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 .
Claims 30-52 are pending and under examination.
Applicant’s amendment and response, filed 3/13/2026 has been entered and carefully considered, but is not completely persuasive.
The objection to claims 51-52 has been withdrawn.
The rejections under 35 USC 112 have been withdrawn.
The IDS filed 3/13/2026 has been entered and considered.
Claim 47 is objected to because of the following informalities: Claim 47 lacks a status identifier, which appears to be a typographical error. Appropriate correction is required.
Claim Interpretation
The claims in this application are given their broadest reasonable interpretation (BRI) 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.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 30-52 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of mental steps, mathematic concepts, organizing human activity, or a natural law without significantly more.
Applicant is directed to MPEP 2106 and the Federal Register notice (FR89, no 137 (7/17/2024) p 58128-58138) for the most current and complete guidelines in the analysis of patent- eligible subject matter. The current MPEP is the primary source for the USPTO’s patent eligibility guidance.
With respect to step (1): YES, the claims are drawn to statutory categories: Methods, a computer system, and a non-transitory computer readable media.
With respect to step (2A) (1): YES, the claims recite an abstract idea, law of nature and/or natural phenomenon. The claims explicitly recite elements that, individually and in combination, constitute one or more judicial exceptions (JE). (MPEP 2106.04(a)(2) I-III, MPEP 2106.04(b).)
Mathematic concepts, Mental Processes or Elements in Addition (EIA) in the claim(s) include:
Claim 30. A method of parametrically representing genotypic or phenotypic association data from a training data set obtained from a plant population or a plant sample set to impute or predict a genotype and/or a phenotype in a non- training data obtained from a non-training plant population or a non-training plant sample data, the method comprising:
(EIA- preamble, setting forth the method, and the sources of data to be used in the method: training data, and non-training data. A data gathering step.)
generating a platform-independent continuous global latent space representation by encoding discrete or continuous variables derived from a genotypic or phenotypic association training data into latent vectors through a machine learning-based global autoencoder framework,
wherein the global latent space is independent of the underlying genotypic or phenotypic association;
(Mathematic concept of taking the discrete or continuous variables of the training data, and calculating latent vectors, using a generically described ML-based “global” autoencoder framework, with the only qualification that the generated space is independent; disclosed in the specification at: [0068-0074] the computation of p(z|x). “Global” defined at [0101]; MPEP 2106.04(a)(2) section I)
generating a local latent representation by encoding a subset of the discrete or continuous variables derived from the genotypic or phenotypic association training data set into latent vectors through a machine learning-based local autoencoder framework,
wherein the local latent space is generated with inputs from the local autoencoder and the global autoencoder;
(Mathematic concept of taking the discrete or continuous variables of the training data, and calculating latent vectors, using a generically described ML-based “local” autoencoder framework, with the only qualification that the space is generated using local and global inputs; disclosed in the specification at: [0068-0080] the computation of p(z|x). “Local” defined at [0102]. MPEP 2106.04(a)(2) section I)
decoding the global latent representation and the local latent representation by a local decoder,
thereby imputing or predicting the genotype or phenotype of the non- training data by the combination of the decoded global latent representation and the local latent representation;
(Mathematic concept of “decoding” the outputs of the local and global representations, “by combination” as set forth in the specification at [0081-0086]. “decoder” defined at [0103-0105]. MPEP 2106.04(a)(2) section I)
and selecting one or more plant populations or members thereof based on the imputed or predicted genotype or phenotype.
(Mental Process of selection of a plant or plant population, by observation of the imputed or predicted quality for the population, and making a judgement as to whether it meets an unstated requirement. MPEP 2106.04(a)(2) section III)
Claim 31. The method of claim 30, wherein the genotypic association training data is genome-wide genotypic association training data.
(EIA- describing the data to be gathered)
Claim 32. The method of claim 30, wherein the phenotypic association training data is phenome-wide phenotypic association training data.
