DETAILED ACTION
Notice of 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 .
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 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.
Status of the Claims
Claims 9-11, 15-18, 23-24, 26-30, 33-34 and 37-97 are canceled.
Claims 1-8, 12-14, 19-22, 25, 31-32 and 35-36 are pending.
Claims 1, 19, 22, 25 and 36 are objected to.
Claims 1-8, 12-14, 19-22, 25, 31-32 and 35-36 are rejected.
Priority
This application US 18/025,603 (03/09/2023) is a 371 of PCT/US2021049923 (09/10/2021) which claims benefit of US Application 63/076,820 (09/10/2020) as reflected in the filing receipt mailed on 06/04/202. The claims to the benefit of priority are acknowledged and the effective filing date of claims 1-8, 12-14, 19-22, 25, 31-32 and 35-36 is 09/10/2020.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 08/07/2023 was considered.
Drawings
The drawings are objected to as failing to comply with 37 CPR 1.84(p)(5) because they include illegible labels in Fig. 17 and Fig. 18A-B.
Corrected drawing sheets in compliance with 37 CPR 1.121 (d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as "amended." If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either "Replacement Sheet" or "New Sheet" pursuant to 3 7 CPR 1.121 (d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim objections
Claim 1 is objected because the recited "based at least in part on" should read "based, at least in part, on" for proper punctuation.
Claims 19, 22 and 25 are objected to because colons should begin lists in which list elements are separated by newlines, e.g. claim 19 "in part by:" should be followed elements separated by newlines, and the same applies in claims 22 and 25. As set forth in 37 CPR 1.75, each element or step of the claim should be separated by a line indentation (608.01(m) Form of Claims). Sub-steps / elements should be indented from their parent step / element. This rule should be applied throughout the claims as needed.
Claim 36 is objected because the recited "determining a maximum likelihood h-mer length" should read "determining a maximum likelihood for a h-mer length" for clarity.
Appropriate correction is required.
Claim Rejections - 35 USC § 112(b)
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.
Claims 1-8, 12-14, 19-22, 25, 31-32 and 35-36 are rejected under 35 U.S.C. 112(b)as being indefinite for failing to particularly point out and distinctly claim the subject matter the invention. Dependent claims are rejected similarly, unless otherwise noted below. The following issues cause the respective claims to be rejected under 112(b) as indefinite:
In claim 1, the relationship is unclear between the recited "(c) … the estimated likelihoods from (b)" and "(b) applying a trained algorithm to … estimate a likelihood." As it appears in the claims, step (b) allows an embodiment where the likelihood of only one sequencing signal is estimated, however step (c) recites multiple likelihoods; which makes unclear what is required by the claim. The rejection may be overcome by amending the claim to clarify the metes and bounds of the limitation.
Claim 3 recites an active step within the recited wherein clause. As set forth in MPEP 2111.04.I, “wherein” clauses raise the question as to the limiting effect of the language in a claim. It is unclear how claim 1 further limits its parent claim 1. It is interpreted that the active is not required to be performed. The rejection may be overcome by amending the claim to clarify the metes and bounds of the limitation. Claims 25 and 31 repeat the issue above.
Claim 19 recites "wherein the trained algorithm is trained at least in part by: obtaining a training set comprising a plurality of training sequencing signals and a plurality of training sequencing reads associated therewith." It is unclear whether the wherein clause actively requires a "training" step or if it should be interpreted as a product by process claim element only further limiting the type of sequencing signals utilized in the invention such that actively "training" is not required within the metes and bounds of the invention. It is noted that claim 1 recites only a trained algorithm I would reject claim 19 similarly for seeming to require the training in a wherein clause, even though claim 1 recites only a trained algorithm. As set forth in MPEP 2111.04.I, “wherein” clauses raise the question as to the limiting effect of the language in a claim. As the instant claim does not recite an active performance of steps, the metes and bounds of the claims are unclear. For compact examination, it is assumed that "training" the sequencing signals is not required to be performed. The rejection may be overcome by clarifying what steps are required to be performed.
