accurately corrected for variations in the perturbing variable, an assay with accuracy and precision can be performed even when changes in the perturbing variable occur. In principle, once the dependence of the dose-response curve on the variable has been measured and quantified by the compensation functions, it is not per se necessary to re-measure the dose-response curve. However, in practice, it is common to periodically re-measure a dose-response curve for the purpose of re-calibrating the assay for potential variations in other variables (for example systematic errors in liquid handling or long term degradation of the reagents).
  • T ⁇ represents the transformation
  • Equation 5 may appear to be advantageous over equation 6 due to the fact that in equation 5, the compensated assay parameters are directly calculated from compensation functions.
  • the second method yielding equation 6 may offer superior performance when the dose-response curve is sensitive to multiple variables. Since the second method permits multiple measurements of the dose-response curve and only corrects for changes in the variable relative to the most recently measured dose-response curve, long-term variations caused by other variables may also be corrected. Therefore, in certain cases, the dose- response curve itself may shift without having any consequence on the validity of the compensation. This may offer particular utility if long-term aging of the assay reagents causes global shifting of the curves, in which case the shift will be compensated via the newly measured dose-response curve.
  • This can be done, for example, by assaying, in addition to the unknown samples and the known standard, additional known standards to serve as controls.
  • the assay signals from the controls are substituted into the compensated dose-response curve and the resulting equation is solved to obtain the control concentrations. If the measured concentrations, when compared to the known concentration of the standard, pass a predetermined criterion, the dose-response curve is deemed to be accurate.
  • the replicate signals can be first analyzed to determine whether or not an outlier has occurred (using, for example, one of many outlier tests known to those skilled in the art). If an outlier is found, the assay run is rejected. If no outlier is found, then prior to performing the calculation in equation 5 or 6 (depending on which method is chosen), the replicate signals S ca/ are first averaged to a more precise result.
  • known standards with different concentrations Ae. different values of C ca/ and S ca i
  • each known standard is used to generate a set of compensated assay parameters via the aforementioned methods. Outlier tests are then performed on each of the assay parameters, and the assay run is rejected if any outliers are found. The multiple values of the compensated assay parameters are then averaged to a more precise result.
  • the two methods can be combined if desired.
  • the assay signal from a known standard has been used as a signal dependent on the perturbing variable.
  • the assays signal can advantageously provide a direct measurement of an assay parameter. For example, in the case of an assay with a dose-response curve that is described by a sigmoid (i.e. equation 2), an assay reaction with the absence of analyte provides a signal with a value equal to a ? .
  • the first signal dependent on a perturbing variable can be a direct measurement of ai, as described in the above paragraph.
  • This signal can clearly be used to provide a compensated value of a-i that corrects for all perturbing variables. If a 2 exhibits a dependence on a ? that holds regardless of which perturbing variable causes a change in a ? , then a 2 can be thermally compensated via the relationship a 2 (ai), which is measured by varying the global perturbing variable only. If a 3 and a 4 are only substantially dependent on the global perturbing variable, they can be thermally be compensated by a second signal dependent on the global perturbing variable, where this second signal is itself not dependent on the other perturbing variables.
  • a ⁇ fai is substantially similar for both changes in temperature and changes in reagent quantity. This behaviour has been observed hold for a class of homogeneous enzyme immunoassays.
  • a direct measurement of ai as the first signal dependent on temperature can therefore be employed to correct for perturbations in reagent quantity and temperature.
  • a direct measurement of temperature can be used as a second signal that is used to compensate only a 3 and a 4 , since a temperature measurement does not depend on reagent quantity. Therefore, corrections of additional perturbations due to changes in reagent quantity can be incorporated into the compensation scheme.
  • the dose-response curve measured during a calibration assay can be accurately thermally compensated via the measurement of the known standard whenever unknown samples are measured.
  • the data used to generate the compensation coefficients in the above example is also used to show self-consistent results.
  • the data taken at 28 0 C is used to generate the calibration dose-response curve.
  • the data at all other temperatures is taken to be real sample data, with the exception of the data at 2500 ng/ml, which is taken to be the signal from the known standard.
