DETAILED ACTION
Claims 1-17 are pending.
Status of Claims
Claims 1-17 are pending. Claims 1-2, 4, 6, and 9-11 have been amended. Claims 12-17 have been withdrawn.
Claims 1-11 are under examination.
Withdrawn Claim Objections and/or Rejections
The rejection of claim 2 under 35 USC 112(b) as being indefinite as set forth on pp. 45 of the previous office action (mailed on 02/05/2026) has been withdrawn in view of the amendments (filed on 05/01/2026).
The rejection of claim 4 under 35 USC 112(b) as being indefinite as set forth on pp. 5 of the previous office action (mailed on 02/05/2026) has been withdrawn in view of the amendments (filed on 05/01/2026).
The rejection of claims 6-7 under 35 USC 112(b) as being indefinite as set forth on p. 5-6 of the previous office action (mailed on 02/05/2026) has been withdrawn in view of the amendments (filed on 05/01/2026).
The rejection of claims 1-2 and 9 under 35 USC 102 as being anticipated by Park et al., as set forth on pp. 6-8 of the previous office action (mailed on 02/05/2026) has been withdrawn in view of the amendments (filed on 05/01/2026).
The rejection of claims 1-3 under 35 USC 102 as being anticipated by Han et al., as set forth on pp. 8-10 of the previous office action (mailed on 02/05/2026) has been withdrawn in view of the amendments (filed on 05/01/2026).
The rejection of claim 4 under 35 USC 103 for being unpatentable over Han et al., as set forth on p. 11 of the previous office action (mailed on 02/05/2026) has been withdrawn in view of the amendments (filed on 05/01/2026).
The rejection of claims 5-8 under 35 USC 103 for being unpatentable over Han and Shen et al., as set forth on pp. 11-13 of the previous office action (mailed on 02/05/2026) has been withdrawn in view of the amendments (filed on 05/01/2026).
The rejection of claims 10-11 under 35 USC for being unpatentable over Park and Shen et al., as set forth on pp. 13-14 of the previous office action (mailed on 02/05/2026) has been withdrawn in view of the amendments (filed on 05/01/2026).
Claim Rejections - 35 USC § 112- Maintained.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
1.Claims 1-11 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites “…test result of a lateral flow-type kit…wherein said lateral flow-type kit”. Claim 9 recites in the third line “…a plurality of different brands of lateral flow-type kit”. Claim 10 recites in the second and sixth line a “lateral flow-type kit”. Claim 11 recites “lateral flow type kit”. The specification does not provide any examples or further clarify what is meant by “lateral flow type kit”. It is unclear what applicant is referring to with “type” lateral flow kits.
While lateral flow kits are well known in the art, it is unclear what “type” entails. Ching, et al., (2015). Lateral Flow Immunoassay. In: Hnasko, R. (eds) ELISA. Methods in Molecular Biology, vol 1318. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-2742-5_13 teaches that at its core lateral flow immunoassays depend on a labeled, mobile reagent and an antibody or analyte immobilized on the analytical membrane (see page 127). Ching teaches that a lateral flow device must contain a plastic backing card, a sample pad, a conjugate release pad, a test line, a control line, an analytical membrane, an absorbent sink/pad, an antibody pair, an antibody label, and a sample buffer (see fig. 2 on page 128, see pages 131-132). Ching teaches that the analytical membrane is commonly a nitrocellulose membrane that contains immobilized capture antibodies and serve as the test platform (see page 129). Ching teaches that lateral flow kits and what they consist of is well known in the art. However, it is unknown what a “lateral flow type kit” consists of. It is unclear if applicant is referring to the type of biomarker that the lateral flow test is used for or the construct of the lateral flow assay (e.g., materials or designs). It is unclear if the kit contains lateral flow tests or not, and what a “lateral flow type” is.
Response to Arguments
The arguments filed on 05/01/2026 has been considered by the examiner.
On pp. 8-9 applicant argues that the term “type” has been replaced with the term “brands” in all claims. However, claims 1-11 still contain the recitation of a “lateral flow-type kit”.
Claim Rejections - 35 USC § 103-New: Necessitated by Amendments.
