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 .
Claim Status
Claims 1-20 are currently pending and under examination herein.
Claims 1-20 are rejected.
Claims 4 and 14 are objected to.
Priority
The instant application claims priority as a 371 of PCT/KR2021/009794 filed 28 July 2021 and foreign priority to KR10-2020-0094684 filed 29 July 2020. Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55. In this action, claims 1-20 are examined as though they had an effective filing date of 29 July 2020. In future actions, the effective filing date of one or more claims may change, due to amendments to the claims, or further analysis of the disclosure(s) of the priority application(s).
Information Disclosure Statement
The information disclosure statement (IDS) submitted 27 January 2023 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Drawings
The drawings filed 27 January 2023 are objected to because they include nucleic acid (NA) sequences (≥ 10 NA) in figures 2 and 22, which require sequence listings (see Nucleotide and/or Amino Acid Sequence Disclosures section below).
Specification
The specification is objected to because it includes nucleic acid sequences (≥ 10 NA) on Page 18, Paragraph 1 and Page 22, Paragraph 2, which require sequence listings (see Nucleotide and/or Amino Acid Sequence Disclosures section below).
The specification is further objected to because it contains embedded hyperlinks and/or other form of browser-executable code. Links were found in the published specification (US 20230274792 A1) at:
paragraph 0094 - http://www.ncbi.nlm.nih.gov/nucleotide
paragraph 0183 - https://biopython.org/docs/1.74/api/Bio.SeqUtils.Melting…
paragraph 0189 - https://www.ncbi.nlm.nih.gov/sra/
paragraph 0290 - http://deepcrispr/DeepPE
Applicant is required to delete the embedded hyperlink and/or other form of browser-executable code; references to websites should be limited to the top-level domain name without any prefix such as www., http://, or other browser-executable code. See MPEP § 608.01.
Nucleotide and/or Amino Acid Sequence Disclosures
REQUIREMENTS FOR PATENT APPLICATIONS CONTAINING NUCLEOTIDE AND/OR AMINO ACID SEQUENCE DISCLOSURES
Items 1) and 2) provide general guidance related to requirements for sequence disclosures.
37 CFR 1.821(c) requires that patent applications which contain disclosures of nucleotide and/or amino acid sequences that fall within the definitions of 37 CFR 1.821(a) must contain a "Sequence Listing," as a separate part of the disclosure, which presents the nucleotide and/or amino acid sequences and associated information using the symbols and format in accordance with the requirements of 37 CFR 1.821 - 1.825. This "Sequence Listing" part of the disclosure may be submitted:
In accordance with 37 CFR 1.821(c)(1) via the USPTO patent electronic filing system (see Section I.1 of the Legal Framework for Patent Electronic System (https://www.uspto.gov/PatentLegalFramework), hereinafter "Legal Framework") as an ASCII text file, together with an incorporation-by-reference of the material in the ASCII text file in a separate paragraph of the specification as required by 37 CFR 1.823(b)(1) identifying:
the name of the ASCII text file;
ii) the date of creation; and
iii) the size of the ASCII text file in bytes;
In accordance with 37 CFR 1.821(c)(1) on read-only optical disc(s) as permitted by 37 CFR 1.52(e)(1)(ii), labeled according to 37 CFR 1.52(e)(5), with an incorporation-by-reference of the material in the ASCII text file according to 37 CFR 1.52(e)(8) and 37 CFR 1.823(b)(1) in a separate paragraph of the specification identifying:
the name of the ASCII text file;
the date of creation; and
the size of the ASCII text file in bytes;
In accordance with 37 CFR 1.821(c)(2) via the USPTO patent electronic filing system as a PDF file (not recommended); or
In accordance with 37 CFR 1.821(c)(3) on physical sheets of paper (not recommended).
When a “Sequence Listing” has been submitted as a PDF file as in 1(c) above (37 CFR 1.821(c)(2)) or on physical sheets of paper as in 1(d) above (37 CFR 1.821(c)(3)), 37 CFR 1.821(e)(1) requires a computer readable form (CRF) of the “Sequence Listing” in accordance with the requirements of 37 CFR 1.824.