  • the dose-response curve from initial calibration (at 28 °C data) is thermally compensated using equation 8.
  • the above embodiments have required the use of a signal from a known standard to compensate the dose-response curve, one may also perform the invention by measuring any signal that is related to the perturbing variable, even if the signal is not obtained via the assay being compensated. This is achieved by modifying the preliminary measurement phase so that in addition to measuring assay signals from a set of known standards at each value of the perturbing variable, a signal related to the perturbing variable is also measured.
  • This signal may be a direct measurement of the variable (e.g. the measurement of temperature with a thermometer) or an indirect measurement of a signal related to the perturbing variable (e.g. the indirect measurement of temperature via an enzymatic reaction producing a colourimetric response).
  • the above embodiments can be further generalized by noting that the signal related to the perturbing variable can be employed to compensate for more than one assay at a time.
  • This is achieved by modifying the preliminary measurement phase to include a characterization of the dependence of the dose-response curves of several assays (instead of a single assay) on the perturbing variable via the measurement of the assay signals from a set of standards for each assay at different values of the perturbing variable, and also measuring a signal related to the perturbing variable.
  • dose- response curves and assay parameters are obtained for each assay.
  • the dependence of the assay parameters for each assay on the signal related to the perturbing variable is then fitted to a known mathematical function to obtain the compensation functions a n (S) if the method of equation 5 is used.
  • the dependence of the assay parameters for each assay on the signal related to the perturbing variable is fitted to a linear function and the slope is obtained according to equation 8 for each assay parameter of each assay.
  • the mathematical relationship between an assay parameter and the signal dependent on the perturbing variable may be double-valued in the assay parameter, i.e. there may be two possible assay parameter values for a single value of the signal dependent on the perturbing variable.
  • a second signal dependent on the perturbing variable may be used to compensate the particular assay parameter, provided that the second signal dependent on the perturbing variable is related to the particular assay parameter in a one-to-one fashion.
  • the value of the perturbing variable must be significantly uniform among all assays.
  • the signal related to the perturbing variable is also measured.
  • the signal related to the perturbing variable is also measured when periodically measuring the dose-response curve of any of the assays. This enables the dose- response curve of any assay to be updated according to either equation 5, 6 or 8, where the assay parameters a n are taken to be assay parameters of any of the assays considered.
  • the signal related to the perturbing variable is an assay signal from a known standard
  • the signal from the known standard is used to further improve the accuracy of the compensated dose-response curve. Since the analyte concentration of the standard is known, the compensated dose-response curve can be forced to pass through the data point produced by the assay signal of the standard (i.e. the assay signal and analyte concentration).
  • Samples with concentrations above and below the cutoff are labelled as positive and negative, respectively.
  • the consequence of a sample being positive or negative differs among applications, but is often therapeutic or legal in nature.
  • a sample that is found to be positive will lead the test administrator to conclude that the individual being tested may be using illegal drugs (in this application, samples found to be high are usually confirmed using a reference test method). It may therefore be desirable to improve the accuracy of the compensation method in the vicinity of the cutoff.
  • the concentration of the known standard is chosen to be the cutoff concentration, then the compensated dose-response curve is forced to pass through the measured cutoff data point. This enables an accurate positive-negative determination and enhances the specificity and sensitivity of the assay.
  • the preceding embodiment involving the substitution of the signal and concentration of a known standard into the dose-response curve to directly solve for a selected assay parameter, can be generalized by measuring multiple standards at different concentrations rather than a single standard and directly compensating more than one assay parameter.
  • a set of averaged assay parameters are first obtained according to the aforementioned embodiment in which multiple standards are measured to obtain an assay with improved precision.
  • One of the known standards and one compensated assay parameter are then selected.
  • the assay signal and concentration from the known standard are substituted into the dose-response curve, and the resulting equation is solved for the assay parameter. This process is repeated for each known standard, and a new dose-response curve is obtained by incorporating the newly compensated assay parameters.
  • a quality control mechanism can be incorporated into the above embodiments to provide a determination of the validity of the compensated dose-response curve.
