DETAILED ACTION
Claim Status
Claims 1-28 are rejected.
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 .
Information Disclosure Statement
No IDS has been filed herein.
Priority
This application claims domestic benefit to provisional application # 63242190, filed 09/09/2021. Domestic benefit is acknowledged. Therefore, the effective filing date of claims 1-28 is 09/09/2021.
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 – 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.
Drawings
The drawings are objected to because they include nucleotide disclosures that are not identified by SEQ ID Nos (see above). Corrected drawing sheets in compliance with 37 CFR 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 37 CFR 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.
Specification
The disclosure is objected to because of the following informalities: , Figs. 2A-2C and 4A-4B are not properly described because the brief description only mentions Fig. 2 and Fig. 4 and does not describe the partial views separately, as required (see MPEP 608.01(f)).
Appropriate correction is required.
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(s) 1-28 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
In accordance with MPEP § 2106, claims found to recite statutory subject matter ( Step 1 : YES) are then analyzed to determine if the claims recite any concepts that equate to an abstract idea, law of nature or natural phenomenon (Step 2A, Prong 1). In the instant application, the claims recite the following limitations that equate to an abstract idea:
Claims 1, 17, and 28 recite “generates an initial plurality of strands by assigning a respective sequence of nucleotides to each of the plurality of strands;”
Assigning a sequence of nucleotides to a strand is a mental process because a human being with a pen and paper could carry it out. There is nothing stating that the assigned nucleotides have to match the strands, so a human could write arbitrary nucleotides, or use their own knowledge.
Claims 1, 17 and 28 recite “evaluates a cost function for the plurality of strands, the cost function indicative of the similarity between an estimated binding pattern of the plurality of strands and the intended binding pattern, wherein evaluating the cost function comprises, for every pair of nucleotides in every pair of the plurality of strands, and each pair of nucleotides comprising a first nucleotide from one of the plurality of strands and a second nucleotide from another of the plurality of strands,”
Evaluating a cost function is a simple mathematical calculation that can be performed with a pen and paper, making it an example of a mental process and a mathematical relationship.
Claims 1, 17 and 28 recite “determining a pair-wise cost based on the intended binding pattern and the retrieved pre-computed binding probability; summing the determined pair-wise costs over all of the pairs of nucleotides to obtain an overall cost; iteratively, until a threshold condition is satisfied, mutates a subset of the nucleotides in at least one of the plurality of strands to different nucleotides; re-evaluates the cost function to determine an updated overall cost; retains the mutated nucleotides responsive to detecting an improvement in the updated overall cost relative to a previously-computed overall cost; and rejects the mutated nucleotides responsive to not detecting an improvement in the updated overall cost relative to a previously-computed overall cost;“
This iterative algorithm involves simple arithmetic calculations and decisions, so it could be performed by a human being with a pen and paper carrying out the steps, which makes it an example of a mental process and a mathematical relationship.
Claims 3-4, 6-11, 14, 18, 20, 22-24 add details about the composition and/or calculation of the overall cost, the maximum neighborhood length, the threshold condition, the initial plurality of strands, and the generation of the initial plurality of strands of claims 1 and 17, which makes them part of the mental process/mathematical relationship of claims 1 and 17.
In claim 3, Incremental evaluation of a cost function based on previously changed nucleotides is a mental process and a mathematical relationship because it is a these are steps of an algorithm that could be performed by a human being with a pen and paper. This could be as simple as adding a different integer value based on the letter of the nucleotide.
Claims 4, 6-11, 14, 20, 22-24 give numerical values to the variables used in the mental process/mathematical relationship of claims 1 and 17, making them part of the mental process of claims 1 and 17 respectively.
In claim 18, assigning a sequence of nucleotides to a plurality of strands using a probability distribution is a mental process and a mathematical relationship because a human being with a pen and paper could use probabilities to assign letters to data
Claims 2 and 18 recite “The system of claim 1 wherein the at least one processor generates the initial plurality of strands by assigning a respective sequence of nucleotides to each of the plurality of strands using at least one probability distribution.”
