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 .
Priority
The present application claims priority from PCT/US2021/058586 filed on 11/09/2020. The priority document was electronically retrieved on 05/09/2023. Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statements (IDS) was filed on 05/09/2023. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Response to arguments
Applicant first mentions that the presented amendments with the RCE, now overcome the claim objections and claim rejections under 112(b). Examiner agrees and removes the claim objections and 112(b).
Applicant argues the presented prior art rejected under 103 when incorporating the amended language to the claims. Examiner agrees and presents a new reference, Lee et. al., that does teach the newly amended claims and presents a new combination of Yakimovich and Lee, eliminating the need for the Kurebayashi reference. Applicant also presents new claims 5 and 6, these claims are also taught by the new combined prior art. Therefore all the claims stay rejected.
Applicant argues that the previously invoked 101 rejection for independent claims 1 and 4 with the newly presented amendments with the RCE, now overcome the rejection, examiner disagrees and presents a new 101 rejection including the new substantial amendments. The applicant presents that the invention is a technological improvement and is integrated into a practical application, however examiner disagrees because the limitations, within the BRI (broadest reasonable interpretation) as interpreted from the claim language in light of the specification, merely confine the use of the abstract idea to a particular field of use, which in this case is imaging/imaging processes, and therefore does not integrate the judicial exception into a practical application. Please see MPEP § 2106.05(h) regarding field of use and technological environment.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
35 U.S.C. 101 requires that a claimed invention must fall within one of the four eligible categories of invention (i.e. process, machine, manufacture, or composition of matter) and must not be directed to subject matter encompassing a judicially recognized exception as interpreted by the courts. MPEP 2106. Three categories of subject matter are found to be judicially recognized exceptions to 35 U.S.C. § 101 (i.e. patent ineligible) (1) laws of nature, (2) physical phenomena, and (3) abstract ideas. MPEP 2106(II). To be patent-eligible, a claim directed to a judicial exception must as whole be integrated into a practical application or directed to significantly more than the exception itself (MPEP 2106). Hence, the claim must describe a process or product that applies the exception in a meaningful way, such that it is more than a drafting effort designed to monopolize the exception.
Claims 1-6 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., an abstract idea) without integration into a practical application or recitation of significantly more. Each of the independent claims 1 and 4 are directed to one of the four statutory categories of eligible subject matter; thus, the claims pass Step 1 of the Subject Matter Eligibility Test (See flowchart in MPEP 2106).
Step 2A, Prong 1 Analysis
The independent claims are directed to, “applying virions on the cells… the virus infected cells… of a growing viral infection… a growth rate of the viral plaque without having to fix and stain the cells and thereby kill the still living cells and… of unfixed and unstained living cells and plaques…”
Each of the above steps can be considered a natural phenomenon. In nature, viruses can naturally infect cells, such as the common cold, flu or covid, also the viruses may not necessarily kill the cells as their goal is to infect and keep reproducing, and also cells in nature are not naturally fixed, therefore “without having to fix the cells and thereby kill the still living cells” and “unfix and unstained living cells and plaques”, occurs naturally. Plaques also occur and grow naturally. As such, the description in independent claims 1 and 4 is a natural phenomenon. Accordingly, the analysis under prong one of step 2A of the Subject Matter Eligibility Test does not result in a conclusion of eligibility (See flowchart in MPEP 2106).
Additional Elements
The additional elements recited in the independent claims 1 and 4 are the steps of
“placing cells in wells of a plate… thereafter imaging the virus infected cells at desired intervals… an imager to produce a time sequence of images… and image processing the time sequence of images to determine changes in appearance of the cells in consecutive images from the sequence of images… and determining where and how many plaques are in a well.”
Independent claim 4 also has “image processing the first and second sequences of images to determine therefrom…”
Step 2A, prong 2 analysis
The above-identified additional elements do not integrate the judicial exception into a practical application.
The steps of “placing cells in wells of a plate” amounts to insignificant extra-solution activity which does not integrate the claimed natural phenomenon into a practical application (See MPEP 2106.05(g)).