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
The 35 USC 103 rejections are new necessitated by amendments. The 35 USC 103 rejection has been amended to include the newly amended limitations of “wherein said lateral-flow-type test kit involves a lateral flow technology so that the solution mixed with the sample is not stationary, but flows from a sampling well to said C-line region and said detection T-line region” and “wherein the resulting image is processed in such a manner that a color map is converted to a grayscale map to extract information in the grayscale image that reflects the color intensity”.
2.Claims 1-2 and 4-9 are rejected under 35 U.S.C. 103 as being unpatentable over Park et al., “An Optimized Colorimetric Readout Method for Lateral Flow Immunoassays.” Sensors (Basel, Switzerland) vol. 18,12 4084. 22 Nov. 2018, doi:10.3390/s18124084 (list of references cited filed on 02/05/2026), in view of Hatamian (US 11275020 B2) (effectively filed on 06/09/2021).
Park teaches a method for quantitatively analyzing a test result of a lateral flow-type test kit, wherein the test kit comprises a result area with a quality control C-line region and a detection T- line region (see figure 3 on page 4 showing the test line and control line of a lateral flow immunoassay strip), wherein said lateral flow-type test kit involves a lateral flow technology so that the solution mixed with the sample is not stationary, but flows from a sampling well to said C-line region and said detection T- line region (see figure 3, see figure 3 legend “Figure 3. Analysis process of the color images for LFIA quantification. The control line captures any particle passing through, and thereby is used to ensure the proper sample flow in an LFIA. Only the test line area was analyzed.”, see page 4 under “2.3. Assay and Sample Used to Verify the Readout Method”), the method comprising: determining an analyte concentration range that the test kit can detect (see abstract “The change in the intensity ratio with increasing concentration of the target substance in the sample was largest in the green channel.”);
diluting a sample into a plurality of sample dilutions having different pre-determined
analyte concentrations within the determined analyte concentration range (see page 4
“Because blood samples were not available for this study, CK-MB (1-028, BioSpecifics,
Lynbrook, NY, USA) was diluted with serum (22000, SeraCare Life Sciences, Milford, MA, USA) to obtain 0, 2, 4, 10, 50, and 100 ng/mL solutions that were used as samples.”);
applying each sample dilution having a pre-determined analyte concentration to a sampling well on the rapid test kit for the analyte, so as to obtain separate resulting images with different color intensities on the T-line region corresponding to different pre-determined analyte concentrations (see page 4 teaching the sample being added to the strip, reacting with a mouse
IgG gold label coated with a monoclonal antibody at the conjugate release pad of the assay,
then the mixture of the sample and antibody flows through the porous membrane by capillary
action to react with capture reagent and generate a colored line, see figure 3, see page 3 “The image passed through the Bayer filter, and the pixel intensity was individually stored as three color bands (i.e., red, green, and blue). From the experiment in Figure 1, we selected the color band (i.e., red, green, or blue) in which the pixel intensity of the test line varied the most
with respect to the change in the target material concentration in the assay”);
calculating a corresponding color intensity index values for the T-line regions of each
resulting image, respectively (see page 3 “From the experiment in Figure 1, we selected the
color band (i.e., red, green, or blue) in which the pixel intensity of the test line varied the most
with respect to the change in the target material concentration in the assay. This selected color
channel was used to quantify the assay. Let I(t) and I(b) be the average pixel intensity values of
the region of interest in the test line portion and the background portion of the assay membrane, respectively. I(b)/I(t) was calculated for the test line that formed when the sample solution was
developed on the assay”); and
creating a continuous curve by fitting the corresponding plurality of color intensity index
values to the plurality of different pre-determined analyte concentrations, wherein the
corresponding analyte concentration can be obtained based on the color intensity index value at
any point on the continuous curve (see figure 6 on page 7 “Pixel intensity response curves
using the total color (i.e., original color), red, green, and blue images of the LFIA (a) and the
enlarged response curves for the creatine kinase–muscle/brain (CKMB) concentration range of
0 to 10 ng/mL (b). An average of 10 measurements is shown, and the error bars show the
standard deviation. The dashed line in (b) shows the linear regression result of the green channel”, see page 4 “These concentrations reflect the criteria for clinical positive and negative
determinations, where the concentration of CK-MB in the blood deemed negative for myocardial
infarction is less than 1.9–8.7 ng/mL [13,14].”) (instant claim 1).
