DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of the Claims
Claims 1-20 are pending.
Claims 1-20 are rejected.
Priority
This application filed July 23, 2021 claims benefit to US provisional 63/055,864 filed July 23, 2020.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 05/08/2023 and 12/20/2023 are in compliance with the provisions of 37 CFR 1.97 and considered. A signed copy of the corresponding 1449 form has been included with this Office action.
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.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim Analysis
In accordance with MPEP § 2106, claims found to recite statutory subject matter are then analyzed to determine if the claims recite any concepts that equate to an abstract idea, law of nature or natural phenomenon (Step 2A, Prong 1).
Framework with which to Evaluate Subject Matter Eligibility:
Step 1: Are the claims directed to a process, machine, manufacture, or composition of matter;
Step 2A, Prong One: Do the claims recite a judicially recognized exception, i.e., a law of nature, a natural phenomenon, or an abstract idea;
Step 2A, Prong Two: If the claims recite a judicial exception under Prong One, then is the judicial exception integrated into a practical application; and
Step 2B: If the claims do not integrate the judicial exceptions, do the claims provide an inventive concept?
Framework Analysis on the Instant Claims:
Step 1:
With respect to Step 1: claims 1-20 are directed to a system, i.e., a process, machine, or manufacture within the above 35 U.S.C. 101 categories [Step 1: YES; See MPEP § 2106.03]
Step 2A, Prong One:
With respect to Step 2A, Prong One, the claims recite judicial exceptions in the form of abstract ideas [see MPEP § 2106.04(a)(2)]. Under the Step 2A, Prong One evaluation, the claims found to recite abstract ideas that fall into the grouping mental steps and mathematical concepts (in particular mathematical relationships and correlations) are as follows:
Independent claims 1, 11, and 17:
Mental steps:
grouping the plurality of sequence reads into bins
identifying a subset of barcode sequences from the bins
removing the subset of barcode sequences
a percentage of correction events in the bin meets a pre-set criterion
Dependent claims 2, 12 and 18:
Mental step:
Identifying a first subset of cells from the second dataset of sequence reads
Dependent Claims 4 and 19:
Mental step:
Ranking barcodes in the second dataset based on molecular counts
determining a threshold value of molecular counts
Dependent Claims 5, 15, and 20:
Mental step:
Identifying a second subset of cells form the third dataset of sequence reads
Dependent Claims 8 and 16:
Mental step:
Bin is placed into the subset of barcode sequences
Dependent Claim 13:
Mental step:
Ranking barcodes in the second dataset
Dependent Claim 14:
Mental step:
determining a threshold value of molecular counts
Dependent claims 3, 6-7, and 9-10 recite further steps that limit the judicial exceptions in independent claims 1, 11, 17, and certain stemming dependent claims, and as such, are also directed to those abstract ideas. For example, claim 3 further limits the parameters of independent claim 1 by specifying the correction event percentage.
These recitations are similar to the concepts of collecting information, analyzing it and displaying certain results of the collection and analysis in Electric Power Group, LLC, v. Alstom (830 F.3d 1350, 119 USPQ2d 1739 (Fed. Cir. 2016)), organizing and manipulating information through mathematical correlations in Digitech Image Techs., LLC v Electronics for Imaging, Inc. (758 F.3d 1344, 111 U.S.P.Q.2d 1717 (Fed. Cir. 2014)) and comparing information regarding a sample or test to a control or target data in Univ. of Utah Research Found. v. Ambry Genetics Corp. (774 F.3d 755, 113 U.S.P.Q.2d 1241 (Fed. Cir. 2014)) and Association for Molecular Pathology v. USPTO (689 F.3d 1303, 103 U.S.P.Q.2d 1681 (Fed. Cir. 2012)) that the courts have identified as concepts that can be practically performed in the human mind or mathematical relationships. Therefore, these limitations fall under the “Mathematical concepts” groupings of abstract ideas. The abstract ideas recited in the claims are evaluated under the Broadest Reasonable Interpretation (BRI). When read in light of and consistent with the specification, the claims are determined to be directed to mental processes that in the simplest embodiments are not too complex to practically perform in the human mind. Additionally, the recited limitations that are identified as judicial exceptions from the mathematical concepts grouping of abstract ideas are abstract ideas irrespective of whether or not the limitations are practical to perform in the human mind. The instant claims must therefore be examined further to determine whether they integrate the abstract idea into a practical application. [Step 2A, Prong 1: YES; See MPEP § 2106.04].Step 2A, Prong Two:
Claims found to recite a judicial exception under Step 2A, Prong 1 are then further analyzed to determine if the claims as a whole integrate the recited judicial exception into a practical application or not (Step 2A, Prong 2). This judicial exception is not integrated into a practical application because the claims do not recite an additional element that reflects an improvement to technology or applies or uses the recited judicial exception to effect a particular treatment for a condition. Rather, the instant claims recite additional elements that amount to mere instructions to implement the abstract idea in a generic computing environment or mere instructions to apply the recited judicial exception via a generic treatment. Specifically, the claims recite the following additional elements:
Independent Claims 1, 11, and 17:
Receiving a first dataset
Generating an output comprising second dataset of sequence reads
There are no limitations that indicate that the claimed analysis engine or the formats of the provided data require anything other than generic computing systems. As such, these limitations equate to mere instructions to implement the abstract idea on a generic computer that the courts have stated does not render an abstract idea eligible in Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984. The steps for treating the tumor cells with a drug or known or available treatment or with a treatment targeting a mutated element common to the tumor cells do not recite a “particular” treatment as there is no indication of the type of drug or treatment that is applied that would have more than a nominal or insignificant relationship to the exception. Rather, these limitations equate to a step of “administering a suitable medication to the tumor cells” that merely apply the exception in a generic way and do no integrate the recited exception into a practical application (see MPEP 2106.04(d)(2)). As such, claims 1, 11, and 17 directed to an abstract idea/law of nature/natural phenomenon (Step 2A, Prong 2: NO).
Step 2B
According to analysis so far, the additional elements described above do not provide
significantly more than the judicial exception. A determination of whether additional elements provide significantly more also rests on whether the additional elements or a combination of elements represents other than what is well-understood, routine, and conventional.
Conventionality is a question of fact and may be evidenced as: a citation to an express statement in the specification or to a statement made by an applicant during prosecution that demonstrates a well-understood, routine or conventional nature of the additional element(s); a citation to one or more of the court decisions as discussed in MPEP 2106(d)(II) as noting the well-understood, routine, conventional nature of the additional element(s); a citation to a publication that demonstrates the well-understood, routine, conventional nature of the additional element(s); and/or a statement that the examiner is taking official notice with respect to the well-understood, routine, conventional nature of the additional element(s) (WURC).
With respect to the instant claims, the courts have found that receiving and outputting data are well-understood, routine, and conventional functions of a computer when claimed in a merely generic manner or as insignificant extra-solution activity (see Symantec, 838 F.3d at
1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information),
buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014)
(computer receives and sends information over a network), Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015), and OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93, as discussed in MPEP 2106.05(d)(II)(i)).
As such, the claims simply append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception (MPEP2106.05(d)). The data gathering steps as recited in the instant claims constitute a general link to a technological environment which is insufficient to constitute an inventive concept which would render the claims significantly more than the judicial exception (MPEP2106.05(g)&(h)).
With respect to claims 1, 11, and 17, and those claims dependent therefrom, the computer-related elements or the general-purpose computer do not rise to the level of significantly more than the judicial exception. The claims state nothing more than a generic computer which performs the functions that constitute the judicial exceptions. Hence, these are mere instructions to apply the judicial exceptions when using a computer, which the courts have found to not provide significantly more when recited in a claim with a judicial exception (see MPEP 2106.06(A)).
The additional elements do not comprise an inventive concept when considered individually or as an ordered combination that transforms the claimed judicial exception into a patent-eligible application of the judicial exception. Therefore, the claims do not amount to significantly more than the judicial exception itself [Step 2B: NO; See MPEP § 2106.05].
As such, claims 1-20 are not patent eligible.
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.
Claims 1, 3-4, 6-9, 11, 16-17, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al., Molecular Cell (2019), in view of Zhou et al., BMC Bioinformatics (2008).
