Improved sensor interrogation method

Abstract

A method for determining the concentration of a target analyte in a sample including interrogating an electrochemical sensor with a potential waveform at a first frequency to provide a first current output value and at a second frequency to provide a second current output value. A mathematical relationship between the first and second current output values is used to determine a concentration value for the target analyte.

Description

IMPROVED SENSOR INTERROGATION METHOD

[0001] . This invention was made with United States Government support under grant EB022015 awarded by the National Institutes of Health. The United States Government has certain rights in the invention.FIELD

[0002] . The present disclosure relates generally to methods for operating an electrochemical sensor. More particularly, the disclosure is directed to methods for operating a sensor such that blanked readings can be made for all sensors of a batch in the absence or even in the presence of target analyte.BACKGROUND

[0003] . Electrochemical sensors are becoming well used in the detection of analytes in bodily fluids such as blood and interstitial fluid. These sensors can be used in a range of applications to detect the presence of species endogenous to the subject such as glucose, hormones, and metabolites. The detection of exogenous species such as therapeutic drugs and toxins has also been achieved with electrochemical sensors.

[0004] . Electrochemical sensors have also proven useful in detecting analytes outside the body in in vitro assays. Such assays may be used to detect analytes in biological fluids drawn from a subject, or indeed any fluid.

[0005] . One example of an electrochemical sensor is that configured to sense the level of glucose in the interstitial fluid of a diabetic subject. A fine wire electrode coated with glucose oxidase (GOX) is introduced into the subcutaneous tissue of the subject. Any glucose molecules contacting the GOX enzyme are oxidised, with the reduced GOX then reducing a mediator such as FAD. The mediator is oxidized back to its original form at the electrode surface causing a net change in transport of electrons to / from the electrode. Alternatively, GOX may reduce dissolved oxygen to form hydrogen peroxide. In any event, there is a net change in electron transport causing a measurable change in electron current in the electrode which is proportional to the concentration of glucose.

[0006] . Other types of electrochemical sensors rely on specific binding of the target analyte to an aptamer that is covalently linked to an electrode. Such sensors are often termed electrochemical aptamer-based (EAB) sensors. As is typical for EAB sensors, signalingoccurs when an electrode-bound, redox -reporter-modified aptamer undergoes a binding- induced conformational change (FIG. 1A). This, in turn, alters the rate of electron transfer from the reporter, causing a measurable signal when the sensor is interrogated using any of a number of electrochemical methods.

[0007] . Square wave voltammetry is one method used in the interrogation of electrochemical sensors, and particularly EAB sensors. A method termed kinetic differential measurement (KDM) may be used to process the current output resulting from square wave voltammetry to improve signal gain and correct for signal drift. KDM exploits the ability to tune square wave voltammetry to render the approach more sensitive to faster electron transfer or more sensitive to slower electron transfer, thus switching the EAB sensor from signal-on behavior (target binding increases the magnitude of the voltametric peak) to signal-off behavior (binding reduces peak height) (FIG. IB). Specifically, KDM takes the difference between the normalized currents seen at two matched square wave frequencies. In one implementation of KDM, it is given by:Equation 1.

[0008] . Here z™(target) and Zq^target) are the peak currents observed at the signal-on and signal-off frequencies in the presence of target, and zon(0) and i ffffi) are the peak currents observed at those frequencies in the absence of target.

[0009] . Conventional KDM requires the normalization of each signal value by the value obtained in a solution with no target in it (zon( 0) and iOff( 0) ). This calibration step reduces the convenience of KDM, particularly for use with targets that are already present in the test fluid.

[0010] . The outputs of square wave voltammetry (the “z”s in Equation 1.) are currents, measured in amperes. A complication is that, in addition to being sensitive to the concentration of the target molecule, such an output also depends on the number of redox reporters on the electrode surface, which in turn depends on the microscopic (i.e., nanometer length scale) surface area of the electrode and on the density with which the aptamers are packed on that surface. While the latter may be reproducible (by controllingthe deposition conditions under which the sensor is fabricated), the former may vary several-fold even between electrodes of the same macroscopic dimensions. This, in turn, leads to large sensor-to-sensor changes in the absolute current observed (FIG. 2A).[Oi l]. To correct for such variation, each sensor may be calibrated by measuring the peak currents it produces at a single, known target concentration, typically using a sample for which the concentration is known to be zero (ion(0) and z (0) inEquation 1.). For example, for in vivo studies of drug pharmacokinetics each sensor may be calibrated in vivo prior to the first drug dosing, when the target concentration is known to be zero. While this approach is effective (FIG. 2B), at best it is cumbersome, and at worst, it fails. For example, it cannot be used in the measurement of endogenous targets such as metabolites, or for drugs after dosing has begun, circumstances for which the concentration of the molecule in the body is unknown. Under these circumstances, ex vivo calibration of each sensor may be implemented, which adds significantly to the workload.

[0012] . The prior art also provides a dual-reporter calibration -free approach for in vivo use via the application of a drift-reducing, anti-fouling coating on the electrode surface. Such antifouling is far from perfect, however, and thus some uncorrected drift remains.

[0013] . A further problem is that loading of the aptamer changes over a time period for which the EAB sensor operates. Some EAB sensors are intended to be operable for days at a time, and over that period it is common for the loading to materially decrease. This causes an undesirable drift in current output over time. Information about the blank is required for every sensor to correct the drift effectively and allow target quantification.

[0014] . It is an aspect of the present disclosure to provide an improvement to prior art methods for operating an electrochemical sensor, so as to improve the accuracy of the output. It is a further aspect of the present disclosure to provide a useful alternative to prior art methods for operating an electrochemical sensor.

[0015] . The discussion of documents, acts, materials, devices, articles, and the like is included in this specification solely for the purpose of providing a context for the present disclosure. It is not suggested or represented that any or all of these matters formed part of the prior art base or were common general knowledge in the field relevant to the present disclosure as it existed before the priority date of each claim of this application.SUMMARY

[0016] . In a first aspect, the present disclosure provides a method for determining the concentration of a target analyte in a sample, the method comprising the steps of: interrogating an electrochemical sensor with a potential waveform at a first frequency to provide a first current output value, interrogating the electrochemical sensor, or a similar electrochemical sensor, with a potential waveform at a second frequency to provide a second current output value; and using a mathematical relationship between the first and second current output values to determine a concentration value for the target analyte.

[0017] . In one embodiment of the first aspect, the mathematical relationship comprises a ratio.

[0018] . In one embodiment of the first aspect, the mathematical relationship comprises a difference.

[0019] . In one embodiment of the first aspect, the ratio of the first and second current output values is used in the calculation of a ratiometric kinetic differential measurement (rKDM) given by, > . > Equation 2Where, in Equation 2, R is an output current at frequency 2 when no target is present divided by an output current at frequency 1 when no target is present, where the R value is measured using a subgroup of sensors from a group of sensors, to represent the behaviour of the entire group of sensors. i_l (target) is the output current at frequency 1 for an individual sensor of interest in the test solution of interest and i_2 (target) is the output current at frequency 2 for the same individual sensor of interest in the same test solution of interest. Since the R value is representative of the entire group of sensors rKDM, unlike KDM, does not require the measurement of an output current value in a test solution not containing target for those sensors not in the subgroup.

[0020] . In one embodiment of the first aspect, the representative R value is taken to be the ratio of the mean output current at frequency 2 across all the sensors in the subgroup divided by the mean output current at frequency 1 across all the sensors in the subgroup.

[0021] . In one embodiment of the first aspect, the representative R value is taken to be the ratio of the median output current at frequency 2 across all the sensors in the subgroup divided by the median output current at frequency 1 across all the sensors in the subgroup.

