DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of the Claims
The Amendment filed December 31, 2025 has been entered. Claims 1, 7-9, 11-13, 15, 21, and 23-25 have been amended; and claims 16-20 have been cancelled. Claims 1-15 and 21-25 are currently pending and examined herein.
Status of the Rejection
Applicant’s amendments to the Claims have overcome each objection and 112(b) rejections previously set forth in the Non-Final Office Action mailed August 13, 2025.
All 35 U.S.C. § 103 rejections from the previous office action are withdrawn in view of the Applicant’s amendment.
New grounds of rejection under 35 U.S.C. § 103 are necessitated by the amendments as outlined below.
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1-15 and 21-25 are rejected under 35 U.S.C. 103 as being unpatentable over Yang et al. (Qualitative immunoassay for the detection of anti-SARS-COV-2 spike antibody in human milk samples, STAR Protocols, 2022, 3, 101203), and in view of Lim et al. (Emerging Biosensors to Detect Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2): A Review, Biosensors, 2021, 11, 434), Liu et al. (US20160334362A1), Huang et al. (US20180203006A1) and Spitz et al. (2020 White Paper on Recent Issues in Bioanalysis: BAV Guidance, CLSI H62, Biotherapeutics Stability, Parallelism Testing, CyTOF and Regulatory Feedback (Part 2A – Recommendations on Biotherapeutics Stability, PK LBA Regulated Bioanalysis, Biomarkers Assays, Cytometry Validation & Innovation Part 2B – Regulatory Agencies’ Inputs on Bioanalysis, Biomarkers, Immunogenicity, Gene & Cell Therapy and Vaccine), Bioanalysis, 2021, 13, 295-361).
Regarding claim 1, Yang teaches a concentration determination method (a protocol for the detection of anti-SARS-COV-2 spike antibody in human milk samples [title and TOC graph]), comprising:
diluting a sample fluid having a target material therein with a 1st dilution factor to an Nth dilution factor to respectively form a 1st sample to an Nth sample (Fig.1 shows sample plate layout with neat, 1:4, 1:16, 1:64, 1:256, 1:1024 and 1:4096; set up 4-fold titrations in separate round-bottom polypropylene dilution plates with samples and any relevant controls [Figure 1] at set concentrations in 1% BSA diluted in 1x PBS, pH 7.4 [step 10 on page 4]) wherein , wherein the Nth dilution factor is greater than the Nth-1 dilution factor (Fig.1 shows the Nth dilution factor is 4 times of the Nth-1 dilution factor);
providing a sensor array, wherein the sensor array is divided into a 1st assay to an Nth assay (see array of sensor wells in the plate as shown in Fig.1; each well is coated with SARS-CoV-2 spike protein [step 1 on page 3], and a sample with different titrations is added to wells in rows from A to G, respectively; the assays in wells of rows from A to G are deemed as the 1st to Nth assays);
respectively applying the 1st sample to the Nth sample onto the 1st assay to the Nth assay (Fig.1 shows respectively applying the 1st sample [Neat] to the Nth sample [1:4096] onto the wells of the 1st assay to the Nth assay);
performing a bio-sensing process on the 1st sample to the Nth sample to obtain a 1st measurement value to an Nth measurement value respectively for the 1st sample to the Nth sample through the 1st assay to the Nth assay (step 21 to read endpoint data from experimental plates at an absorbance of 450 nm on Bio Tek Powerwave TH plate reader [step 21 on page 5]; Fig.2 shows the obtained results for the 1st sample to the Nth sample through the 1st assay to the Nth assay);
comparing the 1st measurement value to the Nth measurement value with a threshold value to determine a threshold dilution factor (Fig.2A shows comparing the 1st measurement value to the Nth measurement value [see x-axis [Log]2 Milk titer] with a threshold value [dotted line in Fig.2A ; steps 5 and 6 in data analysis to determine the positive cutoff value on page 6] to determine a threshold dilution factor [determination of endpoint titer in step 7 of data analysis on page 6]), wherein the threshold dilution factor corresponds to a largest dilution factor that has a measurement value higher than the threshold value (this represents the dilution of the highest analyte that provides a reading above the cutoff chosen at an absorbance best fit for these data [step 7 on page 6]).
Yang is silent to the following limitations: (1) a bio-sensing integrated circuit having the sensor array; (2) performing the bio-sensing process on the 1st sample to the Nth sample “by the bio-sensing integrated circuit” to obtain the 1st measurement value to the Nth measurement value respectively for the 1st sample to the Nth sample through the 1st assay to the Nth assay; (3) converting the 1st measurement value to the Nth measurement value to digital signals through a Trans-impedance Amplifier (TIA) and an analog-to-digital converter (ADC); (4) comparing the digital signals, by a microcontroller unit (MCU), with a threshold value to determine a threshold dilution factor; and (5) calculating a concentration of the target material in the sample fluid based on the threshold dilution factor and a limit of detection of the bio-sensing integrated circuit.
Lim reviews emerging biosensors to detect severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) (title), and further teaches FET biosensor for detecting SARS-COV-2, wherein the FET biosensor consists of a semiconductor substrate with three terminals: (1) the source, (2) the drain and (3) reference or gate in contact with an electrolyte (see Fig..7A). The source and drain terminals are attached to the semiconducting substrate and a thin oxide layer (insulator) is deposited between these two terminals. Generally, biorecognition elements such as antibodies are immobilized on the oxide layer (sensor surface) to complete the biosensor construction. Fig.7B shows the sensing is based on a current change from the source to the drain electrode of the bioFET when analyte in the sample solution binds to the biorecognition element (see Fig.7B and caption of Fig.7B). Overall, the FET-based sensor provides fast detection and low LOD and does not require additional procedures for labelling during sample preparation. It is low cost, small in size and simple to operate (section 2.4 and Figs. 7-9).