Park teaches the analyte being a chemical substance, such as a protein (see page 4 teaching the analyte being CK-MB, which is a known protein) (instant claim 2). Park teaches segmenting the continuous curve, each segment having a range of color intensity index values corresponding to different sample concentrations ranging from low to high (see page 4 “The presence of this colored test line indicates a positive result, and the absence of a test line indicates a negative result. Because blood samples were not available for this study, CK-MB (1-028, BioSpecifics, Lynbrook, NY, USA) was diluted with serum (22000, SeraCare Life Sciences, Milford, MA, USA) to obtain 0, 2, 4, 10, 50, and 100 ng/mL solutions that were used as samples. These concentrations reflect the criteria for clinical positive and negative determinations, where the concentration of CK-MB in the blood deemed negative for myocardial infarction is less than 1.9–8.7 ng/m”, see page 6 “As the concentration of the target material increases in the sample solution, a darker test line forms, and its I(t) value decreases. Assuming that I(b) remains the same at different concentrations, the value of I(b)/I(t) increases as the amount of the target substance increases” see figure 6) (instant claim 4). Park teaches using a color patch that corresponds to one of the ranges of color intensity index values for the continuous curve segment and the color patch is a mean value of the segment corresponding to the range of color intensity index values (see figures 5 and 6, see page 6 “The red channel method showed the largest mean value difference at each CK-MB concentration compared with the original color image method. However, this is because the red channel method has the lowest intensity ratio as shown in Figure 6. The blue channel method had slightly larger mean values and a slightly smaller p-value than the green channel method at 2 ng/mL of CK-MB.”) (instant claims 5-6 and 9).
Park teaches storing the continuous curve associated with analyte concentration in a memory of a computer device (see page 3 “The acquired image was stored in the memory card of the PCB. Then, the image was transferred from the memory card to the desktop computer and analyzed using customized MATLAB code, as shown in Figure 3.”, see figure 5); obtaining an image of the T-line region with the test result by an image acquisition device (see figure 2 showing a camera, see figure 3 showing the image obtained by the camera showing the t line region); analyzing the image of the T-line region to determine the color intensity index value of the T-line region (see figure 3, see figure 3 legend, see page 3 “the image passed through the Bayer filter, and the pixel intensity was individually stored as three color bands (i.e., red, green, and blue). From the experiment in Figure 1, we selected the color band (i.e., red, green, or blue) in which the pixel intensity of the test line varied the most with respect to the change in the target material concentration in the assay”), and obtaining the corresponding analyte concentration according to the continuous curve (see figures 5-6) (instant claim 8).
Park does not teach wherein the resulting image is processed in such a manner that a color map is converted to a grayscale map to extract information in the grayscale image that reflects the color intensity, nor does Park teach determining the color intensity of the test results on the T-line region of a plurality of different brands of lateral flow-type kits.
Hatamian teaches wherein the resulting image is processed in such a manner that a color map is converted to a grayscale map to extract information in the grayscale image that reflects the color intensity (see column 3 lines 19-21 “In some of the present embodiments, the lateral flow assay grayscale may be used to adjust the colors and intensity of the image”, see column 5 lines 47-51 “The grayscale strip may include several intensity lines that may be used to correct the intensity of the images takes from the test results . The color bar and grayscale strip may also both be used together to collectively correct the color and intensity of the images”, see claims 6 and 9 of Hatamian) (instant claim 1). Hatamian teaches making at least one color-block includes displaying the color-block on a display (see figure 2) (instant claim 7). Hatamian teaches determining the color intensity range of the test results on the T-line region (see figure 2), while Hatamian does not explicitly state that the determining the color intensity of the test results on the T-line region of a plurality of different brands of lateral flow-type kits, absent evidence of the contrary, it would have been obvious to one of ordinary skill in the art to determine the color intensities of the rest results on the T-line region on any and all lateral flow tests, as that is obtaining the results of the test performed (instant claim 9).