Assigning nucleotides to strands using a probability distribution is a mental process and a mathematical relationship because assigning numbers to a list of variables could be carried out by a human being with a pen and paper.
Claims 5 and 21 recite “The system of claim 1 wherein the at least one processor mutates a subset of the nucleotides based on at least one probability distribution.”
Mutating nucleotides (in the context of computer information) based on probabilities is a mental process and a mathematical relationship because a human being with a list of nucleotides on a piece of paper could change one nucleotide based on a probability.
Claim 12 recites “The system of claim 1 wherein the pair-wise cost is determined according to the formula: ci j= (ti j+ 1) / 2 - ti j × pi j wherein ci j is the pair-wise cost for the first nucleotide and the second nucleotide, ti j is +1 for an intended binding and -1 for an intended non-binding, and pi,j is the pre-computed binding probability.”
This equation for the determination of pairwise cost involves organizing information by representing mathematical relationships between the nucleotides and their intended binding, and it can be solved by a human being, thus making it a mathematical concept.
Claims 13 and 25 recite “The system of claim 1 wherein the pair-wise cost is determined according to the formula: ci j = 0 for an intended binding, ci j = pi j for an intended non-binding, wherein ci j is the pair-wise cost for the first nucleotide and the second nucleotide, and pi j is the pre-computed binding probability.”
This formula for determining the pairwise cost involves organizing information by representing mathematical relationships between the nucleotides and their intended binding, and it can be solved by a human being, thus making it a mathematical concept.
While claims 1, 17, and 28 recite performing some aspects of the analysis with a system, processor-implemented method, or non-transitory computer memory, there are no additional limitations that indicate that these formats require anything other than carrying out the recited mental process or mathematical concept in a generic computer environment. Merely reciting that a mental process is being performed in a generic computer environment does not preclude the steps from being performed practically in the human mind or with pen and paper as claimed. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then if falls within the “Mental processes” grouping of abstract ideas. As such, claim(s) 1-28 recite an abstract idea/law of nature/natural phenomenon ( Step 2A, Prong 1 : YES).
Claims found to recite a judicial exception under Step 2A, Prong 1 are then further analyzed to determine if the claims as a whole integrate the recited judicial exception into a practical application or not (Step 2A, Prong 2). This judicial exception is not integrated into a practical application because the claims do not recite an additional element that reflects an improvement to technology or applies or uses the recited judicial exception to affect a particular treatment for a condition. Rather, the instant claims recite additional elements that amount to mere instructions to implement the abstract idea in a generic computing environment or mere instructions to apply the recited judicial exception via a generic treatment. Specifically, the claims recite the following additional elements:
Claims 1, 17, and 28 recite a system, non-transitory computer memory, or processor implemented method that “receives data specifying an intended binding pattern between a plurality of strands of nucleotides, each of the plurality of strands comprising a sequence of nucleotides having a respective length of nucleotides;”
Claims 1, 17, and 28 recite “retrieving, from the at least one nontransitory memory, a pre-computed binding probability that the first nucleotide will bind with the second nucleotide, wherein the pre-computed binding probability is based on a model that considers the binding behavior of only a first neighborhood of adjacent nucleotides that includes the first nucleotide and a second neighborhood of adjacent nucleotides that includes the second nucleotide, wherein each of the first and second neighborhoods has a neighborhood length that is less than or equal to a maximum neighborhood length;”
Claims 1, 17, and 28 recite “stores a final plurality of strands, each comprising a respective final sequence of nucleotides, in the at least one nontransitory memory.”
Claims 15 and 26 recite “The system of claim 1 wherein the at least one processor receives data specifying at least one of a temperature condition or a salt condition, and wherein the retrieved pre-computed binding probabilities are based at least part on the temperature condition or salt condition.”
Claims 16 and 27 recite “The system of claim 1 wherein the pre-computed binding probabilities are retrieved from a database addressable by a linear index that is determinable using data identifying the first and second neighborhoods.”