[0022] . In one embodiment of the first aspect, the representative R value is taken to be the ratio of the mode of the output current at frequency 2 across all the sensors in the subgroup divided by the mode of the output current at frequency 1 across all the sensors in the subgroup.

[0023] . In one embodiment of the first aspect, the representative R value is calculated by calculating a separate R value for each sensor in the subgroup and taking the mean, median or mode of those R values to determine the representative R value.

[0024] . In one embodiment of the first aspect, the first frequency and the second frequency are selected such that the output current values at the two frequencies respond differently to the addition of target to the test solution. In some embodiments the current output at one frequency increases when target is added to the test solution and the current output at the second frequency either increases less strongly, or does not change, or decreases when target is added to the test solution.

[0025] . In one embodiment of the first aspect, the first and second current output values are about peak current output values.

[0026] . In one embodiment of the first aspect, the first and second frequencies are selected such that the sensor(s) is / are responsive to the target analyte to different degrees at the first and second frequencies.

[0027] . In one embodiment of the first aspect, one of the first and second frequencies is selected such that the sensor(s) is / are non-responsive or minimally responsive to the target analyte, and the other of the first and second frequencies is selected such that the sensor(s) is / are responsive or highly responsive to the target analyte.

[0028] . In one embodiment of the first aspect, the first frequency and the second frequency are selected such that the sensor(s) is / are responsive to target analyte to different degrees in terms of current output value.

[0029] . In one embodiment of the first aspect, the current output value at the first frequency is different to that at the second frequency by a factor of at least about 1.1, 1.2, 1.3, 1.4,1.5, 1.6, 1.7, 1.8, 1.9, 2, 3, 4, 5, 6, 7, 8,9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1000.

[0030] . In one embodiment of the first aspect, the first frequency and the second frequency are selected by scanning a frequency spectrum when the electrochemical sensor(s) is / are exposed to the target analyte and identifying frequencies providing differential responsiveness.

[0031] . In one embodiment of the first aspect, the potential waveform at the first and second frequencies is each a square waveform.

[0032] . In one embodiment of the first aspect, the method is applied to a group of similar electrochemical sensors.

[0033] . In one embodiment of the first aspect, the similar sensors, or the group of similar sensors, share any one or more of a target analyte detection element, a redox reporter; an electrode material; a production batch; a production time period such as a day, a week, a month, or a year; a manufacturer; a production location; a production line; or a production protocol.

[0034] . In one embodiment of the first aspect, the method is performed at least in part is the absence or the near-absence of the target analyte.

[0035] . In one embodiment of the first aspect, the target analyte concentration is determined by reference to a previously generated calibration curve, or an equation describing or approximating a calibration curve.

[0036] . In one embodiment of the first aspect, the electrochemical sensor is a biosensor or a part of a biosensor.

[0037] . In one embodiment of the first aspect, the electrochemical sensor is configured to output a current that is proportional, or approximately proportional, or inversely proportional, or approximately inversely proportional to the amount of the target analyte in a test fluid.

[0038] . In one embodiment of the first aspect, the electrochemical sensor is operable by way of an enzyme-based catalysis of the target analyte, or by the association of the target analyte with an analyte recognition element associated with the electrochemical sensor.

[0039] . In one embodiment of the first aspect, the analyte recognition element is an aptamer or an antibody or other biological or biomimetic molecule.

[0040] . In one embodiment of the first aspect, the catalysis or recognition causes an alteration in the flow of electrons into and / or out of a working electrode of the electrochemical sensor.

[0041] . In one embodiment of the first aspect, a working electrode of the electrochemical sensor is in the form of a microneedle or a wire insertable into a tissue or fluid of a subject.

[0042] . In one embodiment of the first aspect, the method comprises contacting a test fluid to the electrochemical sensor(s).

[0043] . In one embodiment of the first aspect, the test fluid is disposed in vivo or ex vivo or in vitro.

[0044] . In one embodiment of the first aspect, the test fluid is a biological fluid of a subject in situ.

[0045] . In one embodiment of the first aspect, the test fluid is an undiluted or unmodified biological fluid.

[0046] . In one embodiment of the first aspect, the test fluid is an interstitial fluid.

[0047] . In a second aspect, the present disclosure provides an electrochemical sensor apparatus or system comprising an electrochemical sensor and a microprocessor configured to execute the method of any embodiment of the first aspect.

[0048] . In one embodiment of the second aspect, the electrochemical sensor apparatus or system comprises electronic memory having stored therein program instructions configured to instruct the microprocessor to execute the method of any embodiment of the first aspect.

[0049] . In one embodiment of the second aspect, the electrochemical sensor apparatus or system is a biosensor or a part of a biosensor.

[0050] . In one embodiment of the second aspect, the electrochemical sensor apparatus or system is configured to output a current that is proportional, or approximately proportional, or inversely proportional, or approximately inversely proportional to the amount of the target analyte in a sample.

[0051] . In one embodiment of the second aspect, the electrochemical sensor apparatus or system is operable by way of an enzyme -based catalysis of the target analyte, or by the recognition of the target analyte by an analyte recognition element being part of or associated with the electrochemical sensor apparatus or system.

[0052] . In one embodiment of the second aspect, the analyte recognition element is an aptamer or an antibody or other biological or biomimetic molecule.

[0053] . In one embodiment of the second aspect, the catalysis or recognition causes an alteration in the flow of electrons into and / or out of a working electrode of the electrochemical sensor.

[0054] . In one embodiment of the second aspect, a working electrode of the electrochemical sensor or system is in the form of a needle, a microneedle, or a wire insertable under the skin of a subject.BRIEF DESCRIPTION OF THE FIGURES AND TABLES

[0055] . FIG. 1A illustrates diagrammatically the binding-induced conformational change in an aptamer of an EAB sensor modulates the rate of electron transfer between the redox reporter and the electrode surface.

[0056] . FIG. IB shows first (left) and second (right) graphs current output of an EAB sensor as a function of applied potential in the presence or absence of target analyte. When interrogated with square wave voltammetry, analyte binding-induced change in electron transfer leads to either signal-on (signal increases upon binding, left graph) or signal-off behaviour (signal decreases upon binding, right graph) depending on the square-wave frequency employed.

[0057] . FIG. 1C shows a first (left) and a second (right) graph of normalized signal as a function of time output of an EAB sensor in vivo. Using a pair of square -wave frequencies that drift in concert but respond differentially to the target the drift was removed. And, because the sensor is signal-on and signal-off at the two frequencies employed, the gain is improved.

[0058] . FIG. ID shows a prior art equation for calculation of KDM.

[0059] . FIG. 2A is a graph of raw peak current output as a function of phenylalanine concentration in four individually fabricated phenylalanine-sensitive EAB sensors. This titration was performed in several steps, first in a PBS-BSA (35 mg / ml) solution at 37°C with added rat blood so that the blood-to-PBS-BSA ratio was gradually increased and then in whole blood with added phenylalanine.

[0060] . FIG. 2B is a graph of KDM as a function of phenylalanine concentration in a phenylalanine-sensitive EAB sensor. This titration was performed in step-wise, as described for FIG. 2A.

[0061] . FIG. 2C is a graph of current ratio as a function of phenylalanine concentration in a phenylalanine-sensitive EAB sensor. This titration was performed in step-wise, as described for FIG. 2A.

[0062] . FIG. 2D is a graph of rKDM as a function of phenylalanine concentration in a phenylalanine-sensitive EAB sensor. This titration was performed in step-wise, as described for FIG. 2A.

[0063] . FIG. 3A is a graph of peak current output as a function of vancomycin concentration in four independently fabricated vancomycin-sensitive EAB sensors, demonstrating due to significant differences in, for example, their microscopic surface area, the raw peak currents collected vary significantly from sensor-to-sensor.