If the "Sequence Listing" required by 37 CFR 1.821(c) is filed via the USPTO patent electronic filing system as a PDF, then 37 CFR 1.821(e)(1)(ii) or 1.821(e)(2)(ii) requires submission of a statement that the "Sequence Listing" content of the PDF copy and the CRF copy (the ASCII text file copy) are identical.
If the "Sequence Listing" required by 37 CFR 1.821(c) is filed on paper or read-only optical disc, then 37 CFR 1.821(e)(1)(ii) or 1.821(e)(2)(ii) requires submission of a statement that the "Sequence Listing" content of the paper or read-only optical disc copy and the CRF are identical.
Specific deficiencies and the required response to this Office Action are as follows:
Specific deficiency - This application fails to comply with the requirements of 37 CFR 1.821 - 1.825 because it does not contain a "Sequence Listing" as a separate part of the disclosure or a CRF of the “Sequence Listing.”.
Required response - Applicant must provide:
A "Sequence Listing" part of the disclosure; together with
An amendment specifically directing its entry into the application in accordance with 37 CFR 1.825(a)(2);
A statement that the "Sequence Listing" includes no new matter as required by 37 CFR 1.821(a)(4); and
A statement that indicates support for the amendment in the application, as filed, as required by 37 CFR 1.825(a)(3).
If the "Sequence Listing" part of the disclosure is submitted according to item 1) a) or b) above, Applicant must also provide:
A substitute specification in compliance with 37 CFR 1.52, 1.121(b)(3) and 1.125 inserting the required incorporation-by-reference paragraph, consisting of:
A copy of the previously-submitted specification, with deletions shown with strikethrough or brackets and insertions shown with underlining (marked-up version);
A copy of the amended specification without markings (clean version); and
A statement that the substitute specification contains no new matter.
If the "Sequence Listing" part of the disclosure is submitted according to item 1) c) or d) above, applicant must also provide:
A CRF in accordance with 37 CFR 1.821(e)(1) or 1.821(e)(2) as required by 1.825(a)(5); and
A statement according to item 2) a) or b) above.
Specific deficiency – Nucleotide and/or amino acid sequences appearing in the specification are not identified by sequence identifiers in accordance with 37 CFR 1.821(d).
Required response – Applicant must provide:
A substitute specification in compliance with 37 CFR 1.52, 1.121(b)(3) and 1.125 inserting the required sequence identifiers, consisting of:
A copy of the previously-submitted specification, with deletions shown with strikethrough or brackets and insertions shown with underlining (marked-up version);
A copy of the amended specification without markings (clean version); and
A statement that the substitute specification contains no new matter.
Specific deficiency – Nucleotide and/or amino acid sequences appearing in the drawings are not identified by sequence identifiers in accordance with 37 CFR 1.821(d). Sequence identifiers for nucleotide and/or amino acid sequences must appear either in the drawings or in the Brief Description of the Drawings.
Required response – Applicant must provide:
Replacement and annotated drawings in accordance with 37 CFR 1.121(d) inserting the required sequence identifiers;
AND/OR
A substitute specification in compliance with 37 CFR 1.52, 1.121(b)(3) and 1.125 inserting the required sequence identifiers into the Brief Description of the Drawings, consisting of:
A copy of the previously-submitted specification, with deletions shown with strikethrough or brackets and insertions shown with underlining (marked-up version);
A copy of the amended specification without markings (clean version); and
A statement that the substitute specification contains no new matter.
Claim Objections
Claims 4 and 14 are objected to due to spelling/typographical errors:
oligonucloeitde in claims 4 and 14
Appropriate corrections may be required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation 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 broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
an information input unit in claim 1
a predictive model generator in claim 1
a candidate sequence input unit in claim 1
an efficiency predictor in claim 1
a feature extraction module in claim 8
an output unit in claim 12
Because these claim limitations are being interpreted under 35 U.S.C. 112(f), they would be interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof. However, both the structure and algorithms (for software implementation) required by the 112(f) interpretation were not found within the disclosure (see 112(a) and 112(b) rejections below). This includes computing devices, processors, memory, or other circuitry associated with the generic placeholders to perform the recited functions.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
Claims 1-12 are rejected under 35 U.S.C. 112(a) as failing to comply with the written description requirement. The claims contain subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor at the time the application was filed, had possession of the claimed invention.