It would have been obvious to one of ordinary skill in the art at the time of the instant application to combine the method of optimizing colorimetric readout for lateral flow immunoassays taught by Park, with the automated method of determining a test result of a lateral flow assay device taught by Hatamian. Hatamian provides motivation by teaching that the color bar and grayscale is used to adjust the colors and intensity of the image (see column 3 lines 8-12). Hatamian provides motivation by teaching that the color bars and the grayscale map allow the results to be read and interpreted by teaching that the images are processed by searching the image for groups of pixels with color values that closely match the known color values of the color bars color lines and by searching the images for groups of pixels with intensity values that closely match the intensity values of pixels of the grayscales strip’s intensity lines (see column 3 lines 24-42). The artisan would have reasonable expectation of success based on the cumulative disclosure of these prior art references at the time the instant application was filed.
3.Claims 10-11 are rejected under 35 U.S.C. 103 as being unpatentable over Park and Hatamian et al., as applied to claims 1-2 and 4-9 above, in view of Shen et al. “Point-of-care colorimetric detection with a smartphone.” Lab on a chip vol. 12,21 (2012): 4240-3. doi:10.1039/c2lc40741h (list of references cited filed on 02/05/2026).
The teachings of Park and Hatamian as it pertains to claims 1-2 and 4-9 are discussed in the 35 USC 103 rejection above.
Park teaches creating a continuous curve by fitting the corresponding plurality of color intensity index values to the plurality of different pre-determined analyte concentrations, wherein the corresponding analyte concentration can be obtained based on the color intensity index value at any point on the continuous curve (see figure 2) (instant claim 10).
Park does not teach the result image with different color intensities presented by the different pre-determined analyte concentrations on the T-line area and determining in a coordinate system with the analyte concentration as the abscissa and the color intensity as the ordinate, a starting point and an end point of the fitted continuous curve within determined color intensity range, whereby the corresponding analyte concentration for the corresponding type of kit can be obtained based on the color intensity index value at any point on the continuous curve.
Shen teaches the result image with different color intensities presented by the different pre-determined analyte concentrations on the T-line area and determining in a coordinate system with the analyte concentration as the abscissa and the color intensity as the ordinate, a starting point and an end point of the fitted continuous curve within determined color intensity range, whereby the corresponding analyte concentration for the corresponding type of kit can be obtained based on the color intensity index value at any point on the continuous curve (see figure 1 showing the reference chart of the colorimetric measurements, see figure 2 showing the colorimetric measurement intensities, see figure 3) (instant claims 10-11).
It would have been obvious to one of ordinary skill in the art at the time of the instant application to combine the method of optimizing colorimetric readout for lateral flow immunoassays taught by Park, with the automated method of determining a test result of a lateral flow assay device taught by Hatamian, with the methods of colorimetric detection with a smartphone taught by Shen. Shen provides motivation by teaching that with a tablet or smartphone one could take advantage of cellular network transmission and cloud-based data storage, or perform analysis outside laboratory (see page 4243). Shen teaches that promising colorimetric detection results have been demonstrated using video cameras, digital color analyzers, scanner, and/or custom portable readers (see page 4240). The artisan would have reasonable expectation of success based on the cumulative disclosure of these prior art references at the time the instant application was filed.
4.Claims 1-5, 7, and 9 are rejected under 35 U.S.C. 103 as being unpatentable over Han et al. “Rapid field determination of SARS-CoV-2 by a colorimetric and fluorescent dual-functional lateral flow immunoassay biosensor.” Sensors and actuators. B, Chemical vol. 351 (2022): 130897. doi:10.1016/j.snb.2021.130897 (list of references cited filed on 02/05/2026), in view of Hatamian (US 11275020 B2) (effectively filed on 06/09/2021).
