WO2025059264A1

WO2025059264A1 - Nucleic acid amplification reaction test results validation

Info

Publication number: WO2025059264A1
Application number: PCT/US2024/046330
Authority: WO
Inventors: M. Scott BROWN
Original assignee: Abbott Laboratories
Current assignee: Abbott Laboratories
Priority date: 2023-09-13
Filing date: 2024-09-12
Publication date: 2025-03-20
Anticipated expiration: 2026-03-13

Abstract

Systems, apparatus, articles of manufacture, and methods are disclosed to validate the results of nucleic acid amplification reaction tests. An example apparatus includes programmable circuitry to at least one of instantiate or execute the machine readable instructions to: calculate differences in amplitudes between consecutive cycles of a plurality of cycles in a fluorescence signal obtained from the test; determine a sum of the differences in amplitudes between consecutive cycles; identify a final amplitude; identify a minimum amplitude of the plurality of cycles; determine a distance as the difference between the final amplitude and the minimum amplitude; determine a ratio of the sum to the distance; and validate the result of the test based on the ratio.

Description

NUCLEIC ACID AMPLIFICATION REACTION TEST RESULTS VALIDATION

FIELD OF THE DISCLOSURE

[0001] This disclosure relates generally to nucleic acid amplification reaction tests and, more particularly, to methods and apparatus to validate nucleic action amplification reaction test results.

BACKGROUND

[0002] Determination of a quantity of a nucleic acid of interest in a biological sample is used in many industrial, medical, biological, and/or research fields. For example, detection of nucleic acid of a pathogen in a biological sample may be used to diagnose a disease.

BRIEF DESCRIPTION OF THE DRAWINGS

[0003] FIG. 1 is a block diagram of example result validation circuitry operable to validate nucleic acid amplification test results.

[0004] FIGS. 2A-D show example curves from nucleic acid amplification reactions.

[0005] FIGS. 2E-G are plots of mathematical transformations of the example curves of FIGS. 2A-D.

[0006] FIGS. 3 and 4 are flowcharts representative of example machine readable instructions and/or example operations that may be executed, instantiated, and/or performed by example programmable circuitry to implement the result validation circuitry of FIG. 1.

[0007] FIG. 5 is a block diagram of an example processing platform including programmable circuitry structured to execute, instantiate, and/or perform the example machine readable instructions and/or perform the example operations of FIGS. 3 and 4 to implement the result validation circuitry of FIG. 1.

[0008] FIG. 6 is a block diagram of an example software/firmware/instructions distribution platform (e.g., one or more servers) to distribute software, instructions, and/or firmware (e.g., corresponding to the example machine readable instructions of FIGS. 3 and 4 to client devices associated with end users and/or consumers (e.g., for license, sale, and/or use), retailers (e.g., for sale, re-sale, license, and/or sub-license), and/or original equipment manufacturers (OEMs) (e.g., for inclusion in products to be distributed to, for example, retailers and/or to other end users such as direct buy customers).

[0009] In general, the same reference numbers will be used throughout the drawing(s) and accompanying written description to refer to the same or like parts. The figures are not necessarily to scale. DETAILED DESCRIPTION

[0010] Disclosed herein are example apparatus, systems, methods, and articles of manufacture for analyzing a biological sample containing nucleic acid or other analytes. During a test of the biological sample, copies of the nucleic acid are made in an amplification reaction to generate a detectable signal. The signal is related to a quantity of nucleic acid in the biological sample or a quantity of copies of the nucleic acid produced by the amplification reaction.

[0011] An example amplification reaction is a polymerase chain reaction ( PCR). In a PCR test, a sample of nucleic acid such as, for example, DNA or RNA, is amplified into millions to billions of copies. In the PCR test, reactants including the sample, primers (e.g., oligonucleotides that are a complementary sequence to the target nucleic acid) and an enzyme (e.g., DNA polymerase) are subjected to thermal cycling, which leads to exponential amplification of the target nucleic acid. Detection of the amplified nucleic acid can be based on fluorescence labels, probes, primers, or dyes bound to the nucleic acid. The intensity of the fluorescence is dependent on the concentration or amount of the target nucleic acid in the sample. Thus, the fluorescence material is used to quantify the PCR test results. The amplitude of the fluorescence signal is recorded for each of the thermal cycles. In this disclosure, the amplitude of the fluorescence signal refers to the strength, value, magnitude, or intensity of the fluorescence signal. In some examples, the fluorescence signal is measured via an optical reader and in a unit of measure called a relative fluorescence unit (RFU).

[0012] Ligase chain reaction (LCR) is another amplification method. LCR is similar to PCR. LCR uses two enzymes (e.g., ligase and polymerase). Another amplification method includes isothermal amplification. Isothermal amplification tests run at a constant temperature. These and other amplification or detection systems or processes produce signals that can be measured in a timedependent or cycle-dependent manner and which are indicative of the quantity of a target nucleic acid. Though this disclosure refers to examples involving PCR, the teachings of disclosure are applicable to other amplification or detections systems or processes.

[0013] Signal data representing fluorescence intensity from a PCR test can be plotted as a function of time or cycle number (CN) (or both) in a two-dimensional plot (y versus x). In some examples, such a plot is generally referred to as a PCR amplification curve or a growth curve, and the data plotted can be referred to as the PCR amplification data. In some examples, a plot includes multiple PCR amplification curves from multiple reactions. The multiple reactions may include, for example, reactions in different wells in a multi-well plate or different channels in a multi-channel cartridge (collectively referred to as channels). The different reactions in the different channels can be, for example, different assays that test for different analytes (e.g., different nucleic acids). For example, Abbott Laboratories has a multiplex assay, which is known as the Resp-4-Plex assay, that tests for SARS- CoV-2, flu A, flu B, and RSV.

[0014] Typically in PCR test results, the growth curve characteristically starts out substantially flat or constant during the early reaction cycles when insufficient amplification has occurred to cause a detectable signal, and then rises exponentially until one or more reaction limiting conditions begin to influence the amplification reaction or the detection process. An example limiting condition includes exhaustion of one or more reactants. Typically, at or near the end of the reaction, the curve flattens again.

[0015] In some examples, the fluorescence signals may be altered by noise. For example, a physical bubble in the reaction mixture may move in front of a reader and cause a rapid increase in the fluorescence signal. Additionally or alternatively, there may be background noise from the environment. Noise in the signals can lead to false positives where a fluorescence signal erroneously indicates that a target nucleic acid is present in a biological sample. To account for noise, in some examples, a control or reference dye is used in one of the channels. The signal obtained from the reference dye may be used as a control to identify and normalize out background noise, which can be subtracted from the other curves. However, the inclusion of a reference dye uses a dedicated fluorescence channel, which restricts the ability to multiplex assays because one channel is reserved for the reference dye.

[0016] In addition, within the parameter space defined by existing PCR validity checks to identify false positives due to abnormal and/or noisy PCR curves, it can be difficult to effectively partition positive, negative, and noisy signals from each other. This can force undesirable choices regarding the tradeoff between sensitivity and specificity. Sensitivity and specificity are measures of the ability of a test to correctly classify the presence or absence of a target nucleic acid (which may be used to diagnose a subject as having a disease or not having a disease). Sensitivity reflects the ability of a test to identify a positive result. A highly sensitive test has few false negative results. Specificity reflects the ability of a test to identify a negative result. A highly specific test has few false positive results. Highly sensitive tests miss fewer diseases, and highly specific tests avoid misdiagnosing people as positive, which may result in unnecessary treatment.

[0017] Selecting a high fluorescence signal positivity threshold may protect against noise- associated false positives at the cost of decreased sensitivity. Conversely, selecting a low fluorescence signal positivity threshold may ensure high sensitivity but leave the assay exposed to the risk of noise- associated false positives. While false positives can have many root causes, in this disclosure, false positives specifically refer to the subset of false positives caused by fluorescent signal noise. Similarly, true positives specifically refer to the subset of true positives with canonical amplification curves without fluorescent signal noise abnormalities. [0018] Examples disclosed herein provide validity checks that ensure high sensitivity and low risk of noise-associated false positives. In addition, the examples disclosed herein can validate nucleic acid amplification (e.g., PCR) test results without the use of a reference dye. Thus, in some examples, greater multiplexing is facilitated because an extra channel is free for use for an additional assay rather than being dedicated to the control or reference signal.

[0019] FIG. 1 is a block diagram of example result validation circuitry 100 operable to validate nucleic acid amplification test results and reduce the number of and/or a likelihood of a false positive result. The result validation circuitry 100 includes example interface circuitry 102, example signal processing circuitry 104, example calculation circuitry 106, example evaluation circuitry 108, and an example database 110.

[0020] The interface circuitry 102 receives, accesses, or otherwise obtains signal data including fluorescence amplitude data, cycle number data, and time data for nucleic acid amplification tests. In some examples, the data has already been processed through a noise reduction process such as, for example, signal normalization relative to a passive reference dye. The fluorescence signal data from a single PCR reaction can be represented as the data series shown in Equation 1.

Equation (1)

In Equation 1, F corresponds to the fluorescence, and 1, 2, 3... n correspond to the cycle number in the amplification reaction. The value of the variable n is based on the type of assay for which the amplification reaction is conducted. For example, there may be 42 cycles for the Resp-4-plex assay. Thus, in this example, the value of n is 42.