[0064] . FIG. 3B is a graph of the ratio of the peak currents (ion / io^) measured at a signal on frequency (100 Hz) and a signal-off frequency (30 Hz) as a function of vancomycin concentration in four independently fabricated vancomycin-sensitive EAB sensors, demonstrating that sensor-to-sensor variability is largely eliminated without the need for determining the signal that each sensor produces at some known target concentration, such as in the absence of target. That is, a single calibration curve can be used for all sensors in this class without the need to calibrate each individual device.

[0065] . FIG. 3C is a graph of rKDM as a function of vancomycin concentration for four independently fabricated, vancomycin-sensitive EAB sensors, demonstrating the use of a ratiometric version of KDM (compare Equation 1. and Equation 2.) to eliminate sensor-to- sensor variability, once again obviating the need for the calibration of individual sensors.

[0066] . FIG. 4 shows two graphs (each for a single rat) of vancomycin concentration as a function of time using a vancomycin-sensitive EAB sensor disposed in the jugular vein. Under these circumstances, both simple ratiometric and rKDM analysis of the sensor output produce measurement estimates that are effectively indistinguishable from one another. Here the drug was given as a 30 mg / kg bolus infusion. The post-injection data are presented as semi-log plots to illustrate relative deviations across the orders of magnitude concentration ranges seen in such pharmacokinetic data.

[0067] . FIG. 5 is a graph of phenylalanine concentration as a function of time as measured by a phenylalanine-sensitive EAB sensor disposed in the jugular vein of a rat, demonstrating both simple ratiometric and rKDM methods produce concentration curves that are practically indistinguishable from one another. Here the drug was given as a 50 mg / kg bolus infusion.

[0068] . FIG. 6 shows a series of four graphs, each graph of vancomycin concentration as a function of vancomycin concentration as a function of time as measured in the jugular vein of two rats using a vancomycin-sensitive EAB sensor. Inserting a second calibration-free sensor into an animal after dosing with vancomycin produces the same output as a first sensor inserted before dosing. This is true in both simple ratiometric and rKDM sensor operation. The drug was given as a 30 mg / kg bolus infusion.

[0069] . TABLE 1 shows raw peak current sensor-to-sensor variation and R values in whole blood in the absence of target, R-values, and coefficients of variation, measured in whole blood for vancomycin and phenylalanine.

[0070] . TABLE 2 shows peak current output for each of the batch of six vancomycin sensitive electrodes used in the Example. Interrogation was performed by square wave voltammetry at a responsive frequency (signal-off; 20 Hz) at a number of vancomycin concentrations (including zero).

[0071] . TABLE 3 shows peak current output for each of the batch of four vancomycin sensitive electrodes used in the Example. Interrogation was performed by square wave voltammetry at a responsive frequency (signal-on; 200 Hz) at a number of vancomycin concentrations (including zero).

[0072] . TABLE 4 shows a rKDM according to a preferred embodiment of the present disclosure (using Equation 2.).

[0073] . TABLE 5 shows the ratio of the currents observed at 200 Hz to those seen at 20 Hz (iaoo / iao) according to an alternative embodiment of the present disclosure.

[0074] . TABLE 6 shows KDM output according to a prior art method (using Equation L).DETAILED DESCRIPTION AND PREFERRED EMBODIMENTS

[0075] . After considering this description it will be apparent to one skilled in the art how the disclosure is implemented in various alternative embodiments and alternative applications. However, although various embodiments of the present disclosure will bedescribed herein, it is understood that these embodiments are presented by way of example only, and not limitation. As such, this description of various alternative embodiments should not be construed to limit the scope or breadth of the present disclosure. Furthermore, statements of advantages or other aspects apply to specific exemplary embodiments, and not necessarily to all embodiments, or indeed any embodiment covered by the claims.

[0076] . Throughout the description and the claims of this specification the word “comprise” and variations of the word, such as “comprising” and “comprises” is not intended to exclude other additives, components, integers, or steps.

[0077] . Reference throughout this specification to “one embodiment” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Thus, appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment, but may.

[0078] . The present disclosure is predicated at least in part on the discovery that a base reading (or “blank” reading) taken in the absence of a target analyte and used to calibrate each electrochemical sensor (and particularly an EAB sensor) is not necessary to obtain a reliable target analyte concentration reading. Two calibration-free approaches are found to be useful in that regard. Firstly, a simple ratiometric method employing the ratio of the peak currents observed at two distinct square-wave frequencies is used. In a second method, a ratiometric KDM (rKDM) approach which employs the ratio of the peak currents seen at the two frequencies in the absence of target analyte for a subgroup of a group of sensors. Using in vivo measurements of vancomycin and phenylalanine it has been demonstrated that the output values for the first and second methods compare well with measurements using the same sensor when traditional KDM is employed. In doing it is found that both methods provide accurately drift-corrected, calibration-free measurements in vivo in live rats, even when employing crudely hand-fabricates sensor devices. By removing the need to calibrate individual sensors, these interrogation methods significantly simplify the use of EAB sensors in in vivo applications.

[0079] . These present methods are distinguished from prior art methods which generate a base reading in the absence of analyte and using interrogation frequencies at which thesensor is responsive to the analyte concerned for each individual sensor. In the present methods, it is only necessary to measure the peak current at the two frequencies being employed in the absence of target analyte for only a subgroup of a group of sensors, where the ratio can be used for all sensors in the group of sensors. The subgroup of sensors can be only a single member of a larger group of sensors or the subgroup can be multiple members of the larger group of sensors, with the ratio of the peak currents being applicable to the other members of the same group of sensors.

[0080] . Advantageously, the present disclosure allows for the generation of a base reading for an electrochemical sensor in circumstances where the analyte is endogenous to the subject, or when an exogenous analyte has been administered to the subject before any base reading would normally be possible, as the currents in the absence of target can be measured for the subgroup of sensors during the manufacturing process for the group of sensors. Moreover, the present disclosure may further allow for the correction of drift in an electrochemical sensor over time.

[0081] . In one aspect, the present disclosure may be implemented in relation to a single sensor as a method for determining the concentration of a target analyte in an electrochemical sensor, the method comprising the steps of: interrogating an electrochemical sensor with a potential waveform at a first frequency for which the electrochemical sensor is responsive to the target analyte at a first level to provide a first current output value, interrogating an electrochemical sensor with a potential waveform at a second frequency for which the electrochemical sensor is responsive to the target analyte at a second level to provide a second current output value; and using the ratio of the first and second current output values (ii / is) to determine a concentration value for the target analyte. That is, the simple ratiometric parameter SR is determined via Equation 3. Equation 3.

[0082] . In another aspect the disclosure may be implemented in relation to a group of sensors (such as a the members of a manufacturing batch) as a method for determining the concentration of a target analyte in an electrochemical sensor, the method comprising the steps of: using a test solution that does not contain the target analyte, interrogating a subgroup of electrochemical sensors from a group of similar electrochemical sensors with a potential waveform at a first frequency for which the electrochemical sensor is responsiveto a target analyte at a first level to provide a first current output value representative of the behaviour of the sensors in the subgroup, interrogating the same subgroup of electrochemical sensors from a group of similar electrochemical sensors with a potential waveform at a second frequency for which the electrochemical sensor is responsive to a target analyte at a second level to provide a second current output value representative of the behaviour of the sensors in the subgroup, taking the ratio of these to currents to calculate an R value and using the R value in Equation 2 to calculate an rKDM value. Wherein the subgroup consists of at least one electrochemical sensor from the group of similar electrochemical sensors.

[0083] . Broadly speaking, two exemplary calibration-free approaches were found to be useful. The first is a simple ratiometric approach employing the ratio of the peak currents observed at two distinct square -wave frequencies, with the second being a ratiometric KDM approach which employs the ratio of peak currents seen at the two frequencies in the absences of target analyte for a subgroup of sensors. As demonstrated in the Examples section herein.