Regarding claims 1, 11, and 17:
Zhang does not teach “grouping the plurality of sequence reads into bins, wherein each bin comprises sequence reads that share a common barcode sequence”
Zhang teaches:
a method for removing aggregates from a dataset, the method comprising: receiving a first dataset comprising a plurality of sequence reads (page 133, column 1, para 3, lines 1-5: The pipeline package is freely available online [...] for download. It was designed to accept paired-end sequencing data with one end (read 1);
identifying a subset of barcode sequences from the bins, wherein a bin is placed into the subset of barcode sequences when a percentage of correction events in the bin meets a pre-set criterion for such a percentage, wherein a correction event occurs if a sequence read differs in one nucleotide from one or more other sequence reads in the bin (page 133, column 2, section: Quality of Primers on Beads, para 2, lines 7-11: We aggregated the cell barcodes within 1 Hamming distance. For each valid cell barcode, the proportion of the corrected reads (which contains errors in raw barcode sequences) to the total reads after correction is calculated as the cell barcode error rate.; Page e3, section Barcode correction, lines 4-7: Specifically, the raw barcodes are sorted by abundance, and cell barcodes within 1-bp mismatch are aggregated into the consensus barcode with higher read counts. After the aggregation, each cell barcode consists of the original reads and corrected (but containing barcode errors) reads. The proportion of the corrected reads relative to the total reads for each barcode is calculated and defined as the cell barcode error rate.); removing the subset of barcode sequences from the first dataset to obtain a second dataset of sequence reads (page 133, para 3, lines 6-8: After removing cell barcodes with read counts that are too low (miscellaneous barcodes), the pipeline corrects cell barcode errors) and page 135, column 2, lines 3-5, page 136, column 1, lines 1-3: To further remove possible artifacts caused by barcode errors, we checked the similarity of expression profiles between similar cell barcodes. If the expression profile of a cell barcode was markedly different from its closest cell barcode neighbor (Spearman’s correlation % 0.6; see STAR Methods), we discarded the barcode (Figure 3E; see STAR Methods).); and generating an output comprising the second dataset of sequence reads (para 2, lines 10-14: we developed a versatile pipeline that accepts data from all of these systems and generates matrices of UMI counts (Figure 1C). We applied this pipeline to our data and conducted comparisons on sensitivity, precision, and bias in an objective way.).
Zhou teaches:
grouping the plurality of sequence reads into bins, wherein each bin comprises sequence reads that share a common barcode sequence (page 7 of 11, column 2, para 2, lines 1-3: We have applied a clustering algorithm (see METHODS section) for binning sequence fragments together based on their barcode similarities)
Regarding Claim 3;
Zhang teaches:
wherein a bin is placed into the subset of barcode sequences (page 133, column 1, para 3, lines 9-11: errors may have been introduced during on-bead primer synthesis and also during PCR or sequencing steps. Reads from the same cell barcodes are aggregated) when at least 50% of total sequence reads in the bin have had a correction event (page 133, column 2, para 3, lines 14-18: more than half of the cell barcodes contained obvious mismatches in the other two systems. Specifically, about 10% of Drop-seq beads contained a one-base deletion in cell barcodes, which also required extra care during data analysis)
Regarding Claims 4 and 19:
Zhang teaches:
further comprising ranking barcodes in the second dataset based on molecular counts of each barcode in the second dataset (page 153, Figure 3D: The number of UMIs with cell barcode ranked by read counts) and determining a threshold value of molecular counts for selecting barcodes using a pre-set percentile of ranked barcodes in the second dataset (page e3, section Determination of valid cell barcodes, para 1, lines 6-7: We also followed the method used in the of 10X’s pipeline (Cell Ranger), which set a threshold for UMIs of cells.), wherein any barcodes in the second dataset having a molecular count above the threshold value are selected to obtain a third dataset of sequence reads for cell calling (page e3, section Determination of valid cell barcodes, para 1, lines 8-12: The resulting estimated cell number is referred to as the UMI (1/10). We also observed a distinct knee point on a plot of log-transformed barcode rank and barcode reads (Figure 2D). We generated the derivation of the plot of log-transformed barcode rank and barcode reads (Figure S3A) for 10X samples, and observed a sharp cliff around the estimated cell numbers.).
Regarding Claim 6:
Zhang teaches:
The method of claim 4, wherein the pre-set percentile of ranked barcodes is the 1st percentile barcode of ranked barcodes (page e3, section Determination of valid cell barcodes, para 1, lines 7-8: The hypothesis is that the top 1% of cells contains about 10 times as many UMIs as a typical cell.)
Regarding Claim 7:
Zhang teaches:
The method of claim 4, wherein the threshold value is 10 percent of a molecular count of the 1st percentile barcode of ranked barcodes (page e3, section Determination of valid cell barcodes, para 1, lines 7-8: The hypothesis is that the top 1% of cells contains about 10 times as many UMIs as a typical cell. The resulting estimated cell number is referred to as the UMI (1/10)).