Liu teaches a bio-sensing integrated circuit 170 in Fig.2 comprises an array of bioFETs 125 [para. 0049]. The sensory array comprises pixels arranged in an array (device region 126 includes an array of pixels 128, each pixel including one bioFET 125 [para. 0050]), and each bioFET corresponds to a pixel (each pixel including one bioFET 125 [para. 0050]). BioFETs 125 include source/drain regions 115 and channel regions 127 that are formed in semiconductor active layer 155. BioFETs 125 include fluid gates 117. Fluid gates 117 include a fluid gate dielectric layer 121 and a fluid interfacing surface 122. Fluid interfacing surface 122 is exposed for contacting with fluid. Fluid gates 117 are operative to modulate the source to drain conductivity of bioFET 125 when contacted by a fluid having a suitable composition or carrying specific analytes. Fluid interfacing surface 122 includes a coating of a selective binding agent 119. A selective binding agent 119 is a biological composition having the property of selectively binding with a particular analyte. If a sufficient concentration of the analyte is bound on fluid interfacing surface 122, the overall charge concentration at fluid interfacing surface 122 can become sufficient to modulate the source to drain conductivity of bioFETs 125. In some embodiments, the selective binding agent 119 includes an antibody [para. 0028-0030]. A fluid containment area 104 which can be a well disposed above each bioFET [para. 0018, Fig.1A], and Fig.1A shows the fluid interfacing surface 122 of each bioFET is disposed in the well corresponding to the bioFET.
Given the teachings of Yang regarding detection of anti-SARS-COV-2 spike antibody based on the antigen-antibody binding; the teachings of Lim regarding bioFET for detection of COVID-19 based on analyte binding to the biorecognition element immobilized on the sensor surface (see Fig.7); and the teachings of Liu regarding a bio-sensing integrated circuit comprising BioFET sensor array, wherein the sensory array comprises pixels arranged in an array, and each BioFET corresponds to a pixel, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method in Yang to: (1) provide a bio-sensing integrated circuit having a BioFET sensor array, wherein the BioFET sensory array comprises pixels arranged in an array, and each BioFET corresponds to a pixel and has a well for holding a sample fluid located directly above the BioFET; (2) immobilize the biorecognition element on the sensor surface of each BioFET; and (3) respectively place the 1st to the Nth samples with the 1st dilution factor to the Nth dilution factor to the wells of the bioFET sensor array to perform the bio-sensing process on the 1st sample to the Nth sample by the bio-sensing integrated circuit to obtain the 1st measurement value to the Nth measurement value respectively for the 1st sample to the Nth sample through the 1st assay to the Nth assay, wherein each measurement value is the current between the source and the drain of each bioFET, as taught combined Lim and Liu, since the BioFET-based sensor for COVID would provide fast detection and low LOD and would be low cost, small in size and simple to operate (section 2.4.2 in Lim), and the BioFET sensor array would allow for multiplexed detection of multiple analytes [para. 0013 in Liu].
With the above modification, the wells of the plate holding the samples with different dilution factors in Yang are modified to the wells corresponding to the BioFET sensor array (one sample well located directly above a BioFET is shown in Fig.1A in Liu, and Fig.7A in Lim), and the biorecognition element immobilized on each well in Yang is modified to the biorecognition element immobilized on the sensor surface of each BioFET (see Fig.7A in Lim and the selective binding agent 119 in Figs. 1A and 1B in Liu). The 1st to the Nth assays in the wells of Yang are modified to the 1st to the Nth assays occurring in the wells of the BioFET sensor array, and the 1st to the Nth samples of different dilution factors are introduced to the wells of the BioFET sensor array. The analyte of each sample is detected based on the current from the source to the drain electrode of each BioFET, as shown in Fig.7B in Lim.
Modified Yang is silent to the following limitations: (3) converting the 1st measurement value to the Nth measurement value to digital signals through a Trans-impedance Amplifier (TIA) and an analog-to-digital converter (ADC); (4) comparing the digital signals, by a microcontroller unit (MCU), with a threshold value to determine a threshold dilution factor; and (5) calculating a concentration of the target material in the sample fluid based on the threshold dilution factor and a limit of detection of the bio-sensing integrated circuit.
Huang teaches a BioFET [para. 0027] comprising an array of FET sensors to individually detect binding events at the surface of the FET Sensor sensing layer [para. 0052; Figs. 3-4; sensor array 704 in Fig.7]. When measuring signals (such as Ids) received from a given FET Sensor or a set of FET Sensors in sensor array 704, sensor array circuitry 714 may receive the measured signals and pass them through a trans-impedance amplifier, i.e., a current-to-voltage converter, followed by one or more additional amplification stages, low pass filters, and ultimately an ADC, before the resulting signal is output to an I/O pad 716 [para. 0084]. Fig. 12 shows cartridge 1000 coupled to an analyzer 1200 for performing the biological sensing. analyzer 1200 also includes a processor 1212 which may be any type of central processing unit (CPU) or microcontroller and may be programmable by a user to perform certain functions related to the operation of analyzer 1200. Processor 1212 may be configured to analyze signals received from sensing electronics 1210 to determine a concentration level of a given analyte from the sample in cartridge 1000. Data related to the determined concentration levels may be stored in a memory of analyzer 1200 [para. 0108]. Thus, Huang teaches: (3) converting the 1st measurement value to the Nth measurement value to digital signals through a Trans-impedance Amplifier and an analog-to-digital converter (measuring signals [such as Ids] received from a given FET Sensor or a set of FET Sensors in sensor array 704, sensor array circuitry 714 may receive the measured signals and pass them through a trans-impedance amplifier, and ultimately an ADC [para. 0084]); and a microcontroller unit (a processor 1212) configured to analyze signals received from sensing electronics to determine a concentration level of a given analyte from the sample [para. 0108]. The signals analyzed by the processor must be digital signals in order to determine a concentration level of a given analyte from the sample.
As outlined in the rejection above, Yang teaches comparing the 1st measurement value to the Nth measurement value with a threshold value to determine a threshold dilution factor. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method and bio-sensing integrated circuit in modified Yang to provide the step of: (3) converting the 1st measurement value to the Nth measurement value to digital signals through a Trans-impedance Amplifier (TIA) and an analog-to-digital converter (ADC), as taught by Huang; and further modify the step of comparing the measurement values with a threshold value to determine a threshold dilution factor to (4) compare the digital signals, by a microcontroller unit (a processor), with a threshold value to determine a threshold dilution factor, as taught by combined Yang and Huang, since it would enhance the signal strength to improve the detection ability of the device [para. 0065 in Huang], and determine a concentration level of analyte in the sample [para. 0108 in Huang].
Modified Yang is silent to the following limitations: (5) calculating a concentration of the target material in the sample fluid based on the threshold dilution factor and a limit of detection of the bio-sensing integrated circuit.