Claims 1, 8, and 12 recite generic placeholders modified by functional language (See 112(f) within the claim interpretation above). The recited units/predictors/modules are not adequality described under the requirements of 112(a), for the following:
an information input unit in claim 1
a predictive model generator in claim 1
a candidate sequence input unit in claim 1
an efficiency predictor in claim 1
a feature extraction module in claim 8
an output unit in claim 12
No description of the structure of the recited units/predictors/modules were found within the specification or drawings. The specification recites a computer related to the computer readable medium (claim 20) in paragraphs 0092-0094 of the published specification. However, the computer is not associated with the system of claims 1-12. Claims 2-7 and 9-11 depend on cited Claims, and thus contain the above issues due to said dependence.
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 1-12 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, regards as the invention.
Claims 1, 8, and 12 recite generic placeholders modified by functional language (See 112(f) within the claim interpretation above). The metes and bounds of these limitations are unclear, rendering the claims indefinite, for the following:
an information input unit in claim 1
a predictive model generator in claim 1
a candidate sequence input unit in claim 1
an efficiency predictor in claim 1
a feature extraction module in claim 8
an output unit in claim 12
Claims 2-7 and 9-11 depend on cited claims, and thus contain the above issues due to said dependence. For the purpose of examination, the units, predictor, and module are interpreted as generic computer processing systems.
Claim 11 recites “a prime editor”. Claim 1, upon which claim 11 depends, recites “a prime editor”. It is unclear if the prime editor in claim 11 used during the predicating is a different prime editor than indicted by claim 1 used in generating the model. The metes and bounds of the limitation are therefore unclear, rendering the claim indefinite. The rejection can be overcome by changing “a” to “the” if the prime editors are the same. If the editors are different, a new name should be used for the prime editor of claim 11.
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.
Claim 20 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim 20 does not fall within at least one of the four categories of patent eligible subject matter because the claim recites computer-readable medium but does not specify it as non-transitory. The interpretation for transitory computer-readable medium encompasses signals per se (see MPEP 2106.03).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The 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 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Kim et al. (2018, Nature Biotechnology, Vol. 36, No. 3: 1-6), in view of Xu et al. (2020, Plant communications, Vol 1, No. 3: 1-17). Italicized text from reference art.
Regarding Claim 1, Kim et al. teach (Claim 1.i) an information input unit that receives data on editing efficiency of a gene editor (Page 1, Column 2, Paragraph 2: The high-throughput experiments A and B led to the generation of data sets HT 1 and HT 2; Page 5, Column 2, Paragraph 3: Model selection and pre-training. First, we split data set HT 1 into data sets). The dataset generated by the experiments was received as it is used to train the models. Kim et al. also teach (Claim 1.ii) a predictive model generator for generating editing efficiency predictive models by performing deep learning to learn a relationship between editing efficiency features and editing efficiency (Page 5, Column 1, Paragraph 4: DeepCpf1 is a deep-learning framework for AsCpf1 (a CRISPR–Cas system) indel frequency prediction. DeepCpf1 receives a 34-bp target sequence as input, and it produces a regression score that highly correlates with AsCpf1 activity. DeepCpf1 can thus automatically learn informative representations of target sequences relevant to AsCpf1 activity profiles). DeepCpf1 is a predictive model generated by using the data received from the experiments indicated in Claim 1.i. Generating the predictive models by performing deep learning to learn a relationship is interpreted as training the predictive models. Kim et al. also teach (Claim 1.iii) a candidate sequence input unit that receives an input of a candidate target sequence for gene editing (Page 5, Column 1, Paragraph 4: DeepCpf1 receives a 34-bp target sequence as input). Kim et al. also teach (Claim 1.iv) an efficiency predictor for predicting editing efficiency by applying the candidate target sequence to an efficiency predictive model (Page 5, Column 1, Paragraph 4: DeepCpf1 is a deep-learning framework for AsCpf1 indel frequency prediction. DeepCpf1 receives a 34-bp target sequence as input, and it produces a regression score that highly correlates with AsCpf1 activity). Indel frequency and AsCpf1 activity are interpreted to indicate editing efficiency. Additionally, Kim et al. teach the methods are performed by a computer (Page 6, Column 1, Paragraph 3: Code availability. All custom Python scripts used for the indel frequency analysis, Seq-deepCpf1, and DeepCpf1 are available on GitHub). This is indicative of a system that performs the functions/methods, which include those of the units/predictors/modules recited by the claim (see claim interpretation - 112(f) and the 112(b) rejection above). Kim et al. teaches the systems/methods related to a CRISP-Cas system which would be obvious to combine with a prime editing system (as taught by Xu et al. – see reason to combine).