[0084] . According to the present disclosure, a signal measured from an electrochemical sensor can be used in combination with additional batch calibration parameters to derive a base “no target” signal for each sensor. For example, the sensor may be interrogated by square wave voltammetry using two different frequencies (e.g., a signal -on frequency and a signal -off frequency as employed in a KDM method). The signal-on frequency is a frequency for which an increase in sensor current results upon exposure to the target analyte. The signal-off frequency is a frequency for which a decrease in sensor current results upon exposure to the target analyte. The peak current at these two frequencies is measured for a subgroup of a group of sensors and a ratio of peak current at the signal-off frequency to that at the signal-on frequency are used to calculate an R value representative of the behaviour of the measurements for this group, for example the R value could be calculated as the mean, median or mode of the R value calculated for each individual sensor or it could be calculated by taking the mean, median or mode of the peak current at the signal-off frequency (of those measured for the individual sensors in the subgroup) divided by the mean, median or mode of the peak current at the signal-on frequency (of those measured for the individual sensors in the subgroup) respectively. The R value for thesubgroup can then be applied to all sensors in the group using Equation 4, a version of Equation 2, where frequencies 1 and 2 have been designated as on and off frequencies respectively. c .. . Equation 4.It will be noted that Equation 2. does not require any current to be measured in the absence of target (c = 0) for each individual sensor, and accordingly there is no requirement, for example, to collect information before dosing with a drug because this information is introduced in advance via calibration parameter R. Similarly, where the target analyte is a species that will always be present in a sample (for example an endogenous hormone), the calibration parameter R nevertheless allows for a determination of a base “no target” output of the sensor.

[0085] . In some embodiments, sensor output may be converted to into an analyte concentration by way of a calibration curve or an equation describing a calibration curve. Construction of calibration curves are known in the art, and for sake of brevity and clarity the process will not be described in any detail herein. According to the present disclosure, a calibration curve may be generated to relate target analyte concentration to a derivative of sensor output, S, such as a (rKDM or SR). The next step may be to fit the S as a function of target concentration to a mathematic model of an interaction between a binding site (e.g., an aptamer) with a ligand (e.g., an analyte). An exemplary mathematical model is provided by the Langmuir-Hill Equation, which in the context of the present disclosure may be represented as follows:— „ ^max Smin) [Target]min +[Target]n« + K”H2Equation 3. where Smin and Smax are the signals observed at zero and saturating target, [target] is the analyte concentration, nn is the Hill coefficient, and K / / 2 is the binding midpoint.

[0086] . In a further aspect, the present disclosure may be embodied in the form of an apparatus, or a system configured to facilitate execution of the methods described herein.

[0087] . An apparatus of the present disclosure may be embodied in the form of a wearable device that is substantially self-contained, allowing measurements to be performed whilst the subject is undergoing normal activities and / or over a prolonged period of time. The wearable device may be a collar, a bracelet, a strap, an adhesive, or a patch. The wearable device may include transdermal microneedles, of which one of which functions as the working electrode of the sensor by contacting the interstitial fluid of the subject and detecting analytes therein.

[0088] . The wearable device may further comprise a housing structure enclosing one or more other components, such as a processor-based microcontroller. The controller is configured to be in electrical communication with at least one electrode, and generally would include a power source, a data processing unit, electronic memory, and a wireless transmitter / receiver.

[0089] . When embodied as a system, components may be distributed in different physical locations although still operate in an integrated manner. For example, software instructions may be stored and executed by a smart phone or other remote process in data communication with the microprocessor-based controller in a wearable device.

[0090] . As will be understood, the methods described herein may be deployed in part or in whole through one or more microprocessors that execute computer software, program codes, and / or instructions on a processor. A microprocessor may be any kind of computational or processing device capable of executing program instructions, codes, binary instructions, and the like.

[0091] . Any microprocessor may access a storage medium (such as electronic memory) through an interface that may store methods, codes, and instructions as described herein and elsewhere. The storage medium associated with the processor for storing methods, programs, codes, program instructions or other type of instructions capable of being executed.

[0092] . The computer software, program codes, and / or instructions may be stored and / or accessed on computer readable media that may include: computer components, devices, and recording media that retain digital data used for computing for some interval of time; semiconductor storage known as random access memory (RAM); mass storage typicallyfor more permanent storage, such as non-volatile memory such as read only memory (ROM).

[0093] . The methods described herein may transform physical and / or or intangible items from one state to another. The methods and systems described herein may also transform data representing physical and / or intangible items from one state to another.

[0094] . Software products may be created using a structured programming language such as C, an object oriented programming language such as C++, or any other high-level or low-level programming language (including assembly languages, hardware description languages, and database programming languages and technologies) that may be stored, compiled or interpreted to run on a microprocessor, as well as heterogeneous combinations of processors, processor architectures, or combinations of different hardware and software, or any other machine capable of executing program instructions.

[0095] . Thus, in one aspect, any method may be embodied in computer executable code that, when executing on one or more microprocessors, performs the steps thereof. In another aspect, the methods may be embodied in systems that perform the steps thereof, and may be distributed across devices in a number of ways, or all of the functionality may be integrated into a dedicated, standalone device or other hardware. In another aspect, the means for performing the steps associated with the processes described above may include any of the hardware and / or software described above. All such permutations and combinations are intended to fall within the scope of the present disclosure.

[0096] . The disclosure may be embodied in program instruction set executable on one or more microprocessors. Such instructions set may include any one or more of the following instruction types.

[0097] . Data handling and memory operations, which may include an instruction to set a register to a fixed constant value, or copy data from a memory location to a register, or vice-versa, to store the contents of a register, result of a computation, or to retrieve stored data to perform a computation on it later, or to read and write data from hardware devices.

[0098] . Arithmetic and logic operations, which may include an instruction to add, subtract, multiply, or divide the values of two registers, placing the result in a register, possibly setting one or more condition codes in a status register, to perform bitwise operations, e.g., taking the conjunction and disjunction of corresponding bits in a pair of registers, takingthe negation of each bit in a register, or to compare two values in registers (for example, to determine if one is less, or if they are equal).

[0099] . Control flow operations, which may include an instruction to branch to another location in the program and execute instructions there, conditionally branch to another location if a certain condition holds, indirectly branch to another location, or call another block of code, while saving the location of the next instruction as a point to return to.

[0100] . Coprocessor instructions, which may include an instruction to load / store data to and from a coprocessor, or exchanging with CPU registers, or perform coprocessor operations.

[0101] . A processor of a computer of the present system may include “complex” instructions in their instruction set. A single “complex” instruction does something that may take many instructions on other computers. Such instructions are typified by instructions that take multiple steps, control multiple functional units, or otherwise appear on a larger scale than the bulk of simple instructions implemented by the given processor. Some examples of “complex” instructions include: saving many registers on the stack at once, moving large blocks of memory, complicated integer, and floating-point arithmetic (sine, cosine, square root, etc.), SIMD instructions, a single instruction performing an operation on many values in parallel, performing an atomic test-and-set instruction or other read-modify-write atomic instruction, and instructions that perform ALU operations with an operand from memory rather than a register.

[0102] . An instruction may be defined according to its parts. According to more traditional architectures, an instruction includes an opcode that specifies the operation to perform, such as add contents of memory to register — and zero or more operand specifiers, which may specify registers, memory locations, or literal data. The operand specifiers may have addressing modes determining their meaning or may be in fixed fields. In very long instruction word (VLIW) architectures, which include many microcode architectures, multiple simultaneous opcodes and operands are specified in a single instruction.