Spitz teaches in cases that it may not be possible to utilize samples with concentrations at or near the Cmax. To perform the analysis, samples should be diluted (following the dilution procedure performed during testing) so that as many dilutions as possible fall within the reportable range of the assay (Proposed Procedure on page 317). The highest reported result would be “x” concentration (highest dilution factor times upper limit of quantitation) (Acceptance Criteria on page 318). Thus, Spitz teaches calculating a concentration of an analyte in a sample fluid based on the threshold dilution factor and a limit of detection of the sensor in a dilution assay.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method in modified Yang by adding the step of calculating a concentration of the target material in the sample fluid by the threshold dilution factor times a limit of detection, as taught by Spitz, since it would estimate the concentration of the analyte/target material in the sample (Acceptance Criteria on page 318 in Spitz). Furthermore, one skilled in the art could have applied the same technique of estimating/calculating the analyte concentration by using the highest dilution factor times the limit of quantitation/detection as taught by Spitz
in the same way to calculate the analyte concentration in the dilution assay of modified Yang, yielding predictable results (MPEP 2143(I)(D)).
Regarding claim 2, modified Yang teaches the method of claim 1, wherein the concentration of the target material in the sample fluid is a product of the threshold dilution factor and the limit of detection of the bio-sensing integrated circuit (as outlined in the rejection of claim 1 above, the concentration of the target material in the sample fluid is a product of the threshold dilution factor and the limit of detection of the bio-sensing integrated circuit [highest dilution factor times upper limit of quantitation, Acceptance Criteria on page 318 in Spitz]).
Regarding claim 3, modified Yang teaches the method of claim 1, wherein the bio-sensing integrated circuit comprises Biosensor Field-Effect Transistors (BioFETs), the sensory array comprises pixels arranged in an array, and each BioFET corresponds to a pixel (as outlined in the rejection of claim 1 above, the bio-sensing integrated circuit comprises an array of BioFETs [Fig.2 and para. 0049 in Liu], the sensory array comprises pixels arranged in an array, and each BioFET corresponds to a pixel [device region 126 includes an array of pixels 128, each pixel including one BioFET 125; Fig.2 and para. 0050 in Liu]).
Regarding claim 4, modified Yang teaches the method of claim 3, wherein each BioFET comprises a drain region and a source region (see Source and Drain in Fig.7A of Lim; In the alternative, BioFETs include source/drain regions 115 [para. 0028; Figs. 1A and 1B in Liu]), and the 1st measurement value to the Nth measurement value are currents between the source region and the drain region (as outlined in the rejection of claim 1 above, the detection of the analyte in each BioFET is based on a current change between the source and the drain [see caption of Fig. 7B in Lim], thus the 1st measurement value to the Nth measurement value of the BioFET sensor array are currents between the source region and the drain region).
Regarding claim 5, modified Yang teaches the method of claim 4, and as outlined in the rejection of claim 1 above, the current between the source region and the drain region of each pixel of the sensor array is measured to detect the analyte (see Fig.7 in Lim).
Yang is silent to wherein the first measurement value is an average value of the currents between the source region and the drain region of each pixel in the 1st assay of the sensor array.
Yang does teach experiments were performed in duplicate and repeated twice. Mean with SEM is shown. Dotted lines indicate positive cutoff value (mean OD or endpoint titer of negative control milk samples + 2*SD) (caption of Fig.2B).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to provide two bioFETs for each assay of the first to the Nth assays to duplicate the measurements for each assay and use the mean value of the measurement current values of the two bioFETs as the measurement value of each assay, as taught by combined Yang and Lim, since Yang teaches experiments were performed in duplicate and repeated twice and the use of mean value to represent the measurement value (Fig.2B). One of ordinary skill in the art would recognize that duplicating bioFETs for each assay to duplicate measurements and using the average value to represent the measurement value of each assay would improve accuracy and reliability of the measurements.
Regarding claim 6, modified Yang teaches the method of claim 3, wherein the bio-sensing integrated circuit comprises sensing wells located directly above each BioFET (Fig.1A of Liu shows the bio-sensing integrated circuit comprises sensing wells [fluid containment areas 104 as sensing wells, para. 0018 in Liu] located directly above each BioFET), and each sensing well corresponds to a pixel (each sensing well is located directly above each BioFET as shown in Fig.1A of Liu, and each pixel has one BioFET as shown in Fig.2 of Liu, thus, each sensing well corresponds to a pixel).
Regarding claim 7, modified Yang teaches the method of claim 6, wherein during the bio-sensing process, a probe (SARS-CoV-2 spike protein coated on the plates in Step 1 of Yang; or biorecognition element as shown in Fig.7 of Lim; or the selective binding agent 119 in Fig.1A of Liu) is provided in one of the sensing wells (as outlined in the rejection of claim 1 above, each well of Yang is modified to the well located directly above each BioFET; also see Fig.7A in Lim and Fig.1A in Liu), and the target material is bind to the probe (Yang teaches anti-SARS-COV-2 spike antibody binds to the probe [Step 1 on page 3]; In the alternative, Lim teaches analyte is bind to the biorecognition element as shown in Fig.7A; and Liu teaches the selective binding agent 119 is a biological composition having the property of selectively binding with a particular analyte [para. 0030]).
Regarding claim 8, modified Yang teaches the method of claim 1, wherein the target material comprises SAS-CoV-2 Antigen (Lim teaches FET biosensor for COVID-19 for detecting SAS-CoV-2 Antigen by immobilizing SAS-CoV-2 spike protein antibodies as the biorecognition element [section 2.4.1]) or SARS-CoV-2 Antibody (Yang teaches the target material comprises SARS-CoV-2 antibody by using SARS-CoV-2 antigen as the biorecognition element [abstract; step 1 coat plates with SARS-CoV-2 spike protein on page 3]).