  • an improved value of a selected assay parameter is obtained by substituting a selected assay signal and concentration of a known standard into the compensated dose-response curve and solving for the selected assay parameter. This provides two values for the selected assay parameter; an original value obtained using either equations 5, 6 or 8 (depending on the preferred method), and a new value obtained via the method of substitution. The two values can be compared and pass/fail criteria can be established for the difference between the two values, which, in theory, should be exactly equal.
  • two or more known standards are used for both compensation and quality control. This is achieved via the following method. Initially, the dose-response curve is compensated using a single one of the known standards according to equations 5, 6 or 8 (depending on which method is preferred). The compensated assay parameters are recorded and the compensated dose-response curve is used to estimate the concentrations of the remaining known standard. The known concentrations of the remaining known standards are compared to their estimated values, and are thereby used as controls to verify the accuracy of the initial compensation. This process is then repeated for the second known standard, with the other known standards being used as controls to verify the accuracy of the compensation based on the second known standard. This process is repeated for each known standard.
  • each compensated dose-response curve based on each known standard is deemed to have passed the quality control pass/fail criteria, then the compensated assay parameters obtained for each of the known standards are averaged and the average parameters are used to construct the final compensated dose-response curve.
  • a useful example of the above method involves incorporating two known standards with concentrations above and below the assay cutoff concentration. The dose-response curve is first compensated using the signal from the low standard (with a concentration below the cutoff concentration). The high standard (with a concentration above the cutoff concentration) is used as a control to verify the accuracy of the compensated dose-response curve.
  • the same procedure is then repeated, but with the compensation based on the signal from the high standard and the low standard being used as a control.
  • the compensated dose- response curve is obtained by averaging the two sets of assay parameters obtained using the low and high standards for compensation.
  • the known standards when used as controls, therefore provide high and low controls that ensure that the compensation method is working properly and also that there are no other problems in the measurement that could lead to the reporting of an erroneous result.
  • the use of known standards with concentrations near to that of the cutoff enhances the accuracy of the dose-response curve at the cutoff concentration.
  • the terms “comprises”, “comprising”, “including” and “includes” are to be construed as being inclusive and open ended, and not exclusive. Specifically, when used in this specification including claims, the terms “comprises”, “comprising”, “including” and “includes” and variations thereof mean the specified features, steps or components are included. These terms are not to be interpreted to exclude the presence of other features, steps or components.

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Abstract

L'invention concerne des dosages et des procédés de compensation de changements survenant dans la courbe de relation dose-effet d'un dosage, ces changements étant dus aux variations d'une variable de perturbation telle que la température, entre autres. L'invention concerne plus particulièrement un procédé en deux étapes, la première étape consistant à effectuer des mesures de la courbe de relation dose-effet, et donc des paramètres individuels de dosage, avec de nombreuses valeurs différentes de la variable de perturbation, sur tout l'écart de valeurs attendu de ladite variable. Lors de la deuxième étape, des échantillons inconnus sont analysés simultanément avec un étalon connu, dans une concentration d'analyte déterminée. Pendant ces mesures, la valeur de la variable de perturbation est inconnue et la courbe de relation dose-effet est donc également inconnue. Les différentes courbes de relation dose-effet issues de la première étape sont utilisées pour déterminer une relation mathématique entre les paramètres de dosage et le signal de dosage de l'étalon connu. Avec cette relation, dans laquelle la valeur de la variable de perturbation est implicite plutôt qu'explicite, des paramètres de dosage qui sont valables pour la valeur inconnue de la variable de perturbation peuvent être obtenus par substitution de la valeur du signal de dosage issu de l'étalon connu (mesuré lors de l'analyse des échantillons inconnus) dans la relation mathématique et résolution pour les paramètres de dosage. Le procédé selon l'invention permet de déterminer avec précision la concentration d'analyte, même lorsque la variable de perturbation change ou fluctue d'une mesure d'échantillon à l'autre. Une fois la première étape terminée, la deuxième étape peut être effectuée de façon itérative pour mesurer avec précision des échantillons inconnus.
PCT/CA2007/000398 2007-03-12 2007-03-12 Procede de compensation de la courbe de relation dose-effet d'un dosage servant a mesurer la sensibilite a des variables de perturbation WO2008109977A1 (fr)

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