[0021] The signal processing circuitry 104 processes the signal data. In some examples, the signal processing circuitry 104 plots the signal data into an x-y plot such as, for example, as shown in FIGS. 2A-D. In some examples, the signal processing circuitry 104 plots cycle-to-cycle differences of the fluorescence signals as shown in FIGS. 2E-H. The x-axes of the graphs in FIGS. 2A-H correspond to a cycle number. The y-axes of FIGS. 2A-D correspond to the amplitude of the fluorescence. The y-axes of FIGS. 2E-H correspond to cycle-to-cycle differences of the fluorescence signals. FIGS. 2B, 2D, 2F, and 2H are zoomed versions of FIGS. 2A, 2C, 2E, and 2G, respectively. The graphs show the results from five tests, labeled A, B, C, D, and E. The graphs of FIGS. 2A and 2B are labeled Ff_Un length, which show the data for the test results of the five tests over the full length of the test, i.e., over all of the cycles.

[0022] In some examples, the signal processing circuitry 104 trims the signal data by excluding data from a number of the initial cycles. There may be initial transient changes in the fluorescence reading for the assays that may skew the results because the initial readings are not indicative of the amplification of the nucleic acid. Thus, the signal processing circuitry 104 creates another data set, i.e., a truncated data set, for further analysis as represented by Equation 2.

Equation (2)

ln Equation 2, a corresponds to the cycle (or index) of the first fluorescence reading to include in the analysis. The value of the variable a is based on the type of assay for which the amplification reaction is conducted. For example, for the Resp-4-plex assay, the value of a is 11. Thus, in this example, the signal processing circuitry 104 excludes data from the first 11 cycles from further analysis. In other examples, a has other values such as, for example, 10. The value of a is based on the needs and characteristics of the assay. In some examples, the value of a is empirically determined based on analysis of prior, known results. The graphs of FIGS. 2C and 2D are labeled F and have the first a number of cycles excluded.

[0023] The five tests shown in FIGS. 2A-H are all classified as positive results. However, some are noise-associated false positives. Noise-associated false positives can take many forms. For example, curve C of FIGS. 2A-H is an example of a jagged curve due to noise. Curve D is an example of a one cycle step curve due to noise. In addition, curve E is an example of a two cycle step curve due to noise. If these curves had a reference dye, the reference dye would have very similar fluorescence profiles, resulting in a flat, relatively noise-free normalized signal. However, without normalization, these types of PCR curves may evade current validity checks because they appear similar to normal positive PCR curves in the assessed dimensions such as, for example the cycle number at which the signal crosses a threshold value above the background signal, etc.

[0024] The calculation circuitry 106 calculates the cycle-to-cycle difference in the fluorescence data. The cycle-to-cycle difference in the fluorescence data are also known as differences in amplitude or amplitude differences. The calculation circuitry 106 creates a data series, T, of the cycle-to-cycle differences in fluorescence signal values as represented by Equation 3.

T = [Fa+1 - Fa, Fa+2 - Fa+1, ..., F_n - F_n-i] Equation (3)

The graphs of FIGS. 2E and 2F are labeled T, which are plots of the cycle-to-cycle differences in the five tests.

[0025] The calculation circuitry 106 sorts the cycle-to-cycle differences from highest, largest, or greatest to lowest. The calculation circuitry 106 creates a data series, S, of the sorted cycle-to-cycle differences in fluorescence signal values, which is represented by Equation 4.

S= [Ta+i, Ta+2, ..., T_n] Equation (4)

Si will be the greatest difference, S₂ will be the second greatest difference, etc. The graphs of FIGS. 2G and 2H are labeled S, which are plots of the sorted cycle-to-cycle differences in the five tests.

[0026] The results validation circuitry 100 performs one or more validity checks on the nucleic acid amplification results to verify that a positive result is a genuine positive result indicative of the presence of a target nucleic acid in a biological sample and not a noise-associated false positive. The validity checks expand the dimensions assessed using the data series disclosed herein to recognize noisy PCR curves as abnormal, which prevents false positive PCR results due to fluorescence noise. [0027] A first validity check performed by the result validation circuitry 100 leverages the cycle-to-cycle differences data series, T. In the first validity check, the calculation circuitry 106 calculates a total distance of the cycle-to-cycle differences. The total distance is the sum of the absolute values of the cycle-to-cycle differences, as shown in Equation 5.

Total distance = "₊ T| Equation (5)

The calculation circuitry 106 calculates an upward distance. The upward distance is the difference between the amplitude or strength of the fluorescence signal at the last cycle and the minimum amplitude, as shown in Equation 6.

Upward distance = F_n- min (F_a ... F_n) Equation (6)

The calculation circuitry 106 calculates a total distance ratio (TDR), as shown in Equation 7.

Total Distance

Total Distance Ratio = - Upward Distance Equation (7)

[0028] The evaluation circuitry 108 compares the total distance ratio to a threshold total distance ratio. The threshold total distance ratio is based on the type of assay for which the nucleic acid amplification reaction is performed. In some examples, the threshold total distance ratio is empirically determined. In some examples, the threshold total distance ratio is based on a distribution of normal or known positive nucleic acid amplification curves compared to known false positives. In some examples, the threshold total distance ratio is just over a maximum value for true positive results. In some examples, the threshold total distance ratio is just under a minimum value for false positive results. In some examples, the threshold total distance ratio is derived from or based on a statistical method such as, for example, a specific number of standard deviations away from a mean total distance ratio of a true positive population. In some examples, "just over" a maximum value indicates within 0.1% to 0.9% of the maximum value. In some examples, "just over" a maximum value indicates within 1% of the maximum value. In some examples, "just under" a minimum value indicates within 0.1% to 0.9% of the minimum value. In some examples, "just under" a minimum value indicates within 1% of the minimum value.

[0029] If the total distance ratio satisfies the threshold (e.g., the total distance ratio is less than the threshold total distance ratio), the results of the nucleic acid amplification reaction test will be deemed valid. If the total distance ratio does not satisfy the threshold (e.g., the total distance ratio is greater than the threshold total distance ratio), the results of the nucleic acid amplification reaction test will be deemed invalid. Invalid results are indicative of a false positive.

[0030] A second validity check performed by the result validation circuitry 100 leverages the sorted cycle-to-cycle differences data series, S. In the second validity check, the calculation circuitry 106 identifies the greatest difference and the second greatest difference of the cycle-to-cycle differences. The calculation circuitry 106 calculates a largest delta ratio ( LD R), which is the ratio of the greatest distance and the second greatest distance as shown in Equation 8.

, . s, greatest cycle-to-cycle difference

Largest Delta Ratio = — = - - - - - - - — - Equation (8)

5₂ second greatest cycle-to-cycle difference

[0031] The evaluation circuitry 108 compares the largest delta ratio to a threshold largest delta ratio. The threshold largest delta ratio is based on the type of assay for which the nucleic acid amplification reaction is performed. In some examples, the threshold largest delta ratio is empirically determined. In some examples, the threshold largest delta ratio is based on a distribution of normal or known positive nucleic acid amplification curves compared to known false positives. In some examples, the threshold largest delta ratio is just over a maximum value for true positive results. In some examples, the threshold largest delta ratio is just under a minimum value for false positive results. In some examples, the threshold largest delta ratio is derived from or based on a statistical method such as, for example, a specific number of standard deviations away from a mean largest delta ratio of a true positive population. In some examples, "just over" a maximum value indicates within 0.1% to 0.9% of the maximum value. In some examples, "just over" a maximum value indicates within 1% of the maximum value. In some examples, "just under" a minimum value indicates within 0.1% to 0.9% of the minimum value. In some examples, "just under" a minimum value indicates within 1% of the minimum value.

[0032] If the largest delta ratio satisfies the threshold (e.g., the largest delta ratio is less than the threshold largest delta ratio), the results of the nucleic acid amplification reaction test will be deemed valid. If the largest delta ratio does not satisfy the threshold (e.g., the largest delta ratio is greater than the threshold largest delta distance ratio), the results of the nucleic acid amplification reaction test will be deemed invalid. Invalid results are indicative of a false positive.

[0033] A third validity check performed by the result validation circuitry 100 leverages the sorted cycle-to-cycle differences data series, S. In the third validity check, the calculation circuitry 106 identifies the second greatest difference and the third greatest difference of the cycle-to-cycle differences. The calculation circuitry 106 calculates a second largest delta ratio (2LDR), which is the ratio of the second greatest distance and the third greatest distance as shown in Equation 9. „ , . $■, second greatest cycle-to-cycle difference

Second Largest Delta Ratio = — 5₃ = - third g -r -eatest cy -c -le-to-cy -c -le dif —fe -rence Equation (9)

[0034] The evaluation circuitry 108 compares the second largest delta ratio to a threshold second largest delta ratio. The threshold second largest delta ratio is based on the type of assay for which the nucleic acid amplification reaction is performed. In some examples, the threshold second largest delta ratio is empirically determined. In some examples, the threshold second largest delta ratio is based on a distribution of normal or known positive nucleic acid amplification curves compared to known false positives. In some examples, the threshold second largest delta ratio is just over a maximum value for true positive results. In some examples, the threshold second largest delta ratio is just under a minimum value for false positive results. In some examples, the threshold second largest delta ratio is derived from or based on a statistical method such as, for example, a specific number of standard deviations away from a mean second largest delta ratio of a true positive population. In some examples, "just over" a maximum value indicates within 0.1% to 0.9% of the maximum value. In some examples, "just over" a maximum value indicates within 1% of the maximum value. In some examples, "just under" a minimum value indicates within 0.1% to 0.9% of the minimum value. In some examples, "just under" a minimum value indicates within 1% of the minimum value.