Each of the other additional elements (“thereafter imaging the virus infected cells at desired intervals… an imager to produce a time sequence of images… and image processing the time sequence of images to determine changes in appearance of the cells in consecutive images from the sequence of images… and determining where and how many plaques are in a well” and “image processing the first and second sequences of images to determine therefrom…” ) amounts to merely using a computer or other machinery merely as a tool to perform an existing process. Implementing a natural phenomenon on a computer or tool does not integrate a judicial exception into a practical application (See MPEP 2106.05(f)).
Moreover, the additional elements of the claim does not recite an improvement in the functioning of a computer or other technology or technical field, the claimed steps are not performed using a particular machine, the claimed steps do not effect a transformation, and the claims do not apply the judicial exception in any meaningful way beyond generically linking the use of the judicial exception to a particular technological environment (See MPEP 2106.04(d)). Therefore, the analysis under prong two of step 2A of the Subject Matter Eligibility Test does not result in a conclusion of eligibility (See flowchart in MPEP 2106).
Step 2B
Finally, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
As noted above, the step of “placing cells in wells of a plate” amount to insignificant extra-solution activity which does not integrate the claimed mental process into a practical application (See MPEP 2106.05(g)).
Each of the other additional elements (“thereafter imaging the virus infected cells at desired intervals… an imager to produce a time sequence of images… and image processing the time sequence of images to determine changes in appearance of the cells in consecutive images from the sequence of images… and determining where and how many plaques are in a well” and “image processing the first and second sequences of images to determine therefrom…” ) are generic computer or tool features which perform generic functions that are well-understood, routine, and conventional and do not amount to more than implementing the natural phenomenon with a system. Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea).
Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer and tool implementation, and mere implementation on a generic computer and tool does not add significantly more to the claims. Accordingly, the analysis under step 2B of the Subject Matter Eligibility Test does not result in a conclusion of eligibility (See flowchart in MPEP 2106).
For all of the foregoing reasons, independent claim 1 does not recite eligible subject matter under 35 USC 101.
Independent claim 4 is rejected under the same analysis as claim 1, it only adds a second time sequence of images as opposed to only one and will fall within the same category as the one time sequence.
Claim 2 recites “the images of include cells that manifest plaques and cells that do not manifest plaques and calculating therefrom features of artifacts.” The following is still a natural phenomenon “cells that manifest plaques and cells that do not manifest plaques”. The additional elements amounts to merely using a computer or other machinery merely as a tool to perform an existing process. Implementing a natural phenomenon on a computer or tool does not integrate a judicial exception into a practical application.
Claim 3 recites “determining from the images data relating to features in addition to plaques and using machine learning to predict the presence or lack of plaques based on the additional features.” The additional elements amounts to merely using a computer or other machinery merely as a tool to perform an existing process. Implementing a natural phenomenon on a computer or tool does not integrate a judicial exception into a practical application.
Claims 5 and 6 recite “the imager is a bright-field imager.” The additional elements amounts to merely using a computer or other machinery merely as a tool to perform an existing process. Implementing a natural phenomenon on a computer or tool does not integrate a judicial exception into a practical application.
Claim Rejections - 35 USC § 103
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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
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.
Claims 1, 2, 4 and 5-6 are rejected under 35 U.S.C. 103 as being unpatentable over Yakimovich et. al., hereafter Yakimovich ( Yakimovich, Artur, et al. "Plaque2. 0—a high-throughput analysis framework to score virus-cell transmission and clonal cell expansion." PloS one 10.9 (2015): e0138760.) in view of Lee et. al., hereafter Lee (Lee, Gyuhyun, et al. "DeepHCS: bright-field to fluorescence microscopy image conversion using deep learning for label-free high-content screening." International Conference on Medical Image Computing and Computer-Assisted Intervention. Cham: Springer International Publishing, 2018.).
