Patent Application
20210402392
The invention relates to the field of point-of-care (POC) pathogen and multiplexed pathogen and antibody array detection platforms and methods, such as in CPC C40B 60/12.
COVID-19 testing involves analyzing samples to assess the current or past presence of SARS-CoV-2. The two main branches detect either the presence of the virus or of antibodies produced in response to infection. Tests for viral presence are used to diagnose individual cases and to allow public health authorities to trace and contain outbreaks. Antibody tests instead show whether someone once had the disease. They are less useful for diagnosing current infections because antibodies may not develop for weeks after infection. They are used to assess disease prevalence, which aids the estimation of the infection fatality rate. Individual Jurisdictions have adopted varied testing protocols, including whom to test, how often to test, analysis protocols, sample collection and the uses of test results. This variation has likely significantly impacted reported statistics, including case and test numbers, case fatality rates and case demographics.
Test analysis is often performed in automated, high-throughput, medical laboratories by medical laboratory scientists. Alternatively, point-of-care testing can be done in physician's offices, workplaces, institutional settings or transit hubs. Positive viral tests indicate a current infection, while positive antibody tests indicate a prior infection. Other techniques include a chest CT scan, checking for elevated body temperature or checking for low blood oxygen level.
Detection of the Virus
Reverse Transcription Polymerase Chain Reaction
Polymerase chain reaction (PCR) is a process that amplifies or replicates a small, well-defined segment of DNA many hundreds of thousands of times, creating enough of it for analysis. Test samples are treated with certain chemicals that allow DNA to be extracted. Reverse transcription converts RNA into DNA. Reverse transcription polymerase chain reaction (RT-PCR) first uses reverse transcription to obtain DNA, followed by PCR to amplify that DNA, creating enough to be analyzed. RT-PCR can thereby detect SARS-CoV-2, which contains only RNA. The RT-PCR process generally requires a few hours.
Real-time PCR (qPCR) provides advantages including automation, higher-throughput, and more reliable instrumentation. It has become the preferred method. The combined technique has been described as real-time RT-PCR or quantitative RT-PCR and is sometimes abbreviated qRT-PCR, rRT-PCR, or RT-qPCR, although sometimes RT-PCR or PCR are used. The Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines propose the term RT-qPCR, but not all authors adhere to this.
Samples can be obtained by various methods, including a nasopharyngeal swab, sputum (coughed up material), throat swabs, deep airway material collected via suction catheter or saliva. It has been remarked that for 2003 SARS, “from a diagnostic point of view, it is important to note that nasal and throat swabs seem less suitable for diagnosis, since these materials contain considerably less viral RNA than sputum, and the virus may escape detection if only these materials are tested.” The likelihood of detecting the virus depends on collection method and how much time has passed since infection. Some have found that tests performed with throat swabs are reliable only in the first week. Thereafter the virus may abandon the throat and multiply in the lungs. In the second week, sputum or deep airways collection is preferred. Collecting saliva may be as effective as nasal and throat swabs, although this is not certain. Sampling saliva may reduce the risk for health care professionals by eliminating close physical interaction. It is also more comfortable for the patient. Quarantined people can collect their own samples. A saliva test's diagnostic value depends on sample site (deep throat, oral cavity, or salivary glands). One study found that saliva yielded greater sensitivity and consistency when compared with swab samples. On 15 Aug. 2020, the US FDA authorized a saliva test developed at Yale University, which gives results in hours. Viral burden measured in upper respiratory specimens declines after symptom onset.
Isothermal Amplification Assays
Isothermal nucleic acid amplification tests also amplify the virus's genome. They are faster than PCR because they don't involve repeated heating and cooling cycles. These tests typically detect DNA using fluorescent tags, which are read out with specialized machines. CRISPR gene editing technology was modified to perform the detection: if the CRISPR enzyme attaches to the sequence, it colors a paper strip. The researchers expect the resulting test to be cheap and easy to use in point-of-care settings. The test amplifies RNA directly, without the RNA-to-DNA conversion step of RT-PCR.
Antigens
An antigen is the part of a pathogen that elicits an immune response. Antigen tests look for antigen proteins from the viral surface. In the case of a coronavirus, these are usually proteins from the surface spikes.[40] One of the challenges is to find a target unique to SARS-CoV-2. Isothermal nucleic acid amplification tests can process only one sample at a time per machine. RT-PCR tests are accurate but require too much time, energy, and trained personnel to run the tests. Using these current methods, it is generally believed that there will never be the ability on a [PCR] test to do 300 million tests a day or to test everybody before they go to work or school.
Samples may be collected via nasopharyngeal swab, a swab of the anterior nares, or from saliva. The sample is then exposed to paper strips containing artificial antibodies designed to bind to coronavirus antigens. Antigens bind to the strips and give a visual readout. The process takes less than 30 minutes, can deliver results at point-of-care, and does not require expensive equipment or extensive training. Swabs of respiratory viruses often lack enough antigen material to be detectable. This is especially true for asymptomatic patients who have little if any nasal discharge. Viral proteins are not amplified in an antigen test. According to the World Health Organization (WHO) the sensitivity of similar antigen tests for respiratory diseases like the flu ranges between 34% and 80%. Based on this information, half or more of COVID-19 infected patients might be missed by such tests, depending on the group of patients tested. While some doubt whether an antigen test can be useful against COVID-19, others have argued that antigen tests are highly sensitive when viral load is high and people are contagious, making them suitable for public health screening. Routine antigen tests can quickly identify when asymptomatic people are contagious, while follow-up PCR can be used if confirmatory diagnosis is needed.
Imaging
Typical visible features on chest CT initially include bilateral multilobar ground-glass opacities with a peripheral or posterior distribution. Subpleural dominance, crazy paving, and consolidation may develop as the disease evolves. Chest CT scans and chest x-rays are not recommended for diagnosing COVID-19. Radiologic findings in COVID-19 lack specificity.
Antibody Tests
The body responds to a viral infection by producing antibodies that help neutralize the virus. Blood tests (serology tests) can detect the presence of such antibodies. Antibody tests can be used to assess what fraction of a population has once been infected, which can then be used to calculate the disease's mortality rate. SARS-CoV-2 antibodies' potency and protective period have not been established. Therefore, a positive antibody test may not imply immunity to a future infection. Further, whether mild or asymptomatic infections produce sufficient antibodies for a test to detect has not been established. Antibodies for some diseases persist in the bloodstream for many years, while others fade away. The most notable antibody classes are IgM and IgG. IgM antibodies are generally detectable several days after initial infection, although levels over the course of infection and beyond are not well characterized. IgG antibodies generally become detectable 10-14 days after infection and normally peak around 28 days after infection. Genetic tests verify infection earlier than antibody tests. Only 30% of those with a positive genetic test produced a positive antibody test on day 7 of their infection.