Regarding Claim 3 and 15, Kim et al. teach the prime editing efficiency is represented by a rate of occurrence of intended edits by a gene editor and guide RNA at a target sequence without generation of an unintended mutant (Page 4, Column 2, Paragraph 4: Insertions or deletions located around the expected cleavage site were considered to be Cpf1-induced mutations. To exclude the background indel frequencies that originated from oligonucleotide synthesis and the target site amplification procedure, the bona fide indel frequency induced by Cpf1 and crRNA activity was calculated by subtracting the background indel frequency in the cell library in the absence of Cpf1 delivery from the observed indel frequency).
Regarding Claim 4 and 14, Kim et al. teach (Claim 4.i) introducing a prime editor into a cell library including an oligonucleotide including a nucleotide sequence encoding pegRNA and a target nucleotide sequence targeted by the pegRNA (Page 4, Column 1, Paragraph 2: We designed each oligonucleotide to contain the 20-nt guide-RNA-encoding sequence, 20-nt barcode, and 34-nt target sequence in a total length of 130 nucleotides; Page 4, Column 1, Paragraph 3: Next, the assembled product was transformed into electrocompetent cells). Kim et al. also teach (Claim 4.ii) performing deep sequencing by using DNA obtained from the cell library into which the prime editor has been introduced (Page 4, Column 2, Paragraph 3: Deep sequencing. The resulting products were isolated, purified, mixed, and analyzed using MiSeq or HiSeq). Kim et al. also teach (Claim 4.iii) analyzing editing efficiency from data obtained by the deep sequencing (Page 4, Column 2, Paragraph 4: Analysis of indel frequencies. Deep-sequencing data were sorted and analyzed). The guide RNA of the CRISPR-Cas system is interpreted as equivalent to the pegRNA of a prime editing system (as taught by Xu et al. – see reason to combine)
Regarding Claim 5, Kim et al. teach the oligonucleotide further comprises a barcode sequence (Page 4, Column 1, Paragraph 2: We designed each oligonucleotide to contain the 20-nt guide-RNA-encoding sequence, 20-nt barcode).
Regarding Claim 6 and 16, Kim et al. teach the features affecting prime editing efficiency are extracted from information about guide RNA and a target sequence (Page 5, Column 2, Paragraph 7: For determining the features of nucleotide sequences, we used a previously described feature extraction procedure, which included position-independent nucleotides and dinucleotides, position-dependent nucleotides and dinucleotides, melting temperature, GC counts, and the minimum self-folding free energy). Nucleotide sequence encompass the guide RNA and target sequence. The guide RNA of the CRISPR-Cas system is interpreted as equivalent to the pegRNA of a prime editing system (as taught by Xu et al. – see reason to combine)
Regarding Claim 8, Kim et al. teach the predictive model generator comprises a feature extraction module for extracting features affecting prime editing efficiency from information about pegRNA and a target sequence (Page 5, Column 2, Paragraph 7: For determining the features of nucleotide sequences, we used a previously described feature extraction procedure, which included position-independent nucleotides and dinucleotides, position-dependent nucleotides and dinucleotides, melting temperature, GC counts, and the minimum self-folding free energy). Kim et al. teach the methods are performed by computer (Page 6, Column 1, Paragraph 3: Code availability. All custom Python scripts used for the indel frequency analysis, Seq-deepCpf1, and DeepCpf1 are available on GitHub), which is indicative of a system that performs the functions/methods recited and includes the functions of the units/predictors/modules (see claim interpretation - 112(f) and the 112(b) rejection above).