Han teaches a method for quantitatively analyzing a test result of a lateral flow-type test kit, wherein the test kit comprises a result area with a quality control C-line region and a detection T- line region (see scheme 1 on page 3 showing a lateral flow test strip with a control line and a test line), and wherein said lateral flow-type test kit involves a lateral flow technology so that the solution mixed with the sample is not stationary, but flows from a sampling well to said C-line region and said detection T- line region (see scheme 1, see page 5 “Finally, the mixture was loaded onto the sample pad of the LFIA strip and moved in the direction of the absorbent pad with capillary action. When the immune complex reached the position of the test line, the S1 protein reacted with the capturing antibody. The residual SiO2@Au/QD nanotags continued to migrate and were captured by the goat anti-mouse IgG fixed on the control line. Therefore, a bright colorimetric/ fluorescence control line was observed, indicating that the LFIA strips were working properly. The test line showed colorimetric and fluorescent bands when the S1 protein was present in the sample, whereas no bands appeared on the test line in the absence of the S1 protein in the test sample.”), the method comprising:
determining an analyte concentration range that the test kit can detect (see page 5 “This
assay was designed with the following key parameters as the starting points: type of NC
membrane, reaction time, antibody concentration on the test line.”, see figure 3 showing the
concentrations of an analyte);
diluting a sample into a plurality of sample dilutions having different pre-determined
analyte concentrations within the determined analyte concentration range (see page 5 “All
optimized conditions were applied to detect SARS-CoV-2 S1 protein and evaluate the sensitivity
of SiO2@Au/QDs-based LFIA biosensor. The SARS-CoV-2 S1 protein was serially diluted from
1000 ng/mL to 0.05 ng/mL for eight concentrations and then loaded onto the strip biosensor.
The control lines of all LFIA strips showed purple and fluorescent bands (Fig. 3b), indicating that the strip biosensor was working properly.”);
applying each sample dilution having a pre-determined analyte concentration to a
sampling well on the rapid test kit for the analyte, so as to obtain separate resulting images with
different color intensities on the T-line region corresponding to different pre-determined analyte
concentrations (see page 5 “All optimized conditions were applied to detect SARS-CoV-2 S1
protein and evaluate the sensitivity of SiO2@Au/QDs-based LFIA biosensor. The SARS-CoV-2
S1 protein was serially diluted from 1000 ng/mL to 0.05 ng/mL for eight concentrations and then
loaded onto the strip biosensor. The control lines of all LFIA strips showed purple and
fluorescent bands (Fig. 3b), indicating that the strip biosensor was working properly”);
calculating a corresponding color intensity index values for the T-line regions of each
resulting image, respectively (see figure 3, see figure 5); and
creating a continuous curve by fitting the corresponding plurality of color intensity index
values to the plurality of different pre-determined analyte concentrations, wherein the corresponding analyte concentration can be obtained based on the color intensity index value at
any point on the continuous curve (see figure 2) (instant claim 1).
Han teaches the analyte being a chemical substance and the sample being an inactivated virus (see page 6 “We detected inactivated viruses of SARS-CoV-2 to further verify the practical analytical capability of the new biosensor. SARS-CoV-2 inactivated virus were continuously diluted from 1.41 × 107 copies/mL to 7.06 × 103 copies/mL in 8 concentrations, and then virus diluents were dropped on the sample pads.”, see table 1) (instant claims 2-3). Han teaches segmenting the continuous curve, each segment having a range of color intensity index values corresponding to different sample concentration ranges from low to high, respectively (see figure 4a showing concentration ranges, see figure 2) (instant claims 4-5).
Han does not teach wherein the resulting image is processed in such a manner that a color map is converted to a grayscale map to extract information in the grayscale image that reflects the color intensity. Han does not teach making at least one color-patch corresponding to one of the ranges of the color intensity index values, nor does Han teach determining the color intensity range of the test results on the T-line region.
Hatamian teaches wherein the resulting image is processed in such a manner that a color map is converted to a grayscale map to extract information in the grayscale image that reflects the color intensity (see column 3 lines 19-21 “In some of the present embodiments, the lateral flow assay grayscale may be used to adjust the colors and intensity of the image”, see column 5 lines 47-51 “The grayscale strip may include several intensity lines that may be used to correct the intensity of the images takes from the test results . The color bar and grayscale strip may also both be used together to collectively correct the color and intensity of the images”, see claims 6 and 9 of Hatamian) (instant claim 1). Hatamian teaches making at least one color-patch corresponding to one of the ranges of color intensity index values (see figure 2) (instant claim 5). Hatamian teaches making at least one color-block includes displaying the color-block on a display (see figure 2) (instant claim 7). Hatamian teaches determining the color intensity range of the test results on the T-line region (see figure 2), while Hatamian does not explicitly state that the determining the color intensity of the test results on the T-line region of a plurality of different brands of lateral flow-type kits, absent evidence of the contrary, it would have been obvious to one of ordinary skill in the art to determine the color intensities of the rest results on the T-line region on any and all lateral flow tests, as that is obtaining the results of the test performed (instant claim 9).