Types of Tests
Rapid Diagnostic Test (RDT)
RDTs typically use a small, portable, positive/negative lateral flow assay that can be executed at point-of-care. RDTs may process blood samples, saliva samples, or nasal swab fluids. RDTs produce colored lines to indicate positive or negative results.
Enzyme-Linked Immunosorbent Assay (ELISA)
ELISAs can be qualitative or quantitative and generally require a lab. These tests usually use whole blood, plasma, or serum samples. A plate is coated with a viral protein, such as a SARS-CoV-2 spike protein. Samples are incubated with the protein, allowing any antibodies to bind to it. The antibody-protein complex can then be detected with another wash of antibodies that produce a color/fluorescent readout.
Neutralization Assay
Neutralization assays assess whether sample antibodies prevent viral infection in test cells. These tests sample blood, plasma, or serum. The test cultures cells that allow viral reproduction (e.g., VeroE6 cells). By varying antibody concentrations, researchers can visualize and quantify how many test antibodies block virus replication.
Chemiluminescent Immunoassay
Chemiluminescent immunoassays are quantitative lab tests. They sample blood, plasma, or serum. Samples are mixed with a known viral protein, buffer reagents and specific, enzyme-labeled antibodies. The result is luminescent. A chemiluminescent microparticle immunoassay uses magnetic, protein-coated microparticles. Antibodies react to the viral protein, forming a complex. Secondary enzyme-labeled antibodies are added and bind to these complexes. The resulting chemical reaction produces light. The radiance is used to calculate the number of antibodies. This test can identify multiple types of antibodies, including IgG, IgM, and IgA.
Neutralizing Vs. Binding Antibodies
Most, if not all, large scale COVID-19 antibody testing looks for binding antibodies only and does not measure the more important neutralizing antibodies (NAb). A NAb is an antibody that defends a cell from an infectious particle by neutralizing its biological effects. Neutralization renders the particle no longer infectious or pathogenic. A binding antibody binds to the pathogen but the pathogen remains infective; the purpose can be to flag the pathogen for destruction by the immune system. It may even enhance infectivity by interacting with receptors on macrophages. Since most COVID-19 antibody tests return a positive result if they find only binding antibodies, these tests cannot indicate that the subject has generated protective NAbs that protect against reinfection.
It is expected that binding antibodies imply the presence of NAbs and for many viral diseases total antibody responses correlate somewhat with NAb responses, but this is not established for COVID-19. A study of 175 recovered patients in China who experienced mild symptoms reported that 10 individuals had no detectable NAbs at discharge, or thereafter. How these patients recovered without the help of NAbs and whether they were at risk of reinfection was not addressed. An additional source of uncertainty is that even if NAbs are present, viruses such as HIV can evade NAb responses. Studies have indicated that NAbs to the original SARS virus (the predecessor to the current SARS-CoV-2) can remain active for two years and are gone after six years. Nevertheless, memory cells including Memory B cells and Memory T cells can last much longer and may have the ability to reduce reinfection severity.
Other Tests
Following recovery, many patients no longer have detectable viral RNA in upper respiratory specimens. Among those who do, RNA concentrations three days following recovery are generally below the range in which replication-competent virus has been reliably isolated. No clear correlation has been described between length of illness and duration of post-recovery shedding of viral RNA in upper respiratory specimens.
Infectivity
Infectivity is indicated by the basic reproduction number (R0, pronounced “R naught”) of the disease. SARS-CoV-2 is estimated to have an R0 of 2.2 to 2.5. This means that in a population where all individuals are susceptible to infection, each infected person is expected to infect 2.2 to 2.5 others in the absence of interventions. R0 can vary according factors such as geography, population demographics and density. In New York state R0 was estimated to be 3.4 to 3.8 during its epidemic. On average, an infected person begins showing symptoms five days after infection (the “incubation period”) and can infect others beginning two to three days before that. One study reported that 44% of viral transmissions occur within this period. According to CDC, a significant number of infected people who never show symptoms are nevertheless contagious. In vitro studies have not found replication-competent virus after 9 days from infection. The statistically estimated likelihood of recovering replication-competent virus approaches zero by 10 days. Infectious virus has not been cultured from urine or reliably cultured from feces; these potential sources pose minimal if any risk of transmitting infection and any risk can be sufficiently mitigated by good hand hygiene.
Patterns and duration of illness and infectivity have not been fully described. However, available data indicate that SARS-CoV-2 RNA shedding in upper respiratory specimens declines after symptom onset. At 10 days recovery of replication-competent virus in viral culture (as a proxy of the presence of infectious virus) approaches zero. Although patients may produce PCR-positive specimens for up to six weeks, it remains unknown whether these samples hold infectious virus. After clinical recovery, many patients do not continue to shed. Among recovered patients with detectable RNA in upper respiratory specimens, concentrations after three days are generally below levels where virus has been reliably cultured. These data were generated from adults across a variety of age groups and with varying severity of illness. Data from children and infants were not available.
Nucleic Acid Tests
Tests developed in China, France, Germany, Hong Kong, Japan, the United Kingdom, and the US targeted different parts of the viral genome. WHO adopted the German system for manufacturing kits sent to low-income countries without the resources to develop their own tests.
Abbott Laboratories' ID Now nucleic acid test uses isothermal amplification technology. The assay amplifies a unique region of the virus's RdRp gene; the resulting copies are then detected with “fluorescently-labeled molecular beacons”. The test kit uses the company's “toaster-size” ID Now device, which is widely deployed in the US. The device can be used in laboratories or in point-of-care settings and provides results in 13 minutes or less.
Primerdesign offers its Genesig Real-Time PCR Coronavirus (COVID-19). Cobas SARS-CoV-2 Qualitative assay runs on the Cobas® 6800/8800 Systems by Roche Molecular Systems. They are offered by the United Nations and other procurement agencies.
Antigen Tests
Quidel's “Sofia 2 SARS Antigen FIA” [160][46] is a lateral flow test that uses monoclonal antibodies to detect the virus's nucleocapsid (N) protein. The result is read out by the company's Sofia 2 device using immunofluorescence. The test is simpler and cheaper but less accurate than nucleic acid tests. It can be deployed in laboratories or at point-of-care and gives results in 15 minutes. A false negative result occurs if the sample's antigen level is positive but below the test's detection limit, requiring confirmation with a nucleic acid test.