Regarding claim 9, Yang teaches a concentration determination method (a protocol for the detection of anti-SARS-COV-2 spike antibody in human milk samples [title and TOC graph]), comprising:
diluting a sample fluid having a target material therein with a 1st dilution factor to an Nth dilution factor to respectively form a 1st sample to an Nth sample (Fig.1 shows sample plate layout with neat, 1:4, 1:16, 1:64, 1:256, 1:1024 and 1:4096; set up 4-fold titrations in separate round-bottom polypropylene dilution plates with samples and any relevant controls [Figure 1] at set concentrations in 1% BSA diluted in 1x PBS, pH 7.4 [step 10 on page 4]), wherein the Nth dilution factor is greater than the Nth-1 dilution factor (Fig.1 shows the Nth dilution factor is 4 times of the Nth-1 dilution factor);
respectively applying the 1st sample to the Nth sample onto a 1st bio-sensing well to a Nth bio-sensing well (Fig.1 shows respectively applying the 1st sample to the Nth sample into neat, 1:4, 1:16, 1:64, 1:256, 1:1024 and 1:4096 wells);
performing a bio-sensing process on the 1st sample to the Nth sample to obtain a 1st measurement value to an Nth measurement value respectively for the 1st sample to the Nth sample (step 21 to read endpoint data from experimental plates at an absorbance of 450 nm on Bio Tek Powerwave TH plate reader [step 21 on page 5]; Fig.2 shows the obtained results for the 1st sample to the Nth sample);
comparing the 1st measurement value to the Nth measurement value with a threshold value to determine a threshold dilution factor (Fig.2A shows comparing the 1st measurement value to the Nth measurement value [see x-axis [Log]2 Milk titer] with a threshold value [dotted line in Fig.2A ; steps 5 and 6 in data analysis to determine the positive cutoff value on page 6] to determine a threshold dilution factor [determination of endpoint titer in step 7 of data analysis on page 6]), wherein the threshold dilution factor corresponds to a largest dilution factor that has a measurement value higher than the threshold value (this represents the dilution of the highest analyte that provides a reading above the cutoff chosen at an absorbance best fit for these data [step 7 on page 6]).
Yang is silent to the following limitations: (1) providing a 1st bio-sensing integrated circuit to an Nth bio-sensing integrated circuit, wherein the 1st bio-sensing integrated circuit to the Nth bio-sensing integrated circuit respectively comprise a 1st sensory array to an Nth sensory array; (2) respectively applying the 1st sample to the Nth sample onto the 1st bio-sensing integrated circuit to the Nth bio-sensing integrated circuit; (3) performing the bio-sensing process on the 1st sample to the Nth sample “by the 1st sensory array to the Nth sensory array of the 1st bio-sensing integrated circuit to the Nth bio-sensing integrated circuit” to obtain the 1st measurement value to the Nth measurement value respectively for the 1st sample to the Nth sample; (4) converting the 1st measurement value to the Nth measurement value to digital signals through a Trans-impedance Amplifier (TIA) and an analog-to-digital converter (ADC); (5) comparing the digital signals, by a microcontroller unit (MCU), with a threshold value to determine a threshold dilution factor; and (6) calculating a concentration of the target material in the sample fluid based on the threshold dilution factor and limit of detections of the 1st bio-sensing integrated circuit to the Nth bio-sensing integrated circuit.
Lim reviews emerging biosensors to detect severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) (title), and further teaches FET biosensor for detecting SARS-COV-2, wherein the FET biosensor consists of a semiconductor substrate with three terminals: (1) the source, (2) the drain and (3) reference or gate in contact with an electrolyte (see Fig..7A). The source and drain terminals are attached to the semiconducting substrate and a thin oxide layer (insulator) is deposited between these two terminals. Generally, biorecognition elements such as antibodies are immobilized on the oxide layer (sensor surface) to complete the biosensor construction. Fig.7B shows the sensing is based on a current change from the source to the drain electrode of the bioFET when analyte in the sample solution binds to the biorecognition element (see Fig.7B and caption of Fig.7B). Overall, the FET-based sensor provides fast detection and low LOD and does not require additional procedures for labelling during sample preparation. It is low cost, small in size and simple to operate (section 2.4 and Figs. 7-9).
Liu teaches a bio-sensing integrated circuit 170 in Fig.2 comprises an array of bioFETs 125 [para. 0049]. The sensory array comprises pixels arranged in an array (device region 126 includes an array of pixels 128, each pixel including one bioFET 125 [para. 0050]), and each bioFET corresponds to a pixel (each pixel including one bioFET 125 [para. 0050]). BioFETs 125 include source/drain regions 115 and channel regions 127 that are formed in semiconductor active layer 155. BioFETs 125 include fluid gates 117. Fluid gates 117 include a fluid gate dielectric layer 121 and a fluid interfacing surface 122. Fluid interfacing surface 122 is exposed for contacting with fluid. Fluid gates 117 are operative to modulate the source to drain conductivity of bioFET 125 when contacted by a fluid having a suitable composition or carrying specific analytes. Fluid interfacing surface 122 includes a coating of a selective binding agent 119. A selective binding agent 119 is a biological composition having the property of selectively binding with a particular analyte. If a sufficient concentration of the analyte is bound on fluid interfacing surface 122, the overall charge concentration at fluid interfacing surface 122 can become sufficient to modulate the source to drain conductivity of bioFETs 125. In some embodiments, the selective binding agent 119 includes an antibody [para. 0028-0030]. A fluid containment area 104 which can be a well disposed above each bioFET [para. 0018, Fig.1A], and Fig.1A shows the fluid interfacing surface 122 of each bioFET is disposed in the well corresponding to the bioFET.
Given the teachings of Yang regarding detection of anti-SARS-COV-2 spike antibody of the 1st sample to the Nth sample based on the antigen-antibody binding (Step 1 on page 3); the teachings of Lim regarding BioFET for detection of COVID-19 based on analyte binding to the biorecognition element immobilized on the sensor surface (see Fig.7); and the teachings of Liu regarding a bio-sensing integrated circuit comprising BioFET sensor array, wherein the sensory array comprises pixels arranged in an array, and each BioFET corresponds to a pixel, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method in Yang to: (1) provide a bio-sensing integrated circuit having a BioFET sensor array for multiplexed detection of the 1st sample to the Nth sample, wherein the BioFET sensory array comprises pixels arranged in an array, and each BioFET corresponds to a pixel and has a well located directly above the BioFET for holding one of the 1st sample to the Nth sample; (2) immobilize the biorecognition element on the sensor surface of each bioFET; and (3) respectively apply the 1st to the Nth samples to the wells corresponding to the bioFET sensor array to perform the bio-sensing process on the 1st sample to the Nth sample by the bio-sensing integrated circuit to obtain a 1st measurement value to an Nth measurement value respectively for the 1st sample to the Nth sample, wherein each measurement value is the current between the source and the drain of each bioFET, as taught combined Lim and Liu, since the BioFET-based sensor for COVID would provide fast detection and low LOD and would be low cost, small in size and simple to operate (section 2.4.2 in Lim), and the bioFET sensor array would allow for multiplexed detection of multiple analytes [para. 0013 in Liu].