[0103] . Some types of instruction sets do not have an opcode field (such as TransportTriggered Architectures (TTA) or the Forth virtual machine), only operand(s). Other unusual “0-operand” instruction sets lack any operand specifier fields, such as some stack machines including NOSC.

[0104] . Conditional instructions often have a predicate field — several bits that encode the specific condition to cause the operation to be performed rather than not performed. For example, a conditional branch instruction is executed, and the branch taken, if the condition is true, so that execution proceeds to a different part of the program, and not executed, and the branch not taken, if the condition is false, so that execution continues sequentially. Some instruction sets also have conditional moves, so that the move is executed, and the data stored in the target location, if the condition is true, and not executed, and the target location not modified, if the condition is false. Similarly, IBM z / Architecture has a conditional store. Some instruction sets include a predicate field in every instruction; this is called branch predication.

[0105] . The instructions constituting a program are rarely specified using their internal, numeric form (machine code); they may be specified using an assembly language or, more typically, may be generated from programming languages by compilers.

[0106] . The present disclosure will now be more fully described by reference to the following non-limiting Examples.EXAMPLE 1: In vivo comparison of blank-free vancomycin or phenylalanine sensing method with prior art method requiring a blank sample, including demonstration of drift inhibition in a blank-free method.Materials and MethodsIn vitro sensor fabrication.

[0107] . To create each sensor, a 5 cm long, 0.2 mm diameter gold wire (Thermo FisherScientific, Waltham, MA) was cut. It was then soldered to a gold-plated pin connector (CH Instruments, Inc., Austin, TX) using 60 / 40 lead-selenium solder (Thermoflow, Jacksonville, FL). The sensor area was isolated by covering the gold wire with a 0.356 mm diameter polyolefin heat-shrink tubing (Raychem, Menlo Park, CA) and a hot-air blower (Master Appliance Corp., Racine, WI0) was used to shrink the tubing, leaving 6 mm of the gold wire exposed. Finally, the solder connection was protected by applying a thin layer of thermoplastic connector coating (R.S. Hughes, Sunnyvale, CA).In vivo sensor fabrication.

[0108] . Intravenous sensors were constructed from gold, platinum, and silver wires, individually insulated with polytetrafluoroethylene heat-shrink and bundled together in astaggered manner. 3 mm of the gold wire was exposed at the end of the electrode, with 6 mm exposed platinum wire staggered away from the end followed by 1 cm of silver wire. Once constructed, the silver electrode was chlorinated by immersing the intravenous, three- electrode sensors overnight in household bleach (Clorox, sodium hypochlorite 7.5%). Following this, subsequent rinsing with millipore water was performed prior to electrochemical cleaning.Sensor functionalization.

[0109] . The following protocol was used for both in vitro and in vivo sensors. After fabricating the sensor, the gold surface was cleaned by placing the electrode in an electrochemical cell with a custom-made Teflon lid. The cell was filled with 0.5 M NaOH solution (Sigma Aldrich, St. Louis, MO). Repeated cyclic voltammetry scans were repeated between -1 and -2 V versus Ag|AgCl at a scan rate of 2 Vs1for 1000 scans to ensure the electrode surface was thoroughly cleaned. Surface area of the electrode was then increased by subjecting it to electrochemical roughening. This process was carried out in a 0.5 M H2SO4 solution (Sigma Aldrich, St. Louis, MO). Repeated chronoamperometry between 0 and 2.2 V was used. Following cleaning, electrodes were rinsed with di-ionized water to remove leftover sulfuric acid. For intravenous sensors to be used in vivo, the cleaned and rinsed electrodes were inserted into a 20G catheter (Becton, Dickinson and Company) prior to DNA functionalization.

[0110] . The DNA aptamer sequences used in this Example are as follows:Vancomycin5’- / 5ThioMC6-D / CGA GGG TAC CGC AAT AGT ACT TAT TGT TCG CCT ATT GTG GGT CGG / 3MB / -3’*(SEQ ID NO: 1 CGA GGG TAC CGC AAT AGT ACT TAT TGT TCG CCT ATT GTG GGT CGG)Phenylalanine5’- / 5ThioMC6-D / CGA CCG CGT TTC CCA AGA AAG CAA GTA TTG GTT GGT CG / 3MB / -3’*MB = Methylene Blue(SEQ ID NO: 2 CGA CCG CGT TTC CCA AGA AAG CAA GTA TTG GTT GGT CG)

[0111] . The above DNA sequences labeled with methylene blue (Integrated DNATechnologies, Inc. in Coralville, Iowa) were reduced by incubating 2 pL of 100 pM DNA in 16 pL (vancomycin) or 14 pL (phenylalanine) of 10 mM Tris (2-carboxyethyl) phosphine (Sigma Aldrich, St. Louis, MO) for one hour, shielded from light. The cleaned electrodes were rinsed with millipore water and immersed in a solution containing 500 nM reduced DNA diluted in lx phosphate buffered saline (PBS) for one hour. The PBS was prepared by diluting a 20x stock (Santa Cruz Biotechnologies). After one hour, the electrodes were removed from the DNA solution, rinsed again with millipore water, and incubated overnight in the dark in a 10 mM solution of 6-mercapto-l -hexanol (Sigma Aldrich, St. Louis, MO, diluted in PBS). The following day, the electrodes were rinsed once more with millipore water before being used for the experiments.Calibration curves

[0112] . For in vitro electrochemical measurements, a CH Instruments Multipotentiostat(CHI1040C) with a three-electrode setup was utilized. The working electrode was a gold electrode, the counter electrode was a platinum wire (CH Instruments, Austin, TX) and the reference electrode was an Ag|AgCl electrode (CH Instruments, Austin, TX).

[0113] . To convert traditional KDM, rKDM, or simple ratiometric outputs into estimated concentrations, calibration curves were defined for each sensor class using sensors separate (i.e., out of set) from those employed in vivo. For this, blood (10 mL) from was collected from a -400 g adult male Sprague-Dawley Rats (Charles River Laboratory, Santa Cruz, CA). Briefly, rats were placed under anesthesia using isoflurane gas and, a horizontal incision was made below the rib cage, followed by vertical incisions made through the ribcage to expose the heart. A 20 mL syringe was pre-prepared with 300 units of heparin (Sagent Pharmaceuticals, Schaumburg, IL) to achieve a final concentration range of 15-30 units / mL. An 18G needle was attached to the top of the syringe and inserted into the left ventricle for blood collection (BD, Franklin Lakes, NJ). Very light pressure was placed upon the syringe to facilitate blood removal. Blood draws (12-17 mL total) were stopped when the flow of blood into the syringe finished after which point the animals were euthanized. Blood was then transferred into a custom-made glass cell held at 37°C in a heat block, placed the sensors into this, and allowed them to “settle” for 30 min before starting the titration.

[0114] . To produce calibration curves for the vancomycin sensor, vancomycin hydrochloride (VWR, Radnor, PA) was injected into the cell from a 0.1 M stock solution (diluted in PBS) to achieve the desired concentrations. The sensors were then interrogated with square wave voltammetry at frequencies 100 Hz (signal on) and 30 Hz (signal off). To produce calibration curves for the phenylalanine sensor (FIG. 2), several pre-scans were first run in a PBS-BSA (35 mg / ml) solution at 37°C, followed by pre-scans in rat blood at 37 °C for 30 min to allow for initial drift to settle. Another set of pre-scans were then performed in the PBS-BSA to record the baseline current. Rat blood was then added into the PBS-BSA solution so that the blood-to-PBS-BSA ratio gradually increased until it reached 54% blood. The sensor was then transferred into fresh, whole blood to which phenylalanine was subsequently and step-wise added to reach the higher concentrations on the calibration curves. The endogenous phenylalanine concentration in the rat blood was determined to be 56 p M, measured using a Phenylalanine Assay Kit from Sigma Aldrich.