Regarding Claim 8 and 16:
Zhang teaches:
The method of claim 1, wherein the bin is placed into the subset of barcode sequences when (a) a percentage of correction events in the bin meets a pre-set criterion for such a percentage; and (b) a number of total sequence reads in the bin exceeds or equals to a pre-set threshold of total sequence reads (page 133, column 2, section Quality of Primers on Beads, para 2, lines 8-18: . For each valid cell barcode, the proportion of the corrected reads (which contains errors in raw barcode sequences) to the total reads after correction is calculated as the cell barcode error rate (Figure 2B), which reflects the general quality of on-bead DNA primers. 10X beads showed few mismatches in cell barcodes, indicating good quality control in bead fabrication. In contrast, more than half of the cell barcodes contained obvious mismatches in the other two systems. Specifically, about 10% of Drop-seq beads contained a one-base deletion in cell barcodes, which also required extra care during data analysis (see STAR Methods).
Regarding Claim 9:
Zhang teaches:
The method of claim 8, wherein the pre-set threshold of the number of total sequence reads is 10,000 total sequence reads (page 137, column 2, section Saturation of Sensitivity and Precision at Low Sequencing Depth, para 2, lines 1-5: All of the systems show diminishing returns at higher depths. For more sensitive methods, it is possible to detect the same level of UMIs with fewer reads. All three methods can reach a threshold of 1,000 UMIs with fewer than 10K reads. 10X can detect 10,000 UMIs with about 20K reads as a median.).
Case for prima facie obviousness:
In KSR Int 'l v. Teleflex, the Supreme Court, in rejecting the rigid application of the teaching, suggestion, and motivation test by the Federal Circuit, indicated that “The principles underlying [earlier] cases are instructive when the question is whether a patent claiming the combination of elements of prior art is obvious. When a work is available in one field of endeavor, design incentives and other market forces can prompt variations of it, either in the same field or a different one. If a person of ordinary skill can implement a predictable variation, § 103 likely bars its patentability.” KSR Int'l v. Teleflex lnc., 127 S. Ct. 1727, 1740 (2007).
Applying the KSR standard of obviousness to Zhang in view of Zhou represents combining prior art elements according to known methods to yield predictable results. We conclude the combination of identifying and correcting/removing cell barcodes from an input of sequences and binning them based on similarity would yield the output of similar cell barcodes in one group (i.e. the “second dataset” of sequences as described in the instant claims 1, 11, and 17). Both Zhang and Zhou were directed to optimizing barcode accuracy and sequence readouts and further, Zhang specifically tested the 10X Genomics Chromium RNA-seq system (applicant’s system and included in the information disclosure statement). Zhang’s goal was to compare three droplet-based ultra-high-throughput single-cell RNA-seq systems using a unified bioinformatics pipeline. This pipeline consisting of barcoding/tagging, sequencing, demultiplexing, and UMI counting. Zhang incorporated barcode correction into the demultiplexing and UMI steps but did not bin these subsets into different groups to differentiate them. Zhou utilizes a metagenome binning algorithm by combining the CLUMP program (accurate in identifying core elements of each cluster) with a K-means based clustering approach (which is disclosed in the instant spec, para [00102]) to identify initial clusters based on barcode similarities (page 10 of 11, column 1, section: Metagenome binning algorithm).
One of skill in the art of genetics would have been motivated to apply the pipeline of Zhang to the binning algorithm of Zhou, to create a streamlined way of identifying similar barcode sequences across sequence data to ensure accurate detection of single-cell-associated barcodes. One of skill in the art before the effective filing date of the claimed invention would have had a reasonable expectation of success at performing the workflow and methods of Zhang with the metagenome binning algorithm of Zhou because this combination would have been expected to have provided better determination of valid cell and result in more precise barcode detection.
Therefore, the invention would have been prima facie obvious to one of skill in the art before the effective filing date of the application, absent evidence to the contrary.
Conclusion
No claims allowed.
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Any inquiry concerning this communication or earlier communications from the examiner should be directed to KRITHIKA R KARUNAKARAN whose telephone number is (571)272-5527. The examiner can normally be reached M-F 9am-5:30pm EST.
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/K.R.K./Examiner, Art Unit 1686
/LARRY D RIGGS II/Supervisory Patent Examiner, Art Unit 1686