There are no limitations that indicate that the claimed system, processor-implemented method, non-transitory computer memory or the formats of the provided data require anything other than generic computing systems. As such, these limitations equate to mere instructions to implement the abstract idea on a generic computer that the courts have stated does not render an abstract idea eligible in Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984.
The additional elements of claims 1, 15-17, 26 and 28 do not add a meaningful limitation to the abstract idea because they amount to mere data gathering/output steps that would be required for the claimed mental processes. These limitations serve to gather data that is used as input/output for the abstract idea, which is used at all steps of the recited abstract idea. There is no indication that the abstract idea has any impact on those data gathering steps. The courts have indicated that mere data gathering/outputting activity is insignificant extra-solution activity that does not provide a practical application (see MPEP 2106.05(g)). Therefore, the additional elements of claims 1, 15-17, 26 and 28 are found to not integrate the judicial exception into a practical application ( Step 2A, Prong 2 : NO).
Claims found to be directed to a judicial exception are then further evaluated to determine if the claims recite an inventive concept that provides significantly more than the judicial exception itself (Step 2B). The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims recite additional elements that equate to mere instructions to apply the recited exception in a generic way or in a generic computing environment. The instant claims recite the following additional elements:
Claims 1, 17, and 28 recite “receives data specifying an intended binding pattern between a plurality of strands of nucleotides, each of the plurality of strands comprising a sequence of nucleotides having a respective length of nucleotides;”
Claims 1, 17, and 28 recite “retrieving, from the at least one nontransitory memory, a pre-computed binding probability that the first nucleotide will bind with the second nucleotide, wherein the pre-computed binding probability is based on a model that considers the binding behavior of only a first neighborhood of adjacent nucleotides that includes the first nucleotide and a second neighborhood of adjacent nucleotides that includes the second nucleotide, wherein each of the first and second neighborhoods has a neighborhood length that is less than or equal to a maximum neighborhood length;”
Claims 1, 17, and 28 recite “stores a final plurality of strands, each comprising a respective final sequence of nucleotides, in the at least one nontransitory memory.”
Claims 15 and 26 recite “The system of claim 1 wherein the at least one processor receives data specifying at least one of a temperature condition or a salt condition, and wherein the retrieved pre-computed binding probabilities are based at least part on the temperature condition or salt condition.”
Claims 16 and 27 recite “The system of claim 1 wherein the pre-computed binding probabilities are retrieved from a database addressable by a linear index that is determinable using data identifying the first and second neighborhoods.”
As discussed above, there are no additional limitations to indicate that the claimed system, processor-implemented method, or non-transitory computer memory requires anything other than generic computer components in order to carry out the recited abstract idea in the claims. Claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984.
The courts have decided that storing and retrieving information in memory, as in Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93 is well-understood, routine, conventional activity that amounts to insignificant extra-solution activity. The additional elements of claims 1, 15-17, 26 and 28 would classify as well-understood, routine, conventional activity, and thus insignificant extra-solution activity.
The additional elements do not comprise an inventive concept when considered individually or as an ordered combination that transforms the claimed judicial exception into a patent-eligible application of the judicial exception.
Therefore, the claims do not amount to significantly more than the judicial exception itself ( Step 2B : NO). As such, claims 1-28 are not patent eligible.
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.
Claims 1-11, 14-24, and 26-28 are rejected under 35 U.S.C. 103 as being unpatentable over the Massachusetts Institute of Technology thesis paper “A Systematic and Extensible Approach to DNA Primer Design for Whole Gene Synthesis, Amanda Victrix Allen Wozniak, September 2005 (hereafter ‘Wozniak’”).