Serology (Antibody) Tests
Antibodies are usually detectable 14 days after the onset of the infection. Multiple jurisdictions survey their populations using these tests. The test requires a blood draw. Private US labs including Quest Diagnostics and LabCorp offer antibody testing upon request. Antibody tests are available in various European countries. Quotient Limited developed a CE marked COVID-19 antibody test. Roche offers a selective ELISA serology test.
Sensitivity and Specificity
Sensitivity indicates whether the test accurately identifies whether the virus is present. Each test requires a minimum level of viral load in order to produce a positive result A 90% sensitive test will correctly identify 90% of infections, missing the other 10% (a false negative). Even relatively high sensitivity rates can produce high rates of false negatives in populations with low incidence rates.
Specificity Indicates how well-targeted the test is to the virus in question. Highly specific tests pick up only the virus in question. Non-selective tests pick up other viruses as well. A 90% specific test will correctly identify 90% of those who are uninfected, leaving 10% with a false positive result Low-specificity tests have a low positive predictive value (PPV) when prevalence is low. For example, suppose incidence is 5%. 100 people selected at random would contain 95 people who are negative and 5 people who are positive. Using a test that has a specificity of 95% would yield on average 4.75 people who are actually negative who would incorrectly test positive. If the test has a sensitivity of 100%, all five positive people would also test positive, totaling 9.75 positive results. Thus, the PPV is 51.3%, an outcome comparable to a coin toss. In this situation retesting those with a positive result increases the PPV to 95.5%, meaning that only 4.5% of the second tests would return the incorrect result, on average less than 1 incorrect result
Causes of Test Error
Improper sample collection is exemplified by failure to acquire enough sample and failure to insert a swab deep into the nose. This results in insufficient viral load, one cause of low clinical sensitivity. The time course of infection also affects accuracy. Samples may be collected before the virus has had a chance to establish itself or after the body has stopped its progress and begun to eliminate it. Improper storage for too long a time can cause RNA breakdown and lead to wrong results as viral particles disintegrate. Improper design and manufacturing can yield inaccurate results. Millions of tests made in China were rejected by various countries throughout the period of March 2020 through May 2020. Test makers typically report the accuracy levels of their tests when seeking approval from authorities. In some jurisdictions, these results are cross-validated by additional assessments. Reported results may not be achieved in clinical settings due to such operational inconsistencies.
PCR-Based Test
RT-PCR is the most accurate diagnostic test. It typically has high sensitivity and specificity in a laboratory setting: however, in one study sensitivity dropped to 66-88% clinically. In one study sensitivity was highest at week one (100%), followed by 89.3%, 66.1%, 32.1%, 5.4% and zero by week six. A Dutch CDC-led laboratory investigation compared 7 PCR kits. Test kits made by BGI, R-Biopharm AG, BGI, KH Medical and Seegene showed high sensitivity. High sensitivity kits are recommended to assess people without symptoms, while lower sensitivity tests are adequate when diagnosing symptomatic patients.
Isothermal Nucleic Amplification Test
One study reported that the ID Now COVID-19 test showed sensitivity of 85.2%. Abbott responded that the issue could have been caused by analysis delays. Another study rejected the test in their clinical setting because of this low sensitivity.
What is needed is an apparatus and method for point-of-care, rapid, field-deployable diagnostic testing of Covid-19, viruses, antibodies and markers, which can be used by unskilled health workers, which is sensitive and specific, and which gives diagnostic results in 30 minutes or less with highly developed diagnostic data processing in the Cloud.
The illustrated embodiments of the invention include an automated system communicating with a remote server for diagnostically field testing a sample taken from a subject using an automated portable handheld instrument to determine the presence of viral antigens and/or antibodies thereto comprising: one or more types of microfluidic circuits defined in a rotatable disk, each type of microfluidic disk for performing a bioassay using a predetermined type of biodetector to generate an electrical signal indicative of a bioassay measurement; a biodetector operationally positioned in the microfluidic circuit; one or more lasers; one or more positionable valves in the microfluidic circuit; and a backbone unit for rotating the disk according to a predetermined protocol to perform the bioassay, for controlling and powering the one or more lasers to selectively open one or more positionable valves in the microfluidic disk, for operating the biodetector to generate an electrical signal indicative of a bioassay measurement; for communicating the bioassay measurement to the remote server, and for associating the performed bioassay and its corresponding bioassay measurement to the subject.
The biodetector comprises a microarray and where the bioassay is a serology test, including testing for IgG and/or IgM.
The biodetector comprises a microarray and where the serology test provided by the microarray is a respiratory antibody and/or antigen test.
The serology test tests for Covid-19.
The biodetector comprises a microarray and where microfluidic disk has a center and comprises: a sample inlet; a blood-plasma separation chamber communicated with the sample inlet and positioned on the disk radially farther from the center of the disk than the sample inlet; a mixing chamber communicated to the blood-plasma separation chamber through a corresponding selectively openable valve and positioned on the disk radially farther from the center of the disk than the blood-plasma separation chamber, a first wash chamber communicated to the mixing chamber through a corresponding selectively openable valve and positioned on the disk radially closer to the center of the disk than the mixing chamber; a secondary antibody chamber communicated to the mixing chamber through a corresponding selectively openable valve and positioned on the disk radially closer to the center of the disk than the mixing chamber; a second wash chamber communicated to the mixing chamber through a corresponding selectively openable valve and positioned on the disk radially closer to the center of the disk than the mixing chamber; a microarray chamber communicated to the mixing chamber, the microarray being disposed in the microarray chamber; and the microarray chamber positioned on the disk radially farther from the center of the disk than the mixing chamber; and a waste chamber communicated to the microarray chamber by a siphon and by a corresponding selectively openable spin-dry valve and positioned on the disk radially farther from the center of the disk than the microarray chamber.
The signal indicative of a bioassay measurement is a digital image of microarray spots which have been fluoroscopically activated by the sample in the performance of the bioassay. The remote server is a Cloud server. The backbone unit includes network circuitry which communicates the digital image to the Cloud server and a corresponding schema file associating the subject to the performed bioassay and its corresponding bioassay measurement. The Cloud server, operating in an automated and modular protocol, aligns the microarray spots of the digital image, detects each of the aligned spots of the microarray and analyzes each of the spots of the digital image to assign a scalar value to each microarray spot to produce a processed microarray measurement set of data. The Cloud server, operating in an automated protocol, analyzes the processed microarray measurement set of data to produce a diagnosis of the biomeasurement. The Cloud server, operating in an automated protocol, reports the results to the subject as determined by the schema file.
The Cloud server comprises a cloud-based module for automatically determining under automated control whether the corresponding Z-scores of the communicated data output of positive and/or negative indications are indicative of Covid-19 rather than the Z-scores of the plurality of viral infections sharing at least some of the Covid-19 antigens and/or antibodies.