It would have been obvious to one of ordinary skill in the art to combine the methods of using colorimetric and fluorescent dual-function lateral flow immunoassay biosensors taught by Han, with the automated method of determining a test result of a lateral flow assay device taught by Hatamian. Hatamian provides motivation by teaching that the color bar and grayscale is used to adjust the colors and intensity of the image (see column 3 lines 8-12). Hatamian provides motivation by teaching that the color bars and the grayscale map allow the results to be read and interpreted by teaching that the images are processed by searching the image for groups of pixels with color values that closely match the known color values of the color bars color lines and by searching the images for groups of pixels with intensity values that closely match the intensity values of pixels of the grayscales strip’s intensity lines (see column 3 lines 24-42). The artisan would have reasonable expectation of success based on the cumulative disclosure of these prior art references at the time the instant application was filed.
5.Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Han and Hatamian et al., as applied to claims 1-5, 7, and 9 above, in view of Park et al., “An Optimized Colorimetric Readout Method for Lateral Flow Immunoassays.” Sensors (Basel, Switzerland) vol. 18,12 4084. 22 Nov. 2018, doi:10.3390/s18124084 (list of references cited filed on 02/05/2026).
The teachings of Han and Hatamian as applied to claims 1-5, 7, and 9 are discussed in the 35 USC 103 rejection above.
Han does not teach wherein the color intensity of the at least one-color patch is the mean value of the segment corresponding to the range of color intensity index values.
Park teaches the color patch is a mean value of the segment corresponding to the range of color intensity index values (see figures 5 and 6, see page 6 “The red channel method showed the largest mean value difference at each CK-MB concentration compared with the original color image method. However, this is because the red channel method has the lowest intensity ratio as shown in Figure 6. The blue channel method had slightly larger mean values and a slightly smaller p-value than the green channel method at 2 ng/mL of CK-MB.”, see page 3 “Let I(t) and I(b) be the average pixel intensity values of the region of interest in the test line portion and the background portion of the assay membrane, respectively. I(b)/I(t) was calculated for the test line that formed when the sample solution was developed on the assay) (instant claim 6).
It would have been obvious to one of ordinary skill in the art to combine the methods of using colorimetric and fluorescent dual-function lateral flow immunoassay biosensors taught by Han, with the automated method of determining a test result of a lateral flow assay device taught by Hatamian, with the method of optimizing colorimetric readout for lateral flow
immunoassays taught by Park. Park provides motivation by teaching that the mean of the color intensity index shows the level of improvement in the measurement performance (see page 6). Further, it would have been obvious to one of ordinary skill in the art to use the average of the measurements to correspond with the range of the color intensity value as it is a common technique in the art. The artisan would have reasonable expectation of success based on the cumulative disclosure of these prior art references at the time the instant application was filed.
6.Claims 8 and 10-11 are rejected under 35 U.S.C. 103 as being unpatentable over Han and Hatamian et al., as applied to claims 1-5, 7, and 9 above, in view of Shen et al. “Point-of-care colorimetric detection with a smartphone.” Lab on a chip vol. 12,21 (2012): 4240-3. doi:10.1039/c2lc40741h (list of references cited filed on 02/05/2026).
The teachings of Han and Hatamian as it pertains to claims 1-5, 7, and 9 are discussed in the 35 USC 103 rejection above.
Han teaches obtaining an image of the T-line region with the test result by an image acquisition device (see figures 5a and 5d); analyzing the image of the T-line region to determine the color intensity index value of the T-line region (see figures 5a and 5d), and obtaining the corresponding analyte concentration according to the continuous curve (see figure 4a) (instant claim 8).