With the above modification, the wells of the plate holding the 1st sample to the Nth sample with different dilution factors in Yang are modified to the wells located directly above the BioFET sensor array (note that one sample well is located directly above each BioFET as shown in Fig.1A of Liu and Fig.7A in Lim) for holding the 1st sample to the Nth sample, and the biorecognition element immobilized on each well in Yang is modified to the biorecognition element immobilized on the sensor surface of each BioFET (see Fig.7A in Lim and the selective binding agent 119 in Figs. 1A and 1B in Liu). The BioFET(s) of the BioFET sensor array for the 1st sample to the Nth sample is, respectively, deemed as the 1st bio-sensing integrated circuit to the Nth bio-sensing integrated circuit. The first to the Nth samples of different dilution factors are introduced to the wells of the bioFETs of the 1st bio-sensing integrated circuit to the Nth bio-sensing integrated circuit. The analyte in each sample solution is detected by each BioFET based on the current from the source to the drain electrode of the BioFET, as shown in Fig.7B in Lim.
Yang Further teaches experiments were performed in duplicate and repeated twice. Mean with SEM is shown. Dotted lines indicate positive cutoff value (mean OD or endpoint titer of negative control milk samples + 2*SD) (caption of Fig.2B).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to provide two bioFETs for each bio-sensing integrated circuit of the first to the Nth bio-sensing integrated circuits to duplicate the measurements for each bio-sensing integrated circuit and use the mean value of the measurement current values of the two bioFETs as the measurement value of each bio-sensing integrated circuit, as taught by combined Yang and Lim, since Yang teaches experiments were performed in duplicate and repeated twice and the use of mean value to represent the measurement value (Fig.2B). One of ordinary skill in the art would recognize that two bioFETs for each bio-sensing integrated circuit to duplicate measurements and using the average value to represent the measurement value of each bio-sensing integrated circuit would improve accuracy and reliability of the measurements.
With the above modifications, modified Yang teaches: (1) providing a 1st bio-sensing integrated circuit to an Nth bio-sensing integrated circuit, wherein the 1st bio-sensing integrated circuit to the Nth bio-sensing integrated circuit respectively comprise a 1st sensory array to an Nth sensory array; (2) respectively applying the 1st sample to the Nth sample onto the 1st bio-sensing integrated circuit to the Nth bio-sensing integrated circuit; (3) performing the bio-sensing process on the 1st sample to the Nth sample “by the 1st sensory array to the Nth sensory array of the 1st bio-sensing integrated circuit to the Nth bio-sensing integrated circuit” to obtain the 1st measurement value to the Nth measurement value respectively for the 1st sample to the Nth sample.
Modified Yang is silent to the following limitations: (4) converting the 1st measurement value to the Nth measurement value to digital signals through a Trans-impedance Amplifier (TIA) and an analog-to-digital converter (ADC); (5) comparing the digital signals, by a microcontroller unit (MCU), with a threshold value to determine a threshold dilution factor; and (6) calculating a concentration of the target material in the sample fluid based on the threshold dilution factor and limit of detections of the 1st bio-sensing integrated circuit to the Nth bio-sensing integrated circuit.
Huang teaches a BioFET [para. 0027] comprising an array of FET sensors to individually detect binding events at the surface of the FET Sensor sensing layer [para. 0052; Figs. 3-4; sensor array 704 in Fig.7]. When measuring signals (such as Ids) received from a given FET Sensor or a set of FET Sensors in sensor array 704, sensor array circuitry 714 may receive the measured signals and pass them through a trans-impedance amplifier, i.e., a current-to-voltage converter, followed by one or more additional amplification stages, low pass filters, and ultimately an ADC, before the resulting signal is output to an I/O pad 716 [para. 0084]. Fig. 12 shows cartridge 1000 coupled to an analyzer 1200 for performing the biological sensing. analyzer 1200 also includes a processor 1212 which may be any type of central processing unit (CPU) or microcontroller and may be programmable by a user to perform certain functions related to the operation of analyzer 1200. Processor 1212 may be configured to analyze signals received from sensing electronics 1210 to determine a concentration level of a given analyte from the sample in cartridge 1000. Data related to the determined concentration levels may be stored in a memory of analyzer 1200 [para. 0108]. Thus, Huang teaches: (4) converting the 1st measurement value to the Nth measurement value to digital signals through a Trans-impedance Amplifier and an analog-to-digital converter (measuring signals [such as Ids] received from a given FET Sensor or a set of FET Sensors in sensor array 704, sensor array circuitry 714 may receive the measured signals and pass them through a trans-impedance amplifier, and ultimately an ADC [para. 0084]); and a microcontroller unit (a processor 1212) configured to analyze signals received from sensing electronics to determine a concentration level of a given analyte from the sample [para. 0108]. The signals analyzed by the processor must be digital signals in order to determine a concentration level of a given analyte from the sample.
As outlined in the rejection above, Yang teaches comparing the 1st measurement value to the Nth measurement value with a threshold value to determine a threshold dilution factor. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method and bio-sensing integrated circuits in modified Yang to provide the step of: (4) converting the 1st measurement value to the Nth measurement value to digital signals through a Trans-impedance Amplifier (TIA) and an analog-to-digital converter (ADC), as taught by Huang; and further modify the step of comparing the measurement values with a threshold value to determine a threshold dilution factor to (5) compare the digital signals, by a microcontroller unit (a processor), with a threshold value to determine a threshold dilution factor, as taught by combined Yang and Huang, since it would enhance the signal strength to improve the detection ability of the device [para. 0065 in Huang], and determine a concentration level of analyte in the sample [para. 0108 in Huang].
Modified Yang is silent to the following limitations: (6) calculating a concentration of the target material in the sample fluid based on the threshold dilution factor and limit of detections of the 1st bio-sensing integrated circuit to the Nth bio-sensing integrated circuit.
Spitz teaches in cases that it may not be possible to utilize samples with concentrations at or near the Cmax. To perform the analysis, samples should be diluted (following the dilution procedure performed during testing) so that as many dilutions as possible fall within the reportable range of the assay (Proposed Procedure on page 317). The highest reported result would be “x” concentration (highest dilution factor times upper limit of quantitation) (Acceptance Criteria on page 318). Thus, Spitz teaches calculating a concentration of an analyte in a sample fluid based on the threshold dilution factor and a limit of detection of the sensor.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method in modified Yang by adding the step of calculating a concentration of the target material in the sample fluid based on the threshold dilution factor and limit of detections of the sensor (corresponding to the 1st bio-sensing integrated circuit to the Nth bio-sensing integrated circuit which are the BioFET sensor array for the first to Nth samples), as taught by Spitz, since it would estimate the concentration of the analyte/target material in the sample (Acceptance Criteria on page 318 in Spitz). Furthermore, one skilled in the art could have applied the same technique of estimating/calculating the analyte concentration by using the highest dilution factor times the limit of quantitation/detection of the sensor as taught by Spitz in the same way to calculate the analyte concentration in the dilution assay of modified Yang, yielding predictable results (MPEP 2143(I)(D)).