Regarding claim 1:
at least one nontransitory memory that stores at least one of processor-executable instructions or data; and at least one processor communicatively coupled to the at least one nontransitory memory, in operation, the at least one processor
Wozniak discusses a primer design algorithm designed to be implemented on a generic computer, which would have the claimed parts (Chapter 1 introduction, pg. 15)
receives data specifying an intended binding pattern between a plurality of strands of nucleotides, each of the plurality of strands comprising a sequence of nucleotides having a respective length of nucleotides
Section 4.1.2 of Wozniak discusses the requirements of input to the system: “User requirements, such as avoiding primers and primer overlaps with a Tm outside the acceptable range, or overlaps which do not properly buffer repeat sequences, are applied as unary constraints to prune the set of possible primers down to the set of valid primer overlaps. This valid overlap set is then traversed by a backtracking constraint propagation algorithm which uses nucleotide locations in the target strand as the variables and the set of primer overlaps which span that base position as the values.” These user requirements describe the intended binding pattern. Figure 4-1 on page 56, reproduced below, shows the input sequence and user input parameters.
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This figure specifies the relationship between the input/”target” sequence and the sequence element array, which together form the “plurality of strands”.
generates an initial plurality of strands by assigning a respective sequence of nucleotides to each of the plurality of strands
This is equivalent to the construction of the “Sequence Element Array” found in 4.4.2 on page 61 of Wozniak (“Construct the Sequence Element Array using these codon assignments for all optimisable nucleotides in ORFs and the user's input for all remaining nucleotides.”).
evaluates a cost function for the plurality of strands, the cost function indicative of the similarity between an estimated binding pattern of the plurality of strands and the intended binding pattern, wherein evaluating the cost function comprises, for every pair of nucleotides in every pair of the plurality of strands, and each pair of nucleotides comprising a first nucleotide from one of the plurality of strands and a second nucleotide from another of the plurality of strands,
Section 5.3.1 of Wozniak: “Evaluate the melting temperature of potential primer or primer overlaps and determine if they are valid according to a user's Tm restrictions for purification and assembly. - (CHECKTEMP: evaluates a constraint for feature-driven primer design, used to build the TVO, given an annotated SEA.)”.
The determination of Tm is computed in Wozniak as part of the salt-corrected nearest-neighbors method (Wozniak section 2.3, page 24 ¶ 1), and it is based on the intended binding pattern because of the setting of target Tm by the user, which specifies how the user expects the binding to behave. Therefore it is a type of evaluated cost function.
retrieving, from the at least one nontransitory memory, a pre-computed binding probability that the first nucleotide will bind with the second nucleotide, wherein the pre-computed binding probability is based on a model that considers the binding behavior of only a first neighborhood of adjacent nucleotides that includes the first nucleotide and a second neighborhood of adjacent nucleotides that includes the second nucleotide, wherein each of the first and second neighborhoods has a neighborhood length that is less than or equal to a maximum neighborhood length;
Section 5.3.1 of Wozniak: “Evaluate the melting temperature of potential primer or primer overlaps and determine if they are valid according to a user's Tm restrictions for purification and assembly. - (CHECKTEMP: evaluates a constraint for feature-driven primer design, used to build the TVO, given an annotated SEA.)”.
Tm is the melting temperature of a given sequence and is stated to be calculated by the salt-corrected nearest neighbors method (Wozniak section 2.3, page 24 ¶ 1). The step of determining if the melting temperatures are valid according to the restriction converts the melting temperature into a “binding probability,” either 0 or 1. Since a probability can be in the range of zero to one, and this step makes a determination about the possibility of the binding of nucleotides to one another, this step falls within the broadest reasonable interpretation of “binding probability.” This section of Wozniak is silent as to the neighborhood of nucleotides, but it is discussed beforehand:
In section 4.4.4 of Wozniak, there is a step to “Flag all entries in the SEA which are in a repeat or within buffer_size of a repeat as being invalid overlap end sites. Flag all remaining entries as valid end sites.”
The evaluation of overlaps based on Tm is “based on a neighborhood of adjacent nucleotides that includes the first nucleotide and a second neighborhood of adjacent nucleotides that includes the second nucleotide, wherein each of the first and second neighborhoods has a neighborhood length that is less than or equal to a maximum neighborhood length”, because the evaluation is over the SEA, which has been filtered based on buffer_size, which would be the maximum neighborhood length.
determining a pair-wise cost based on the intended binding pattern and the retrieved pre-computed binding probability; summing the determined pair-wise costs over all of the pairs of nucleotides to obtain an overall cost;
Section 4.4.5 of Wozniak: “Apply the following constraints to the completely annotated SEA to build the Valid Overlap Table (TVO): the outside/end nucleotides of valid overlaps must be valid end sites; valid overlaps must meet a user's length criteria; valid overlaps must satisfy Tm criteria. Each entry in the Valid Overlap Table contains the terminating indices which define that overlap along with a value representing how much that overlap's melting temperature varies from the user's target mean.”