Han does not teach storing the continuous curve associated with analyte concentration in a memory of a computer device, nor does Han teach the result image with different color intensities presented by the different pre-determined analyte concentrations on the T-line area and determining in a coordinate system with the analyte concentration as the abscissa and the color intensity as the ordinate, a starting point and an end point of the fitted continuous curve within determined color intensity range, whereby the corresponding analyte concentration for the corresponding type of kit can be obtained based on the color intensity index value at any point on the continuous curve.
Shen teaches storing the continuous curve associated with analyte concentration in a
memory of a computer device (see page 4243 “Further, as already mentioned, with a tablet or
smartphone one could take advantage of cellular network transmission and cloud-based data
storage, or perform analysis outside laboratory.”) (instant claim 8). Shen teaches the result image with different color intensities presented by the different pre-determined analyte concentrations on the T-line area and determining in a coordinate system with the analyte concentration as the abscissa and the color intensity as the ordinate, a starting point and an end point of the fitted continuous curve within determined color intensity range, whereby the corresponding analyte concentration for the corresponding type of kit can be obtained based on the color intensity index value at any point on the continuous curve (see figure 1 showing the reference chart of the colorimetric measurements, see figure 2 showing the colorimetric measurement intensities, see figure 3) (instant claims 10-11).
It would have been obvious to one of ordinary skill in the art to combine the methods of using colorimetric and fluorescent dual-function lateral flow immunoassay biosensors taught by Han, with the automated method of determining a test result of a lateral flow assay device taught by Hatamian, with the methods of colorimetric detection with the smartphone taught by Shen. Shen provides motivation by teaching that with a tablet or smartphone one could take advantage of cellular network transmission and cloud-based data storage, or perform analysis outside laboratory (see page 4243). Shen teaches that promising colorimetric detection results have been demonstrated using video cameras, digital color analyzers, scanner, and/or custom portable readers (see page 4240). The artisan would have reasonable expectation of success based on the cumulative disclosure of these prior art references at the time the instant application was filed.
Response to Arguments
Applicant's arguments filed 05/01/2026 have been fully considered but they are not persuasive.
On p. 9 applicant argues that Park does not disclose or teach a continuous curve by fitting color intensity index values to a plurality of different pre-determined analyte concentrations. Applicant argues that Park does not disclose steps (ii) and (iii) of instant claim 1.
However, Park does disclose a continuous curve by fitting color intensity index values (see figure 6). Figure 6 shows a continuous curve of each color intensity and different concentrations of the analyte. A continuous curve is known in the art as a line that can be traced on paper without ever lifting the pencil. It is known in the art of mathematics as a curve without any abrupt changes, holes, or sudden jumps. Thus, figure 6 is a continuous curve.
Further, the instant claims do not recite the order of steps. Therefore, it is unclear what the applicant is referring to when reciting in the arguments steps (ii) and (iii).
On pp. 9-10 applicant argues that Park does not teach obtaining separate resulting images with different color intensities on the T-line region corresponding to different pre-determined analyte concentrations.
However, Park does teach obtaining images with different color intensities on the T-line region corresponding to different pre-determined analyte concentrations in figures 3 and 5. Park explicitly teaches acquiring images of the test line (see page 1, see page 3).
On p. 10 applicant argues that Park does not teach the newly recited limitation of “wherein the resulting image is processed in such a manner that a color map is converted to a grayscale map to extract information in the grayscale image that reflects the color intensity”.
However, Hatamian teaches wherein the resulting image is processed in such a manner that a color map is converted to a grayscale map to extract information in the grayscale image that reflects the color intensity (see column 3 lines 19-21, see column 5 lines 47-51, see claims 6 and 9).
On p. 11 applicant argues figures 3 and 5 of Han disclose calculating the vLOD or LOD of the fluorescence detection, rather than to calculate the protein or inactivated virus coentration according to the fluorescence intensity.
However, figure 3 c is explicitly showing the fluorescent intensity and correlating the intensity to the protein concentration. Figure 4 shows the sample concentrations and their corresponding intensity. Figure 5b shows the concentration of SARS-CoV-2 inactivated virus and corresponding the concentration to the intensity.