The Cloud server comprises means for identifying positive and/or negative indications of the digital image of microarray spots for a plurality of acute respiratory infections selected from the group including SARS-CoV-2, SARS-CoV, MERS-CoV, common cold coronaviruses (HKU1, OC43, NL63, 229E), and multiple subtypes of influenza, adenovirus, metapneumovirus, parainfluenza, and/or respiratory syncytial virus.
The Cloud server comprises a cloud-based module for automatically evaluating antigens to discriminate output data of a positive group of antigens from a negative group of antigens across a range of assay cutoff values using receiver-operating-characteristic (ROC) curves for which an area-under curve (AUC) is measured to determine high performing antigens to diagnose Covid-19.
The Cloud server comprises a cloud based module for automatically determining under automated control an optimal sensitivity and specificity for Covid-19 from a combination of a plurality of high performing antigens based on a corresponding Youden Index calculated for the combination of plurality of high-performing antigens.
More particularly, the illustrated embodiment of the invention includes an automated system communicated to a cloud-based server for diagnostically field testing a sample taken from a subject using an automated portable handheld instrument to determine the presence of viral antigens and/or antibodies thereto in a serology test to detect Covid-19. The system includes: a microfluidic circuit defined in a rotatable disk for performing a bioassay using a microassay to generate an digital image indicative of a bioassay measurement; a microassay operationally positioned in the microfluidic circuit; one or more positionable valves in the microfluidic circuit; one or more lasers; a fluoroscopic microassay reader; and a backbone unit for rotating the disk according to a predetermined protocol to perform the bioassay, for controlling and powering the one or more lasers to selectively open one or more positionable valves in the microfluidic disk, for operating the fluoroscopic microassay reader to generate the digital image indicative of a bioassay measurement; for communicating the digital image to the cloud-based server, and for associating the performed bioassay and its corresponding bioassay measurement to the subject. The microfluidic disk has a center and comprises: a sample inlet; a blood-plasma separation chamber communicated with the sample inlet and positioned on the disk radially farther from the center of the disk than the sample inlet; a mixing chamber communicated to the blood-plasma separation chamber through a corresponding selectively openable valve and positioned on the disk radially farther from the center of the disk than the blood-plasma separation chamber; a first wash chamber communicated to the mixing chamber through a corresponding selectively openable valve and positioned on the disk radially closer to the center of the disk than the mixing chamber; a secondary antibody chamber communicated to the mixing chamber through a corresponding selectively openable valve and positioned on the disk radially closer to the center of the disk than the mixing chamber; a second wash chamber communicated to the mixing chamber through a corresponding selectively openable valve and positioned on the disk radially closer to the center of the disk than the mixing chamber; a microarray chamber communicated to the mixing chamber, the microarray being disposed in the microarray chamber; and the microarray chamber positioned on the disk radially farther from the center of the disk than the mixing chamber; and a waste chamber communicated to the microarray chamber by a siphon and by a corresponding selectively openable spin-dry valve and positioned on the disk radially farther from the center of the disk than the microarray chamber. The backbone unit includes network circuitry which communicates the digital image to the Cloud server and a corresponding schema file associating the subject to the performed bioassay and its corresponding bioassay measurement. The Cloud server, operating in an automated and modular protocol, aligns the microarray spots of the digital image, detects each of the aligned spots of the microarray and analyzes each of the spots of the digital image to assign a scalar value to each microarray spot to produce a processed microarray measurement set of data. The Cloud server, operating in an automated protocol, analyzes the processed microarray measurement set of data to produce a diagnosis of the biomeasurment. The Cloud server, operating in an automated protocol, reports the results to the subject as determined by the schema file.
The Cloud server comprises a cloud-based module for automatically determining under automated control whether the corresponding Z-scores of the communicated data output of positive and/or negative indications are indicative of Covid-19 rather than the Z-scores of the plurality of viral infections sharing at least some of the Covid-19 antigens and/or antibodies.
The Cloud server comprises means for identifying positive and/or negative indications of the digital image of microarray spots for a plurality of acute respiratory infections selected from the group including SARS-CoV-2, SARS-CoV, MERS-CoV, common cold coronaviruses (HKU1, OC43, NL63, 229E), and multiple subtypes of influenza, adenovirus, metapneumovirus, parainfluenza, and/or respiratory syncytial virus.
The Cloud server comprises a cloud-based module for automatically evaluating antigens to discriminate output data of a positive group of antigens from a negative group of antigens across a range of assay cutoff values using receiver-operating-characteristic (ROC) curves for which an area-under curve (AUC) is measured to determine high performing antigens to diagnose Covid-19.
The Cloud server comprises a cloud based module for automatically determining under automated control an optimal sensitivity and specificity for Covid-19 from a combination of a plurality of high performing antigens based on a corresponding Youden Index calculated for the combination of plurality of high-performing antigens.
The illustrated embodiments of the invention also extend to a method for operating an automated system communicated to a remote server for diagnostically field testing a sample taken from a subject using an automated portable handheld instrument to determine the presence of viral antigens and/or antibodies thereto comprising the steps of: introducing the sample into a sample inlet; transferring the sample to a blood-plasma separation chamber communicated with the sample inlet and positioned on the disk radially farther from the center of the disk than the sample inlet; separating the blood from the plasma by spinning the disk at 5500 rpm for 5 minutes; opening a first valve using a laser-meltable plug, the first valve being disposed in a conduit in the disk between the blood-plasma chamber and a mixing chamber communicated to the blood-plasma separation chamber through the selectively openable first valve and positioned on the disk radially farther from the center of the disk than the blood-plasma separation chamber; transferring the serum to the mixing chamber and to a microarray chamber communicated to the mixing chamber, the microarray being disposed in the microarray chamber; and the microarray chamber positioned on the disk radially farther from the center of the disk than the mixing chamber; reciprocating the sample in the microarray chamber for 40 cycles at 2700-5428 rpm, followed by prime at 170 rpm and evacuation at 1000 rpm for 5 minutes to a waste chamber communicated to the microarray chamber by a siphon and by a corresponding selectively openable spin-dry valve and positioned on the disk radially farther from the center of the disk than the microarray chamber; opening a second valve using a laser-meltable plug, the second valve being disposed in a conduit in the disk between the mixing chamber and a first wash chamber communicated to the mixing chamber through a corresponding selectively openable valve and positioned on the disk radially closer to the center of the disk than the mixing chamber; transferring a first wash from the first wash chamber through the mixing chamber to the microarray chamber; reciprocating the first wash in the microarray chamber for 20 cycles at 2700-5428 rpm, followed by prime at 170 rpm and evacuation at 1000 rpm for 2 minutes to the waste chamber, opening a third valve using a laser-meltable plug, the third valve being disposed in a conduit in the disk between the mixing chamber and a secondary antibody chamber communicated to the mixing chamber through a corresponding selectively openable valve and positioned on the disk radially closer to the center of the disk than the mixing chamber; transferring the secondary antibody from the secondary antibody chamber through the mixing chamber to the microarray chamber; reciprocating the secondary antibody in the microarray chamber for 20 cycles at 2700-5428 rpm, followed by prime at 170 rpm and evacuation at 1000 rpm for 2 minutes to the waste chamber; opening a fourth valve using a laser-meltable plug, the fourth valve being disposed in a conduit in the disk between the mixing chamber and a second wash chamber communicated to the mixing chamber through a corresponding selectively openable valve and positioned on the disk radially closer to the center of the disk than the mixing chamber; transferring a second wash from the second wash chamber through the mixing chamber to the microarray chamber; reciprocating the second wash in the microarray chamber for 20 cycles at 2700-5428 rpm, followed by prime at 170 rpm and evacuation at 1000 rpm for 2 minutes to the waste chamber; opening a fifth valve using a laser-meltable plug, the fifth valve being disposed in a conduit in the disk between the microarray chamber and the waste chamber; spin drying the microarray chamber by spinning the disk at 5500 rpm for one minute; moving the microarray chamber to a position wherein a fluoroscopically induced digital image can be taken of the microarray; and generating the fluoroscopically induced digital image of the microarray.
