DETAILED ACTION
Applicant's response, filed 8/26/2025, has been fully considered. The following rejections and/or objections are either reiterated or newly applied. They constitute the complete set presently being applied to the instant application.
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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 8/26/2025 has been entered.
Status of the Claims
Claims 1-16 are examined. The examiner would like to note that instant claim 11 previously recited "covers all amino acids or covers at least the amino acids" and now recites "covers the amino acids or covers at least the amino acids" without properly striking the previous “all” term. In the interest of compact prosecution, the examination will proceed. However, the applicant is being reminded to make sure to properly annotate all claim amendments.
Priority
This application 17/302,591 was filed on 08/23/2021. The application does not claim the benefit of priority to any earlier filed applications. As such, the effective filing date of claims 1-16 is 8/23/2021.
Withdrawal / Revision of Objections and/or Rejections
In view of the amendment and remarks from 03/20/2025, the objection to claims 1, 15-16 and rejection of claims 15-16 under 35 USC § 112(a) and 112(b) are hereby withdrawn in view of Applicant's amendments. The rejections of claims 1-16 under 35 U.S.C. 101 are hereby withdrawn in view of Applicant's amendments rendering the ground of rejection moot. Regarding the rejection of claims under 35 U.S.C. 101, in view of the amended “predicting, by the at least one trained machine learning model as a function of the two input strings provided as input, an optimal amino acid sequence of an optimized enzyme capable of catalyzing the chemical reaction of interest” and “modifying, utilizing one or more genetic engineering techniques, an amino acid sequence of an existing enzyme with one or more cloning techniques to transfer a gene to encode the optimized enzyme into an expression vector; and synthesizing the chemical of interest utilizing the optimized enzyme”, the instant claims recite a practical application constituting both an improvement to technology and a particular transformation particular (i.e. predicting an optimal amino acid sequence and utilizing a transformed expression vector to transfer a gene to encode the optimized enzyme).
The rejections of claims 1-3, 9-10, 13-16 over Schwaller and Wilbraham; the rejections of claims 4 and 8 over Schwaller, Wilbraham and Coley; the rejections of claim 5 over Schwaller, Wilbraham, Coley and Forsgren and the rejections of claims 6-7 and 11-12 over Schwaller, Wilbraham and Li are hereby withdrawn in view of Applicant's amendments rendering the ground of rejection moot. Regarding the rejection of claims under 35 U.S.C. 102(a)(1), in view of the amended “predicting, by the at least one trained machine learning model as a function of the two input strings provided as input, an optimal amino acid sequence of an optimized enzyme capable of catalyzing the chemical reaction of interest” and “modifying, utilizing one or more genetic engineering techniques, an amino acid sequence of an existing enzyme with one or more cloning techniques to transfer a gene to encode the optimized enzyme into an expression vector; and synthesizing the chemical of interest utilizing the optimized enzyme”; the prior art can no longer anticipate the recited limitations and it is not clear that any combination of art would have rendered the claims obvious.
However, the following rejections and/or objections are either maintained or newly applied for claims 1-16. They constitute the complete set applied to the instant application.
Claim objections
Claim 16 objected to because of the following informalities: the last sentence of the recited claim ends in “and” referring to potential missing term. Additionally, the recitation is missing a period at the end of the claim. Appropriate correction is required.
Claim Rejections - 35 USC § 112(a)
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.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
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 of carrying out his invention.
Claims 1-16 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains 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, or for pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention. This is a written description rejection.
Claims 1 and 15-16 recite “modifying, utilizing one or more genetic engineering techniques, an amino acid sequence of an existing enzyme with one or more cloning techniques to transfer a gene to encode the optimized enzyme into an expression vector; and synthesizing the chemical of interest utilizing the optimized enzyme” performed by a computer/ processor; which could not modify an amino acid sequence using genetic engineering techniques on its own. To the extent that a functional description can meet the requirement for an adequate written description, it can do so only in accordance with PTO guidelines stating that the requirement can be met by disclosing “sufficiently detailed, relevant identifying characteristics,” including “functional characteristics when coupled with a known or disclosed correlation between function and structure.” Univ. of Rochester v. G.D. Searle, 68 USPQ2d 1424, 1432 (DC WNY 2003).