(EIA- describing the data to be gathered)
Claim 33. . The method of claim 30, wherein the genotypic association data comprises a collection of genotypic markers or single nucleotide polymorphisms (SNPs) from a plurality of genetically divergent populations.
(EIA- describing the data to be gathered)
Claim 34. The method of claim 30, wherein the subset of the discrete variables is a plurality of single nucleotide polymorphisms (SNPs) localized to a segment of the chromosome.
(EIA- describing a subset of data to be used from the gathered data)
Claim 35. The method of claim 30, wherein the genotypic association data is obtained from populations of plants derived from two or more breeding programs, wherein the breeding programs do not comprise an identical set of markers or single nucleotide polymorphisms (SNPs) corresponding to the genotypic association data.
(EIA- description of the source of the data to be gathered.)
Claim 36. The method of claim 30, wherein the machine learning-based global autoencoder framework or machine learning-based local autoencoder framework or a combination thereof is a variational autoencoder.
(Mathematic concept modification, identifying a type of autoencoder.)
Claim 37. The method of claim 36, wherein the variational autoencoder is based on a neural network algorithm.
(Mathematic concept modification, identifying a type of autoencoder.)
Claim 38. The method of claim 30, wherein the machine learning-based global autoencoder framework, machine learning-based local autoencoder framework, or a combination thereof is a generative adversarial network.
(Mathematic concept modification, identifying a type of autoencoder.)
Claim 39. The method of claim 30, the method comprising: training the decoder to learn a prediction or imputation of a genotype or phenotype of interest based on an objective function for the encoded latent vectors.
(Mathematic concept modification: training is applying the vectors to a particular function or algorithm)
Claim 40. The method of claim 39, the method further comprising: decoding by the decoder the encoded latent vector for the objective function.
(Mathematic concept modification: decoding is a mathematic reconstruction to the desired output)
Claim 41. The method of claim 40, the method comprising: providing an output for the objective function of the decoded latent vector.
(Mathematic concept modification: providing the output of the function)
Claim 42. The method of claim 30, the method comprising crossing with another population or member the one or more selected populations or members thereof imputed or predicted to comprise a genotype associated with a desirable trait of interest.
(Mathematic concept modification: “crossing” refers to in silico addition of different data to the model, to identify a trait of interest and the associated genotype; [0082])
Claim 43. The method of claim 30, the method comprising counter- selecting from a breeding program the one or more selected populations or members thereof imputed or predicted to comprise a genotype associated with an undesirable trait of interest.
(Mental process of observing an “undesirable trait” and marking the plant population or member as undesired, or unable to be selected.)
Claim 44. The method of claim 30, the method comprising crossing with another population or member the one or more selected populations or members thereof imputed or predicted to comprise a phenotype associated with a desirable trait of interest.
(Mathematic concept modification: “crossing” refers to in silico addition of different data to the model, to identify a trait of interest and the associated genotype; [0082])
Claim 45. The method of claim 30, the method comprising counter- selecting from a breeding program the one or more selected populations or members thereof imputed or predicted to comprise a phenotype associated with an undesirable trait of interest.
(Mental process of observing an “undesirable trait” and marking the plant population or member as undesired, or unable to be selected.)
Claim 46. The method of claim 30, wherein the plant is a soybean, maize, sorghum, cotton, canola, sunflower, rice, wheat, sugarcane, alfalfa tobacco, barley, cassava, peanuts, millet, oil palm, potatoes, rye, or sugar beet plant.
(EIA- identifying the source of the data collected, by plant type)
Claim 47. The method of claim 30, wherein the imputed or predicted phenotype is yield gain.
(Mental process/ mathematic concept: defining the trait to be imputed or predicted by the model.)
Claim 48. The method of claim 30, wherein the decoder imputes or predicts a molecular phenotype selected from gene expression.
(Mental process/ mathematic concept: defining the output of the decoder, by the label of the desired phenotype)
Claim 49. The method of claim 30, wherein the imputed or predicted genotype is a plurality of haplotypes.
(Mental process/mathematic concept of identifying multiple haplotypes to be predicted.)