Regarding claim 10, modified Yang teaches the method of claim 9, wherein the limitation of detections of the 1st bio-sensing integrated circuit to the Nth bio-sensing integrated circuit are identical (since the BioFETs of the BioFET sensor array for the 1st sample to the Nth sample are identical, the limitation of detections of the 1st bio-sensing integrated circuit to the Nth bio-sensing integrated circuit are identical).
Regarding claim 11, modified Yang teaches the method of claim 10, wherein the concentration of the target material in the sample fluid is a product of the threshold dilution factor and the limit of detections (as outlined in the rejection of claim 9 above, the concentration of the target material in the sample fluid is a product of the threshold dilution factor and the limit of detections [highest dilution factor times upper limit of quantitation, Acceptance Criteria on page 318 in Spitz]).
Regarding claim 12, modified Yang teaches the method of claim 9, wherein each of the 1st bio-sensing integrated circuit to the Nth bio-sensing integrated circuit respectively comprises Biosensor Field-Effect Transistors (BioFETs) (as outlined in the rejection of claim 9 above, each of the 1st bio-sensing integrated circuit to the Nth bio-sensing integrated circuit respectively comprises two BioFETs to duplicate experiments), each BioFET comprises a drain region and a source region (see Source and Drain in Fig.7A of Lim; or BioFETs include source/drain regions 115 [para. 0028; Figs. 1A and 1B in Liu]), and the 1st measurement value to the Nth measurement value are currents between the source region and the drain region of each BioFET (as outlined in the rejection of claim 9 above, the detection of the analyte by each BioFET is based on a current change between the source and the drain [see caption of Fig. 7B in Lim], thus the 1st measurement value to the Nth measurement value of the BioFET sensor array are currents between the source region and the drain region of each BioFET).
Regarding claim 13, modified Yang teaches the method of claim 12, wherein the first measurement value is an average value of the currents between the source region and the drain region of each BioFET in the 1st bio-sensing integrated circuit (as outlined in the rejection of claim 9 above, the 1st bio-sensing integrated circuit comprises two BioFETs to duplicate the experiments and use the mean value of the measured current values as the 1st measurement value).
Regarding claim 14, modified Yang teaches the method of claim 9, wherein the 1st bio-sensing integrated circuit to the Nth bio-sensing integrated circuit are placed on a same cartridge (Liu teaches wherein the 1st bio-sensing integrated circuit to the Nth bio-sensing integrated circuit [the BioFET sensor array for the first sample to the Nth sample] are placed on a same cartridge [the array of bioFETs 125 are placed on a same circuit 170; Fig.2 and para. 0049]).
Regarding claim 15, modified Yang teaches the method of claim 9, wherein the target material comprises SAS-CoV-2 Antigen (Lim teaches FET biosensor for COVID-19 for detecting SAS-CoV-2 Antigen by immobilizing SAS-CoV-2 spike protein antibodies as the biorecognition element [section 2.4.1]) or SARS-CoV-2 Antibody (Yang teaches the target material comprises SARS-CoV-2 antibody by using SARS-CoV-2 antigen as the biorecognition element [abstract; step 1 coat plates with SARS-CoV-2 spike protein on page 3]).
Regarding claim 21, Yang teaches a concentration determination method (a protocol for the detection of anti-SARS-COV-2 spike antibody in human milk samples [title and TOC graph]), comprising:
providing a 1st sample to an Nth sample respectively having a concentration of 1/N1 to 1/Nth of a sample fluid, wherein the concentration decreases from the 1st sample to the Nth sample (Fig.1 shows sample plate layout with neat, 1:4, 1:16, 1:64, 1:256, 1:1024 and 1:4096; set up 4-fold titrations in separate round-bottom polypropylene dilution plates with samples and any relevant controls [Figure 1] at set concentrations in 1% BSA diluted in 1x PBS, pH 7.4 [step 10 on page 4]; Samples of neat, 1:4, 1:16, 1:64, 1:256, 1:1024 and 1:4096 are deemed as the 1st sample to an Nth sample respectively having a concentration of 1/N1 to 1/Nth of a sample fluid, wherein the concentration decreases from the 1st sample to the Nth sample due to the sequential 4-fold titration);
respectively applying the 1st sample to the Nth sample onto a 1st assay to an Nth assay (Fig.1 shows respectively applying the 1st sample to the Nth sample onto wells of row A to row G, wherein each well is coated with a biorecognition element [SARS-CoV-2 Spike protein in Step 1 on page 3] to bind the target material of anti-SARS-COV-2 spike antibody in each sample. The assays in wells of rows A to G are deemed as the 1st assay to the Nth assay);
performing a bio-sensing process on the 1st sample to the Nth sample to obtain a 1st measurement value to an Nth measurement value respectively for the 1st sample to the Nth sample (step 21 to read endpoint data from experimental plates at an absorbance of 450 nm on Bio Tek Powerwave TH plate reader [step 21 on page 5]; Fig.2 shows the obtained results for the 1st sample to the Nth sample);
comparing the 1st measurement value to the Nih measurement value with a threshold current to determine a threshold dilution factor (Fig.2A shows comparing the 1st measurement value to the Nth measurement value [see x-axis [Log]2 Milk titer] with a threshold value [dotted line in Fig.2A ; steps 5 and 6 in data analysis to determine the positive cutoff value on page 6] to determine a threshold dilution factor [determination of endpoint titer in step 7 of data analysis on page 6]), wherein the threshold dilution factor corresponds to a largest dilution factor that has a measurement value higher than the threshold value (this represents the dilution of the highest analyte that provides a reading above the cutoff chosen at an absorbance best fit for these data [step 7 on page 6]).
Yang is silent to the following limitations: (1) performing the bio-sensing process on the 1st sample to the Nth sample “by a bio- sensing integrated circuit having the 1st assay to the Nth assay” to obtain the 1st measurement value to the Nth measurement value; (2) converting the 1st measurement value to the Nth measurement value to digital signals through a Trans-impedance Amplifier (TIA) and an analog-to-digital converter (ADC); (3) comparing the digital signals, by a microcontroller unit (MCU), with a threshold current to determine a threshold dilution factor; and (4) calculating a concentration of the target material in the sample fluid based on the threshold dilution factor and a limit of detection of the bio-sensing integrated circuit.