Claim 20, recites "wherein… sequencing reads are aligned." It is unclear whether the wherein clause actively requires "aligning" the sequencing reads or if it should be interpreted as a product by process claim element only further limiting the type of sequencing reads utilized in the invention such that actively "aligning" is not required within the metes and bounds of the invention. As set forth in MPEP 2111.04.I, “wherein” clauses raise the question as to the limiting effect of the language in a claim. As the instant claim does not recite an active performance of steps, the metes and bounds of the claims are unclear. For compact examination, it is assumed that "aligning" the sequencing reads is not required to be performed. The rejection may be overcome by clarifying what steps are required to be performed.
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 1-8, 12-14, 19-22, 25, 31-32 and 35-36 are rejected under 35 USC § 101 because the claimed inventions are directed to one or more Judicial Exceptions (JEs) without significantly more. Regarding JEs, "Claims directed to nothing more than abstract ideas..., natural phenomena, and laws of nature are not eligible for patent protection" (MPEP 2106.04 §I). Abstract ideas include mathematical concepts and procedures for evaluating, analyzing or organizing information, which are a type of mental process (MPEP 2106.04(a)(2)).
101 background
MPEP 2106 organizes JE analysis into Steps 1, 2A (Prong One & Prong Two), and 2B as analyzed below. MPEP 2106 and the following USPTO website provide further explanation and case law citations: uspto.gov/patent/laws-and-regulations/examination-policy/examination-guidance-and-training-materials.
Step 1: Are the claims directed to a process, machine, manufacture, or composition of matter (MPEP 2106.03)?
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 (MPEP 2106.04(a-c))?
Step 2A, Prong Two: If the claims recite a judicial exception under Prong One, then is the judicial exception integrated into a practical application by an additional element (MPEP 2106.04(d))?
Step 2B: Do the claims recite a non-conventional arrangement of elements in addition to any identified judicial exception(s) (MPEP 2106.05)?
Analysis of instant claims
Step 1: Are the claims directed to a 101 process, machine, manufacture, or composition of matter (MPEP 2106.03)?
The instant claims are directed to a method (claims 1-8, 12-14, 19-22, 25, 31-32 and 35-36) which falls within one of the categories of statutory subject matter.
[Step 1: claims 1-8, 12-14, 19-22, 25, 31-32 and 35-36: Yes]
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 (MPEP 2106.04(a-c))?
Background
With respect to Step 2A, Prong One, the claims recite judicial exceptions in the form of abstract ideas. MPEP § 2106.04(a)(2) further explains that abstract ideas are defined as:
• mathematical concepts (mathematical formulas or equations, mathematical relationships
and mathematical calculations) (MPEP 2106.04(a)(2)(I));
• certain methods of organizing human activity (fundamental economic principles or practices, managing personal behavior or relationships or interactions between people) (MPEP 2106.04(a)(2)(II)); and/or
• mental processes (concepts practically performed in the human mind, including observations, evaluations, judgments, and opinions) (MPEP 2106.04(a)(2)(III)).
Analysis of instant claims
With respect to the instant claims, under the Step 2A, Prong One evaluation, the claims are found to recite abstract ideas that fall into the grouping of mathematical concepts (in particular mathematical relationships and formulas) and mental processes (in particular procedures for observing, analyzing and organizing information) are as follows.
Mathematical concepts (in particular mathematical relationships and formulas) include:
• "(b) applying a trained algorithm to at least a portion of the plurality of sequencing signals to estimate a likelihood that one or more of the plurality of sequencing signals is produced by a particular nucleic acid sequence" (independent claim 1);
• "(c) determining the sequence of the nucleic acid based at least in part on the estimated likelihoods from (b)" (independent claim 1);
• "wherein (b) further comprises estimating a likelihood of each of a plurality of haplotypes, and wherein (c) further comprises determining the sequence of the nucleic acid based at least in part on the estimated likelihoods of each of the plurality of haplotypes" (claim 14);
• "using the training set to generate the trained algorithm, wherein the trained algorithm comprises a mapping between input sequencing signals and output sequencing reads comprising base calls" (claim 19);
• "determining a likelihood of the sequence of the nucleic acid determined in (c) being correct" (claim 35); and
• "determining a maximum likelihood h-mer length of the sequence of the nucleic acid" (claim 36).