The method further the steps of: communicating the digital image using a backbone unit including network circuitry which communicates the digital image to a Cloud server and communicates a corresponding schema file associating the subject to the performed bioassay and its corresponding bioassay measurement; aligning the microarray spots of the digital image in the Cloud server, operating in an automated and modular protocol; detecting each of the aligned spots of the microarray in the Cloud server, operating in an automated and modular protocol; analyzing each of the spots of the digital image in the Cloud server, operating in an automated and modular protocol to assign a scalar value to each microarray spot to produce a processed microarray measurement set of data; analyzing the processed microarray measurement set of data to produce a diagnosis of the biomeasurement in the Cloud server, operating in an automated protocol; and reporting the results to the subject as determined by the schema file using the Cloud server, operating in an automated protocol.
The step of analyzing the processed microarray measurement set of data comprises the step of identifying positive and/or negative indications of the digital image of microarray spots for a plurality of acute respiratory infections selected from the group including SARS-CoV-2, SARS-CoV, MERS-CoV, common cold coronaviruses (HKU1, OC43, NL63, 229E), and multiple subtypes of influenza, adenovirus, metapneumovirus, parainfluenza, and/or respiratory syncytial virus.
While the apparatus and method has or will be described for the sake of grammatical fluidity with functional explanations, it is to be expressly understood that the claims, unless expressly formulated under 35 USC 112, are not to be construed as necessarily limited in any way by the construction of “means” or “steps” limitations, but are to be accorded the full scope of the meaning and equivalents of the definition provided by the claims under the judicial doctrine of equivalents, and in the case where the claims are expressly formulated under 35 USC 112 are to be accorded full statutory equivalents under 35 USC 112. The disclosure can be better visualized by turning now to the following drawings wherein like elements are referenced by like numerals.
The disclosure and its various embodiments can now be better understood by turning to the following detailed description of the preferred embodiments which are presented as illustrated examples of the embodiments defined in the claims. It is expressly understood that the embodiments as defined by the claims may be broader than the illustrated embodiments described below.
The apparatus of the illustrated embodiments include a backbone unit which includes the electronics, camera, optics, digital data gathering and communication via the internet to Cloud-based expert diagnostic servers, and electromechanical elements needed to provide field portable diagnostic testing of Covid-19 and other viral or bacterial infections. The same backbone unit supports at least three different microfluidic compact disks 68 (CDs) used for diagnostic assays or testing, namely for virology detection using a surface acoustical wave (SAW) detector, for microarray serology detectors for antibodies like IgG and IgM, and RT-PCR assays for nucleic acid targets using fluorescence detectors, which are denoted by Autonomous Medical Devices Inc. as its A10, A20 and A30 CD's respectively. The unit and its corresponding CDs are measurement or assay devices and do not perform high level diagnosis analysis, but provide the data needed to do so to fully developed diagnostic databases and expert systems resident in the Cloud in internet communication with the backbone unit.
The Backbone Unit
The backbone unit 10 shown in
The operation of unit 10 is now better understood by referring to the block diagram of
CPU 43 is an ARM-based (Advanced RISC machine) processor with a Linux operating system. CPU 43 is coupled to and drives camera 32 and provides raw image processing though a USB link to generate a transmissible digital data image through a wireless module ultimately to Cloud 134. CPU 43 is associated with a fan 55, clock 35, RAM memory 37 and an eMMC (embedded multimedia controller) flash memory 39, a micro-secure digital memory card (SD) 61, an audio amplifier 65 with headphone speakers 63, power management circuit 71 and a power connector 69. Memory card 61 is used to capture copies of the test results that are additionally transmitted on the cloud 134. The audio amplifier 65 is to be used with the speaker 63 which wig transmit the health or status of the device to the user (test status, errors, etc). CPU 43 is coupled to display 12, both through HDMI and USB connections. Display 12 optionally drives a pair of stereo speakers 13 for communication to the user. CPU 43 is optionally communicated through a seven port USB hub 91 with a 6-degrees of freedom inertial measurement unit (IMU) 93, microphone 95, global navigation satellite system (GNSS) 97 with antenna, mouse/keyboard 99, barcode reader 89 allowing for location tracking, handing history, and user interaction and developer programming in the field.
A microcontroller with CPU 41 with its memory 43 and external oscillator/clock 43 in photonics board 40 is coupled to CPU 42 and provides the controls for motor 26 according to the protocol shown in the flow diagram of
As shown in
The operation of photonics board 40 with respect to disk 68 can now be understood. The movement and position of disk 68 is tracked by a disk mounted magnet 66 sensed by magnetic and optical index driver 64 coupled to CPU 41 by which the angular orientation or position of disk 68 is determined. The test sample is disposed into sample inlet 94 of
A20—Disk Operation
Before discussing diagnostic methods for Covid-19 on a microarray, turn now and consider the general operation of disk 68 when a microarray detector 92 is employed as depicted in the top plan view of
At 199 laser valve 106 is aligned with a laser 48 in unit 10 and opened with a 0.5 min exposure. Thereafter, a wash buffer #1 stored in chamber 100 is transferred to microarray chamber 74 by reciprocation at step 201 for about 5 min at step 197 for 20 cycles at 2700-5428 rpm followed by priming chamber 100 at 170 rpm and then evacuating chamber 74 by rotation at 1000 rpm for about 2 min.
