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 .
Response to Arguments
Applicant’s arguments have been fully considered and are persuasive. With respect to the rejections under 35 U.S.C. 102 and 103, Applicant argues that limitations that have been newly added to claim 55 by the instant amendment are not taught by the prior art of record. The examiner agrees and therefore has withdrawn the rejections. However, new grounds of rejection are set forth below. The rejection of claim 62 under 35 U.S.C. 112(b) is overcome by the amendment to claim 62 and is therefore withdrawn.
Information Disclosure Statement
The information disclosure statements (IDSs) submitted on November 20, 2024, August 27, 2025, December 12, 2025, January 21, 2026, May 4, 2026 and July 2, 2026 meet the requirements of 37 CFR 1.97 and 1.98 and therefore have been considered by the examiner and placed in the file.
Claim Interpretation
The claims in this application are given their broadest reasonable interpretation (BRI) using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The BRI of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification.
In the following, some of the terms in the claims have been given BRIs in light of the specification. These BRIs are used for purposes of searching for prior art and examining the claims, but cannot be incorporated into the claims. Should Applicant believe that different interpretations are appropriate, Applicant should point to the portions of the specification that clearly support a different interpretation.
Claim Rejections - 35 USC § 103
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 55-57, 59-63, 65-67, 69, 70 and 72-74 are rejected under 35 U.S.C. 103 as being unpatentable over WIPO Publication No. WO 2019/199579 A1 to Wang et al. (hereinafter referred to as “Wang”) in view of an article entitled “Whole-brain tissue mapping toolkit using large-scale highly multiplexed immunofluorescence imaging and deep neural networks”, by Dragan et al., published March 10, 2021 in Nature Communications, 12, 1550 (hereinafter referred to as “Dragan”).
Regarding claim 55, Wang discloses a method, comprising:
(a) receiving a plurality of images of a sample comprising an amplicon with a barcode molecule associated therewith (para. [0004], the in situ tissue samples have amplicons fixed thereto that comprise barcode sequences; para. [0099]-[00113] discuss different imaging modalities that are suitable for obtaining images of the samples: “[t]he methods disclosed include imaging the one or more hydrogel-embedded amplicons using any of a number of different types of microscopy, e.g., confocal microscopy, two- photon microscopy, light-field microscopy, intact tissue expansion microscopy, and/or CLARITY™-optimized light sheet microscopy (COLM)”; para. [0058] discusses adding the barcode to the sample during the amplification process that generates the amplicon);
(b) measuring a multi-channel fluorescent signal of said barcode molecule for each image of said plurality of images, to thereby yield a plurality of multi-channel fluorescent signals (para. [00150] discusses a multi-channel measurement of optical signals (i.e., at least four color channels) and paras. [0087] and [00114]-[00115] are examples of portions of Wang that discuss that the signals that are detected are fluorescent signals);
(c) computer processing said plurality of multi-channel fluorescent signals to identify said barcode sequence (para. [0058] discusses identifying the barcode sequence of the amplicon to thereby identify the target nucleic acid of the amplicon; paras. [00124]-[00128] discuss the processor unit that performs the method), wherein said computer processing comprises subtracting an estimated carry-over signal from a previous imaging cycle from said plurality of multi-channel fluorescent signals (Wang does not explicitly disclose subtracting an estimated carry-over signal from a previous imaging cycle from said plurality of multi-channel fluorescent signals); and
(d) upon identifying said barcode sequence, identifying said amplicon (para. [0058] discusses identifying the barcode sequence of the amplicon to thereby identify the target nucleic acid of the amplicon).
As indicated above, Wang does not explicitly disclose subtracting an estimated carry-over signal from a previous imaging cycle from said plurality of multi-channel fluorescent signals.