The claims identified above read on math. The abstract ideas recited in the claims are evaluated under the Broadest Reasonable Interpretation and determined each element performed by mathematical operation. The step directed to “executing a trained algorithm to determine sequences of nucleic acids” requires mathematical techniques as the only supported embodiments because it describes a mathematical technique (MPEP 2106.04(a)(2) pertains). Further support for the mathematical techniques used in the claims is provided in the specification at [007], which discloses trained algorithm comprises a trained machine learning algorithm and … comprises a neural network, a support vector machine, a random forest, or a deep learning algorithm. Thus, the recited terms correspond to verbal equivalents of mathematical concepts because they constitute actions executed by a group of mathematical steps in a form of a mathematical algorithm; thus mathematical concepts (MPEP 2106.04(a)(2)). A mathematical concept need not be expressed in mathematical symbols, because "words used in a claim operating on data to solve a problem can serve the same purpose as a formula." In re Grams, 888 F.2d 835, 837 and n.1, 12 USPQ2d 1824, 1826 and n.1 (Fed. Cir. 1989). MPEP 2106.04(a)(2) pertains.
Mental processes, defined as concepts or steps practically performed in the human mind such as steps of observations, evaluations, judgments, analysis, opinions or organizing information include:
• "obtaining a training set comprising a plurality of training sequencing signals and a plurality of training sequencing reads associated therewith" (claim 19).
The abstract ideas recited in the claims are evaluated under the Broadest Reasonable Interpretation (BRI) and determined to each cover performance either in the mind (i.e. concepts practically performed in the human mind, including observations, evaluations, judgments, and opinions) or because the method only requires a user to manually determine action based on an added number. Under the BRI, the recited limitations are mental processes because a human mind is also sufficiently capable of choosing a training set comprising a plurality of training sequencing signals and a plurality of training sequencing reads based on data evaluation.
Dependent claims 2-8, 12-13, 20-22, 25 and 31-32 recite further steps that limit the judicial exceptions in independent claim 1 and, as such, also are directed to those abstract ideas. For example, claim 2 recites further details about the nucleic acid; claims 3-8 recite further details about the plurality of sequencing signals without clearly requiring the performance of flow sequencing; claims 12-13 recite further details about the plurality of substrate segments and claims 20-22, 25 and 31-32 recite further details about the training sequencing reads.
[Step 2A Prong One: claims 1-8, 12-14, 19-22, 25, 31-32 and 35-36: Yes ]
Step 2A, Prong Two: If the claims recite a judicial exception under Prong One, then is the judicial exception integrated into a practical application by an additional element (MPEP 2106.04(d))?
Background
MPEP 2106.04(d).I lists the following example considerations for evaluating whether a judicial exception is integrated into a practical application:
An improvement in the functioning of a computer or an improvement to other technology or another technical field, as discussed in MPEP §§ 2106.04(d)(1) and 2106.05(a);
Applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, as discussed in MPEP § 2106.04(d)(2);
Implementing a judicial exception with, or using a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, as discussed in MPEP § 2106.05(b);
Effecting a transformation or reduction of a particular article to a different state or thing, as discussed in MPEP § 2106.05(c); and
Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception, as discussed in MPEP § 2106.05(e).
Analysis of instant claims
Instant claims 1-8, 12-14, 19-22, 25, 31-32 and 35-36 recite additional elements that are not abstract ideas:
• "(a) receiving a plurality of sequencing signals of the nucleic acid that are generated at least in part by imaging a substrate comprising a plurality of substrate segments" (independent claim 1).
Considerations under Step 2A, Prong Two
Claims directed to "receiving a plurality of sequencing signals …" read on just necessary data gathering and therefore correspond to insignificant extra-solution activity.
Hence, these are mere instructions to apply the abstract idea using a computer and insignificant extra-solution activity and therefore the claims do not integrate that abstract idea into a practical application (see MPEP 2106.04(d) § I; 2106.05(f); and 2106.05(g)).
In Step 2A, Prong One above, claim steps and/or elements were identified as part of one or more judicial exceptions (JEs).
In this Step 2A, Prong Two immediately above claim steps and/or elements were identified as part of one or more additional elements. Additional elements are further discussed in Step 2B below.
Here in Step 2A, Prong Two, no additional step or element clearly demonstrates integration of the JE(s) into a practical application.
[Step 2A Prong Two: claims 1-8, 12-14, 19-22, 25, 31-32 and 35-36: No]
Step 2B: Do the claims recite a non-conventional arrangement of elements in addition to any identified judicial exception(s) (MPEP 2106.05)?