The determination of pairwise cost between individual nucleotide pairs is computed in Wozniak as part of the salt-corrected nearest-neighbors method (Wozniak section 2.3, page 24 ¶ 1), and it is based on the intended binding pattern because of the setting of target Tm as part of the user requirements. The variance in overlap melting temperature would be equivalent to the overall cost.
iteratively, until a threshold condition is satisfied, mutates a subset of the nucleotides in at least one of the plurality of strands to different nucleotides; re-evaluates the cost function to determine an updated overall cost; retains the mutated nucleotides responsive to detecting an improvement in the updated overall cost relative to a previously-computed overall cost; and rejects the mutated nucleotides responsive to not detecting an improvement in the updated overall cost relative to a previously-computed overall cost; and stores a final plurality of strands, each comprising a respective final sequence of nucleotides, in the at least one nontransitory memory.
Wozniak states: “The solution to the overlap constraint satisfaction problem is stored in the Solution Overlap Array (SOA), and then is converted into the SOLUTION PRIMER ARRAY (SPA). Additional data, such as the user's input options, are stored in auxillary variables which do not contribute significantly to the memory overhead of our primer design software.” (section 5.1 pg 68 ¶ 2)
Wozniak Section 5.8.3 provides an algorithm for post-optimization search:
Find and flag all codons which are eligible for substitution. Based on the Tm information for the codon, indicate the preferred thermal bias (if any).
Using the thermally ranked codon usage table for the host organism, identify the valid substitutions which satisfy the above thermal bias constraint.
Change one codon at random. Run the feature-driven design preprocessor and count the number of valid overlaps in the solution search database.
If the number of valid overlaps decreased, revert the current codon and flag it so that particular substitution no longer considered a valid option.
If the number of valid overlaps did not change, make a different codon substitution.
If the number of valid overlaps increased, run the remainder of the FD design process and see if a valid solution now exists. Iterate until a solution is found.
This algorithm iteratively mutates nucleotides and re-evaluates updated thermal bias (cost function), deciding to retain or reject changes based on the change in thermal bias, and continues until a solution is found. This is the same process that is described in the limitation.
Regarding claim 2:
The system of claim 1 wherein the at least one processor generates the initial plurality of strands by assigning a respective sequence of nucleotides to each of the plurality of strands using at least one probability distribution.
Wozniak section 4.4.2: “Our pre-optimisation strategy can only be applied to amino-acid sequences. If a user provides a nucleotide sequence with ORFs, use the Codon Usage Table to translate from a, nucleotide sequence to an amino acid sequence for each ORF, and pre-optimise the ORFs in aggregate. Identify repeated amino acid sequences and construct the Identified AA Repeat Table (IART). Using the IART, assign each repeat a different codon usage pattern and assign codons randomly for those amino acids which are not in a repeat sequence. Construct the Sequence Element Array using these codon assignments for all optimisable nucleotides in ORFs and the user's input for all remaining nucleotides. Flag those nucleotides which were in an amino-acid level repeat as being non-optimisable.”
The codon usage pattern of Wozniak is a kind of probability distribution applied to the plurality of strands.
Regarding claim 3:
The system of claim 1 wherein, to evaluate the cost function to determine an updated overall cost, the at least one processor incrementally evaluates the cost function based on the nucleotides that were mutated relative to the previous iteration.
This is covered by the algorithm for post-optimization search found in section 5.8.3 of Wozniak and reproduced above.
Regarding claim 4:
The system of claim 1 wherein the overall cost is based at least in part on the thermodynamics of binding of the plurality of strands.