As per claim 1, Yakimovich teaches “A plaque assay counting method, comprising the steps of: placing cells in wells of a plate, applying virions on the cells, thereafter imaging the virus infected cells at desired intervals of a growing viral infection with an imager to produce a time sequence of images of a growth rate of the viral plaque… and image processing the time sequence of images in an image processor to determine changes in appearance of the cells in consecutive images from the sequence of images… and plaques and determining where and how many plaques are in a well.” (See abstract, Using the Plaque2.0 software on page 6, Fluorescence microscopy extends conventional plaque assay section on page 9, Vaccinia viruses paragraph on page 3, Time-lapse multi-site multi-channel microscopy paragraph on page 5, fig. 1 with accompanying paragraph on page 10 and fig. 3 with accompanying paragraph on page 12. The reference teaches a plaque assay (plaque counting) method in which the cells were placed in wells of a plate (the monkey kidney cells), then virions were applied (VACV is a virion) on the cells, and the infected cells are imaged at desired intervals (depending on the time-lapse) and also use of imaging plates which perform live imaging that also create time lapses and the Plaque2.0 software takes these images as input (which includes time lapses, interpreted as a time sequence of images) and detects plaques for counting and changes in the appearance of the cell (See fig. 3 with accompanying paragraph on page 12). See also page 16 with fig. 7 and accompanying paragraph, it shows the changes in appearance of the cells and where and how many plaques are throughout the time lapse. See also page 8 section Identification of plaques, it shows that plaques are identified to determine a count in a specific region. (The fluorescence microscopy extends conventional plaque assay section on page 9 “We explored if fluorescence imaging was suitable to measure viral plaque morphologies. For this we used two strains of VACV, the Western Reserve (WR) strain producing circular plaques, and International Health Department J (IHD-J) producing comet-shaped plaques [32, 34]. VACV-WR-E/L-GFP or VACV-IHD-J-E/L-GFP expressing GFP from early-late promoter was inoculated onto monkey kidney BSC40 cell monolayers in 96-well imaging plates, or 6-well plates for conventional plaque assay. Both plates were fixed 48 h pi. In both conventional and Plaque2.0 assays the IHD-J strain produced comet-shaped fluorescent foci, so called fluorescent plaques (in short ‘plaques’), while the WR strain produced circular plaques (Fig 1)”. Yakimovich), however Yakimovich does not teach “without having to fix and stain the cells and thereby kill the still living cells” and “of unfixed and unstained living cells…”
Lee teaches “without having to fix and stain the cells and thereby kill the still living cells” and “of unfixed and unstained living cells…” (See page 2 fig.1 along with its accompanying paragraph “Fig.1. DeepHCS eliminates the cell fixation and staining progress in the original HCS workflow and generates corresponding fluorescence image based bright-field image by Operetta. DeepHCS can keep the cells alive during the entire progress.”. See also page 2 paragraph2 “Among them, HCS uses high throughput imaging and automatic image analysis to evaluate changes in the phenotype of the whole cells, such as counting the number of living cells versus dead cells, measuring the size of the cells, comparing the shape of the cells, etc.” See also page 2 paragraph 2 “One advantage of using bright-field images in HCS is its ability to acquire a photographic record of cells without any extra preparation while fluorescence images require time-consuming cell fixation and staining procedures. Another advantage of the bright-field image method is its ability to capture the dynamics of cells because cell fixation and cell staining are not required (Fig.1 lower row).” Lee)
It would have been obvious to one of ordinary skill in the art before the effective filing
date of the claimed invention to combine the teachings of Yakimovich with the teachings of Lee to take a time sequence of images showing the growth rate without fixing and without staining the cells. The modification would have been motivated by the desire to: keep the cells alive and prevent time-consuming procedures (therefore be more time-efficient), therefore it is an improvement, as suggested by Lee (See page 2 fig.1 along with its accompanying paragraph “Fig.1. DeepHCS eliminates the cell fixation and staining progress in the original HCS workflow and generates corresponding fluorescence image based bright-field image by Operetta. DeepHCS can keep the cells alive during the entire progress.” See also page 2 paragraph 2 “One advantage of using bright-field images in HCS is its ability to acquire a photographic record of cells without any extra preparation while fluorescence images require time-consuming cell fixation and staining procedures. Another advantage of the bright-field image method is its ability to capture the dynamics of cells because cell fixation and cell staining are not required (Fig.1 lower row).”. See also page 3 paragraph 2 “By doing this, DeepHCS effectively avoids the time-consuming and laborious cell preparation process for generating biomarkers while providing accurate image analysis results by using the well-established conventional HCS workflow (Fig.1 bottom row).” Lee )