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 examination 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).
The courts have found that receiving data is a well-understood, routine, and conventional function of a computer when claimed in a 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), Versa ta 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)(Il)(i)).
When the claims are considered as a whole, they do not integrate the abstract idea into a practical application; they do not confine the use of the abstract idea to a particular technology; they do not solve a problem rooted in or arising from the use of a particular technology; they do not improve a technology by allowing the technology to perform a function that it previously was not capable of performing; and they do not provide any limitations beyond generally linking the use of the abstract idea to a broad technological environment. See MPEP 2106.05(a) and 2106.05(h).
The instant claims constitute insignificant extra solution activity, and when considered individually, are insufficient to constitute inventive concepts that would render the claims significantly more than an abstract idea (see MPEP 2106.05(g)). Hence, these elements, when considered individually, are insufficient to constitute inventive concepts that would render the claims significantly more than an abstract idea (see MPEP 2106.05(d)).
[Step 2B: claims 1-8, 12-14, 19-22, 25, 31-32 and 35-36: No]
Conclusion: Instant claims are directed to non-statutory subject matter
For the reasons above, the claims in this instant application, when the limitations are considered individually and as a whole, are directed to an abstract idea and lack an inventive concept not clearly anything significantly more.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless -
(a)(l) the claimed invention was patented, described in a printed publication, or in public use, on sale,
or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-7, 12-13, 19-20, 22, 25 and 35 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Menges ("TotalReCaller: improved accuracy and performance via integrated alignment and base-calling." Bioinformatics 27.17: 2330-2337 (2011)), as cited on the attached Form PTO-892. Claim 22 is additionally evidenced by Ledergerber ("Base-calling for next-generation sequencing platforms." Briefings in bioinformatics 12.5:489-497 (2011)).
Claim 1 recites:
(a) receiving a plurality of sequencing signals of the nucleic acid that are generated at least in part by imaging a substrate comprising a plurality of substrate segments;
(b) applying a trained algorithm to at least a portion of the plurality of sequencing signals to estimate a likelihood that one or more of the plurality of sequencing signals is produced by a particular nucleic acid sequence; and
(c) determining the sequence of the nucleic acid based at least in part on the estimated likelihoods from (b)
• Menges teaches a base calling algorithm TotalReCaller that takes the vector analog time series of signals (i.e. reading on receiving a plurality of sequencing signals of the nucleic acid) generated by the sequencing machines as input, and produces a base-by-base digitized estimate of the underlying DNA sequence that is most likely to have given rise to those signals (i.e. reading on applying an algorithm to at least a portion of the plurality of sequencing signals to estimate a likelihood that one or more of the plurality of sequencing signals is produced by a particular nucleic acid sequence) (pg. 2330 col. 2 para. 2); wherein said algorithm uses a training phase and performs genome alignment while base calling (i.e. reading on applying a trained algorithm) (pg. 2333 col. 2 para. 2) and addresses base-calling for Illumina sequencing machines (pg. 2331 col. 2 para. 1) in which generating raw signals prior to base-calling and alignment, consists out of five steps in which: (i) DNA sample is prepared; (ii) pieces of DNA in the sample are randomly fragmented and placed on a flow cell (i.e. reading on a plurality of substrate segments); (iii) fragments are amplified into clusters ∼1000 identical strands each; (iv) fluorescent markers, lasers and CCD sensors are used to read the clusters base by base (so called cycles), resulting in four images for each cycle; and finally (v) the images are analyzed and a single analog intensity value is determined for each image (i.e. reading on signals generated at least in part by imaging a substrate comprising a plurality of substrate segments) (pg. 2331 col. 2 para. 1); wherein the most likely estimate for the correct sequence read(s) is therefore obtained by simply choosing the node with the (globally) highest score from the branch-and-bound strategy that combines intensity and alignment information by sequentially constructing a tree of hypothetical sequences (i.e. reading on step (c)) (pg. 2336 col. 1 para. 5).
Claim 2 recites:
wherein the nucleic acid comprises deoxyribonucleic acid (DNA) or ribonucleic acid (RNA)
• Menges teaches a base calling algorithm that takes the vector analog time series of signals generated by the sequencing machines as input, and produces a base-by-base digitized estimate of the underlying DNA sequence that is most likely to have given rise to those signals (pg. 2330 col. 2 para. 2).