Dragan, in the same field of endeavor, discloses subtracting an estimated carry-over signal from a previous imaging cycle from said plurality of multi-channel fluorescent signals (Dragan discloses a method for estimating the carry-over signal, which is referred to in Dragan as a “spectral bleed-through” signal, from the previous cycle and subtracting it from the multi-channel fluorescent signals to correct for the spectral bleed-through, page, 3, Results section: “[n]ext, we developed an efficient semi-supervised sparse linear spectral unmixing algorithm to correct for spectral bleed-through16, and cross-labeling17 (Fig. 3c) as detailed in Methods section”. This estimation method and subtraction process are described in detail from the bottom of page 9 through the top of page 10 with reference to equations (1) and (2). These equations are used in an optimization algorithm that estimates a bleed-through channel fraction, αc’, and then subtracts it from the original channel signals: “[o]ptimization algorithm will solve for αc’… and subtract the fraction of non-specific signal from the original channel”).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the present disclosure, to use the carry-over signal estimation and subtraction method of Dragan in the system and method of Wang to eliminate errors associated with bleed-through as taught by Dragan. One of ordinary skill in the art would have been motivated to make the modification to remove optical noise and thereby reduce sequencing errors. The modification could have been made by one of ordinary skill in the art before the effective filing date of the present disclosure with a reasonable expectation of success because making the modification merely involves combining prior art elements according to known methods to yield predictable results (suitable software to implement the optimization algorithm of Dragan in the system and method of Wang).
Regarding claim 56, Wang discloses that step (c) of claim 55 comprises for each image of said plurality of images, determining an identity of said barcode molecule by
(i) determining a signal in a channel of said multi-channel fluorescent signal,
(ii) using said signal to determine a portion of an identity of said barcode molecule, and
(iii) repeating (i) and (ii) for each other image of said plurality of images, thereby determining a sequence of said barcode molecule (paras. [00147]-[00171] disclose that during the experiment the process of determining the barcode sequence was an iterative process of acquiring image signals, measuring the acquired image signals, registering the images, and processing the registered images until the entire barcode sequence has been identified).
Regarding claim 57, Wang discloses using a machine learning algorithm to perform a segmentation process that processes the fluorescent signals to identify the barcode molecule (para. [00186]).
Regarding claim 59, the claim recites that the plurality of images is acquired over a time period of at least 3 days. The present specification makes no reference to image acquisition occurring over any particular time period, much less over a time period of at least 3 days. Para. [0179] of the present specification describes the final results of the method being obtained in 3 or 4 days, but the method involves steps in addition to the image acquisition step. For these reasons, the BRI for this limitation is that it means that the result obtained in step (d) of claim 1 is the result of performing the method over a period of time of at least 3 days. Wang discloses this limitation (para. [00129]: “”[e]xamples of advantages of the methods described herein include efficiency, where it takes merely 3 or 4 days to obtain final data from a raw sample….”).
Regarding claim 60, Wang discloses that the signal is a fluorescent wavelength or a fluorescent intensity (paras. [0087] and [00114]-[00115] are examples of portions of Wang that discuss that the signals that are detected are fluorescent signals; fluorescent signals having both fluorescent wavelengths and fluorescent intensity, as is known in the art).
Regarding claim 61, Wang discloses that after identifying a barcode sequence, identifying a nucleic acid molecule based the identified barcode sequence (para. [0058]: “the second oligonucleotide includes a barcode sequence, wherein the barcode sequence of the second oligonucleotide provides barcoding information for identification of the target nucleic acid…Barcode sequences can be linked to a target nucleic acid of interest during amplification and used to trace back the amplicon to the cell from which the target nucleic acid originated. A barcode sequence can be added to a target nucleic acid of interest….”).
Regarding claim 62, Wang discloses that identifying the barcode sequence comprises using a closest codebook entry (para. [00151]: “Dots were first filtered based on quality score. The quality score quantified the extent to which each dot on each sequencing round came from one color rather than a mixture of color. The barcode codebook was converted into colorspace, based on the expected color sequence following 2-base encoding of the barcode DNA sequence. Dot color sequences that passed the quality threshold and matched sequences in the codebook were kept, and identified with the specific gene that that barcode represented; all other dots were rejected. The high quality dots and associated gene identities in the codebook were then saved out for downstream analysis.”).