Regarding Claim 9 and 18, Kim et al. teach wherein the predictive model generator performs deep learning based on a convolutional neural network (CNN) (Page 5, Column 1, Paragraph 2: Convolutional neural network; Page 4, Column 1, Paragraph 4: DeepCpf1 eliminates the need for laborious manual feature engineering, leveraged by the use of a CNN. DeepCpf1 can thus automatically learn informative representations of target sequences relevant to AsCpf1 activity profiles).
Regarding Claim 10, Kim et al. teach the candidate target sequence comprises a protospacer adjacent motif (PAM), and a protospacer sequence (Page 5, Column 1, Paragraph 1: For each target site, 27 bases of the protospacer adjacent motif (PAM) plus protospacer sequence were aligned).
Regarding Claim 11, Kim et al. the efficiency predictor predicts editing efficiency of candidate target sequences by an editor and guide RNA (Page 4, Column 1, Paragraph 2: we used 20-nt guide sequences because this guide RNA truncation perfectly preserves Cpf1 activity; Page 5, Column 1, Paragraph 4: DeepCpf1 receives a 34-bp target sequence as input, and it produces a regression score that highly correlates with AsCpf1 activity). It would be obvious to swap the CRISPR-Cas editing system of Kim et al. for the prime editing system of Xu et al. (see reason to combine). Relatedly, the guide RNA recited Kim et al. is equivalent to the pegRNA of Xu et al.
Regarding Claim 12, Kim et al. teach an output unit for outputting the editing efficiency predicted by the efficiency predictor (Page 5, Column 2, Paragraph 1: The last stage, the regression output layer, performs a linear transformation of the outputs of the chromatin accessibility integration layer and makes a prediction of AsCpf1 activity (i.e. the model outputs information)). Kim et al. teach the methods are performed by computer (Page 6, Column 1, Paragraph 3: Code availability. All custom Python scripts used for the indel frequency analysis, Seq-deepCpf1, and DeepCpf1 are available on GitHub). This is indicative a system that performs the functions/methods recited and includes the functions of the units/predictors/modules (see claim interpretation - 112(f) and the 112(b) rejection above). A generic computer inherently has an interface (e.g. a display) for outputting information. It would be obvious to swap the editing system of Kim et al. for the prime editing system of Xu et al. (see reason to combine).
Regarding Claim 13, Kim et al. teach (Claim 13.i) obtaining an editing efficiency data set of a gene editor (Page 1, Column 2, Paragraph 2: The high-throughput experiments A and B led to the generation of data sets HT 1 and HT 2; Page 5, Column 2, Paragraph 3: Model selection and pre-training. First, we split data set HT 1 into data sets). The dataset generated by the experiments was received as it is used to train the models. Kim et al. also teach (Claim 13.ii) generating editing efficiency predictive models by performing deep learning to learn a relationship between features affecting editing efficiency and editing efficiency, by using the prime editing efficiency data set (Page 5, Column 1, Paragraph 4: DeepCpf1 is a deep-learning framework for AsCpf1 indel frequency prediction. DeepCpf1 receives a 34-bp target sequence as input, and it produces a regression score that highly correlates with AsCpf1 activity. DeepCpf1 can thus automatically learn informative representations of target sequences relevant to AsCpf1 activity profiles). DeepCpf1 is a predictive that model that is generated by using the data received from the experiments. Performing deep learning to learn a relationship is interpreted as training the predictive model.