As per claim 2, Yakimovich in view of Lee teaches “The method according to claims 1, wherein the images of include cells that manifest plaques and cells that do not manifest plaques and calculating therefrom features of artifacts.” (See page 8 section Identification of plaques and section features of plaques. See also fig. 1 and fig. 3. See also page 11-12 section Plaque2.0 scores plaques from cell-free spreading adenovirus, “Alternatively, population-based fluorescence or luminescence measurements of transgene expression, immuno-fluorescence staining or counting of infected and uninfected cells are used. We developed Plaque2.0 to measure a combination of direct and indirect infection features based on multi-parametric datasets, including cell-based information, such as infection intensity of individual cells, and object-based information, such as viral plaque features… We compared plaque numbers with the overall infection index, which was defined as the ratio of infected to uninfected cells, and the total infection signal measured as GFP intensity per well 72 h pi (Fig 4C).” Uninfected cells do not manifest plaques and are also imaged by the Plaque2.0 assay using a time lapse as seen on fig. 3, fig. 4 and fig. 7, not all cells are infected. Examiner interprets “features of artifacts” as viral plaque features, as seen in page 8 section features of plaques. Yakimovich)
As per claim 4 “A plaque assay counting method, comprising the steps of: placing cells in wells of a plate, applying virions on the cells, thereafter imaging the virus infected cells at desired intervals of a growing viral infection with an imager… to produce a first time sequence of images… and plaques showing a growth rate of the viral plaque and thereafter, imaging the virus infected cells at desired intervals with the imager… to produce a second time sequence of images… and plaques and image processing the first and second sequences of images to determine therefrom where and how many plaques are in a well.” (See abstract, Using the Plaque2.0 software on page 6, Fluorescence microscopy extends conventional plaque assay section on page 9, Vaccinia viruses paragraph on page 3, Time-lapse multi-site multi-channel microscopy paragraph on page 5, fig. 1 with accompanying paragraph on page 10 and fig. 3 with accompanying paragraph on page 12. The reference teaches a plaque assay (plaque counting) method in which the cells were placed in wells of a plate (the monkey kidney cells), then virions were applied (VACV is a virion) on the cells, and the infected cells are imaged at desired intervals (depending on the time-lapse) and also use of imaging plates which perform live imaging that also create time lapses and the Plaque2.0 software takes these images as input (which includes time lapses, interpreted as a time sequence of images) and detects plaques for counting and changes in the appearance of the cell (See fig. 3 with accompanying paragraph on page 12). See also page 16 with fig. 7 and accompanying paragraph, it shows the changes in appearance of the cells and where the plaques are throughout the time lapse. See also page 8 section Identification of plaques, it shows that plaques are identified to determine a count in a specific region. (The fluorescence microscopy extends conventional plaque assay section on page 9 “We explored if fluorescence imaging was suitable to measure viral plaque morphologies. For this we used two strains of VACV, the Western Reserve (WR) strain producing circular plaques, and International Health Department J (IHD-J) producing comet-shaped plaques [32, 34]. VACV-WR-E/L-GFP or VACV-IHD-J-E/L-GFP expressing GFP from early-late promoter was inoculated onto monkey kidney BSC40 cell monolayers in 96-well imaging plates, or 6-well plates for conventional plaque assay. Both plates were fixed 48 h pi. In both conventional and Plaque2.0 assays the IHD-J strain produced comet-shaped fluorescent foci, so called fluorescent plaques (in short ‘plaques’), while the WR strain produced circular plaques (Fig 1)”. On fig. 7 there are two time lapses measured at desired intervals. Yakimovich)