An applicant may also show that an invention is complete by disclosure of sufficiently detailed, relevant identifying characteristics which provide evidence that inventor was in possession of the claimed invention, i.e., complete or partial structure, other physical and/or chemical properties, functional characteristics when coupled with a known or disclosed correlation between function and structure, or some combination of such characteristics. Enzo Biochem., 323 F.3d at 964, 63 USPQ2d at 1613 (quoting the Written Description Guidelines, 66 Fed. Reg. at 1106, n. 49, stating that “if the art has established a strong correlation between structure and function, one skilled in the art would be able to predict with a reasonable degree of confidence the structure of the claimed invention from a recitation of its function”. Thus, the written description requirement may be satisfied through disclosure of function and minimal structure when there is a well-established correlation between structure and function. See MPEP 2163.
Claims 2-14 are similarly rejected because they are dependent on claim 16 and do not resolve the lack of clarity introduced by claim 1.
Conclusion
No claims are allowed.
Subject to resolution of the above 112 rejections; claims 1-16 appear to be are clear of the prior art. Similar art, such as:
Schwaller, P. et. al. “Molecular Transformer: A Model for Uncertainty-Calibrated Chemical Reaction Prediction” ACS Cent. Sci. 5:1572−1583 (2019) as evidenced by Lowe, D. M. Extraction of Chemical Structures and Reactions from the Literature. Ph.D. Thesis, University of Cambridge (2012) – Schwaller teaches a multihead attention Molecular Transformer model to predict products given the reactants and reagents (pg. 1572 para. 1) for computational reaction prediction by inferring the correlations (between the presence and absence of chemical motifs in the reactant, reagent, and product present in the data set (pg. 1572 para. 1); using simplified molecular-input line-entry system (SMILES) strings of reactants, reagents, and the products. (pg. 1572 para. 1); wherein publicly available chemical reactions datasets derived from patent mining work were used (pg. 1573 col. 2 para. 3) including a plurality of enzymes (i.e., luciferase, elastase-1, methyltransferase, galactosyltransferase, phosphorylase and phosphodiesterase) - enzymes found by an algorithm that identifies chemical entities as evidenced by Lowe (pg. 15 para. 3 and SI text file “2011OSCAR4” by Lowe); wherein training of the machine learning model used the ADAM optimizer and varied the learning rate using 8000 warm up steps and batch size set to about 4096 tokens (pg. 1575 col. 1 para. 1); Schwaller teaches the first network takes a graph representation of the reactants as input and predicts reactivity scores that allow product candidates to be generated and then ranked by a second network (pg. 1573 col. 1 para. 2); using simplified molecular-input line-entry system (SMILES) strings of reactants, reagents, and the products. (pg. 1572 para. 1); wherein the Molecular Transformer model is not simply memorizing the data (i.e., storing the data via a computer readable storage medium) but can leverage information inferred from more common reactions to make predictions on rarer reactions (pg. 1575 col. 2 para. 2)
However the described prior art above does not teach the instant combination of particular steps/elements regarding ““predicting, by the at least one trained machine learning model as a function of the two input strings provided as input, an optimal amino acid sequence of an optimized enzyme capable of catalyzing the chemical reaction of interest” and “modifying, utilizing one or more genetic engineering techniques, an amino acid sequence of an existing enzyme with one or more cloning techniques to transfer a gene to encode the optimized enzyme into an expression vector; and synthesizing the chemical of interest utilizing the optimized enzyme”; and it is not clear that any combination of art would have rendered the claims obvious. Therefore, the claims are interpreted as free of the prior art.'
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/F.F.L./Examiner, Art Unit 1685
/OLIVIA M. WISE/Supervisory Patent Examiner, Art Unit 1685
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