[0035] If the second largest delta ratio satisfies the threshold (e.g., the second largest delta ratio is less than the threshold second largest delta ratio), the results of the nucleic acid amplification reaction test will be deemed valid. If the second largest delta ratio does not satisfy the threshold (e.g., the second largest delta ratio is greater than the threshold second largest delta distance ratio), the results of the nucleic acid amplification reaction test will be deemed invalid. Invalid results are indicative of a false positive.

[0036] The example five curves in FIGS. 2A-H all show a positive test result. In this example, assays C, D, and E are false positives due to noise, and assays A and B are true positives that are legitimate PCR amplification curves. Example data shown in Table 1.

TABLE 1

[0037] In some examples, a positive PCR curve will have a total distance ratio (TDR), a largest delta ratio (LDR), and second largest delta ratio (2LDR) values close to one. As expected of a strong positive PCR curve, example assay A has TDR, LDR, and 2LDR values close to one. Very weak positive PCR curves tend to have slightly greater TDR, LDR, and 2LDR values as manifested by example assay B. However, even the values associated with weak, legitimate positive PCR curves are distant from the values associated with noisy, false positive PCR curves. Example assays C, D, and E demonstrate how the TDR, LDR, or 2LDR values can be dramatically elevated in noisy PCR curves relative to normal PCR curves.

[0038] If, in one example, the threshold total distance ratio, (X_TDR), the threshold largest delta ratio (X_LDR), and the threshold second largest delta ratio (X₂LOR) all have a value of 2.5, then: • Example assay A remains valid (i.e., is legitimately identified as a positive result) because the TDR = 1.004, which is less than or equal to 2.5 (the XTDR); the LDR = 1.010, which is less than or equal to 2.5 (the XLDR); and 2LDR = 1.193, which is less than or equal to 2.5 (the X₂LDR).

• Example assay B remains valid (i.e., is legitimately identified as a positive result) because the TDR = 1.163 which is less than or equal to which is less than or equal to 2.5 (the X_TDR); and the LDR = 1.246, which is less than or equal to 2.5 (the XLDR); and the 2LDR = 1.317, which is less than or equal to 2.5 (the X₂LDR).

• Example assay C is successfully invalidated (i.e., properly identified as a false positive) because the TDR = 5.937, which is greater than 2.5 (the XTDR).

• Example assay D is successfully invalidated (i.e., properly identified as a false positive) because the LDR = 17.233, which is greater than 2.5 (the XLDR).

• Example assay E is successfully invalidated (i.e., properly identified as a false positive) because the 2LDR = 24.146, which is greater than 2.5 (the X_2LDR).

This example demonstrates how the TDR, LDR, and 2LDR validity checks performed by the result validation circuitry 100 can selectively invalidate false positive results due to noisy signals. Also, though three types of validity checks are disclosed herein, in some examples the failure of one validity check is enough to categorize the result as invalid (i.e., as a false positive). In other examples, two or three validity checks may be used to confirm a result.

[0039] The validity checks performed by the result validation circuitry 100 create measurements that can be compared to theoretically ideal values and increase the number of orthogonal assessments of PCR curve normality. For example, curve C in FIGS. 2A-H is not sufficiently different from normal PCR curves in the dimensions of cycle difference, LDR, and 2LDR to invalidate as a false positive. However, curve C is sufficiently different in the TDR dimension to identify that the curve C is disparate from normal curves and should be invalidated as a false positive. Likewise, curves D and E are relatively normal in all dimensions except LDR and 2LDR, respectively. The validity checks disclosed herein protect against noise-related false positives, without having to resort to a higher Ct threshold, for example, which could decrease sensitivity of the assay.

[0040] In some examples, the evaluation circuitry 108 identifies if a parameter is met before implementing one or more of the validity checks disclosed herein. For example, the result validation circuitry 100 implements one or more of the total distance ratio, largest delta ratio, and/or second largest delta ratio validity check if the evaluation circuitry 108 identifies that the Ct (a threshold cycle number) is earlier than a positive cycle cutoff number.

[0041] The data used by the elements of the result validation circuitry and data produced by the components of the result validation circuitry 100 can be stored and/or retrieved from the database 110. In addition, the results (e.g., a true positive or a false positive designation of a nucleic acid a mplification test) can be communicated from the result validation circuitry 100 through the interface circuitry 102.

[0042] The result validation circuitry 100, the interface circuitry 102, the signal processing circuitry 104, the calculation circuitry 106, and/or the evaluation circuitry 108 of FIG. 1 may be instantiated (e.g., creating an instance of, bring into being for any length of time, materialize, implement, etc.) by programmable circuitry such as a Central Processor Unit (CPU) executing first instructions. Additionally or alternatively, the result validation circuitry 100, the interface circuitry 102, the signal processing circuitry 104, the calculation circuitry 106, and/or the evaluation circuitry 108 of FIG. 1 may be instantiated (e.g., creating an instance of, bring into being for any length of time, materialize, implement, etc.) by (i) an Application Specific Integrated Circuit (ASIC) and/or (ii) a Field Programmable Gate Array (FPGA) structured and/or configured in response to execution of second instructions to perform operations corresponding to the first instructions. It should be understood that some or all of the circuitry of FIG. 1 may, thus, be instantiated at the same or different times. Some or all of the circuitry of FIG. 1 may be instantiated, for example, in one or more threads executing concurrently on hardware and/or in series on hardware. Moreover, in some examples, some or all of the circuitry of FIG. 1 may be implemented by microprocessor circuitry executing instructions and/or FPGA circuitry performing operations to implement one or more virtual machines and/or containers.

[0043] In some examples, the apparatus includes means for validating results of a nucleic acid amplification reaction. For example, the means for validating may be implemented by the result validation circuitry 100. In some examples, the result validation circuitry 100 may be instantiated by programmable circuitry such as the example programmable circuitry 512 of FIG. 5. For instance, the result validation circuitry 100 may be instantiated by the example processor circuitry 512 of FIG. 5 executing machine executable instructions such as those implemented by the blocks of FIGS. 3 and 4. In some examples, result validation circuitry 100 may be instantiated by hardware logic circuitry, which may be implemented by an ASIC, XPU, FPGA circuitry configured and/or structured to perform operations corresponding to the machine readable instructions. Additionally or alternatively, the result validation circuitry 100 may be instantiated by any other combination of hardware, software, and/or firmware. For example, the result validation circuitry 100 may be implemented by at least one or more hardware circuits (e.g., processor circuitry, discrete and/or integrated analog and/or digital circuitry, an FPGA, an ASIC, an XPU, a comparator, an operational-amplifier (op-amp), a logic circuit, etc.) configured and/or structured to execute some or all of the machine readable instructions and/or to perform some or all of the operations corresponding to the machine readable instructions without executing software or firmware, but other structures are likewise appropriate.

[0044] While an example manner of implementing the result validation circuitry 100 is illustrated in FIG. 1, one or more of the elements, processes, and/or devices illustrated in FIG. 1 may be combined, divided, re-arranged, omitted, eliminated, and/or implemented in any other way. Further, the example interface circuitry 102, the example signal processing circuitry 104, the example calculation circuitry 106, the example evaluation circuitry 110, and/or, more generally, the example result validation circuitry 100 of FIG. 1, may be implemented by hardware alone or by hardware in combination with software and/or firmware. Thus, for example, any of the example interface circuitry 102, the example signal processing circuitry 104, the example calculation circuitry 106, the example evaluation circuitry 110, and/or, more generally, the example result validation circuitry 100, could be implemented by programmable circuitry in combination with machine readable instructions (e.g., firmware or software), processor circuitry, analog circuit(s), digital circuit(s), logic circuit(s), programmable processor(s), programmable microcontroller(s), graphics processing unit(s) (GPU(s)), digital signal processor(s) (DSP(s)), ASIC(s), programmable logic device(s) (PLD(s)), and/or field programmable logic device(s) (FPLD(s)) such as FPGAs. Further still, the example result validation circuitry 100 of FIG. 1 may include one or more elements, processes, and/or devices in addition to, or instead of, those illustrated in FIG. 1, and/or may include more than one of any or all of the illustrated elements, processes and devices.

[0045] Flowchart(s) representative of example machine readable instructions, which may be executed by programmable circuitry to implement and/or instantiate the result validation circuitry 100 of FIG. 1 and/or representative of example operations which may be performed by programmable circuitry to implement and/or instantiate the result validation circuitry 100 of FIG. 1, are shown in FIGS. 3 and 4. The machine readable instructions may be one or more executable programs or portion(s) of one or more executable programs for execution by programmable circuitry such as the processor circuitry 512 shown in the example processor platform 500 discussed below in connection with FIG. 5. In some examples, the machine readable instructions cause an operation, a task, etc., to be carried out and/or performed in an automated manner in the real world. As used herein, "automated" means without human involvement.