Regarding claim 63, Wang discloses that the sample is an in situ tissue (para. [0004]: “[t]he present disclosure provides a method for in situ gene sequencing of a target nucleic acid in a cell in an intact tissue….”).
Regarding claim 65, Wang discloses that each image of the plurality of images uses a different channel of said multi-channel fluorescent signal (paras. [00149]-[00151] disclose that in the four-color-channel experimental setup, each fluorescent image uses a different color channel where the images are represented by respective dots (each dot corresponding to a 7-pixel diameter channel)).
Regarding claim 66, the BRI for the term “applying configuration parameters”, based on para. [0003] of the present specification, is that it means applying one or more of an encoding scheme, a codebook, image acquisition parameters, and sample metadata. Wang discloses this limitation (para. [00151] discusses converting the barcode codebook color space based on 2-base encoding; see also para. [00173] discussing applying 2-base encoding for error correction; see also para. [00182] discussing applying I-base encoding).
Regarding claim 67, under MPEP 2111.04, Claim scope is not limited by claim language that suggests or makes optional but does not require steps to be performed. In addition, when a claim requires selection of an element from a list of alternatives, the prior art teaches the element if one of the alternatives is taught by the prior art. See, e.g., Fresenius USA, Inc. v. Baxter Int’l, Inc., 582 F.3d 1288, 1298, 92 USPQ2d 1163, 1171 (Fed. Cir. 2009). The claim limitation “configuration parameters comprise an encoding scheme, a codebook, image acquisition parameters, or sample metadata” is is interpreted as requiring any one or more of the listed items. Wang expressly discloses at least the encoding scheme list item and the codebook list item (para. [00151] discusses converting the barcode codebook color space based on 2-base encoding; see also para. [00173] discussing applying 2-base encoding for error correction; see also para. [00182] discussing applying I-base encoding).
Regarding claim 69, Wang discloses prior to receiving the plurality of images of the sample comprising the amplicon with the barcode molecule associated therewith, registering said plurality of images (para. [00149], under the image registration heading, registering the plurality of images is discussed, which occurs prior to receiving and processing the images to identify the barcode molecule).
Regardinjg claim 70, Wang discloses that the identifying step comprises sequencing because the barcode comprises a sequence (para. [0058]) that is decoded via a sequencing process to identify the barcode sequence (paras. [00147]-[00171] discuss imaging and sequencing processes that are performed to identify the barcode molecule).
Regarding claim 72, for the reasons stated above in the rejection of claim 67, the BRI for this claim is that the claim requires any one or more of the recited alternatives. (Wang discloses that the plurality of images further comprises morphological information, para. [0079], “the improved sequencing-by-ligation method herein includes operating at room temperature for best preservation of tissue morphology with low background noise and error reduction”; paras. [0032], [0044], [0085], [00134] and [00136] disclose that the plurality of images comprises sequential readout amplicon data).
Regarding claim 73, Wang discloses that prior to receiving and processing the images of the samples comprising the amplicons with barcode molecules, a cell segmentation process is performed that segments the sample into a plurality of images of single cells of the sample (paras. [00152]-[00153] discuss 2D cell segmentation of the images followed by single-cell processing of the segmented image data).
Regarding claim 74, Wang discloses that the segmenting includes semi-manual segmenting of the plurality of images (para. [00152] discloses that the 2D cell segmenting of the image data is semi-manually performed based on the maximum intensity projection of the DAPI channel following the final round of sequencing).
Claim 58 is rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of Dragan and further in view of U.S. Publ. Appl. No. 2022/0084629 A1 to Shah (hereinafter referred to as “Shah”).