At step 203 laser valve 108 is aligned with a laser 48 in unit 10 and opened with a 0.5 min exposure. A secondary antibody stored in chamber 102 is transferred to microarray chamber 74 by reciprocation for about 5 min for 20 cycles at 2700-5428 rpm followed by priming chamber 102 at 170 rpm and then evacuating chamber 74 by rotation at 1000 rpm at step 205 for about 2 min. The secondary antibody is an anti-antibody. The antibody in blood binds to the antigen. The secondary antibody is an antibody that specifically binds to the tail of the antibody in the blood sample. This secondary antibody carries the fluorescent tag.
At step 207 laser valve 110 is aligned with a laser 48 in unit 10 and opened with a 0.5 min exposure. Thereafter, a wash buffer #2 stored in chamber 104 is transferred to microarray chamber 74 by reciprocation at step 209 for about 5 min at step 197 for 20 cycles at 2700-5428 rpm followed by priming chamber 104 at 170 rpm and then evacuating chamber 74 by rotation at 1000 rpm for about 2 min.
At step 211 valve 112 is aligned with a laser 48 in unit 10 and opened with a 0.5 min exposure. At step 213 disk 68 is spun at 5500 rpm for about 1 min to spin dry chamber 74 with wash #2 being evacuated to waste chamber 114. Chamber 74 and microarray 92 are then moved to align with camera 32 in unit 10. One or more grayscale images using induced fluorescence are taken by camera 32, stored and transmitted at step 215 in about 1 min by CPU 42 to the Cloud for data processing and diagnostic analysis as described below.
The total time needed to run the assay is about 16.5 minutes.
Cloud Processing and Diagnosis
Unit 10 performs the physical assay test using disk 68 and the detector provided in disk 68. What results in raw data in some form. Unit 10 does not further process the data nor analyze it to derive a diagnosis of the patient, but transmits the raw data to the Cloud, where remote servers provide processing and diagnostic analysis of the data. Using information associated with or in the patient's scanned QR code, the test results are then stored in a database and transmitted back to the patient's computer, smartphone or other electronic address of a health provider associated with the patient without further involvement with unit 10.
Prior to transmission of the captured data, unit 10 operates under software control as depicted in
Unit 10 operates autonomously under client/Python module 122, which includes responsive action to exterior communications as well as operating according to the onboard stored Linux Oracle programming protocol. The operator interface 118 communicates with the autonomously running backend software 120, which controls all operations of unit 10 through device control module 124. Major functions include Cloud bidirectional communication by Cloud module 126 hardware control module 128 and database module 130.
Image Processing in the Cloud
As described above unit 10 generates raw digital images taken by camera 32 and transmits them unprocessed to Cloud 134. The object is to convert the scanned microarray images into a scalar value for each microarray dot or site. The image data processing proceeds by the steps of alignment 136, spot detection 138 and spot analysis 140 as depicted in
The primary goal of the alignment step 236 is to correct for image inconsistencies, including angle of rotation, scale, and background noise. The alignment algorithm filters through all the shapes in an image, looking for objects that would qualify for spots or fiducials. After finding any potential spot or fiducial, the program looks for spacing ratios between all the potential fiducials that match the fiducial pattern indicated in the JSON schema file. Once the fiducials have been found, the image is rotated and cropped at step 246 to include only the region of interest. All processing is done on grayscale images.
Original or raw grayscale images 142 are imported into the program. The image 142 contains background information or noise that is not relevant to the processing of the image 142. The alignment phase aims to remove this region of noninterest (nROI) information by identifying the three bright fiducial spots at the corners of the microarray. A bilateral filter is applied to the image to reduce noise, but to keep sharp edges for downstream processing. Next, the image 142 is processed through an adaptive threshold filter to obtain a binary image of contours. Each contour is then filtered for a range of sizes or pixel areas. The size ranges are known beforehand and scale with the dimension of the image. Contours that are too large or too small are ignored. The remaining contours have a minimum fit circle drawn around their perimeter; the area of this circle is compared to the area of the contour to determine how ‘circular’ the contour is. Contours that have an area similar to the area of the bounding circle are retained. After potential fiducials are identified, the program compares the distance ratios between all sets (combinations) of three contours, looking for ratios that match the theoretical fiducial spacing ratios given in the schema file (
In the spot detection step 238 the primary purpose is to determine where each microarray spot is located within the region of interest image. This will be used downstream to determine each spot value. Using the fiducial locations and known size of the microarray, the cropped image is subdivided into a grid, where each square should contain a spot. Adaptive thresholding is applied within each square of the grid. The adaptive threshold image of each square is used to calculate the image moment, which is used to determine centroids for spots:
Where Ip is the pixel intensity at the pixel p,
The purpose of the spot analysis phase is to assign a single scalar value to each spot in the grid. Currently this is done by calculating the foreground median intensity and subtracting it from the background mean intensity. Each spot is individually masked, and the median of each spot is calculated. Likewise, the mean of each background annulus is calculated and subtracted from the spot median (
Diagnostic Processing the Cloud
Before considering the details of diagnostic processing of the processed image data in the Cloud, turn first and consider the microarrays used in the illustrated embodiments. The “multiplexed antibody array” in disk 68 provides an individual's virus “exposure fingerprint”, the “legacy antibody profile” reflecting past exposure and vaccination history. This array analysis approach is significantly more data rich (e.g. 67 antigens with 4 replicates per array) and is more quantitative than lateral flow assays in current use for measuring antibodies against the virus. To appreciate this point turn to
High throughput cloning and constructing microarrays have previously been developed that contain human and animal antibodies with antigens from more than 35 medically important pathogens, including bacteria, parasites, fungi and viruses such as vaccinia, monkey pox, Herpes 1 & 2, Varicella zoster, HPV, HIV, Dengue, Influenza, West Nile, Chikungunya, adenovirus, and coronaviruses. A DNA microarray (also commonly known as DNA chip or biochip) is a collection of microscopic DNA spots attached to a solid surface. DNA microarrays are used to measure the expression levels of large numbers of genes simultaneously or to genotype multiple regions of a genome. Each DNA spot contains picomoles (10−12 moles) of a specific DNA sequence, known as probes (or reporters or oligos). These can be a short section of a gene or other DNA element that are used to hybridize a cDNA or cRNA, also called anti-sense RNA, sample, called target, under high-stringency conditions. Probe-target hybridization is usually detected and quantified by detection of fluorophore-, silver-, or chemiluminescence-labeled targets to determine relative abundance of nucleic acid sequences in the target. The original nucleic acid arrays were macro arrays approximately 9 cm×12 cm and the first computerized image-based analysis was published in 1981. We have probed over 25000 samples from humans and animals infected with pathogens and identified over 1000 immunodominant and candidate vaccine antigens against these pathogens. We have shown that the individual proteins/antibodies printed on these arrays 92 capture antibodies and/or antigens present in serum from infected individuals and the amount of captured antibody can be quantified using fluorescent secondary antibody.