[0046] The program may be embodied in instructions (e.g., software and/or firmware) stored on one or more non-transitory computer readable and/or machine readable storage medium such as cache memory, a magnetic-storage device or disk (e.g., a floppy disk, a Hard Disk Drive (HDD), etc.), an optical-storage device or disk (e.g., a Blu-ray disk, a Compact Disk (CD), a Digital Versatile Disk (DVD), etc.), a Redundant Array of Independent Disks (RAID), a register, ROM, a solid-state drive (SSD), SSD memory, non-volatile memory (e.g., electrically erasable programmable read-only memory (EEPROM), flash memory, etc.), volatile memory (e.g., Random Access Memory (RAM) of any type, etc.), and/or any other storage device or storage disk. The instructions of the non-transitory computer readable and/or machine readable medium may program and/or be executed by programmable circuitry located in one or more hardware devices, but the entire program and/or parts thereof could alternatively be executed and/or instantiated by one or more hardware devices other than the programmable circuitry and/or embodied in dedicated hardware. The machine readable instructions may be distributed across multiple hardware devices and/or executed by two or more hardware devices (e.g., a server and a client hardware device). For example, the client hardware device may be implemented by an endpoint client hardware device (e.g., a hardware device associated with a human and/or machine user) or an intermediate client hardware device gateway (e.g., a radio access network (RAN)) that may facilitate communication between a server and an endpoint client hardware device. Similarly, the non-transitory computer readable storage medium may include one or more mediums. Further, although the example program is described with reference to the flowchart(s) illustrated in FIGS. 3 and 4, many other methods of implementing the example result validation circuitry 100 may alternatively be used. For example, the order of execution of the blocks of the flowchart(s) may be changed, and/or some of the blocks described may be changed, eliminated, or combined. Additionally or alternatively, any or all of the blocks of the flow chart may be implemented by one or more hardware circuits (e.g., processor circuitry, discrete and/or integrated analog and/or digital circuitry, an FPGA, an ASIC, a comparator, an operational-amplifier (op-amp), a logic circuit, etc.) structured to perform the corresponding operation without executing software or firmware. The programmable circuitry may be distributed in different network locations and/or local to one or more hardware devices (e.g., a single-core processor (e.g., a single core CPU), a multi-core processor (e.g., a multi-core CPU, an XPU, etc.)). For example, the programmable circuitry may be a CPU and/or an FPGA located in the same package (e.g., the same integrated circuit (IC) package or in two or more separate housings), one or more processors in a single machine, multiple processors distributed across multiple servers of a server rack, multiple processors distributed across one or more server racks, etc., and/or any combination(s) thereof.

[0047] The machine readable instructions described herein may be stored in one or more of a compressed format, an encrypted format, a fragmented format, a compiled format, an executable format, a packaged format, etc. Machine readable instructions as described herein may be stored as data (e.g., computer-readable data, machine-readable data, one or more bits (e.g., one or more computer-readable bits, one or more machine-readable bits, etc.), a bitstream (e.g., a computer- readable bitstream, a machine-readable bitstream, etc.), etc.) or a data structure (e.g., as portion(s) of instructions, code, representations of code, etc.) that may be utilized to create, manufacture, and/or produce machine executable instructions. For example, the machine readable instructions may be fragmented and stored on one or more storage devices, disks and/or computing devices (e.g., servers) located at the same or different locations of a network or collection of networks (e.g., in the cloud, in edge devices, etc.). The machine readable instructions may require one or more of installation, modification, adaptation, updating, combining, supplementing, configuring, decryption, decompression, unpacking, distribution, reassignment, compilation, etc., in order to make them directly readable, interpretable, and/or executable by a computing device and/or other machine. For example, the machine readable instructions may be stored in multiple parts, which are individually compressed, encrypted, and/or stored on separate computing devices, wherein the parts when decrypted, decompressed, and/or combined form a set of computer-executable and/or machine executable instructions that implement one or more functions and/or operations that may together form a program such as that described herein.

[0048] In another example, the machine readable instructions may be stored in a state in which they may be read by programmable circuitry, but require addition of a library (e.g., a dynamic link library (DLL)), a software development kit (SDK), an application programming interface (API), etc., in order to execute the machine-readable instructions on a particular computing device or other device. In another example, the machine readable instructions may need to be configured (e.g., settings stored, data input, network addresses recorded, etc.) before the machine readable instructions and/or the corresponding program(s) can be executed in whole or in part. Thus, machine readable, computer readable and/or machine readable media, as used herein, may include instructions and/or program(s) regardless of the particular format or state of the machine readable instructions and/or program(s).

[0049] The machine readable instructions described herein can be represented by any past, present, or future instruction language, scripting language, programming language, etc. For example, the machine readable instructions may be represented using any of the following languages: C, C++, Java, C#, Perl, Python, JavaScript, HyperText Markup Language (HTML), Structured Query Language (SQL), Swift, etc.

[0050] As mentioned above, the example operations of FIGS. 3 and 4 may be implemented using executable instructions (e.g., computer readable and/or machine readable instructions) stored on one or more non-transitory computer readable and/or machine readable media. As used herein, the terms non-transitory computer readable medium, non-transitory computer readable storage medium, non-transitory machine readable medium, and/or non-transitory machine readable storage medium are expressly defined to include any type of computer readable storage device and/or storage disk and to exclude propagating signals and to exclude transmission media. Examples of such non-transitory computer readable medium, non-transitory computer readable storage medium, non-transitory machine readable medium, and/or non-transitory machine readable storage medium include optical storage devices, magnetic storage devices, an HDD, a flash memory, a read-only memory (ROM), a CD, a DVD, a cache, a RAM of any type, a register, and/or any other storage device or storage disk in which information is stored for any duration (e.g., for extended time periods, permanently, for brief instances, for temporarily buffering, and/or for caching of the information). As used herein, the terms "non- transitory computer readable storage device" and "non-transitory machine readable storage device" are defined to include any physical (mechanical, magnetic and/or electrical) hardware to retain information for a time period, but to exclude propagating signals and to exclude transmission media. Examples of non-transitory computer readable storage devices and/ or non-transitory machine readable storage devices include random access memory of any type, read only memory of any type, solid state memory, flash memory, optical discs, magnetic disks, disk drives, and/or redundant array of independent disks (RAID) systems. As used herein, the term "device" refers to physical structure such as mechanical and/or electrical equipment, hardware, and/or circuitry that may or may not be configured by computer readable instructions, machine readable instructions, etc., and/or manufactured to execute computer-readable instructions, machine-readable instructions, etc.

[0051] "Including" and "comprising" (and all forms and tenses thereof) are used herein to be open ended terms. Thus, whenever a claim employs any form of "include" or "comprise" (e.g., comprises, includes, comprising, including, having, etc.) as a preamble or within a claim recitation of any kind, it is to be understood that additional elements, terms, etc., may be present without falling outside the scope of the corresponding claim or recitation. As used herein, when the phrase "at least" is used as the transition term in, for example, a preamble of a claim, it is open-ended in the same manner as the term "comprising" and "including" are open ended. The term "and/or" when used, for example, in a form such as A, B, and/or C refers to any combination or subset of A, B, C such as (1) A alone, (2) B alone, (3) C alone, (4) A with B, (5) A with C, (6) B with C, or (7) A with B and with C. As used herein in the context of describing structures, components, items, objects and/or things, the phrase "at least one of A and B" is intended to refer to implementations including any of (1) at least one A, (2) at least one B, or (3) at least one A and at least one B. Similarly, as used herein in the context of describing structures, components, items, objects and/or things, the phrase "at least one of A or B" is intended to refer to implementations including any of (1) at least one A, (2) at least one B, or (3) at least one A and at least one B. As used herein in the context of describing the performance or execution of processes, instructions, actions, activities and/or steps, the phrase "at least one of A and B" is intended to refer to implementations including any of (1) at least one A, (2) at least one B, or (3) at least one A and at least one B. Similarly, as used herein in the context of describing the performance or execution of processes, instructions, actions, activities and/or steps, the phrase "at least one of A or B" is intended to refer to implementations including any of (1) at least one A, (2) at least one B, or (3) at least one A and at least one B.

[0052] As used herein, singular references (e.g., "a", "an", "first", "second", etc.) do not exclude a plurality. The term "a" or "an" object, as used herein, refers to one or more of that object. The terms "a" (or "an"), "one or more", and "at least one" are used interchangeably herein. Furthermore, although individually listed, a plurality of means, elements, or actions may be implemented by, e.g., the same entity or object. Additionally, although individual features may be included in different examples or claims, these may possibly be combined, and the inclusion in different examples or claims does not imply that a combination of features is not feasible and/or advantageous.

[0053] FIGS. 3 and 4 are flowcharts representative of example machine readable instructions and/or example operations 300 that may be executed, instantiated, and/or performed by programmable circuitry to validate the results of nucleic acid amplification reactions. The example machine-readable instructions and/or the example operations 300 of FIG. 3 include the interface circuitry 102 accessing fluorescence signal data (block 302). The signal processing circuitry 104 excludes data from a number of cycles (a) (block 304). For example, data from a number of initial cycles is excluded from further analysis to avoid using inaccurate data that may include initial transient signal anomalies. In some examples, the signal processing circuitry 104 creates a data set in accordance with Equation 2.

[0054] The calculation circuitry 106 calculates cycle-to-cycle differences in amplitudes of the fluorescence between consecutive cycles (block 306). For example, the calculation circuitry 106 creates a data set in accordance with Equation 3. The calculation circuitry 106 identifies a final amplitude of a last of the cycles (block 308) and a minimum amplitude of the cycles (block 310). The calculation circuitry 106 calculates a sum (e.g., a total distance) of the differences determined in block 306 (block 312). For example, the calculation circuitry 106 calculates the sum in accordance with Equation 5. The calculation circuitry 106 calculates a distance (e.g., an upward distance) as the difference between the final amplitude and the minimum amplitude (block 314). For example, the calculation circuitry 106 calculates the distance in accordance with Equation 6. The calculation circuitry 106 determines a ratio (e.g., total distance ratio) of the sum to the distance (block 316). For example, the calculation circuitry 106 determines the ratio in accordance with Equation 7.