Regarding claim 58, Wang does not explicitly disclose using a machine learning algorithm to perform the image registration process. Shah, in the same field of endeavor, discloses using a machine learning algorithm to perform a variety of tasks including image registration (Shah, para. [0190]). It would have been obvious to one of ordinary skill in the art, before the effective filing date of the present disclosure, to substitute the image registration machine learning algorithm of Shah for the registration algorithm of Wang. One of ordinary skill in the art would have been motivated to make the modification to take advantage of the well-known benefits of using machine learning algorithms in image processing/analysis applications to improve the robustness of the registration algorithm, thereby reducing barcode decoding and identification errors as taught by Shah. The modification could have been made by one of ordinary skill in the art before the effective filing date of the present disclosure with a reasonable expectation of success because making the modification merely involves combining prior art elements according to known methods to yield predictable results (modifying and/or replacing software executed by the processor of Wang that performs image registration).
Claim 68 is rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of Dragan and further in view of U.S. Publ. Appl. No. 2024/0254545 A1 to Wang et al. (hereinafter referred to as “Wang 2”).
Claim 68 recites performing several preprocesses that are well known in the art. Merging of overlapping fields of view of images is performed as a normal part of the image registration process. Wang discloses performing an image registration process during which overlapping fields of view of the images are merged in order to register and align the image data (paras. [00149]-[00152]). Wang also discloses performing preprocessing filtering to remove optical aberrations in cases where a fluorescence microscope is used for image acquisition (para. [00106]). Although Wang does not explicitly disclose using deconvolution and background subtraction, these preprocesses are commonly used in the art.
Wang 2, in the same field of endeavor, discloses performing deconvolution of image data as a preprocess to the amplicon decoding process (para. [0326]).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the present disclosure, to apply the preprocesses of deconvolution as taught by Wang 2 in conjunction with the merging and filtering preprocesses disclosed in Wang. One of ordinary skill in the art would have been motivated to make the modification to reduce optical distortion and remove noise in the image data that can lead to errors in barcode decoding and amplicon identification. The modification could have been made by one of ordinary skill in the art before the effective filing date of the present disclosure with a reasonable expectation of success because making the modification merely involves combining prior art elements according to known methods to yield predictable results (employing known preprocesses in combination with one another to reduce or eliminate barcode decoding and amplicon identification errors).
Claim 71 is rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of Dragan and further in view of U.S. Publ. Appl. No. 2023/0238078 A1 of Gonzalez Lozano et al. (hereinafter referred to as “Lozano”).
Wang does not explicitly disclose that the computer processing is performed on a cloud. Lozano discloses using a cloud computing system to process image data sets comprising molecular measurement data of a biological sample (paras. [0482]-[0483]). It would have been obvious to one of ordinary skill in the art, before the effective filing date of the present disclosure, to use a cloud computing system as the computing system of Wang to enable the computer processing of Wang to be performed in the cloud as taught by Lozano. A person of ordinary skill in the art would have been motivated to make the modification to take advantage cloud-based resources such as data centers that employ processors equipped with artificial intelligence (AI). The modification could have been made by one of ordinary skill in the art before the effective filing date of the present disclosure with a reasonable expectation of success because making the modification merely involves combining prior art elements according to known methods to yield predictable results (moving on-premises operations to a cloud-based data center).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
An article entitled “Bleed-through correction for rendering and correlation analysis in multi-colour localization micros”, by Kim et al., published July 14, 2015 in HHS Public Access J Opt. 2013 September; 15(9): . doi:10.1088/2040-8978/15/9/094011, discloses a method of bleed-through correction applicable to the rendering and correlation analysis of multi-colour localization microscopy images. The method of bleed-through correction relies on obtaining correct numbers of each species within a sufficiently large area (i.e. within pixels of order tens of nanometers in size), given the rates of bleed-through are provided. The Pearson correlation coefficient is used as a measure of the correction accuracy, and compared its pre- and post-correction values to determine the accuracy and applicability of our bleed-through correction.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DANIEL J SANTOS whose telephone number is (571)272-2867. The examiner can normally be reached M-F 9-5.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Matt Bella can be reached at (571)272-7778. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DANIEL J. SANTOS/Examiner, Art Unit 2667
/MATTHEW C BELLA/Supervisory Patent Examiner, Art Unit 2667
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