In this way a comprehensive profile of antibodies that result after infection or exposure can be determined that is characteristic of the type of infection and the stage of diseases. Arrays 92 can be produced and probed in large numbers (>500 serum or plasma specimens per day) while consuming <2 μl of each sample. This microarray approach allows investigators to assess the antibody repertoire in large collections of samples not possible with other technologies.
A coronavirus antigen microarray 92 (COVAM) was constructed containing 67 antigens that are causes of acute respiratory infections. The viral antigens printed on this array 92 are from epidemic coronaviruses including SARS-CoV-2, SARS-CoV, MERS-CoV, common cold coronaviruses (HKU1, OC43, NL63, 229E), and multiple subtypes of influenza, adenovirus, metapneumovirus, parainfluenza, and respiratory syncytial virus. The SARS-CoV-2 antigens on this array 92 include the spike protein (S), the receptor-binding (RBD), S1, and S2 domains, the whole protein (S1+S2), and the nucleocapsid protein (NP) as shown in the graph of
To determine the antibody profile of SARS-CoV-2 Infection, the differential reactivity to these antigens was evaluated for SARS-CoV-2 convalescent blood specimens from PCR-positive individuals (positive group) and sera collected prior to the COVID-19 pandemic from naïve individuals (negative control group). As shown in the heatmaps of
Table 1 contains the fluorescence intensity results for IgG shown in
Antigens were then evaluated to discriminate the positive group from the negative group across a full range of assay cutoff values using receiver-operating-characteristic (ROC) curves for which an area-under curve (AUC) was measured. High-performing antigens for detection of IgG are defined by ROC AUC>0.85 as shown in Table 1. Four antigens are ranked as high-performing antigens: SARS-CoV-2 NP, SARS-CoV NP, SARS-CoV-2S1+S2, and SARS-CoV-2_S2. Additional high-performing antigens included SARS-CoV-2 S1 (with mouse Fc tag) and RBD, and MERS-CoV S2. The optimal sensitivity and specificity were also estimated for the seven high-performing antigens based on the Youden Index. Youden's J statistic (also called Youden's index) is a single statistic that captures the performance of a dichotomous diagnostic test. Informedness is its generalization to the multiclass case and estimates the probability of an informed decision. The lowest sensitivity was seen for SARS-CoV-2 S1, which correlates with the relatively lower reactivity to this antigen in the positive group. The lowest specificity was seen for SARS-CoV-2 S2, which correlates with the cross-reactivity for this antigen seen in a subset of the negative group. To estimate the gain in performance by combining antigens, all possible combinations of up to four of the seven high-performing antigens were tested in silico for performance in discriminating the positive and negative groups. The ROC curve with AUC, sensitivity, and specificity was calculated for each combination. There is a clear gain in performance by combining two or three antigens. For IgG, the best discrimination was achieved with the two-antigen combination of SARS-CoV-2S2 and SARS-CoV NP, with similar performance upon the addition of SARS-CoV-2S1 with mouse Fc tag (AUC=0.994, specificity=1, sensitivity=0.944). The addition of a fourth antigen decreased the performance.
Table 2 shows the performance data for combinations of high-performing antigens. ROC, AUC values and sensitivity and specificity based on Youden index for discrimination of positive and negative sera were derived for each individual antigen ranked, and high-performing antigens with ROC AUC>0.86 are indicated above the lines.
More particularly, the A20 serology test is an optical microarray test that performs an indirect immunofluorescence assay for qualitative detection of IgM and IgG antibodies to SARS-CoV-2 in human blood. The serology test is intended for use as an aid in identifying individuals with an adaptive immune response to SARS-CoV-2, indicating recent or prior infection. The serology test currently produces an image of the microarray and a graph of the intensities of the spots on the array. To develop a diagnostic standard known RT-PCR positive and negative samples are tested on the apparatus described above. This establishes cutoff thresholds for reactivity to each of the three SARS-CoV-2 antigens in the microarray, which enables the apparatus to autonomously provide a qualitative “yes” (reactive) or “no” (non-reactive) result.
Microarray Description
The serology test contains two identical microarrays on disk 68, one for testing IgG presence and the other for IgM presence. The two classes of antibodies are probed separately by using IgG or IgM reporter antibodies. Each of the two microarrays has the form diagrammatically depicted in
a. Negative Controls: BUFFER (10 spots): Phosphate-buffered saline (PBS) with 0.001% Tween-20 (Polyethylene glycol sorbitan monolaurate, Polyoxyethylenesorbitan monolaurate). These spots are printing buffers and serve as a negative control to determine the baseline fluorescence of the array.
b. Positive Controls 1: HuIgG (5 spots): Human IgG printed in concentrations of eight dilutions from 0.3 to 0.001 mg/ml for a total of 40 spots. These spots serve as a positive control to indicate that the reporter antibody for IgG is performing appropriately to accurately determine cutoff values of the array when testing on serum samples. The concentration ladder can serve as a rough guide to interpret the microarray's fluorescence.
c. HuIgM (5 spots): Human IgM printed in concentrations of eight dilutions from 0.3 to 0.001 mg/ml for a total of 40 spots. These spots serve as a positive control to indicate that the reporter antibody for IgM is performing appropriately to accurately determine cutoff values of the array when testing on serum samples. The concentration ladder can serve as a rough guide to interpret the microarray's fluorescence.
d. Positive Controls 2: a. HuIgG (3 spots): anti-Human IgG printed in concentrations of 0.3, 0.1, and 0.03 mg/ml. These spots serve as a positive control to indicate that there are human IgG antibodies in the sample. a. HuIgM (3 spots): anti-Human IgM printed in concentrations of 0.3, 0.1, and 0.03 mg/ml. These spots serve as a positive control to indicate that there are human IgM antibodies in the sample.
e. Antigens: SGC-SPIKE19200701 (8 spots): SARS-Cov-2 Spike Protein (University of Oxford). Printed at 0.2 mg/ml. SARS-CoV2.NP (8 spots): SARS-Cov-2 Nucleocapsid Protein (Sinobiological). Printed at 0.2 mg/ml. SARS-CoV2.RBD.mFc (8 spots): SARS-Cov-2 Spike Protein (RBD, mFc Tag) (Sinobiological). Printed at 0.2 mg/ml.
f. Fiducial (3 spots): Streptavidin, Alexa Fluor 647 conjugate. These spots are designed to be the brightest spots on the array and are used to locate and orient the array.
g. PBSTwash (21 spots): PBS+0.05% tween20 used for washing pins.
h. Blank (2 spots): Unused microarray locations.