Regarding Claim 19, Kim et al teach (Claim 19.i) designing candidate target sequences for gene editing (Page 4, Column 1, Paragraph 2: For high-throughput experiments A and B, a total of 67,301 Cpf1 target sequences were designed from the coding sequences of 19,565 human genes using Cpf1-Database). Kim et al teach (Claim 19.ii) predicting editing efficiency by applying the designed candidate target sequences to the system for predicting editing efficiency of claim 1 (see regarding claim 1).
Regarding Claim 20, Kim et al. teach a computer-readable recording medium on which a program on a computer is recorded as Kim et al. teach the methods are performed by computer (Page 6, Column 1, Paragraph 3: Code availability. All custom Python scripts used for the indel frequency analysis, Seq-deepCpf1, and DeepCpf1 are available on GitHub), which inherently contain computer-readable recording medium on which a program is recorded. Kim et al. in combination with Xu et al. teach the method of claim 19 (see Regarding Claim 19).
Kim et al. does not teach the gene editing system is a prime editing system or components related to a prime editing system (Claim 1-20). Kim et al. also does not teach the prime editor 2 (Claim 2). Kim et al. also does not teach information about a reverse transcriptase (RT) template sequence or information about a primer binding site (PBS) sequence (Claims 7 and 17).
Regarding Claim 1, Xu et al. teach use of prime editors (Page 6, Column 1, Paragraph 3: The plant prime editor 2 (pPE2) was assembled). Xu et al. also teach the measuring and use of the efficiency of prime editing systems, including PE2, to edit target sequences and was confirmed by sequencing (Page 6, Column 2, Paragraph 2: To determine the prime editing in T0 transgenic plants, we selected at least three leaves of each event together as a single sample for genotyping; Page 4, Column 1, Paragraph 2: To test whether pPE2 edits rice genome, we selected three genomic sites, OsPDS, OsACC1, andOsWx, as targets. We found that seven plants (7.3%) were precisely edited). It would be obvious combine the gene editing methods and system of Kim et al. with the prime editing methods and system of Xu et al. (see reason to combine below).
Regarding Claim 2, Xu et al. teach the use of prime editor 2 (Page 6, Column 1, Paragraph 3: The plant prime editor 2 (pPE2) was assembled).
Regarding Claim 3 and 15, Xu et al. teach the prime editing efficiency is represented by a rate of occurrence of intended edits by a prime editor and pegRNA at a target sequence without generation of an unintended mutant (Page 4, Column 1, Paragraph 2: We found that seven plants (7.3%) were precisely edited). 7 out of 96 *100 = 7.3% which is interpreted as a rate of occurrence. Precisely edited is interpreted as the plants showed only the desired change (i.e. without unintended mutant).
Regarding Claim 7 and 17, Xu et al. teach information about a reverse transcriptase (RT) template sequence, information about a primer binding site (PBS) sequence, and information about the target sequence (Page 6, Column 1, Paragraph 3: then assembled with sgRNA scaffold and PBS plus RT template sequence. To construct HPT-ATG, we introduced the mutation at the start codon and the artificial target sequence by direct PCR amplification). The cited section of the art indicate the sequences of the PBS, RT, and target (HPT). It would be obvious to use the feature extractor of Kim et al. (see regarding claim 6) that function given nucleotide sequences, which is discussed by Xu et al.
Regarding Claim 13, Xu et al. teach use of prime editors (Page 6, Column 1, Paragraph 3: The plant prime editor 2 (pPE2) was assembled). The efficiency of prime editing systems, including the pPE2, were confirmed by sequencing (Page 6, Column 2, Paragraph 2: To determine the prime editing in T0 transgenic plants, we selected at least three leaves of each event together as a single sample for genotyping; Page 4, Column 1, Paragraph 2: To test whether pPE2 edits rice genome, we selected three genomic sites, OsPDS, OsACC1, andOsWx, as targets. We found that seven plants (7.3%) were precisely edited).