On p. 11 applicant argues that Han discloses the use of two signals and the only one that was utilized for quantitative detection of virus infections at an early stage was fluorescence and the instant application does not utilize two signals, only color intensity index values for the T-line region are taken into account.
However, Han teaches the use of a lateral-flow kit that utilizes colorimetric signals for visual detection and rapid screening of SARS-CoV-2 infection on site and a fluorescence signal was utilized for sensitive and quantitative detection of the viral infection (see abstract). The signals were used for two completely different reasons. One of ordinary skill in the art would have been motivated to select which signal method would be appropriate based on what is being measured.
On p. 12 applicant argues that Han does not teach step iv of instant claim 1.
However, the instant claims do not recite the order of steps. Therefore, it is unclear what the applicant is referring to when reciting in the argument step iv. For compact prosecution, examiner is going to interpret the step of “iv” to “calculating a corresponding color intensity index values for the T-line regions of each resulting image, respectively, wherein the resulting image is processed in such a manner that a color map is converted to a grayscale map to extract information in the grayscale image that reflects the color intensity”.
Han teaches calculating a corresponding color intensity index values for the T-line regions of each resulting image (see figures 3 and 5, see page 5 teaching the calculations used to determine the values in figure 3).
Hatamian teaches the new limitation “wherein the resulting image is processed in such a manner that a color map is converted to a grayscale map to extract information in the grayscale image that reflects the color intensity” (see column 3 lines 19-21, column 5 lines 47-51, and claims 6 and 9).
On p. 13 applicant argues that Shen does not remedy the deficiencies of Han.
Han teaches obtaining an image of the T-line region with the test result by an image acquisition device, analyzing the image of the T-line region to determine the color intensity index value of the T-line region (see figures 5a and 5d), and obtaining the corresponding analyte concentration according to the continuous curve.
Hatamian teaches wherein the resulting image is processed in such a manner that a color map is converted to a grayscale map to extract information in the grayscale image that reflects the color intensity.
Shen teaches storing the continuous curve associated with analyte concentration in a
memory of a computer device and the result image with different color intensities presented by the different pre-determined analyte concentrations on the T-line area and determining in a coordinate system with the analyte concentration as the abscissa and the color intensity as the ordinate, a starting point and an end point of the fitted continuous curve within determined color intensity range, whereby the corresponding analyte concentration for the corresponding type of kit can be obtained based on the color intensity index value at any point on the continuous curve.
On pp. 13-14 applicant argues that Shen does not remedy the deficiencies of Park.
Park teaches creating a continuous curve by fitting the corresponding plurality of color intensity index values to the plurality of different pre-determined analyte concentrations, wherein the corresponding analyte concentration can be obtained based on the color intensity index value at any point on the continuous curve.
Hatamian teaches teaches wherein the resulting image is processed in such a manner that a color map is converted to a grayscale map to extract information in the grayscale image that reflects the color intensity.
Shen teaches the result image with different color intensities presented by the different pre-determined analyte concentrations on the T-line area and determining in a coordinate system with the analyte concentration as the abscissa and the color intensity as the ordinate, a starting point and an end point of the fitted continuous curve within determined color intensity range, whereby the corresponding analyte concentration for the corresponding type of kit can be obtained based on the color intensity index value at any point on the continuous curve.
On p. 14 applicant argues that Park does not teach a continuous curve that establishes a quantitative relationship between color intensity index values and analyte concentrations and the grayscale conversion process.
Park does disclose a continuous curve by fitting color intensity index values (see figure 6). Figure 6 shows a continuous curve of each color intensity and different concentrations of the analyte. A continuous curve is known in the art as a line that can be traced on paper without ever lifting the pencil. It is known in the art of mathematics as a curve without any abrupt changes, holes, or sudden jumps. Thus, figure 6 is a continuous curve.
Hatamian teaches the color map is converted to a grayscale map to extract information in the grayscale image that reflects the color intensity.
Conclusion
No claim is allowed.
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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/MCKENZIE A DUNN/ Examiner, Art Unit 1678
/GREGORY S EMCH/ Supervisory Patent Examiner, Art Unit 1678
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