[0055] The evaluation circuitry 108 compares the ratio to a threshold (e.g., a total distance ratio threshold) (block 318). The evaluation circuitry 108 determines if the ratio satisfies the threshold (block 320). If and/or when the evaluation circuitry 108 determines that the ratio satisfies the threshold (block 320: YES), then the evaluation circuitry 108 validates the test result (block 322). For example, if and/or when the evaluation circuitry 108 determines that the ratio (e.g., the total distance ratio) is less than the threshold ratio (e.g., the threshold total distance ratio), the evaluation circuitry 108 validates the results of the nucleic acid amplification reaction (i.e., indicates or confirms that the results are a true positive).

[0056] If and/or when the evaluation circuitry 108 determines that the ratio does not satisfy the threshold (block 320: NO), then the evaluation circuitry 108 invalidates the test result (block 324). For example, if and/or when the evaluation circuitry 108 determines that the ratio (e.g., the total distance ratio) is greater than the threshold ratio (e.g., the threshold total distance ratio), the evaluation circuitry 108 invalidates the results of the nucleic acid amplification reaction (i.e., indicates or determines that the results are a false positive). After the results have been validated (block 322) or invalidated (block 324) by the evaluation circuitry 108, the example operations 300 end.

[0057] The example machine-readable instructions and/or the example operations 400 of FIG. 4 include the interface circuitry 102 accessing fluorescence signal data (block 402). The signal processing circuitry 104 excludes data from a number of cycles (a) (block 404). For example, data from a number of initial cycles is excluded from further analysis to avoid using inaccurate data that may include initial transient signal anomalies. In some examples, the signal processing circuitry 104 creates a data set in accordance with Equation 2.

[0058] The calculation circuitry 106 calculates cycle-to-cycle differences in amplitudes of the fluorescence between consecutive cycles (block 406). For example, the calculation circuitry 106 creates a data set in accordance with Equation 3. The calculation circuitry 106 sorts the differences from high to low (block 408). For example, the calculation circuitry 106 creates a data set in accordance with Equation 4.

[0059] The calculation circuitry 106 identifies a first greatest difference in amplitude (block 410). In this example, the first greatest difference in amplitude is the greatest difference in amplitude among the differences in amplitude calculated in block 406. The calculation circuitry 106 also identifies a second greatest difference in amplitude (block 412).

[0060] The result validation circuitry 100 determines if the validity check operations are implemented for a largest delta validity check or a second largest delta validity check (block 414). In some examples, there is no determination of the type of validity check. Rather the operations 400 proceed with either the largest delta validity check or a second largest delta validity check without regard to elements used in the other of the largest delta validity check or a second largest delta validity check.

[0061] If the operations 400 are for the largest delta validity check (block 414: LDR), the calculation circuitry 106 calculates a first ratio of the first greatest difference to the second greatest difference (block 416). For example, the calculation circuitry 106 calculates a largest delta ratio in accordance with Equation 8.

[0062] The evaluation circuitry 108 compares the first ratio to a first threshold (e.g., a threshold largest delta ratio) (block 418). The evaluation circuitry 108 determines if the first ratio satisfies the first threshold (block 420). If and/or when the evaluation circuitry 108 determines that the first ratio satisfies the first threshold (block 420: YES), then the evaluation circuitry 108 validates the test result (block 422). For example, if and/or when the evaluation circuitry 108 determines that the first ratio (e.g., the largest delta ratio) is less than the first threshold ratio (e.g., the threshold largest delta ratio), the evaluation circuitry 108 validates the results of the nucleic acid amplification reaction (i.e., indicates or confirms that the results are a true positive). [0063] If and/or when the evaluation circuitry 108 determines that the first ratio does not satisfy the first threshold (block 420: NO), then the evaluation circuitry 108 invalidates the test result (block 424). For example, if and/or when the evaluation circuitry 108 determines that the first ratio (e.g., the largest delta ratio) is greater than the first threshold ratio (e.g., the threshold largest delta ratio), the evaluation circuitry 108 invalidates the results of the nucleic acid amplification reaction (i.e., indicates or determines that the results are a false positive). After the results have been validated (block 422) or invalidated (block 424) by the evaluation circuitry 108, the example operations 300 end.

[0064] If the operations 400 are for the second largest delta validity check (block 414: 2LDR), the calculation circuitry 106 identifies a third greatest difference in amplitude (block 426). For example, the calculation circuitry 106 identifies the third greatest difference in amplitude based on the sorted data set of block 408.

[0065] The calculation circuitry 106 calculates a second ratio of the second greatest difference to the third greatest difference (block 428). For example, the calculation circuitry 106 calculates a largest delta ratio in accordance with Equation 9. The evaluation circuitry 108 compares the second ratio to a second threshold (e.g., a threshold second largest delta ratio) (block 430). The evaluation circuitry 108 determines if the second ratio satisfies the second threshold (block 432). If and/or when the evaluation circuitry 108 determines that the second ratio satisfies the second threshold (block 432: YES), then the evaluation circuitry 108 validates the test result (block 422). For example, if and/or when the evaluation circuitry 108 determines that the second ratio (e.g., the second largest delta ratio) is less than the second threshold ratio (e.g., the threshold second largest delta ratio), the evaluation circuitry 108 validates the results of the nucleic acid amplification reaction (i.e., indicates or confirms that the results are a true positive).

[0066] If and/or when the evaluation circuitry 108 determines that the second ratio does not satisfy the second threshold (block 432: NO), then the evaluation circuitry 108 invalidates the test result (block 424). For example, if and/or when the evaluation circuitry 108 determines that the second ratio (e.g., the second largest delta ratio) is greater than the second threshold ratio (e.g., the threshold second largest delta ratio), the evaluation circuitry 108 invalidates the results of the nucleic acid amplification reaction (i.e., indicates or determines that the results are a false positive). After the results have been validated (block 422) or invalidated (block 424) by the evaluation circuitry 108, the example operations 300 end.

[0067] FIG. 5 is a block diagram of an example programmable circuitry platform 500 structured to execute and/or instantiate the example machine-readable instructions and/or the example operations of FIGS. 3 and 4 to implement the result validation circuitry 100 of FIG. 1. The programmable circuitry platform 500 can be, for example, a server, a personal computer, a workstation, a self-learning machine (e.g., a neural network), a mobile device (e.g., a cell phone, a smart phone, a tablet such as an iPad™), a personal digital assistant (PDA), an Internet appliance, a headset (e.g., an augmented reality (AR) headset, a virtual reality (VR) headset, etc.) or other wearable device, or any other type of computing and/or electronic device.

[0068] The programmable circuitry platform 500 of the illustrated example includes programmable circuitry 512. The programmable circuitry 512 of the illustrated example is hardware. For example, the programmable circuitry 512 can be implemented by one or more integrated circuits, logic circuits, FPGAs, microprocessors, CPUs, GPUs, DSPs, and/or microcontrollers from any desired family or manufacturer. The programmable circuitry 512 may be implemented by one or more semiconductor based (e.g., silicon based) devices. In this example, the programmable circuitry 512 implements the example interface circuitry 102, the example signal processing circuitry 104, the example calculation circuitry 106, the example evaluation circuitry 110, and/or, more generally, the example result validation circuitry 100.

[0069] The programmable circuitry 512 of the illustrated example includes a local memory 513 (e.g., a cache, registers, etc.). The programmable circuitry 512 of the illustrated example is in communication with main memory 514, 516, which includes a volatile memory 514 and a non-volatile memory 516, by a bus 518. The volatile memory 514 may be implemented by Synchronous Dynamic Random Access Memory (SDRAM), Dynamic Random Access Memory (DRAM), RAMBUS® Dynamic Random Access Memory (RDRAM®), and/or any other type of RAM device. The non-volatile memory 516 may be implemented by flash memory and/or any other desired type of memory device. Access to the main memory 514, 516 of the illustrated example is controlled by a memory controller 517. In some examples, the memory controller 517 may be implemented by one or more integrated circuits, logic circuits, microcontrollers from any desired family or manufacturer, or any other type of circuitry to manage the flow of data going to and from the main memory 514, 516.

[0070] The programmable circuitry platform 500 of the illustrated example also includes interface circuitry 520. The interface circuitry 520 may be implemented by hardware in accordance with any type of interface standard, such as an Ethernet interface, a universal serial bus (USB) interface, a Bluetooth® interface, a near field communication (NFC) interface, a Peripheral Component Interconnect (PCI) interface, and/or a Peripheral Component Interconnect Express (PCIe) interface.

[0071] In the illustrated example, one or more input devices 522 are connected to the interface circuitry 520. The input device(s) 522 permit(s) a user (e.g., a human user, a machine user, etc.) to enter data and/or commands into the programmable circuitry 512. The input device(s) 522 can be implemented by, for example, an audio sensor, a microphone, a camera (still or video), a keyboard, a button, a mouse, a touchscreen, a trackpad, a trackball, an isopoint device, and/or a voice recognition system. [0072] One or more output devices 524 are also connected to the interface circuitry 520 of the illustrated example. The output device(s) 524 can be implemented, for example, by display devices (e.g., a light emitting diode (LED), an organic light emitting diode (OLED), a liquid crystal display (LCD), a cathode ray tube (CRT) display, an in-place switching (IPS) display, a touchscreen, etc.), a tactile output device, a printer, and/or speaker. The interface circuitry 520 of the illustrated example, thus, typically includes a graphics driver card, a graphics driver chip, and/or graphics processor circuitry such as a GPU.

[0073] The interface circuitry 520 of the illustrated example also includes a communication device such as a transmitter, a receiver, a transceiver, a modem, a residential gateway, a wireless access point, and/or a network interface to facilitate exchange of data with external machines (e.g., computing devices of any kind) by a network 526. The communication can be by, for example, an Ethernet connection, a digital subscriber line (DSL) connection, a telephone line connection, a coaxial cable system, a satellite system, a beyond-line-of-site wireless system, a line-of-site wireless system, a cellular telephone system, an optical connection, etc.