Lim reviews emerging biosensors to detect severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) (title), and further teaches FET biosensor for detecting SARS-COV-2, wherein the FET biosensor consists of a semiconductor substrate with three terminals: (1) the source, (2) the drain and (3) reference or gate in contact with an electrolyte (see Fig..7A). The source and drain terminals are attached to the semiconducting substrate and a thin oxide layer (insulator) is deposited between these two terminals. Generally, biorecognition elements such as antibodies are immobilized on the oxide layer (sensor surface) to complete the biosensor construction. Fig.7B shows the sensing is based on a current change from the source to the drain electrode of the bioFET when analyte in the sample solution binds to the biorecognition element (see Fig.7B and caption of Fig.7B). Overall, the FET-based sensor provides fast detection and low LOD and does not require additional procedures for labelling during sample preparation. It is low cost, small in size and simple to operate (section 2.4 and Figs. 7-9).
Liu teaches a bio-sensing integrated circuit 170 in Fig.2 comprises an array of bioFETs 125 [para. 0049]. The sensory array comprises pixels arranged in an array (device region 126 includes an array of pixels 128, each pixel including one bioFET 125 [para. 0050]), and each bioFET corresponds to a pixel (each pixel including one bioFET 125 [para. 0050]). BioFETs 125 include source/drain regions 115 and channel regions 127 that are formed in semiconductor active layer 155. BioFETs 125 include fluid gates 117. Fluid gates 117 include a fluid gate dielectric layer 121 and a fluid interfacing surface 122. Fluid interfacing surface 122 is exposed for contacting with fluid. Fluid gates 117 are operative to modulate the source to drain conductivity of bioFET 125 when contacted by a fluid having a suitable composition or carrying specific analytes. Fluid interfacing surface 122 includes a coating of a selective binding agent 119. A selective binding agent 119 is a biological composition having the property of selectively binding with a particular analyte. If a sufficient concentration of the analyte is bound on fluid interfacing surface 122, the overall charge concentration at fluid interfacing surface 122 can become sufficient to modulate the source to drain conductivity of bioFETs 125. In some embodiments, the selective binding agent 119 includes an antibody [para. 0028-0030]. A fluid containment area 104 which can be a well disposed above each bioFET [para. 0018, Fig.1A], and Fig.1A shows the fluid interfacing surface 122 of each bioFET is disposed in the well corresponding to the bioFET.
Given the teachings of Yang regarding detection of anti-SARS-COV-2 spike antibody based on the antigen-antibody binding; the teachings of Lim regarding BioFET for detection of COVID-19 based on analyte binding to the biorecognition element immobilized on the sensor surface (see Fig.7); and the teachings of Liu regarding a bio-sensing integrated circuit comprising BioFET sensor array, wherein the sensory array comprises pixels arranged in an array, and each pixel has one BioFET, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method in Yang to: (1) provide a bio-sensing integrated circuit having a BioFET sensor array of a 1st assay to an Nth assay for multiplexed detection of the 1st sample to the Nth sample, respectively, wherein the BioFET sensor array comprises pixels arranged in an array, and each pixel comprising one BioFET which has a well located directly above the BioFET for holding the respective sample fluid; (2) immobilize the biorecognition element on the sensor surface of each bioFET; and (3) respectively apply the 1st to the Nth samples to the wells of the bioFET sensor array to perform the bio-sensing process on the 1st sample to the Nth sample by the bio-sensing integrated circuit having the 1st assay to the Nth assay to obtain the 1st measurement value to the Nth measurement value respectively for the 1st sample to the Nth sample, wherein each measurement value is the current between the source and the drain of each bioFET, as taught combined Lim and Liu, since the bioFET-based sensor for COVID would provide fast detection and low LOD and would be low cost, small in size and simple to operate (section 2.4.2 in Lim), and the bioFET sensor array would allow for multiplexed detection of multiple analytes [para. 0013 in Liu].
With the above modification, the wells of the plate for holding the 1st to the Nth samples with different dilution factors in Yang are modified to the wells of the BioFET sensor array (note that one sample well located directly above one BioFET is shown in Fig.1A of Liu and Fig.7A in Lim), and the biorecognition element immobilized on each well in Yang is modified to the biorecognition element immobilized on the sensor surface of each BioFET (see Fig.7A in Lim and the selective binding agent 119 in Figs. 1A and 1B in Liu). The 1st to the Nth assays in the wells of Yang are modified to the 1st to the Nth assays occurring in the wells of the BioFET sensor array, and the 1st to the Nth samples of different dilution factors are introduced to the wells of the BioFET sensor array. The analyte of each sample solution is detected based on the current from the source to the drain electrode of each bioFET, as shown in Fig.7B in Lim.
Modified Yang is silent to the following limitations: (2) converting the 1st measurement value to the Nth measurement value to digital signals through a Trans-impedance Amplifier (TIA) and an analog-to-digital converter (ADC); (3) comparing the digital signals, by a microcontroller unit (MCU), with a threshold current to determine a threshold dilution factor; and (4) calculating a concentration of the target material in the sample fluid based on the threshold dilution factor and a limit of detection of the bio-sensing integrated circuit.
Huang teaches a BioFET [para. 0027] comprising an array of FET sensors to individually detect binding events at the surface of the FET Sensor sensing layer [para. 0052; Figs. 3-4; sensor array 704 in Fig.7]. When measuring signals (such as Ids) received from a given FET Sensor or a set of FET Sensors in sensor array 704, sensor array circuitry 714 may receive the measured signals and pass them through a trans-impedance amplifier, i.e., a current-to-voltage converter, followed by one or more additional amplification stages, low pass filters, and ultimately an ADC, before the resulting signal is output to an I/O pad 716 [para. 0084]. Fig. 12 shows cartridge 1000 coupled to an analyzer 1200 for performing the biological sensing. analyzer 1200 also includes a processor 1212 which may be any type of central processing unit (CPU) or microcontroller and may be programmable by a user to perform certain functions related to the operation of analyzer 1200. Processor 1212 may be configured to analyze signals received from sensing electronics 1210 to determine a concentration level of a given analyte from the sample in cartridge 1000. Data related to the determined concentration levels may be stored in a memory of analyzer 1200 [para. 0108]. Thus, Huang teaches: (2) converting the 1st measurement value to the Nth measurement value to digital signals through a Trans-impedance Amplifier and an analog-to-digital converter (measuring signals [such as Ids] received from a given FET Sensor or a set of FET Sensors in sensor array 704, sensor array circuitry 714 may receive the measured signals and pass them through a trans-impedance amplifier, and ultimately an ADC [para. 0084]); and a microcontroller unit (a processor 1212) configured to analyze signals received from sensing electronics to determine a concentration level of a given analyte from the sample [para. 0108]. The signals analyzed by the processor must be digital signals in order to determine a concentration level of a given analyte from the sample.