Microarray Results
The images of each microarray in an A20 serology test are uploaded to a server on the Oracle Cloud for analysis. After the corner fiducials are used to locate and orient the microarrays, the images are analyzed to produce scalar values for each spot in the microarray. These measurements are the median fluorescence intensity of each spot, minus the mean fluorescence intensity of the surrounding annulus. These measurements will be available to the user online in a file in JSON format, along with a plot summarizing the values of the three SARS-CoV-2 antigens printed on the microarray. The JSON file is a hierarchical file with the following top-level structure:
The measurements for each spot are contained in a list in the “spots” entry, with thorough details of each spot:
The accompanying summary figure of each microarray is a bar chart, which reports the value of each control spot, and mean value and standard deviation for each antigen such as shown in an example in
Overall System Usage
The overall user flow or user interaction with the system is illustrated in
On the day of the appointment at step 408 in
If it is determined at step 420 that the authority to use disk 68 is denied, the operator is advised to reject disk 68 and replace it with another at step 424, after which the procedure returns to step 414. If use of disk 68 is authorized, then a blood sample, such as a finger prick, is taken from the patient by the test operator at step 426, loaded by the test operator into disk 68 at step 428, and disk 68 then loaded into unit 10 at step 430. Unit 10 displays a screen prompt to the test operator to begin the test at step 432 in
Pretest diagnostic data is gathered in step 436, this includes checking the optical system at step 438 with both microarrays 92 in disk 68 by verifying that: 1) the three fiducial spots in each array are visible; 2) the fiducial intensity is within 20% of the original images of the microarray; and 3) the fiducial spots are in focus. Similarly, a watchdog routine in COU 43 at step 440 outputs diagnostic data from camera 32, the LEDs 56, motor 26, and lasers 48. Thereafter, unit 10 runs a spin protocol on disk 68 at step 442 as described above and takes a grayscale image of each microarray 92 at the end of the assay. The watchdog routine in CPU 43 at step 444 continues to monitor unit 10 during the assay procedure and generates an error message display in the event of a fault and stops the test or assay if needed.
The grayscale TIF image taken by camera 32 of each microarray 92 is uploaded to Cloud 134 at step 446 in
From the JSON output file the test processing is determined as being passed or failed at step 452 in
Data Chain Identification
Control of the data sent to the remote server in Cloud 134 is realized utilizing the identification chain 300 of
Attaching a unique cartridge code 312 further guarantees the uniqueness of each test and its results, but also creates a complete identification chain to connect a particular test 302 and its results to every relevant assembly component involved in that test 302. This provides full traceability, allowing one to identify all component lot numbers used in a particular disc 68, or all discs 68 utilizing a particular component lot number. This allows one to acquire data from compromised tests and determine a faulty component lot or recall all discs that utilize a faulty component lot.
The machine ID 310 is uniquely defined by its camera serial number 316 and on-board computer (pi raspberry) serial number 318. The machine ID 310 can then provide the hierarchy of al sub-assemblies of all its mechanical and electrical components.
The cartridge code 312 is traced to the cartridge assembly batch 320, which details the date of assembly 328, microarray information 322, disc information 324, and reagent catalog and lot number 326 stored on the cartridge. The disc information 324 contains details of the disc design 330 and disc injection batch 332. The microarray information 322 contains details of the printing date 334, the microarray layout 336, the glass slide etching batch 338, the printing protein catalog and lot number 340, the nitrocellulose lot 342 used in the microarray. The glass slide etching batch 338 refers in turn to the glass slide lot 344.
Many alterations and modifications may be made by those having ordinary skill in the art without departing from the spirit and scope of the embodiments. Therefore, it must be understood that the illustrated embodiment has been set forth only for the purposes of example and that it should not be taken as limiting the embodiments as defined by the following embodiments and its various embodiments.
Therefore, it must be understood that the illustrated embodiment has been set forth only for the purposes of example and that it should not be taken as limiting the embodiments as defined by the following claims. For example, notwithstanding the fact that the elements of a claim are set forth below in a certain combination, it must be expressly understood that the embodiments includes other combinations of fewer, more or different elements, which are disclosed in above even when not initially claimed in such combinations. A teaching that two elements are combined in a claimed combination is further to be understood as also allowing for a claimed combination in which the two elements are not combined with each other but may be used alone or combined in other combinations. The excision of any disclosed element of the embodiments is explicitly contemplated as within the scope of the embodiments.
The words used in this specification to describe the various embodiments are to be understood not only in the sense of their commonly defined meanings, but to include by special definition in this specification structure, material or acts beyond the scope of the commonly defined meanings. Thus if an element can be understood in the context of this specification as including more than one meaning, then its use in a claim must be understood as being generic to all possible meanings supported by the specification and by the word itself.
The definitions of the words or elements of the following claims are, therefore, defined in this specification to include not only the combination of elements which are literally set forth, but all equivalent structure, material or acts for performing substantially the same function in substantially the same way to obtain substantially the same result. In this sense it is therefore contemplated that an equivalent substitution of two or more elements may be made for any one of the elements in the claims below or that a single element may be substituted for two or more elements in a claim. Although elements may be described above as acting in certain combinations and even initially claimed as such, it is to be expressly understood that one or more elements from a claimed combination can in some cases be excised from the combination and that the claimed combination may be directed to a subcombination or variation of a subcombination.
Insubstantial changes from the claimed subject matter as viewed by a person with ordinary skill in the art, now known or later devised, are expressly contemplated as being equivalently within the scope of the claims. Therefore, obvious substitutions now or later known to one with ordinary skill in the art are defined to be within the scope of the defined elements.
The claims are thus to be understood to include what is specifically illustrated and described above, what is conceptionally equivalent, what can be obviously substituted and also what essentially incorporates the essential idea of the embodiments.
This application is a continuation in part and claims priority to, and the benefit of the earlier filing date of US non provisional patent application entitled AN AUTOMATED, CLOUD-BASED, POINT-OF-CARE (POC) PATHOGEN AND ANTIBODY ARRAY DETECTION SYSTEM AND METHOD, filed on Jun. 25, 2020, Ser. No. 16/912,568, pursuant to 35 USC 120, the contents of which is incorporated herein by reference.
| Number | Date | Country | |
|---|---|---|---|
| Parent | 16912568 | Jun 2020 | US |
| Child | 17083113 | US |