[0074] The programmable circuitry platform 500 of the illustrated example also includes one or more mass storage discs or devices 528 to store firmware, software, and/or data. Examples of such mass storage discs or devices 528 include magnetic storage devices (e.g., floppy disk, drives, HDDs, etc.), optical storage devices (e.g., Blu-ray disks, CDs, DVDs, etc.), RAID systems, and/or solid-state storage discs or devices such as flash memory devices and/or SSDs.

[0075] The machine readable instructions 532, which may be implemented by the machine readable instructions of FIGS. 3 and 4, may be stored in the mass storage device 528, in the volatile memory 514, in the non-volatile memory 516, and/or on at least one non-transitory computer readable storage medium such as a CD or DVD which may be removable.

[0076] A block diagram illustrating an example software distribution platform 605 to distribute software such as the example machine readable instructions 532 of FIG. 5 to other hardware devices (e.g., hardware devices owned and/or operated by third parties from the owner and/or operator of the software distribution platform) is illustrated in FIG. 6. The example software distribution platform 605 may be implemented by any computer server, data facility, cloud service, etc., capable of storing and transmitting software to other computing devices. The third parties may be customers of the entity owning and/or operating the software distribution platform 605. For example, the entity that owns and/or operates the software distribution platform 605 may be a developer, a seller, and/or a licensor of software such as the example machine readable instructions 532 of FIG. 5. The third parties may be consumers, users, retailers, OEMs, etc., who purchase and/or license the software for use and/or resale and/or sub-licensing. In the illustrated example, the software distribution platform 605 includes one or more servers and one or more storage devices. The storage devices store the machine readable instructions 532, which may correspond to the example machine readable instructions of FIGS. 3 and 4, as described above. The one or more servers of the example software distribution platform 605 are in communication with an example network 610, which may correspond to any one or more of the Internet and/or any of the example networks described above. In some examples, the one or more servers are responsive to requests to transmit the software to a requesting party as part of a commercial transaction. Payment for the delivery, sale, and/or license of the software may be handled by the one or more servers of the software distribution platform and/or by a third party payment entity. The servers enable purchasers and/or licensors to download the machine readable instructions 532 from the software distribution platform 605. For example, the software, which may correspond to the example machine readable instructions of FIG. 3 and 4, may be downloaded to the example programmable circuitry platform 500, which is to execute the machine readable instructions 532 to implement the result validation circuitry 100. In some examples, one or more servers of the software distribution platform 605 periodically offer, transmit, and/or force updates to the software (e.g., the example machine readable instructions 532 of FIG. 5) to ensure improvements, patches, updates, etc., are distributed and applied to the software at the end user devices. Although referred to as software above, the distributed "software" could alternatively be firmware.

[0077] Unless specifically stated otherwise, descriptors such as "first," "second," "third," etc., are used herein without imputing or otherwise indicating any meaning of priority, physical order, arrangement in a list, and/or ordering in any way, but are merely used as labels and/or arbitrary names to distinguish elements for ease of understanding the disclosed examples. In some examples, the descriptor "first" may be used to refer to an element in the detailed description, while the same element may be referred to in a claim with a different descriptor such as "second" or "third." In such instances, it should be understood that such descriptors are used merely for identifying those elements distinctly within the context of the discussion (e.g., within a claim) in which the elements might, for example, otherwise share a same name.

[0078] As used herein, the phrase "in communication," including variations thereof, encompasses direct communication and/or indirect communication through one or more intermediary components, and does not require direct physical (e.g., wired) communication and/or constant communication, but rather additionally includes selective communication at periodic intervals, scheduled intervals, aperiodic intervals, and/or one-time events.

[0079] As used herein, "programmable circuitry" is defined to include (i) one or more special purpose electrical circuits (e.g., an application specific circuit (ASIC)) structured to perform specific operation(s) and including one or more semiconductor-based logic devices (e.g., electrical hardware implemented by one or more transistors), and/or (ii) one or more general purpose semiconductorbased electrical circuits programmable with instructions to perform specific functions(s) and/or operation(s) and including one or more semiconductor-based logic devices (e.g., electrical hardware implemented by one or more transistors). Examples of programmable circuitry include programmable microprocessors such as Central Processor Units (CPUs) that may execute first instructions to perform one or more operations and/or functions, Field Programmable Gate Arrays (FPGAs) that may be programmed with second instructions to cause configuration and/or structuring of the FPGAs to instantiate one or more operations and/or functions corresponding to the first instructions, Graphics Processor Units (GPUs) that may execute first instructions to perform one or more operations and/or functions, Digital Signal Processors (DSPs) that may execute first instructions to perform one or more operations and/or functions, XPUs, Network Processing Units (NPUs) one or more microcontrollers that may execute first instructions to perform one or more operations and/or functions and/or integrated circuits such as Application Specific Integrated Circuits (ASICs). For example, an XPU may be implemented by a heterogeneous computing system including multiple types of programmable circuitry (e.g., one or more FPGAs, one or more CPUs, one or more GPUs, one or more NPUs, one or more DSPs, etc., and/or any combination(s) thereof), and orchestration technology (e.g., application programming interface(s) (API(s)) that may assign computing task(s) to whichever one(s) of the multiple types of programmable circuitry is/are suited and available to perform the computing task(s).

[0080] As used herein integrated circuit/circuitry is defined as one or more semiconductor packages containing one or more circuit elements such as transistors, capacitors, inductors, resistors, current paths, diodes, etc. For example an integrated circuit may be implemented as one or more of an ASIC, an FPGA, a chip, a microchip, programmable circuitry, a semiconductor substrate coupling multiple circuit elements, a system on chip (SoC), etc.

[0081] From the foregoing, it will be appreciated that example systems, apparatus, articles of manufacture, and methods have been disclosed that identify false positive results in nucleic acid amplification reactions due to fluorescence signal noise. The example total distance ratio, the example largest delta ratio, and the example second largest delta ratio validity checks can be used to prevent false positive PCR or other nucleic acid amplification test results due to fluorescence signal noise. These examples protects against noise-associated false positives while leaving a fluorescence channel (which would have been used by reference dye in prior approaches) open, which facilitates greater multiplexing. Additionally, the examples disclosed herein avoid decreasing PCR assay sensitivity because overly restrictive data reduction parameters are not needed (e.g., overly increasing a cycle threshold used to identify positive results).

[0082] Example systems, apparatus, articles of manufacture, and methods are disclosed to validate the results of nucleic acid amplification reaction tests. Example 1 includes an apparatus to validate a result from a nucleic acid amplification reaction test, the apparatus comprising: interface circuitry; machine readable instructions; and programmable circuitry to at least one of instantiate or execute the machine readable instructions to: calculate differences in amplitudes between consecutive cycles of a plurality of cycles in a fluorescence signal obtained from the test; determine a sum of the differences in amplitudes between consecutive cycles; identify a final amplitude at a last of the cycles; identify a minimum amplitude of the plurality of cycles; determine a distance as the difference between the final amplitude and the minimum amplitude; determine a ratio of the sum to the distance; and validate the result of the test based on the ratio.

[0083] Example 2 includes the apparatus of Example 1, wherein the programmable circuitry is to exclude a number of cycles in the test from the plurality of cycles, the number of cycles being cycles at a beginning of the test.

[0084] Example 3 includes the apparatus of Example 2, wherein the number is based on a type of target DNA or RNA for the test.

[0085] Example 4 includes the apparatus of any of Examples 1-3, wherein the programmable circuitry is to compare the ratio to a threshold and validate the result of the test when the ratio satisfies the threshold.

[0086] Example 5 includes the apparatus of Example 4, wherein the threshold is based on a comparison of known positive nucleic acid amplification reaction data and known false positive nucleic acid amplification reaction data.

[0087] Example 6 includes an apparatus to validate a result from a nucleic acid amplification reaction test, the apparatus comprising: interface circuitry; machine readable instructions; and programmable circuitry to at least one of instantiate or execute the machine readable instructions to: calculate amplitude differences between consecutive cycles of a plurality of cycles in a fluorescence signal obtained from the test; identify a first amplitude difference; identify a second amplitude difference, the second amplitude difference being lower than the first amplitude difference; determine a ratio of the first amplitude difference to the second amplitude difference; and validate the result of the test based on the ratio.

[0088] Example 7 includes the apparatus of Example 6, wherein the first amplitude difference is a greatest of the amplitude differences and the second amplitude difference is a second greatest of the amplitude differences.

[0089] Example 8 includes the apparatus of any of Examples 6 or 7, wherein the first amplitude difference is a second greatest of the amplitude differences and the second amplitude difference is a third greatest of the amplitude differences.

[0090] Example 9 includes the apparatus of any of Examples 6-8, wherein the programmable circuitry is to exclude a number of cycles in the test from the plurality of cycles, the number of cycles being cycles at a beginning of the test.

[0091] Example 10 includes the apparatus of Example 9, wherein the number is based on a type of target DNA or RNA for the test. [0092] Example 11 includes the apparatus of any of Examples 6-10, wherein the programmable circuitry is to compare the ratio to a threshold and validate the result of the test when the ratio satisfies the threshold.

[0093] Example 12 includes the apparatus of Example 11, wherein the threshold is based on a comparison of known positive nucleic acid amplification reaction data and known false positive nucleic acid amplification reaction data.