Claim 3 recites:
wherein the plurality of sequencing signals is generated at least in part by performing flow sequencing of the nucleic acid
Claim 4 recites:
wherein the plurality of sequencing signals comprises analog values produced by the imaging
Claim 5 recites:
wherein the analog values comprise fluorescence signals
• Menges teaches a base calling algorithm that takes the vector analog time series of signals (i.e. reading on receiving a plurality of sequencing signals of the nucleic acid) generated by the sequencing machines as input, and produces a base-by-base digitized estimate of the underlying DNA sequence that is most likely to have given rise to those signals (i.e. reading on applying an algorithm to at least a portion of the plurality of sequencing signals to estimate a likelihood that one or more of the plurality of sequencing signals is produced by a particular nucleic acid sequence) (pg. 2330 col. 2 para. 2); wherein said algorithm uses a training phase and performs genome alignment while base calling (i.e. reading on applying a trained algorithm) (pg. 2333 col. 2 para. 2) and addresses base-calling for Illumina sequencing machines (pg. 2331 col. 2 para. 1) in which generating raw signals prior to base-calling and alignment, consists out of five steps in which: (i) DNA sample is prepared; (ii) pieces of DNA in the sample are randomly fragmented and placed on a flow cell (i.e. reading on wherein the plurality of sequencing signals is generated at least in part by performing flow sequencing of the nucleic acid as in claim 3); (iii) fragments are amplified into clusters (i.e. reading on discrete DNA extensions) ∼1000 identical strands each; (iv) fluorescent markers, lasers and CCD sensors are used to read the clusters base by base (so called cycles), resulting in four images for each cycle and finally (v) the images are analyzed and a single analog intensity value is determined for each image (i.e. reading on sequencing signals comprises analog values produced by the imaging as in claim 4 and analog values comprising fluorescence signals as in claim 5 ) (pg. 2331 col. 2 para. 1).
Claim 6 recites:
wherein the fluorescence signals correspond to discrete DNA extensions sensed from introduction of single nucleotide solutions in the flow sequencing
Claim 7 recites:
wherein the introduction of single nucleotide solutions in the flow sequencing is cyclic
• Menges teaches an algorithm to perform genome alignment while base calling (pg. 2333 col. 2 para. 2) and address base-calling for Illumina sequencing machines (pg. 2331 col. 2 para. 1) in which generating raw signals prior to base-calling and alignment, consists out of five steps in which: (i) DNA sample is prepared (i.e. reading on preparation of DNA solutions as in claim 6); (ii) pieces of DNA in the sample are randomly fragmented and placed on a flow cell; (iii) fragments are amplified into clusters (i.e. reading on reading on discrete DNA extensions as in claim 6) ∼1000 identical strands each; (iv) fluorescent markers, lasers and CCD sensors (i.e. reading on sensing discrete DNA extensions as in claim 6) are used to read the clusters base by base (so called cycles), resulting in four images for each cycle (i.e. reading on introduction of single nucleotide solutions in the flow sequencing is cyclic as in claim 7) and finally (v) the images are analyzed and a single analog intensity value is determined for each image (pg. 2331 col. 2 para. 1).
Claim 12 recites:
wherein the plurality of substrate segments comprises a same shape and/or size
Claim 13 recites:
wherein at least two of the plurality of substrate segments differ by at least one shape and size
• Menges teaches steps in sequencing of nucleic acid where pieces of DNA in the sample are randomly fragmented and placed on a flow cell; (iii) fragments are amplified into clusters ∼1000 identical strands each (i.e. reading on a plurality of substrate segments comprises a same shape and/or size as in claim 12) (pg. 2331 col. 2 para. 1); wherein sources of errors in Illumina raw sequencing data such as lagging effects causes many false-positive insertions in the distal extending-end of sequence reads (i.e. reading on sequence that were initially identical now differ in size as in claim 13 - due to insertions) (pg. 2332 col. 1 para. 3).