The determination of Tm, defined in Wozniak as the DNA melting temperature (Wozniak section 2.3, pg 28 ¶ 1), is computed as part of the salt-corrected nearest-neighbors method (Wozniak section 2.3, page 24 ¶ 1), and the variance in Tm in Wozniak is equivalent to the “overall cost” of the instant application, as previously argued.
Regarding claim 5:
The system of claim 1 wherein the at least one processor mutates a subset of the nucleotides based on at least one probability distribution.
The iterative mutation algorithm of 5.8.3 of Wozniak is based on the codon usage pattern (“probability distribution”) calculation found in 4.4.2.
Regarding claim 6:
The system of claim 1 wherein the threshold condition comprises one or more of an amount of improvement in the overall cost, a number of iterations, or an elapsed time.
In 5.8.1 of Wozniak, the algorithm iterates “until a solution is found”, which would correspond to an improvement in the overall cost.
Regarding claims 7-11 and 14:
7. The system of claim 1 wherein the maximum neighborhood length is equal to seven.
8. The system of claim 1 wherein the maximum neighborhood length is greater than or equal to seven.
9. The system of claim 1 wherein the maximum neighborhood length is an odd integer.
10. The system of claim 1 wherein the maximum neighborhood length is an odd integer, and the first and second nucleotides are the center nucleotides in the first and second neighborhoods, respectively.
11. The system of claim 1 wherein the maximum neighborhood length is an even integer, and the first and second nucleotides are nucleotides just to the left or right of the center of the first and second neighborhoods, respectively.
14. The system of claim 1 wherein each of the plurality of strands comprise a sequence of four nucleotides.
Regarding claims 7-11, the “maximum neighborhood length” of the instant application is equivalent to the buffer_size of Wozniak, as argued above. Wozniak writes: “We choose the default for buffer_size to be on the order of 4-8 nucleotides” (Section 3.3.2.3 pg 47 ¶ 3). This means the possible ranges of the instant application are all found in Wozniak.
Regarding claim 14, there is no limit to the number of nucleotides used as input in Wozniak. Wozniak writes: “We choose the default for buffer_size to be on the order of 4-8 nucleotides” (Section 3.3.2.3 pg 47 ¶ 3).
Regarding claim 15:
The system of claim 1 wherein the at least one processor receives data specifying at least one of a temperature condition or a salt condition, and wherein the retrieved pre-computed binding probabilities are based at least part on the temperature condition or salt condition.
The determination of Tm is computed in Wozniak as part of the salt-corrected nearest-neighbors method (Wozniak section 2.3, page 24 ¶ 1). The user input specifies the target Tm (section 4.1.2 page 56 ¶ 2): “User requirements, such as avoiding primers and primer overlaps with a TA. outside the acceptable range, or overlaps which do not properly buffer repeat sequences, are applied as unary constraints to prune the set of possible primers down to the set of valid primer overlaps”.
Regarding claim 16:
The system of claim 1 wherein the pre-computed binding probabilities are retrieved from a database addressable by a linear index that is determinable using data identifying the first and second neighborhoods.
The “valid overlap table” of 4.4.5 of Wozniak, from which the binding probabilities are received, is addressable by a linear index because it is a table, and it is determinable from the neighborhoods because they are sets of nucleotides from which the probabilities are computed.
Claim 17 is a restatement of claim 1 as a “processor-implemented method” rather than as a “system.” This does not change the substance of the claim and all the arguments from claim 1 apply.
Regarding claim 18:
18. The system of claim 17 wherein the at least one processor generates the initial plurality of strands by assigning a respective sequence of nucleotides to each of the plurality of strands using at least one probability distribution.
Wozniak section 4.4.2: “Our pre-optimisation strategy can only be applied to amino-acid sequences. If a user provides a nucleotide sequence with ORFs, use the Codon Usage Table to translate from a, nucleotide sequence to an amino acid sequence for each ORF, and pre-optimise the ORFs in aggregate. Identify repeated amino acid sequences and construct the Identified AA Repeat Table (IART). Using the IART, assign each repeat a different codon usage pattern and assign codons randomly for those amino acids which are not in a repeat sequence. Construct the Sequence Element Array using these codon assignments for all optimisable nucleotides in ORFs and the user's input for all remaining nucleotides. Flag those nucleotides which were in an amino-acid level repeat as being non-optimisable.”