[0094] Example 13 includes a machine readable storage medium comprising instructions to cause programmable circuitry to at least: calculate differences in amplitudes between consecutive cycles of a plurality of cycles in a fluorescence signal obtained from a nucleic acid amplification reaction test; determine a sum of the differences in amplitudes between consecutive cycles; identify a final amplitude at a last of the cycles; identify a minimum amplitude of the plurality of cycles; determine a distance as the difference between the final amplitude and the minimum amplitude; determine a ratio of the sum to the distance; and validate a result of the test based on the ratio.

[0095] Example 14 includes the machine readable storage medium of Example 13, wherein the instructions cause the programmable circuitry to exclude a number of cycles in the test from the plurality of cycles, the number of cycles being cycles at a beginning of the test.

[0096] Example 15 includes the machine readable storage medium of Example 14, wherein the number is based on a type of target DNA or RNA for the test.

[0097] Example 16 includes the machine readable storage medium of any of Examples 13-15, wherein the instructions cause the programmable circuitry to compare the ratio to a threshold and validate the result of the test when the ratio satisfies the threshold.

[0098] Example 17 includes the machine readable storage medium of Example 16, wherein the threshold is based on a comparison of known positive nucleic acid amplification reaction data and known false positive nucleic acid amplification reaction data.

[0099] Example 18 includes a machine readable storage medium comprising instructions to cause programmable circuitry to at least: calculate amplitude differences between consecutive cycles of a plurality of cycles in a fluorescence signal obtained from a nucleic acid amplification reaction test; identify a first amplitude difference; identify a second amplitude difference, the second amplitude difference being lower than the first amplitude difference; determine a ratio of the first amplitude difference to the second amplitude difference; and validate a result of the test based on the ratio.

[00100] Example 19 includes the machine readable storage medium of Example 18, wherein the first amplitude difference is a greatest of the amplitude differences and the second amplitude difference is a second greatest of the amplitude differences. [00101] Example 20 includes the machine readable storage medium of any of Examples 18 or 19, wherein the first amplitude difference is a second greatest of the amplitude differences and the second amplitude difference is a third greatest of the amplitude differences.

[00102] Example 21 includes the machine readable storage medium of any of Examples 18-20, wherein the instructions cause the programmable circuitry to exclude a number of cycles in the test from the plurality of cycles, the number of cycles being cycles at a beginning of the test.

[00103] Example 22 includes the machine readable storage medium of Example 21, wherein the number is based on a type of target DNA or RNA for the test.

[00104] Example 23 includes the machine readable storage medium of any of Examples 18-22, wherein the instructions cause the programmable circuitry to compare the ratio to a threshold and validate the result of the test when the ratio satisfies the threshold.

[00105] Example 24 includes the machine readable storage medium of Example 23, wherein the threshold is based on a comparison of known positive nucleic acid amplification reaction data and known false positive nucleic acid amplification reaction data.

[00106] Example 25 includes a method to validate results of a nucleic acid amplification reaction test, the method comprising: calculating differences in amplitudes between consecutive cycles of a plurality of cycles in a fluorescence signal obtained from the test; determining a sum of the differences in amplitudes between consecutive cycles; identifying a final amplitude at a last of the cycles; identifying a minimum amplitude of the plurality of cycles; determining a distance as the difference between the final amplitude and the minimum amplitude; determining a ratio of the sum to the distance; and validating the result of the test based on the ratio. One or more elements or steps of this method and/or other methods disclosed herein may be performed by executing instructions with a processor, processor circuitry, programmable circuitry, and/or a processor circuit.

[00107] Example 26 includes the method of Example 25, further including excluding a number of cycles in the test from the plurality of cycles, the number of cycles being cycles at a beginning of the test.

[00108] Example T1 includes the method of Example 26, wherein the number is based on a type of target DNA or RNA for the test.

[00109] Example 28 includes the method of any of Examples 25-27, further including comparing the ratio to a threshold and validating the result of the test when the ratio satisfies the threshold.

[00110] Example 29 includes the method of Example 28, wherein the threshold is based on a comparison of known positive nucleic acid amplification reaction data and known false positive nucleic acid amplification reaction data.

[00111] Example 30 includes a method to validate results of a nucleic acid amplification reaction test, the method comprising: calculating amplitude differences between consecutive cycles of a plurality of cycles in a fluorescence signal obtained from the test; identifying a first amplitude difference; identifying a second amplitude difference, the second amplitude difference being lower than the first amplitude difference; determining a ratio of the first amplitude difference to the second amplitude difference; and validating the result of the test based on the ratio.

[00112] Example 31 includes the method of Example 30, wherein the first amplitude difference is a greatest of the amplitude differences and the second amplitude difference is a second greatest of the amplitude differences.

[00113] Example 32 includes the method of any of Examples 30 or 31, wherein the first amplitude difference is a second greatest of the amplitude differences and the second amplitude difference is a third greatest of the amplitude differences.

[00114] Example 33 includes the method of any of Examples 30-32, further including excluding a number of cycles in the test from the plurality of cycles, the number of cycles being cycles at a beginning of the test.

[00115] Example 34 includes the method of Example 33, wherein the number is based on a type of target DNA or RNA for the test.

[00116] Example 35 includes the method of any of Examples 30-34, further including comparing the ratio to a threshold and validating the result of the test when the ratio satisfies the threshold.

[00117] Example 36 includes the method of Example 35, wherein the threshold is based on a comparison of known positive nucleic acid amplification reaction data and known false positive nucleic acid amplification reaction data.

[00118] Example 37 includes one or more servers to distribute first instructions on a network, the one or more servers comprising: at least one storage device including second instructions; and at least one processor to execute the second instructions to transmit the first instructions over the network, the first instructions, when executed, cause a device to at least: calculate differences in amplitudes between consecutive cycles of a plurality of cycles in a fluorescence signal obtained from a nucleic acid amplification reaction test; determine a sum of the differences in amplitudes between consecutive cycles; identify a final amplitude at a last of the cycles; identify a minimum amplitude of the plurality of cycles; determine a distance as the difference between the final amplitude and the minimum amplitude; determine a ratio of the sum to the distance; and validate a result of the test based on the ratio.

[00119] Example 38 includes the one or more servers of Example 37, wherein the first instructions cause the device to exclude a number of cycles in the test from the plurality of cycles, the number of cycles being cycles at a beginning of the test.

[00120] Example 39 includes the one or more servers of Example 38, wherein the number is based on a type of target DNA or RNA for the test. [00121] Example 40 includes the one or more servers of any of Examples 37-39, wherein the first instructions cause the device to compare the ratio to a threshold and validate the result of the test when the ratio satisfies the threshold.

[00122] Example 41 includes the one or more servers of Example 40, wherein the threshold is based on a comparison of known positive nucleic acid amplification reaction data and known false positive nucleic acid amplification reaction data.

[00123] Example 42 includes one or more servers to distribute first instructions on a network, the one or more servers comprising: at least one storage device including second instructions; and at least one processor to execute the second instructions to transmit the first instructions over the network, the first instructions, when executed, cause a device to at least: calculate amplitude differences between consecutive cycles of a plurality of cycles in a fluorescence signal obtained from a nucleic acid amplification reaction test; identify a first amplitude difference; identify a second amplitude difference, the second amplitude difference being lower than the first amplitude difference; determine a ratio of the first amplitude difference to the second amplitude difference; and validate a result of the test based on the ratio.

[00124] Example 43 includes the one or more servers of Example 42, wherein the first amplitude difference is a greatest of the amplitude differences and the second amplitude difference is a second greatest of the amplitude differences.

[00125] Example 44 includes the one or more servers of any of Examples 42 or 43, wherein the first amplitude difference is a second greatest of the amplitude differences and the second amplitude difference is a third greatest of the amplitude differences.

[00126] Example 45 includes the one or more servers of any of Examples 42-44, wherein the first instructions cause the device to exclude a number of cycles in the test from the plurality of cycles, the number of cycles being cycles at a beginning of the test.

[00127] Example 46 includes the one or more servers of Example 45, wherein the number is based on a type of target DNA or RNA for the test.

[00128] Example 47 includes the one or more servers of any of Examples 42-46, wherein the first instructions cause the device to compare the ratio to a threshold and validate the result of the test when the ratio satisfies the threshold.

[00129] Example 48 includes the one or more servers of Example 47, wherein the threshold is based on a comparison of known positive nucleic acid amplification reaction data and known false positive nucleic acid amplification reaction data.

[00130] Example 49 includes an apparatus that includes means to perform a method as claimed in any preceding claim. [00131] Example 50 includes machine-readable storage including machine-readable instructions, when executed, to implement a method or realize an apparatus as claimed in any preceding claim.

[00132]The following claims are hereby incorporated into this Detailed Description by this reference. Although certain example systems, apparatus, articles of manufacture, and methods have been disclosed herein, the scope of coverage of this patent is not limited thereto. On the contrary, this patent covers all systems, apparatus, articles of manufacture, and methods fairly falling within the scope of the claims of this patent.

Claims

What Is Claimed Is:

1. An apparatus to validate a result from a nucleic acid amplification reaction test, the apparatus comprising: interface circuitry; machine readable instructions; and programmable circuitry to at least one of instantiate or execute the machine readable instructions to: calculate differences in amplitudes between consecutive cycles of a plurality of cycles in a fluorescence signal obtained from the test; determine a sum of the differences in amplitudes between consecutive cycles; identify a final amplitude at a last of the cycles; identify a minimum amplitude of the plurality of cycles; determine a distance as the difference between the final amplitude and the minimum amplitude; determine a ratio of the sum to the distance; and validate the result of the test based on the ratio.