Claim 19 recites:
wherein the trained algorithm is trained at least in part by: obtaining a training set comprising a plurality of training sequencing signals and a plurality of training sequencing reads associated therewith, and using the training set to generate the trained algorithm, wherein the trained algorithm comprises a mapping between input sequencing signals and output sequencing reads comprising base calls
• Menges teaches a base calling algorithm (i.e. reading on outputting comprising base calls) that takes the vector analog time series of signals generated by the sequencing machines as input, and produces a base-by-base digitized estimate of the underlying DNA sequence that is most likely to have given rise to those signals (i.e. reading on the trained algorithm comprises a mapping between input sequencing signals and output sequencing reads comprising base calls.) (pg. 2330 col. 2 para. 2); wherein said algorithm uses a training phase and performs genome alignment while base calling (i.e. reading on applying a trained algorithm) (pg. 2333 col. 2 para. 2).
Claim 20 recites:
wherein the training sequencing reads in the plurality of training sequencing reads are aligned to a reference genome
• Menges teaches that TotalReCaller uses a training phase and performs genome alignment while base calling (pg. 2333 col. 2 para. 2); improving the quality of reads by injecting knowledge of the reference genome into the base-calling step (pg. 2331 col. 1 para. 4).
Claim 22 recites:
wherein the aligning comprises:
(i) using a set of common base calling variants,
(ii) detecting contamination from a different genome, or
(iii) using indicators of pre-determined adapter sequences
• Menges teaches the Illumina sequencing and base calling pipeline in which images of DNA fragments placed in a flow cell are analyzed and a single analog intensity value is determined for each image with correct sequences been determined from such signals (pg. 2331 col. 2 para. 1) while a combined pipeline has the ability to concurrently perform base-calling, alignment and SNP detection (pg. 2331 col. 1 para. 4); wherein Illumina platform relies on the generation of a single strand DNA library by random fragmentation of a DNA sample followed by addition of universal adapters to the templates and placement in a flow cell - as evidenced by pg. 490 col. 1 para. 3 Ledergerber. Here, the concurrent base-calling, alignment and SNP detection and addition of universal adapters to the templates with the platform reads on "using indicators of pre-determined adapter sequences."
Claim 25 recites:
wherein the plurality of training sequencing reads is filtered to remove at least one training sequencing read that:
(i) is not fully aligned to the reference,
(ii) does not comprise a largest segment that is fully aligned to the reference,
(iii) has a quality score that fails to meet a pre-determined criterion,
(iv) has a length that differs from a reference length, or
(v) comprises a pre-determined adapter sequence.
• Menges teaches that during the training phase, a given base-caller computes the parameters for its underlying error models (pg. 2333 col. 1 para. 5); wherein TotalReCaller dynamically prunes unpromising sequences based on the evaluation of the score function in a branch-and- bound scheme which is done when the sequencer is extremely noisy and/or when the reference is incorrect (i.e. reading on (ii) does not comprise a largest segment that is fully aligned to the reference) in which the solution in these cases would then involve terminating the sequence read at a smaller read length or rejecting it outright (i.e. reading on filtered to remove at least one training sequencing read) (pg. 2336 col. 1 para. 1).
Claim 35 recites:
further comprising determining a likelihood of the sequence of the nucleic acid determined in (c) being correct
• Menges teaches a base calling algorithm TotalReCaller that takes the vector analog time series of signals) generated by the sequencing machines as input, and produces a base-by-base digitized estimate of the underlying DNA sequence that is most likely to have given rise to those signals (pg. 2330 col. 2 para. 2); wherein the most likely estimate for the correct sequence read(s) is therefore obtained by simply choosing the node with the (globally) highest score from the branch-and-bound strategy that combines intensity and alignment information by sequentially constructing a tree of hypothetical sequences (pg. 2336 col. 1 para. 5).
Claim Rejections - 35 USC § 103
The following is a quotation of pre-AIA 35 U.S.C. 103(a) which forms the basis for all obviousness rejections set forth in this Office action:
(a) A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter 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 pre-AIA 35 U.S.C. 103(a) 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.
A. Claim 8 is rejected under 35 U.S.C. 103(a) as being unpatentable over Menges as applied to claim 1 in the 102 rejection above further in view of Stranneheim ("Stepping stones in DNA sequencing." Biotechnology journal 7.9:1063-1073 (2012)), as cited on the attached Form PTO-892.
Claim 8 recites:
wherein the introduction of single nucleotide solutions in the flow sequencing is acyclic.