The codon usage pattern of Wozniak is a kind of probability distribution applied to the plurality of strands.
Regarding claim 19:
The system of claim 1 wherein, to evaluate the cost function to determine an updated overall cost, the at least one processor incrementally evaluates the cost function based on the nucleotides that were mutated relative to the previous iteration.
This is covered by the algorithm for post-optimization search found in section 5.8.3 of Wozniak and reproduced above.
Regarding claims 20-24:
20. The method of claim 17 wherein the overall cost is based at least in part on the thermodynamics of binding of the plurality of strands.
21. The method of claim 17 wherein mutating a subset of the nucleotides comprises mutating a subset of the nucleotides based on at least one probability distribution.
22. The method of claim 17 wherein the threshold condition comprises one or more of an amount of improvement in the overall cost, a number of iterations, or an elapsed time.
23. The method of claim 17 wherein the maximum neighborhood length is greater than or equal to seven.
24. The method of claim 17 wherein the maximum neighborhood length is an odd integer, and the first and second nucleotides are the center nucleotides in the first and second neighborhoods, respectively.
The “maximum neighborhood length” of the instant application is equivalent to the buffer_size of Wozniak. This means the possible ranges of the instant application are all found in Wozniak.
Regarding claim 26:
The system of claim 1 wherein the at least one processor receives data specifying at least one of a temperature condition or a salt condition, and wherein the retrieved pre-computed binding probabilities are based at least part on the temperature condition or salt condition.
The determination of Tm is computed in Wozniak as part of the salt-corrected nearest-neighbors method (Wozniak section 2.3, page 24 ¶ 1). The user input specifies the target Tm (section 4.1.2 page 56 ¶ 2): “User requirements, such as avoiding primers and primer overlaps with a TA. outside the acceptable range, or overlaps which do not properly buffer repeat sequences, are applied as unary constraints to prune the set of possible primers down to the set of valid primer overlaps”
Regarding claim 27:
The system of claim 1 wherein the pre-computed binding probabilities are retrieved from a database addressable by a linear index that is determinable using data identifying the first and second neighborhoods.
The “valid overlap table” of 4.4.5 of Wozniak, from which the binding probabilities are received, is addressable by a linear index because it is a table, and it is determinable from the neighborhoods because they are sets of nucleotides from which the probabilities are computed.
Claim 28 is a restatement of claim 1, but directed towards “a non-transitory computer memory that stores at least one of instructions or data that, when executed by at least one processor, cause the at least one processor to perform operations, the operations comprising” the steps of claim 1. This does not affect the arguments previously applied to claim 1.
Wozniak does not provide a computer implementation of their algorithm, but does provide a suggestion to do so: “Future developments on this thesis include implementing the system in a programming language such as SCHEME or PERL” (Wozniak chapter 6 pg 87 ¶ 2).
Regarding claims 1-11, 14-24, and 26-28, An invention would have been prima facie obvious to one of ordinary skill in the art at the time of the effective filing date of the invention if some teaching, suggestion, or motivation in the prior art would have led that person to combine the prior art teachings to arrive at the claimed invention. There is a suggestion to implement a design algorithm in the text of Wozniak (Wozniak chapter 6 pg 87 ¶ 2). There would be a reasonable expectation of success in making this combination to a person of ordinary skill in the art, because the algorithm is described in detail in the thesis. Therefore, it would have been prima facie obvious to one of ordinary skill in the art at the time to modify the algorithm of Wozniak by implementing it, in order to use the program.