[0115] . Traditional KDM, rKDM, and simple ratiometric calibration curves were defined using Equations 1., 2., and 3., respectively and the signal-on and signal -off peak currents measured at each target concentration above. For rKDM, the R-value was determined as the average of those of four independently fabricated sensors (TABLE 1), as measured at the first point in the calibration curve, i.e., in 37°C rat blood with no added target for vancomycin and in room temperature PBS-BSA with no added target for phenylalanine. For vancomycin, the calibration data was fitted with a Langmuir isotherm (Equation 3. in which nn = 1). For phenylalanine, a Hill-Langmuir equation (Equation 3. for which nn > 1) was applied.Results and discussion

[0116] . Due to significant differences in, for example, their microscopic surface area, the raw peak currents collected from the (hand-made) EAB sensors used in this Example vary significantly from sensor-to- sensor (FIG 3 A). This variation can be corrected by calibrating each sensor at a single, known concentration, such as the known-to-be-zero concentration of a drug prior to its first administration . Such calibration, however, adds significant additional workload, and is particularly cumbersome for the measurement of endogenous targets, for which “zero-target” calibration samples are not easily obtained.

[0117] . The drift environment found in vitro is less complex than that found in vivo, and thus it would not be expected that information provided by such dual-frequency interrogation is sufficient to both obviate the need for calibration and, simultaneously, to correct for the drift seen in vivo. This Example demonstrates that dual frequency measurements can indeed support calibration-and-drift-free in vivo environments.

[0118] . Reference is made FIG. 2A. Due to significant differences in, for example, their microscopic surface area, the raw peak currents collected from hand-fabricated EAB sensors vary significantly from sensor-to-sensor. To illustrate this, titration curves were generated at the (analyte responsive) signal -on frequency of 100 Hz for 4 independently- hand-made, vancomycin-detecting sensors. (FIG. 2B) That variation is conventionally corrected by traditional KDM (Equation 1.), an approach that removes sensor-to-sensor variability by normalizing the peak currents observed for each sensor by the signal it produces in the absence of target. The error bars in this and the subsequent figures reflect standard deviations of the four independently fabricated sensors. (FIG. 2C) By measuring the ratio of the peak currents observed at a signal on frequency (100 Hz, analyte responsive) and a signal-off (30 Hz, analyte non-responsive) (zon / z ) frequency, however, sensor-to- sensor variability is largely eliminated without the need for determining the signal that each sensor produces in the absence of target. That is, a single calibration curve can be used for all sensors in this class without the need to calibrate each individual device, even for the fairly crude, hand-fabricated devices employ in this Example. (FIG. 2D) The use of rKDM (compare Equation 1. and Equation 2.) likewise eliminates sensor-to-sensor variability, once again obviating the need for the calibration of individual sensors. The data presented here were collected in vitro in undiluted, whole rat blood held at 37°C.

[0119] . Two exemplary approaches to performing calibration-free EAB sensor operation are presented. The first is a rKDM (Equation 2.). Using rKDM, the significant sensor-to- sensor variability observed in raw peak currents largely collapses for these hand-made devices, without the need to calibrate each individual device (FIG. 3C).

[0120] . The ratio of the two peak currents SR, is also a unitless value that is independent of the number of redox -reporter-modified aptamers on the sensor surface, indicating that this analysis method, which we have termed simple ratiometric, supports calibration-free EAB sensor operation. Consistent with this, when this approach is applied to the same independently fabricated sensors,their signals are found to overlap without the necessity calibrating each individual device (FIG. 3B).

[0121] . It may not be expected that calibration -free performance in vitro would translate to calibration-free performance in a living body, where the drift behavior of EAB sensors can be more extreme (FIG. 1C). To test this possibility, a vancomycin-detecting EAB sensor was placed into the right ascending jugulars of two live rats, which were then dosed with drug at 30 mg / kg in a rapid, bolus infusion. Analyzing the resulting data using Equation 1. (traditional KDM), Equation 2. (rKDM), or Equation 3. (SR) with the appropriate, equivalent calibration curve (FIG. 3), the in vivo performance of rKDM was found to largely match that of traditional KDM (FIG. 4).

[0122] . Furthermore, it could not be expected that a simple ratiometric analysis (Equation4.) of EAB sensors would allow for calibration -free and drift-corrected operation in vivo. Surprisingly, the in vivo concentration estimates produced by this approach are effectively indistinguishable from those produced by either traditional KDM or rKDM (FIG. 4).

[0123] . The rKDM and simple ratiometric EAB sensor interrogation methods generally recover the expected zero concentration baseline in the animal prior to vancomycin challenge. This is in contrast to the traditional KDM approach, which only achieves this by "fiat" by assigning the peak current (and resulting KDM signal) seen under these conditions a value of 0. Nevertheless, small offsets from zero were observed for both approaches due to the less-than-perfect reproducibility of the value of R (the ratio of the two peak currents seen at some known target concentration, such as zero target) for the hand-built devices used in this Example. It is proposed that with more highly reproducible, microfabrication of sensors, R will prove even more reproducible sensor-to-sensor, still further improving the calibration-free approaches described herein.

[0124] . Reference is made to FIG. 4 showing plasma vancomycin measurements collected in the jugular veins of two rats. Under these circumstances, simple ratiometric and rKDM analysis of the sensor output produced measurement estimates that are effectively indistinguishable from those produced using traditional KDM. Here the drug was given as a 30 mg / kg bolus infusion. The post-injection data are presented as semi -log plots to illustrate relative deviations across the orders of magnitude concentration ranges seen in such pharmacokinetic data.

[0125] . In the prior art, the calibration of EAB sensors required zero target concentration in situ in the animal prior to challenging it with the target. That approach cannot be employed if the target is present in the subject at unknown concentration prior to the first measurement. Such as, for example, a metabolite that is endogenously present in the body. To address that problem, prior artisans calibrated using an ex vivo sample (of blood or a blood proxy) of known target analyte concentration. A calibration-free approach, such as those described herein, enable the elimination of this additional step. In proof, a sensor for the amino acid phenylalanine was placed in the jugular vein of a live rat. After collecting baseline measurements, the animal was challenged with an intravenous injection of the amino acid at 50 mg / kg before following the resulting plasma concentrations as metabolism returned the animal to homeostasis. Using traditional KDM (here calibrated ex vivo due to the unknown concentration of this endogenous compound in the animal), rKDM, or simple ratiometric approach once again returned pharmacokinetic time courses that are effectively indistinguishable.

[0126] . Reference is made to FIG. 5 showing when measuring the endogenous target phenylalanine in vivo in the jugular vein of a rat, both simple ratiometric and rKDM methods produce concentration curves that are practically indistinguishable from the one produced by the traditional KDM method. Here the drug was given as a 50 mg / kg bolus infusion.

[0127] . A second example for which calibration-free operation is particularly advantageous is in the monitoring of a drug that is already present in the subject. To illustrate this, a vancomycin-detecting sensor was inserted into the right jugular in two live rats, dosed with a bolus of 30 mg / kg vancomycin, and then, ~10 min after peak plasma concentrations were reached, a second sensor was inserted into the left jugular. In both cases the second sensor produced concentration readings highly similar to those of the first sensor when either simple ratiometric or rKDM interrogation was employed.