Regarding Claim 19, Xu et al. teach (Claim 19.i) designing candidate target sequences for prime editing (Page 6, Column 1, Paragraph 3: Vector Construction. The double strands of protospacers, the sgRNA scaffold, and PBS plus RT template sequences were synthesized, annealed, and inserted into a BsaI-predigested, OsU3 promoter driving expression cassette in the pHUC411-PE2 vector. To construct HPT-ATG, we introduced the mutation at the start codon and the artificial target sequence by direct PCR amplification; Page 2, Figure 1: pegRNAs designed for editing on HPT-ATG. Upper: schematic illustration of the HPT-ATG reporter. Lower: the target sequence for pegRNA design). It is obvious that the custom vector constructed for the experiment was designed. Kim et al. in combination with Xu et al. teach (Claim 19.ii) predicting prime editing efficiency by applying the designed candidate target sequences to the system for predicting prime editing efficiency of claim 1 (see regarding claim 1).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date to modify Kim et al. with Xu et al. (i.e. replace the CRISPR-Cas of Kim et al. with system with the prime editing system of Xu et al.). Xu et al. teach prime editing is a novel and useful gene editing system that overcomes limitations of previous gene editing systems (Page 3, Column 1, Paragraph 2: Recently, prime editors (PEs) were developed to generate precise editing without the requirement of DSBs or donor DNA. A prime-editing guide RNA (pegRNA) was designed to mediate site-specific nicking by nCas9 and then served as a template for RT to install customizable mutations. PEs could efficiently produce all possible base conversions and small insertions in a wider targeting range with limited byproducts in human cells). Prime editing and its components are seen as a functionally equivalent and related gene editing system to CRISPR-Cas systems. This is supported by Paragraph 0003 of the published specification of the instant application which indicates certain CRISPR and Cas9 components are involved in prime editing systems. It would therefore have been obvious to utilize the prime editing system in place of the older less versatile gene editing system used by Kim et al. Furthermore, one of ordinary skill in the art would predict that the different methods could be readily combined with a reasonable expectation of success because both utilize closely related gene editing systems. Additionally, the input of the models of Kim et al. include sequencing data and related information and output includes efficiency of gene editing. These pieces of data are considered by methods Xu et al. Accordingly, Claims 1-20 taken as a whole would have been prima facie obvious before the effective filing date and are rejected under 35 U.S.C. 103.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 13-17 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 4, 5, 7, and 20 of copending Application No. 19109301 (reference application). Although the claims at issue are not identical, they are not patentably distinct from each other (see table below).
Instant Application Claim
Matching Reference Application 19109301 Claim
13
1 or 7
14
5
15
4
17
20
This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented.
Claim 1, 3, 4, 6, 9, 10, 12, 19, and 20 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 3, 5, 6, and 8-12 of copending Application No. 18319071 in view of the published specification of the instant application that indicates a prime editor contains Cas9 (Paragraph 0003), which is used in application 18319071.
Instant Application Claim
Matching Reference Application 18319071 Claim
1
1
3
5
4
8
6
3
9
6
10
10
12
9
19
11
20
12
This is a provisional nonstatutory double patenting rejection.
Claim 1, 3, 4, 12, 19, and 20 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 2, 4, 7, 10, 12, and 13 of copending Application No. 18309208 in view of the published specification of the instant application that indicates a prime editor contains Cas9 (Paragraph 0003), which is used in application 18309208.
Instant Application Claim
Matching Reference Application 18309208 Claim
1
1 and 2
3
10
4
4
12
7
19
12
20
13
This is a provisional nonstatutory double patenting rejection.
Conclusion
No claims are allowed.
No subject matter eligibility rejection (under 35 USC 101) was made because an unconventional additional element was recited by independent claims (Claim 1 and 13) – receive/obtain information on prime editing efficiency. Prime editing techniques were unconventional at the time the effective filing date (2020).
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/B.H.E./Examiner, Art Unit 1687
/Karlheinz R. Skowronek/Supervisory Patent Examiner, Art Unit 1687
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