Claims 12, 13, and 25 are rejected under 35 U.S.C. 103 as being unpatentable over Wozniak as applied to claims 1-11, 14-24, and 26-28 above, and in further view of Dirks and Pierce et al. (Dirks, R.M. and Pierce, N.A. (2004), An algorithm for computing nucleic acid base-pairing probabilities including pseudoknots. J. Comput. Chem., 25: 1295-1304) (hereafter “Dirks”) and the University of North Carolina Thesis “Constraint-Based Design by Cost Function Optimization”, by Eric Douglas Grant, 1991 (hereafter “Grant”).
Claim 12 recites “The system of claim 1 wherein the pair-wise cost is determined according to the formula: ci j= (ti j+ 1) / 2 - ti j × pi j wherein ci j is the pair-wise cost for the first nucleotide and the second nucleotide, ti j is +1 for an intended binding and -1 for an intended non-binding, and pi,j is the pre-computed binding probability.”
Claims 13 and 25 recite “The system of claim 1 wherein the pair-wise cost is determined according to the formula: ci j = 0 for an intended binding, ci j = pi j for an intended non-binding, wherein ci j is the pair-wise cost for the first nucleotide and the second nucleotide, and pi j is the pre-computed binding probability.”
Dirks introduced that “base-pairing probabilities can also be used to construct metrics for evaluating nucleic acid designs. The secondary structure s may be described by a symmetric N × N matrix S with entries Si,j = 1 if s contains base pair i · j and Si,j = 0 otherwise. We augment this matrix by an additional column with entries Si,N+1 = 1 if base i is unpaired and Si,N+1 = 0 otherwise. Hence, each row sum is one.” This describes the general notion of the equations claimed, where intended binding of base pairs is used to score a nucleotide strand.
Grant’s thesis expounds on the iterative optimization of cost functions, and suggests to the reader many ways to improve a cost function for an optimization problem based on the constraints of the problem before the mathematician. In section 5.4.1, Grant gives suggestions for how to incorporate the parameters of a problem into a cost function. Below, figure 5.5 is reproduced, which illustrates the formation of cost function parameters based on constraints.
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Applicant states in their specification that they were inspired by Dirks in creating these equations: “Before discussing implementations of the present disclosure, a naive cost function that works, but is unusable, is first examined. We consider the interaction of every nucleotide i in every strand in the design against every nucleotide j in every strand in the design. The Dirks-Pierce algorithm gives the probability pi,j that nucleotides i and j will pair in equilibrium. See Dirks, R. M. and N. A. Pierce (2004)."An algorithm for computing nucleic acid base-pairing probabilities including pseudoknots." J Comput Chem15 250): 1295-1304. It is noted that this binding probability is independent of concentration, but is dependent on temperature and free energy (e.g., salts, etc.). The design of the DNA system on the other hand, gives us an intention, tij, as to whether these nucleotides i and j are intended to pair or not. As an example, ti,j may be equal to 1 for an intended pairing and -1 for an intended non-pairing.”
However, applicant states that they altered the parameters of their implementation of the Dirks-Peirce algorithm to improve the cost function for some of their use cases. When discussing the equation of claims 13 and 25, applicant writes: “This second example cost function may be advantageous because it may be more worthwhile to penalize an unintended pairing rather than reward an intended pairing.”
Regarding claims 12, 13, and 25, an invention would have been prima facie obvious to one of ordinary skill in the art at the time of the effective filing date of the invention if some suggestion in the prior art would have led that person to combine the prior art teachings to arrive at the claimed invention. Wozniak teaches the steps of claim 1 from which these claims depend, as argued above. Dirks teaches the use of a pair-wise cost function that is based on intended binding. Grant suggests to alter cost functions according to the constraints of a given problem, in order to find a global optimum faster (Grant section 1.8 pg 11). There would be a reasonable expectation of success to a person of ordinary skill in the art because there are a multitude of ways to implement the cost function, and the implementation based on constraints is explained by Grant. Therefore, it would have been prima facie obvious to one of ordinary skill in the art at the time to modify the method of Dirks with the suggestions of Grant to better incorporate the parameters of the problem into the algorithm design.
Conclusion
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/G.M.H./ Examiner, Art Unit 1685
/OLIVIA M. WISE/ Supervisory Patent Examiner, Art Unit 1685