[0128] . Reference is made to FIG. 6 showing that inserting a second calibration-free sensor into an animal after dosing it with vancomycin produces the same output as a first sensor inserted before dosing. This is true with both simple ratiometric and rKDM sensor operation.Conclusions

[0129] . Due to significant, sensor-to-sensor variation in the number of their redox-reporter- modified aptamers, the absolute currents produced by EAB sensors vary many-fold, a problem that has traditionally been overcome by calibrating each individual sensor. Here, however, measurements of plasma vancomycin and phenylalanine in live rats are used to show that two calibration-free methods, a ratiometric version of KDM (rKDM) and a simple ratiometric method, return concentration estimates effectively within error of those obtained using calibrated sensors. Thus, these two EAB interrogation methods, rKDM and simple ratiometric, can both be used for the effective and accurate, calibration-free measurement of exogenous and endogenous targets in vivo.EXAMPLE 2: In vitro comparison of blank-free vancomycin sensing method with prior art method requiring a blank samplePreparation of aptamer-based vancomycin sensors

[0130] . 2 pL of 100 mM (tris(2-carboxyethyl)phosphine hydrochloride - CAS Number:51805-45-9) was added to 2 pL of 100 pM methylene blue labelled synthetic DNA (5’ThioMC6D / CGAGGGTACCGCAATAGTACTTATTGTTCGCCTATTGTGGGTCG G / 3’MeBIN) (SEQ ID NO: 3CGAGGGTACCGCAATAGTACTTATTGTTCGCCTATTGTGGGTCG) in nuclease- free water over 1 hour in the dark. The DNA solution was then diluted with a phosphate- based saline lx solution to match a final concentration of 0.5 pM DNA and 2 mM MgCh (CAS Number: 7791-18-6).

[0131] . A total of six sensors were prepared as described herein. The working electrode consisted of a gold plated, stainless-steel needles 250 pm in diameter and 4 cm in length. The first step was to partially coat the gold needles with an ultrathin (thickness = 127 pm) heat shrink polyolefin-based tubing. On one terminus, 4 mm of the gold remained exposed for the chemical steps required to prepare the sensor. The opposite terminus remained with 2.8 cm of uncapped gold for electrical connection to an external potentiostat. The polyolefin-coated gold needles were cleaned in high-pressure oxygen plasma (45 W, 5 min) and immediately incubated in the DNA solution for over 1 hour in the dark. After the incubation time in DNA, sensors were transferred to a solution phosphate -based saline lx solution containing 5 mM 6-mercapto-l -hexanol (HS(CH2)eOH - CAS Number: 1633-78- 9) and 2 mM MgCh.

[0132] . Sensors were washed with Milli-Q water to remove residual vancomycin before being immersed in lx PBS containing 0.7 mM MgCh at 35°C for electrochemical interrogation.Interrogation of sensors

[0133] . The experimental set up included the working electrode and discussed above, forming a circuit with a counter electrode, a silver pseudo-reference electrode and a potentiostat.

[0134] . The temperature for interrogation was chosen to mimic skin temperature.

[0135] . Sensors were interrogated via square-wave voltammetry using 20 Hz as the signal- off frequency (TABLE 2), and 200 Hz as the signal-on frequency (TABLE 3). For each sensor, signal was collected in blank (i.e., zero target) and in the presence of 0; 0.5; 1; 2; 4; 8; 15; 25; 40; 55; 75; 100; 200 and 500 pM vancomycin.Results

[0136] . Peak currents for each of the four sensors prepared above were recorded at 20 Hz and 200 Hz (TABLES 2 to 3).

[0137] . For sensors 5 and 6, calculations were made for R as batch representatives, that is, being the ratio of peak currents for signal-off (20 Hz) and signal-on (200 Hz) frequencies (TABLE 4).

[0138] . The calculated values for R were used with Equation 2 to determine a rKDM value(TABLE 4). A subset of two sensors was chosen at random to represent a batch calibration situation for R (per Equation 2.). The motivation is that this subset would then later represent all electrodes. That is, a subset of a batch is chosen to obtain the blank’s peak currents for all devices. where ip is the peak current collected for the signal-off and signal-on frequencies in the absence and in the presence of vancomycin.

[0139] . The calculated values for ip(200 Hz) / ip(20 Hz) was used to determine a sR value(TABLE 5). where ip is the peak current collected for the signal-on and signal-off frequencies in the absence and in the presence of vancomycin.

[0140] . To summarise, a batch of 6 electrodes was analysed. KDM generated a pooled SD of 0.004 for vancomycin concentrations equal or below 2 M, a pooled %CV of 1.74% forthe remaining calibration curve and a pooled %CV of 2.19% inside the clinical range for vancomycin (TABLE 6). Two electrodes were randomly chosen to represent part of the batch and calculate R. rKDM generated a pooled SD of 0.015 for vancomycin concentrations equal or below 2 pM, a pooled %CV of 7.61% for the remaining calibration curve and a pooled %CV of 6.93% inside the clinical range. Numbers were comparable, showing that the present disclosure is able to achieve accuracy similar to that of the prior art by using a blank generated in the presence of the target analyte. sR generated a pooled SD of 0.054 for vancomycin concentrations equal or below 2 pM, a pooled %CV of 0.89 % for the remaining calibration curve and a pooled %CV of 0.69 % inside the clinical range

[0141] . Those skilled in the art will appreciate that the present disclosure is susceptible to further variations and modifications other than those specifically described. It is understood that all such variations and modifications which fall within the spirit and scope of the present disclosure. For example, while the disclosure refers mainly to the use of DNA aptamers as a species of the genus analyte recognition element, the disclosure applies more broadly than DNA aptamers. In accordance with the present disclosure, the term "analyte recognition element" includes any molecule(s) that specifically interact with a target analyte of interest, the interaction causing a discernible change in the molecule(s). An analyte recognition element may be a polymer, and may comprise from about 5 to about 100 monomers, or from about 15 to about 50 monomers.

[0142] . An aptamer is an exemplary form of analyte recognition element. Aptamers are small (usually from 20 to 60 nucleotides) RNA or DNA oligonucleotides formed from a single strand and able to bind a target analyte with high affinity and specificity. Aptamers may be considered as nucleotide analogues of antibodies, but aptamer production is an in vitro cell-free process that is significantly easier and cheaper than the production of antibodies by cell culture or in vivo methods. Aptamers typically comprise a polynucleotide sequence that promotes the assumption of 3-dimensional shapes in the form of helices and single-stranded loops. Indeed, the specificity of aptamer binding is dictated not by the primary polynucleotide sequence, but instead by its 3-dimensional structure, at least is part. In some circumstances, binding will be influenced by hydrophobic interactions, hydrogen bonding, Van der Waals forces, base-stacking, and intercalation.

[0143] . An analyte recognition element may be a biological molecule or an analogue thereof. An exemplary analyte recognition element may be comprised of DNA, RNA, PNA, XNA. Single-stranded and double-stranded arrangements are contemplated.

[0144] . An analyte recognition element may comprise a non-natural nucleic acid. As used herein, the term "non-natural nucleic acid" is intended to include a polymer that is biosimilar to a natural nucleic acid polymer such as DNA or RNA, but having a chemical structure that is altered and not found in nature. As a result of the altered structure, the non- natural nucleic acid may be more resistant than a natural nucleic acid against degradation (such as cleavage of a chemical bond) occasioned by nucleases found in biological fluids such as blood and the ISF.

[0145] . A non-natural nucleic acid may derive from a naturally occurring nucleic acid, but having had an alteration to its chemical structure such that the chemical structure is considered non-natural. More typically, the non-natural nucleic acid will be synthesised de novo in an altered form.

[0146] . A non-natural nucleic acid molecule useful in the context of the present invention may be an altered form of an aptamer. The non-natural nucleic acid may be an oligomer having a non-natural backbone, being a molecular analogue to DNA or RNA. Examples of non-natural backbone oligomers include, but are not limited, to 2' -fluoroarabinoside nucleic acid (FANA), 2'-0-methyl RNA, locked nucleic acid (LNA), and threose nucleic acid (TNA). Collectively, these non-natural backbone oligomers are referred to as xeno nucleic acids (XNAs).