As outlined in the rejection above, Yang teaches comparing the 1st measurement value to the Nth measurement value with a threshold value to determine a threshold dilution factor. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method and bio-sensing integrated circuit in modified Yang to provide the step of: (2) converting the 1st measurement value to the Nth measurement value to digital signals through a Trans-impedance Amplifier (TIA) and an analog-to-digital converter (ADC), as taught by Huang; and further modify the step of comparing the measurement values with a threshold value to determine a threshold dilution factor to (3) compare the digital signals, by a microcontroller unit (a processor), with a threshold value to determine a threshold dilution factor, as taught by combined Yang and Huang, since it would enhance the signal strength to improve the detection ability of the device [para. 0065 in Huang], and determine a concentration level of analyte in the sample [para. 0108 in Huang].
Modified Yang is silent to the following limitations: (4) calculating a concentration of the target material in the sample fluid based on the threshold dilution factor and a limit of detection of the bio-sensing integrated circuit.
Spitz teaches in cases that it may not be possible to utilize samples with concentrations at or near the Cmax. To perform the analysis, samples should be diluted (following the dilution procedure performed during testing) so that as many dilutions as possible fall within the reportable range of the assay (Proposed Procedure on page 317). The highest reported result would be “x” concentration (highest dilution factor times upper limit of quantitation) (Acceptance Criteria on page 318). Thus, Spitz teaches calculating a concentration of an analyte in a sample fluid based on the threshold dilution factor and a limit of detection of the sensor in a dilution assay.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method in modified Yang by adding the step of calculating a concentration of the target material in the sample fluid based on the threshold dilution factor and a limit of detection of the sensor (corresponding to the bio-sensing integrated circuit), as taught by Spitz, since it would estimate the concentration of the analyte/target material in the sample (Acceptance Criteria on page 318 in Spitz). Furthermore, one skilled in the art could have applied the same technique of estimating/calculating the analyte concentration by using the highest dilution factor times the limit of quantitation/detection as taught by Spitz
in the same way to calculate the analyte concentration in the dilution assay of modified Yang, yielding predictable results (MPEP 2143(I)(D)).
Regarding claim 22, modified Yang teaches the method of claim 21, wherein the concentration of the target material in the sample fluid is a product of the threshold dilution factor and the limit of detection of the bio-sensing integrated circuit (as outlined in the rejection of claim 21 above, the concentration of the target material in the sample fluid is the highest dilution factor times upper limit of quantitation [Acceptance Criteria on page 318 in Spitz]).
Regarding claim 23, modified Yang teaches the method of claim 21, wherein the bio-sensing integrated circuit comprises Biosensor Field-Effect Transistors (BioFETs) (as outlined in the rejection of claim 21 above, the bio-sensing integrated circuit comprises BioFET sensor array [Fig.2 and para. 0049-0050 in Liu]), each BioFET comprises a drain region and a source region (see Source and Drain in Fig.7A of Lim; or bioFETs include source/drain regions 115 [para. 0028; Figs. 1A and 1B in Liu]), and the 1st measurement value to the Nth measurement value are currents between the source region and the drain region of each BioFET (as outlined in the rejection of claim 21 above, the detection of the analyte by each BioFET is based on a current change between the source and the drain [see caption of Fig. 7B in Lim], thus the 1st measurement value to the Nth measurement value of the BioFET sensor array are currents between the source region and the drain region of each BioFET).
Regarding claim 24, modified Yang teaches the method of claim 23, and as outlined in the rejection of claim 21 above, the current between the source region and the drain region of each BioFET of the BioFET sensor array is measured to detect the analyte (see Fig.7 in Lim).
Yang is silent to wherein the first measurement value is an average value of the currents between the source region and the drain region of each BioFET in the 1st assay.
Yang does teach experiments were performed in duplicate and repeated twice. Mean with SEM is shown. Dotted lines indicate positive cutoff value (mean OD or endpoint titer of negative control milk samples + 2*SD) (caption of Fig.2B).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to provide two BioFETs for each assay of the 1st to the Nth assays to duplicate the measurements for each assay and use the mean value of the measurement current values of the two bioFETs in each assay as the measurement value of each assay, as taught by combined Yang and Lim, since Yang teaches experiments were performed in duplicate and repeated twice and the use of mean value to represent the measurement value (Fig.2B). One of ordinary skill in the art would recognize that duplicating BioFETs for each assay to duplicate measurements and using the average value to represent the measurement value of each assay would improve accuracy and reliability of the measurements.
Regarding claim 25, modified Yang teaches the method of claim 21, wherein the target material comprises SAS-CoV-2 Antigen (Lim teaches FET biosensor for COVID-19 for detecting SAS-CoV-2 Antigen by immobilizing SAS-CoV-2 spike protein antibodies as the biorecognition element [section 2.4.1]) or SARS-CoV-2 Antibody (Yang teaches the target material comprises SARS-CoV-2 antibody by using SARS-CoV-2 antigen as the biorecognition element [abstract; step 1 coat plates with SARS-CoV-2 spike protein on page 3]).
Response to Arguments
Applicant's arguments, see Remarks Pgs. 7-11, filed 12/31/2025, with respect to the 35 U.S.C. § 103 rejections have been fully considered and all prior art rejections from the previous office action are withdrawn.
Applicant’s Argument #1:
Regarding claims 1, 9 and 21, Applicant argues at pages 8-10 that the amended claims 1, 9 and 21 recite new features: converting the 1st measurement value to the Nth measurement value to digital signals through a Trans-impedance Amplifier (TIA) and an analog-to-digital converter (ADC); and comparing the digital signals, by a microcontroller unit (MCU), with a threshold value to determine a threshold dilution factor, and the prior art of the record fail to disclose the foregoing limitations recited in amended claims 1, 9 and 21. Claims 2-8, 10-15 and 22-25 respectively depend from and add further features to the amended claims 1, 9 and 21.
Examiner’s Response #1:
Applicant’s arguments have been fully considered, but are moot in view of the new grounds of rejections for the amended claims 1, 9 and 21 above.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/SHIZHI QIAN/Examiner, Art Unit 1795