2. The apparatus of claim 1, wherein the programmable circuitry is to exclude a number of cycles in the test from the plurality of cycles, the number of cycles being cycles at a beginning of the test.

3. The apparatus of claim 2, wherein the number is based on a type of target DNA or RNA for the test.

4. The apparatus of any of claims 1-3, wherein the programmable circuitry is to compare the ratio to a threshold and validate the result of the test when the ratio satisfies the threshold.

5. The apparatus of claim 4, wherein the threshold is based on a comparison of known positive nucleic acid amplification reaction data and known false positive nucleic acid amplification reaction data.

6. An apparatus to validate a result from a nucleic acid amplification reaction test, the apparatus comprising: interface circuitry; machine readable instructions; and programmable circuitry to at least one of instantiate or execute the machine readable instructions to: calculate amplitude differences between consecutive cycles of a plurality of cycles in a fluorescence signal obtained from the test; identify a first amplitude difference; identify a second amplitude difference, the second amplitude difference being lower than the first amplitude difference; determine a ratio of the first amplitude difference to the second amplitude difference; and validate the result of the test based on the ratio.

7. The apparatus of claim 6, wherein the first amplitude difference is a greatest of the amplitude differences and the second amplitude difference is a second greatest of the amplitude differences.

8. The apparatus of claim 6, wherein the first amplitude difference is a second greatest of the amplitude differences and the second amplitude difference is a third greatest of the amplitude differences.

9. The apparatus of any of claims 6-8, wherein the programmable circuitry is to exclude a number of cycles in the test from the plurality of cycles, the number of cycles being cycles at a beginning of the test.

10. The apparatus of claim 9, wherein the number is based on a type of target DNA or RNA for the test.

11. The apparatus of any of claims 6-10, wherein the programmable circuitry is to compare the ratio to a threshold and validate the result of the test when the ratio satisfies the threshold.

12. The apparatus of claim 11, wherein the threshold is based on a comparison of known positive nucleic acid amplification reaction data and known false positive nucleic acid amplification reaction data.

13. A machine readable storage medium comprising instructions to cause programmable circuitry to at least: calculate differences in amplitudes between consecutive cycles of a plurality of cycles in a fluorescence signal obtained from a nucleic acid amplification reaction test; determine a sum of the differences in amplitudes between consecutive cycles; identify a final amplitude at a last of the cycles; identify a minimum amplitude of the plurality of cycles; determine a distance as the difference between the final amplitude and the minimum amplitude; determine a ratio of the sum to the distance; and validate a result of the test based on the ratio.

14. The machine readable storage medium of claim 13, wherein the instructions cause the programmable circuitry to exclude a number of cycles in the test from the plurality of cycles, the number of cycles being cycles at a beginning of the test.

15. The machine readable storage medium of claim 14, wherein the number is based on a type of target DNA or RNA for the test.

16. The machine readable storage medium of any of claims 13-15, wherein the instructions cause the programmable circuitry to compare the ratio to a threshold and validate the result of the test when the ratio satisfies the threshold.

17. The machine readable storage medium of claim 16, wherein the threshold is based on a comparison of known positive nucleic acid amplification reaction data and known false positive nucleic acid amplification reaction data.

18. A machine readable storage medium comprising instructions to cause programmable circuitry to at least: calculate amplitude differences between consecutive cycles of a plurality of cycles in a fluorescence signal obtained from a nucleic acid amplification reaction test; identify a first amplitude difference; identify a second amplitude difference, the second amplitude difference being lower than the first amplitude difference; determine a ratio of the first amplitude difference to the second amplitude difference; and validate a result of the test based on the ratio.

19. The machine readable storage medium of claim 18, wherein the first amplitude difference is a greatest of the amplitude differences and the second amplitude difference is a second greatest of the amplitude differences.

20. The machine readable storage medium of claim 18, wherein the first amplitude difference is a second greatest of the amplitude differences and the second amplitude difference is a third greatest of the amplitude differences.

21. The machine readable storage medium of any of claims 18-20, wherein the instructions cause the programmable circuitry to exclude a number of cycles in the test from the plurality of cycles, the number of cycles being cycles at a beginning of the test.

22. The machine readable storage medium of claim 21, wherein the number is based on a type of target DNA or RNA for the test.

23. The machine readable storage medium of any of claims 18-22, wherein the instructions cause the programmable circuitry to compare the ratio to a threshold and validate the result of the test when the ratio satisfies the threshold.

24. The machine readable storage medium of claim 23, wherein the threshold is based on a comparison of known positive nucleic acid amplification reaction data and known false positive nucleic acid amplification reaction data.

25. A method to validate results of a nucleic acid amplification reaction test, the method comprising: calculating differences in amplitudes between consecutive cycles of a plurality of cycles in a fluorescence signal obtained from the test; determining a sum of the differences in amplitudes between consecutive cycles; identifying a final amplitude at a last of the cycles; identifying a minimum amplitude of the plurality of cycles; determining a distance as the difference between the final amplitude and the minimum amplitude; determining a ratio of the sum to the distance; and validating the result of the test based on the ratio.

26. The method of claim 25, further including excluding a number of cycles in the test from the plurality of cycles, the number of cycles being cycles at a beginning of the test.

27. The method of claim 26, wherein the number is based on a type of target DNA or RNA for the test.

28. The method of any of claims 25-27, further including comparing the ratio to a threshold and validating the result of the test when the ratio satisfies the threshold.

29. The method of claim 28, wherein the threshold is based on a comparison of known positive nucleic acid amplification reaction data and known false positive nucleic acid amplification reaction data.

30. A method to validate results of a nucleic acid amplification reaction test, the method comprising: calculating amplitude differences between consecutive cycles of a plurality of cycles in a fluorescence signal obtained from the test; identifying a first amplitude difference; identifying a second amplitude difference, the second amplitude difference being lower than the first amplitude difference; determining a ratio of the first amplitude difference to the second amplitude difference; and validating the result of the test based on the ratio.

31. The method of claim 30, wherein the first amplitude difference is a greatest of the amplitude differences and the second amplitude difference is a second greatest of the amplitude differences.

32. The method of claim 30, wherein the first amplitude difference is a second greatest of the amplitude differences and the second amplitude difference is a third greatest of the amplitude differences.

33. The method of any of claims 30-32, further including excluding a number of cycles in the test from the plurality of cycles, the number of cycles being cycles at a beginning of the test.

34. The method of claim 33, wherein the number is based on a type of target DNA or RNA for the test.

35. The method of any of claims 30-34, further including comparing the ratio to a threshold and validating the result of the test when the ratio satisfies the threshold.

36. The method of claim 35, wherein the threshold is based on a comparison of known positive nucleic acid amplification reaction data and known false positive nucleic acid amplification reaction data.

37. One or more servers to distribute first instructions on a network, the one or more servers comprising: at least one storage device including second instructions; and at least one processor to execute the second instructions to transmit the first instructions over the network, the first instructions, when executed, cause a device to at least: calculate differences in amplitudes between consecutive cycles of a plurality of cycles in a fluorescence signal obtained from a nucleic acid amplification reaction test; determine a sum of the differences in amplitudes between consecutive cycles; identify a final amplitude at a last of the cycles; identify a minimum amplitude of the plurality of cycles; determine a distance as the difference between the final amplitude and the minimum amplitude; determine a ratio of the sum to the distance; and validate a result of the test based on the ratio.

38. The one or more servers of claim 37, wherein the first instructions cause the device to exclude a number of cycles in the test from the plurality of cycles, the number of cycles being cycles at a beginning of the test.

39. The one or more servers of claim 38, wherein the number is based on a type of target DNA or RNA for the test.

40. The one or more servers of any of claims 37-39, wherein the first instructions cause the device to compare the ratio to a threshold and validate the result of the test when the ratio satisfies the threshold.

41. The one or more servers of claim 40, wherein the threshold is based on a comparison of known positive nucleic acid amplification reaction data and known false positive nucleic acid amplification reaction data.

42. One or more servers to distribute first instructions on a network, the one or more servers comprising: at least one storage device including second instructions; and at least one processor to execute the second instructions to transmit the first instructions over the network, the first instructions, when executed, cause a device to at least: calculate amplitude differences between consecutive cycles of a plurality of cycles in a fluorescence signal obtained from a nucleic acid amplification reaction test; identify a first amplitude difference; identify a second amplitude difference, the second amplitude difference being lower than the first amplitude difference; determine a ratio of the first amplitude difference to the second amplitude difference; and validate a result of the test based on the ratio.

43. The one or more servers of claim 42, wherein the first amplitude difference is a greatest of the amplitude differences and the second amplitude difference is a second greatest of the amplitude differences.

44. The one or more servers of claim 42, wherein the first amplitude difference is a second greatest of the amplitude differences and the second amplitude difference is a third greatest of the amplitude differences.

45. The one or more servers of any of claims 42-44, wherein the first instructions cause the device to exclude a number of cycles in the test from the plurality of cycles, the number of cycles being cycles at a beginning of the test.

46. The one or more servers of claim 45, wherein the number is based on a type of target DNA or

RNA for the test.

47. The one or more servers of any of claims 42-46, wherein the first instructions cause the device to compare the ratio to a threshold and validate the result of the test when the ratio satisfies the threshold.

48. The one or more servers of claim 47, wherein the threshold is based on a comparison of known positive nucleic acid amplification reaction data and known false positive nucleic acid amplification reaction data.

49. An apparatus comprising means to perform a method as claimed in any preceding claim.

50. Machine-readable storage comprising machine-readable instructions, when executed, to implement a method or realize an apparatus as claimed in any preceding claim.