Lee teaches “… without having to fix and stain the cells and thereby kill the still living cells…” , “of unfixed and unstained living cells…” , “… without having to fix and stain the cells and thereby kill the still living cells…” and “of unfixed and unstained living cells…” (See page 2 fig.1 along with its accompanying paragraph “Fig.1. DeepHCS eliminates the cell fixation and staining progress in the original HCS workflow and generates corresponding fluorescence image based bright-field image by Operetta. DeepHCS can keep the cells alive during the entire progress.”. See also page 2 paragraph2 “Among them, HCS uses high throughput imaging and automatic image analysis to evaluate changes in the phenotype of the whole cells, such as counting the number of living cells versus dead cells, measuring the size of the cells, comparing the shape of the cells, etc.” See also page 2 paragraph 2 “One advantage of using bright-field images in HCS is its ability to acquire a photographic record of cells without any extra preparation while fluorescence images require time-consuming cell fixation and staining procedures. Another advantage of the bright-field image method is its ability to capture the dynamics of cells because cell fixation and cell staining are not required (Fig.1 lower row).” Lee)
It would have been obvious to one of ordinary skill in the art before the effective filing
date of the claimed invention to combine the teachings of Yakimovich with the teachings of Lee to take two time sequence of images showing the growth rate without fixing and without staining the cells. The modification would have been motivated by the desire to: keep the cells alive and prevent time-consuming procedures (therefore be more time-efficient), therefore it is an improvement, as suggested by Lee (See page 2 fig.1 along with its accompanying paragraph “Fig.1. DeepHCS eliminates the cell fixation and staining progress in the original HCS workflow and generates corresponding fluorescence image based bright-field image by Operetta. DeepHCS can keep the cells alive during the entire progress.” See also page 2 paragraph 2 “One advantage of using bright-field images in HCS is its ability to acquire a photographic record of cells without any extra preparation while fluorescence images require time-consuming cell fixation and staining procedures. Another advantage of the bright-field image method is its ability to capture the dynamics of cells because cell fixation and cell staining are not required (Fig.1 lower row).”. See also page 3 paragraph 2 “By doing this, DeepHCS effectively avoids the time-consuming and laborious cell preparation process for generating biomarkers while providing accurate image analysis results by using the well-established conventional HCS workflow (Fig.1 bottom row).” Lee )
As per claim 5, Yakimovich in view of Lee teaches “The method according to claim 1, wherein the imager is a bright-field imager.” (See fig. 1 and page 2 paragraph 2 “In HCS, multiple imaging modalities are commonly used together to image various aspects of the cell phenotypes (Fig.1). Such imaging modalities include bright-field and fluorescence microscopy, in which the former can capture the overall morphology of the cells, while the latter can image various fluorescent biomarkers. One advantage of using bright-field images in HCS is its ability to acquire a photographic record of cells without any extra preparation while fluorescence images require time-consuming cell fixation and staining procedures. Another advantage of the bright-field image method is its ability to capture the dynamics of cells because cell fixation and cell staining are not required (Fig.1 lower row).” See also pages 3-4 section 2.1 Data, it uses a bright field imager “Each well was imaged with the Operetta CLSTM high content analysis system equipped with an high resolution 14bit CCD camera for cell imaging and the Harmony 3.5 software.” Lee)
It would have been obvious to one of ordinary skill in the art before the effective filing
date of the claimed invention to combine the teachings of Yakimovich with the teachings of Lee to use a bright field imager as the imager. The modification would have been motivated by the desire to: have less time consuming procedures (more time efficient and without extra preparation) and have the ability to capture dynamics of the cells without having to stain or fix the cells , therefore it is an improvement, as suggested by Lee (See fig. 1 and page 2 paragraph 2 “…One advantage of using bright-field images in HCS is its ability to acquire a photographic record of cells without any extra preparation while fluorescence images require time-consuming cell fixation and staining procedures. Another advantage of the bright-field image method is its ability to capture the dynamics of cells because cell fixation and cell staining are not required (Fig.1 lower row).” Lee)