[0147] . Apart from the altered chemical structure which confirms stability in biological fluids, a non-natural nucleic acids may share one or more general features of aptamers such as length, base sequence (primary structure), secondary structure and tertiary structure.

[0148] . One method of identifying aptamers useful in the context of the present invention is to use a method of the prior art (such as SELEX) to identify a natural DNA or RNA aptamer, and optionally to then modify the identified aptamer so as to have a non-natural chemical structure. Alternatively, methods such as SELEX may be adapted by the use enzymes configured to synthesise and amplify non-natural nucleic acids in the first instance.

[0149] . An analyte recognition element may be a protein. The protein may in the form of a peptide, optionally having a length of between 10 and 100 amino acids or longer. The protein may be in the form of a monomer, dimer, trimer, tetramer or higher. Antibodies, antibody fragments (such as Fab fragments) and antibody-like molecules may be useful, whether polyclonal or monoclonal.

[0150] . As for polynucleotides, proteins may be subject to modification. For example, backbone modification may be used to improve proteolytic stability of the peptide. Backbone modification includes the substitution of L-amino acids by D-amino acids , insertion of methyl-amino acids, and the incorporation of ?-amino acids and peptoids. Introducing these non-natural amino acids into the peptide sequence, particularly at a proteolysis site, is an effective strategy for improving resistance to proteases or other deleterious factors.

[0151] . Side chain modifications may be achieved by replacing the natural amino acids with their analogues during peptide synthesis, to improve their binding affinity and target selectivity. Variants of natural amino acid analogues such as homoarginine, benzyloxytyrosine, and P-phenylalanine are commonly commercially available, and can be conveniently used to chemically modify the peptide side chain during peptide synthesis.

[0152] . The weak forces in proteins, such as hydrogen bonds, van der Waals forces, and intramolecular hydrophobic interactions may not be adequate for a stable secondary structure conformation. Additional modifications of the backbone, N- or C-termini, or sidechains for stabilization of secondary structures may be pursued.

[0153] . Cyclization is another potentially useful protein modification technique that can include various strategies, such as head-to-tail, backbone -to-side chain, and side chain-to- side chain cyclization. Cyclization can increase proteolytic stability, and allows mimicking and stabilization of the secondary structure.

[0154] . Accordingly, the spirit and scope of the present disclosure is not to be limited by the foregoing examples, but is to be understood in the broadest sense allowable by law.

Claims

CLAIMS:

1. A method for determining the concentration of a target analyte in a sample, the method comprising the steps of: interrogating an electrochemical sensor with a potential waveform at a first frequency to provide a first current output value, interrogating the electrochemical sensor, or a similar electrochemical sensor, with a potential waveform at a second frequency to provide a second current output value; and using a mathematical relationship between the first and second current output values to determine a concentration value for the target analyte.

2. The method of claim 1 , wherein the mathematical relationship comprises a ratio.

3. The method of claim 1, wherein the mathematical relationship comprises a difference.

4. The method of any one of claims 1 to 3, wherein the first and second current output values are about peak current output values.

5. The method of any one of claims 1 to 4, wherein the first and second frequencies are selected such that the sensor(s) is / are responsive to the target analyte to different degrees at the first and second frequencies.

6. The method of claim 5, wherein one of the first and second frequencies is selected such that the sensor(s) is / are non-responsive or minimally responsive to the target analyte, and the other of the first and second frequencies is selected such that the sensor(s) is / are responsive or highly responsive to the target analyte.

7. The method of claim 5 or claim 6, wherein the first frequency and the second frequency are selected such that the sensor(s) is / are responsive to target analyte to different degrees in terms of current output value.

8. The method of claim 7, wherein the current output value at the first frequency is different to that at the second frequency by a factor of at least about 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2, 3, 4, 5, 6, 7, 8,9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1000.

9. The method of any one of claims 1 to 8, wherein the first frequency and the second frequency are selected by scanning a frequency spectrum when the electrochemical sensor(s) is / are exposed to the target analyte and identifying frequencies providing differential responsiveness.

10. The method of any one of claims 1 to 9, wherein the potential waveform at the first and second frequencies is each a square waveform.

11. The method of any one of claims 1 to 10, applied to a group of similar electrochemical sensors.

12. The method of any one of claims 1 to 10, wherein the similar sensors, or the group of similar sensors, share any one or more of a target analyte detection element, a redox reporter; an electrode material; a production batch; a production time period such as a day, a week, a month, or a year; a manufacturer; a production location; a production line; or a production protocol.

13. The method of any one of claims 1 to 12, performed at least in part is the absence or the near-absence of the target analyte.

14. The method of any one of claims 1 to 13, wherein the target analyte concentration is determined by reference to a previously generated calibration curve, or an equation describing or approximating a calibration curve.

15. The method of any one of claims 1 to 14, wherein the electrochemical sensor is a biosensor or a part of a biosensor.

16. The method of any one of claims 1 to 15, wherein the electrochemical sensor is configured to output a current that is proportional, or approximately proportional, or inversely proportional, or approximately inversely proportional to the amount of the target analyte in a test fluid.

17. The method of any one of claims 1 to 16, wherein the electrochemical sensor is operable by way of an enzyme -based catalysis of the target analyte, or by the recognition of the target analyte by an analyte recognition element associated with the electrochemical sensor.

18. The method of claim 17, wherein the analyte recognition element is an aptamer or an antibody or other biological or biomimetic molecule.

19. The method of claim 16 or claim 17, wherein the catalysis or recognition causes an alteration in the flow of electrons into and / or out of a working electrode of the electrochemical sensor.

20. The method of any one of claims 1 to 19, wherein a working electrode of the electrochemical sensor is in the form of a microneedle or a wire insertable into a tissue or fluid of a subject.

21. The method of any one of claims 1 to 20, comprising contacting a test fluid to the electrochemical sensor(s).

22. The method of claim 21, wherein the test fluid is disposed in vivo or ex vivo or in vitro.

23. The method of claim 21 or claim 22, wherein the test fluid is a biological fluid of a subject in situ.

24. The method of any one of claims 21 to 23, wherein the test fluid is an undiluted or unmodified biological fluid.

25. The method of any one of claims 21 to 24, wherein the test fluid is an interstitial fluid.

26. An electrochemical sensor apparatus or system comprising an electrochemical sensor and a microprocessor configured to execute the method of any one of claims 1 to 25.

27. The electrochemical sensor apparatus or system of claim 26 comprising electronic memory having stored therein program instructions configured to instruct the microprocessor to execute the method of any one of claims 1 to 25.

28. The electrochemical sensor apparatus or system of claim 26 or claim 27, that is a biosensor or a part of a biosensor.

29. The electrochemical sensor apparatus or system of any one of claims 26 to 28, configured to output a current that is proportional, or approximately proportional, or inversely proportional, or approximately inversely proportional to the amount of the target analyte in a sample.

30. The electrochemical sensor apparatus or system of any one of claims 26 to 29, operable by way of an enzyme -based catalysis of the target analyte, or by the recognition of thetarget analyte by an analyte recognition element being part of or associated with the electrochemical sensor apparatus or system.

31. The electrochemical sensor apparatus or system of claim 30, wherein the analyte recognition element is an aptamer or an antibody or other biological or biomimetic molecule.

32. The electrochemical sensor apparatus or system of claim 30 or claim 31, wherein the catalysis or recognition causes an alteration in the flow of electrons into and / or out of a working electrode of the electrochemical sensor.

33. The electrochemical sensor apparatus or system of any one of claims 29 to 32, wherein a working electrode of the electrochemical sensor apparatus or system is in the form of a needle, a microneedle, or a wire insertable under the skin of a subject.

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