• Menges does not teach the recitation above. However, Stranneheim teaches reversible dye terminator sequencing by-synthesis technology where only single base extensions are possible due to the 3’ modification of the chain-termination nucleotides, and each cluster incorporates only one type of nucleotide, as dictated by the DNA template forming the cluster, meanwhile the incorporated base in all clusters is detected by fluorescence imaging of the surface before chemical removal of the dye and terminator, generating an extendable base that is ready for a new round of sequencing (i.e. reading on a stepwise introduction of single nucleotide solutions in the flow sequencing – hence acyclic) (pg. 1067 col. 1 para. 1).
Rationale for combining (MPEP §2142-2143)
Regarding claim 8, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the methods of Menges in view of Stranneheim because all references disclose methods for the investigation of nucleic acid sequences. The motivation would have been to create a surface with a high density of spatially distinct clusters, each cluster of which contains a unique DNA template (pg. 1066 col. 2 para. 4 Stranneheim).
Therefore it would have been obvious to one of ordinary skill in the art to substitute the nucleic acid sequences investigation of Menges to the methods by Stranneheim because such a substitution is no more than the simple substitution of one known element for another. One of ordinary skill in the art would be able to motivated to combine the teachings in these references with a reasonable expectation of success since the described teachings pertain to methods for investigating nucleic acid sequences.
B. Claim 14 is rejected under 35 U.S.C. 103(a) as being unpatentable over Menges as applied to claim 1 in the 102 rejection above further in view of Kang ("Incorporating genotyping uncertainty in haplotype inference for single-nucleotide polymorphisms." The American Journal of Human Genetics 74.3:495-510 (2004)), as cited on the attached Form PTO-892.
Claim 14 recites:
wherein (b) further comprises estimating a likelihood of each of a plurality of haplotypes, and wherein (c) further comprises determining the sequence of the nucleic acid based at least in part on the estimated likelihoods of each of the plurality of haplotypes
• Menges does not teach the recitation above. However, Kang teaches a genotype clustering algorithm to assign a set of probabilities for each data point belonging to the candidate genotype clusters (pg. 495 para. 1); wherein two different alleles are labeled with two different dyes, and for each dye used, the reader produces a fluorescent intensity signal (pg. 496 col. 2 para. 3); wherein the maximum-likelihood estimate accounts for haplotype occurrences and frequency estimation (pg. 499 col. 2 para. 2).
Rationale for combining (MPEP §2142-2143)
Regarding claim 14, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the methods of Menges in view of Kang because all references disclose methods for the investigation of nucleic acid sequences. The motivation would have been to incorporate an expectation-maximization algorithm for haplotype inference that outperforms conventional methods (pg. 496 col. 12 para. 2 Kang).
Therefore it would have been obvious to one of ordinary skill in the art to substitute the nucleic acid sequences investigation of Menges to the methods by Kang because such a substitution is no more than the simple substitution of one known element for another. One of ordinary skill in the art would be able to motivated to combine the teachings in these references with a reasonable expectation of success since the described teachings pertain to methods for investigating nucleic acid sequences.
C. Claim 21 is rejected under 35 U.S.C. 103(a) as being unpatentable over Menges as applied to claims 1 and 19-20 in the 102 rejection above further in view of Lysholm ("FAAST: Flow-space assisted alignment search tool." BMC bioinformatics 12.1:293 (2011)), as cited on the attached Form PTO-892.
Claim 21 recites:
wherein the aligning is performed in flow space.
• Menges does not teach the recitation above. However, Lysholm teaches the use of flow space assisted Smith-Waterman-Gotoh alignments, i.e. giving the local alignment algorithm the ability to correct for likely sequencing errors while computing the alignment (i.e. wherein the aligning is performed in flow space) (pg. 2 col. 2 para. 2).
Rationale for combining (MPEP §2142-2143)
Regarding claim 21, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the methods of Menges in view of Lysholm because all references disclose methods for the investigation of nucleic acid sequences. The motivation would have been to incorporate more accurate alignments and correct for reading errors with sequence alignments (pg. 2 col. 2 para. 2 Lysholm).
Therefore it would have been obvious to one of ordinary skill in the art to substitute the nucleic acid sequences investigation of Menges to the methods by Lysholm because such a substitution is no more than the simple substitution of one known element for another. One of ordinary skill in the art would be able to motivated to combine the teachings in these references with a reasonable expectation of success since the described teachings pertain to methods for investigating nucleic acid sequences.