As per claim 6, Yakimovich in view of Lee teaches “The method according to claim 4, wherein the imager is a bright-field imager.” (See fig. 1 and page 2 paragraph 2 “In HCS, multiple imaging modalities are commonly used together to image various aspects of the cell phenotypes (Fig.1). Such imaging modalities include bright-field and fluorescence microscopy, in which the former can capture the overall morphology of the cells, while the latter can image various fluorescent biomarkers. One advantage of using bright-field images in HCS is its ability to acquire a photographic record of cells without any extra preparation while fluorescence images require time-consuming cell fixation and staining procedures. Another advantage of the bright-field image method is its ability to capture the dynamics of cells because cell fixation and cell staining are not required (Fig.1 lower row).” See also pages 3-4 section 2.1 Data, it uses a bright field imager “Each well was imaged with the Operetta CLSTM high content analysis system equipped with an high resolution 14bit CCD camera for cell imaging and the Harmony 3.5 software.” Lee)
It would have been obvious to one of ordinary skill in the art before the effective filing
date of the claimed invention to combine the teachings of Yakimovich with the teachings of Lee to use a bright field imager as the imager. The modification would have been motivated by the desire to: have less time consuming procedures (more time efficient and without extra preparation) and have the ability to capture dynamics of the cells without having to stain or fix the cells , therefore it is an improvement, as suggested by Lee (See fig. 1 and page 2 paragraph 2 “…One advantage of using bright-field images in HCS is its ability to acquire a photographic record of cells without any extra preparation while fluorescence images require time-consuming cell fixation and staining procedures. Another advantage of the bright-field image method is its ability to capture the dynamics of cells because cell fixation and cell staining are not required (Fig.1 lower row).” Lee)
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Yakimovich in view of Lee and further in view of Itu et. al., hereafter Itu (US Publication No. 20180336319 A1) .
As per claim 3, Yakimovich in view of Lee already teaches “the method according to claim 1, further comprising determining from image data relating to features in addition to plaques… the presence or lack of plaques based on the features in addition to plaques.”, however Yakimovich in view of Lee does not teach “and using machine learning to predict the presence or lack of plaques based on the features in addition to plaques”
Itu teaches “and using machine learning to predict the presence or lack of plaques based on the features in addition to plaques”” (See paragraph 6 and 9 “Then, the machine learning models are trained to predict measures of interest related to atherosclerotic plaque using the measures of interest from the output data, the geometric features, and the plaque-related features.” “[0009] In some embodiments, multiple machine learning models may be used with the aforementioned method. For example, in one embodiments, the machine learning models comprise a first machine model trained to predict plaque formation,” Itu)
It would have been obvious to one of ordinary skill in the art before the effective filing
date of the claimed invention to combine the teachings of Yakimovich with the teachings of Lee and Itu to apply machine learning to detect plaques based on features. The modification would have been motivated by the desire to have better treatment planning and predict risks, therefore it is an improvement, as suggested by Itu (See paragraph 12 “One or more machine learning models are used to predict an effect of a treatment plan using the geometric features of interest and plaque related features of interest, wherein the machine learning models are trained using patient-specific features and longitudinal data related to effects of treatment plans.” See also paragraph 38 “More specifically, the techniques described herein use ML models to predict measures of interest related to plaque such as risk of a cardiovascular event, indication of a future screening date, plaque composition (absolute/relative values of plaque components), plaque evolution related measure of interest (future size, shape, composition and location of plaques), in-stent restenosis, lesions requiring sealing, therapy planning, etc. ”)
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DYLAN J MENDEZ MUNIZ whose telephone number is (703)756-5672. The examiner can normally be reached M-F, 8AM - 5PM ET.
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/DYLAN JOHN MENDEZ MUNIZ/Examiner, Art Unit 2675 /ANDREW M MOYER/Supervisory Patent Examiner, Art Unit 2675