D. Claims 31 and 36 are rejected under 35 U.S.C. 103(a) as being unpatentable over Menges as applied to claims 1 and 19 in the 102 rejection above further in view of Gulli (Deep learning with Keras. Packt Publishing Ltd, (2017)), as cited on the attached Form PTO-892.
Claim 31 recites:
wherein at least one of the training sequence reads in the plurality of training sequencing reads is padded with filler values, such that the plurality of training sequencing reads has a substantially identical length
• Menges does not teach the recitation above. However, Gulli teaches a deep learning method using the Kera algorithm with functionality of padding data sequences so that all sequences are of the same length (i.e. reading on training data padded with filler values, such that the plurality of training data values has a substantially identical length) (pg. 316 para. 6); wherein an output can be the same size as the input, for which the area around the input is padded with zeros (i.e. reading on filler values) (pg. 207 para. 1).
Claim 36 recites:
further comprising determining a maximum likelihood h-mer length of the sequence of the nucleic acid
• Menges does not teach the recitation above. However, Gulli teaches a deep learning method that uses a classifier that takes the context words (i.e. reading on sequence of symbols – which is applicable to nucleic acid sequences) as input and predicts the maximum probability of the output being a target word (i.e. reading on maximum likelihood of a sequence) (pg. 289 para. 1); wherein the input comprises the size of each input (i.e. reading on a length of the sequence) (pg. 289 para. 1). Here, the inputting of a size value for each word and outputting of the maximum probability of a target word with a certain desired reads on "determining a maximum likelihood h-mer length of the sequence of the nucleic acid").
Rationale for combining (MPEP §2142-2143)
Regarding claims 31 and 36, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the methods of Menges in view of Gulli because all references disclose methods for algorithmic prediction of sequences. The motivation would have been to incorporate the breakthrough progress provided by deep learning in preserving spatial information, adding convolution, pooling and feature maps (pg. 213 para. 2 Gulli).
Therefore it would have been obvious to one of ordinary skill in the art to substitute the algorithmic prediction of sequences of Menges to the methods by Gulli because such a substitution is no more than the simple substitution of one known element for another. One of ordinary skill in the art would be able to motivated to combine the teachings in these references with a reasonable expectation of success since the described teachings pertain to methods for algorithmic prediction of sequences.
E. Claim 32 is rejected under 35 U.S.C. 103(a) as being unpatentable over Menges and Gulli as applied to claims 1, 19 and 31 above further in view of Yun ("Masking as an effective quality control method for next-generation sequencing data analysis." BMC bioinformatics 15.1:382 (2014)), as cited on the attached Form PTO-892.
Claim 32 recites:
wherein the filler values are masking values comprising negative numbers, and are indicative of a class of trimmed flows, wherein the class of trimmed flows is selected from the group consisting of low quality flows, flows comprising three consecutive zero-signals, flows with errors, and flows with variants
• Menges does not teach the recitation above. However, Yun teaches masking as an effective quality control method for next generation sequencing data analysis (pg. 1 Title); wherein masking and trimming effectiveness is compared when addressing low quality base calls (i.e. reading on low quality flows - interpretation supported by this instant specification [00116]) (pg. 1 Abstract); wherein low quality base calls are substituted with N (undetermined bases) - hence absent (i.e. reading on wherein the filler values are masking values comprising negative numbers – interpretation supported by this instant specification [00178] where negative values translates to absent values) (pg. 1 Abstract).
Rationale for combining (MPEP §2142-2143)
Regarding claim 32, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the methods of Menges and Gulli in view of Yun because all references disclose methods for algorithmic prediction of sequences. The motivation would have been to incorporate an effective preprocessing method for next generation sequencing data analysis (pg. 1 Abstract Yun).
Therefore it would have been obvious to one of ordinary skill in the art to substitute the algorithmic prediction of sequences of Menges and Gulli to the methods by Yun because such a substitution is no more than the simple substitution of one known element for another. One of ordinary skill in the art would be able to motivated to combine the teachings in these references with a reasonable expectation of success since the described teachings pertain to methods for algorithmic prediction of sequences.
Conclusion
No claims are allowed.
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/F.F.L./Examiner, Art Unit 1685
/JANNA NICOLE SCHULTZHAUS/Examiner, Art Unit 1685
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