Claim 50. The method of claim 30, the method further comprising the step of:
(a) imputing or predicting by the local decoder local high-density (HD) SNPs.
(Mathematic concept: additional mathematic calculations using SNP inputs and the related outputs)
Claim 51. A computing device comprising a processor configured to perform the steps comprising [snip]
(EIA- a general-purpose computing device; the remainder of the analysis is the same as that for claim 30)
Claim 52. A non-transitory computer-readable storage medium comprising instructions which, when executed by a computing device, cause the computing device to carry out the steps comprising [snip]
(EIA- a general-purpose non-transitory computer readable media. The remainder of the analysis is the same as that for claim 30.)
Natural law embraced by claim(s) 30-52:
The claims recite the naturally occurring relationships between naturally occurring genotypes and naturally occurring phenotypes in plant populations using mathematic representations. This is a genotype/ phenotype relationship which exists in nature whether it is measured or not. (MPEP 2106.04(b))
This meets at least the following examples provided by the courts as representing a natural law:
MPEP 2106.04(b): “iii. a correlation between variations in non-coding regions of DNA and allele presence in coding regions of DNA, Genetic Techs. Ltd. v. Merial LLC, 818 F.3d 1369, 1375, 118 USPQ2d 1541, 1545 (Fed. Cir. 2016);
vii. qualities of bacteria such as their ability to create a state of inhibition or non-inhibition in other bacteria, Funk Bros., 333 U.S. at 130, 76 USPQ at 281;”
As explained in MPEP § 2106.04, a claim that recites a law of nature or a natural phenomenon requires further analysis in Step 2A Prong Two to determine whether the claim integrates the exception into a practical application.
With respect to step 2A (2): NO, the claims do not integrate any JE into a practical application (MPEP 2106.04(d)):
“Examiners evaluate integration into a practical application by: (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception(s); and (2) evaluating those additional elements individually and in combination to determine whether they integrate the exception into a practical application, using one or more of the considerations introduced in subsection I supra, and discussed in more detail in MPEP §§ 2106.04(d)(1), 2106.04(d)(2), 2106.05(a) through (c) and 2106.05(e) through (h).”
Claim(s) 30-35, 46 recite the additional non-abstract element(s) of data gathering or a description of the data gathered.
Data gathering steps are not an abstract idea, they are extra-solution activity, as they collect the data necessary to carry out the JE. MPEP 2106.05(g).
The data gathering does not impose any meaningful limitation on the JE, or how the JE is performed. MPEP 2106.05(g).
The data gathering steps constitute a general link to a technological environment: the trait prediction methods are intended to be applied to plant populations. (MPEP 2106.05(h), citing Mayo, Bilski, electric Power Group, Genetic Techs Ltd v Merial LLC.)
The additional limitation (data gathering) must have more than a nominal or insignificant relationship to the identified judicial exception to provide integration into a practical application. (MPEP 2106.05(g) citing Mayo, PerkinElmer, Inc. v. Interna Ltd, Intellectual Ventures LLC v. Erie Indem. Co., Electric Power Group LLC v. Alstom S.A.).
Claim(s) 51, 52 recite the additional non-abstract element (EIA) of a general-purpose computer system or parts thereof.
The claims do not provide any details of how specific structures of the computer elements are used to implement the JE. MPEP 2106.05(a), contrasting decisions identifying how the computer implements an abstract idea, such as in McRo to decisions which found no specific interaction with the computer, such as in Affinity Labs of Tex v. DirecTV, LLC.
The computer elements of the claims do not provide improvements to the functioning of the computer itself. MPEP 2106.05(a) I, contrasting decisions indicating an improvement to the computer, such as DDR Holdings, LLC v. Hotels.com LP, with decisions that did not identify an improvement to the computer, such as FairWarning IP, LLC v. Iatrix Sys.
The computer elements of the claims do not provide improvements to any other technology or technical field. MPEP 2106.05(a) II: contrasting decisions indicating an improvement to the technology, such as Diamond v. Diehr, Trading Techs. Int’l v. CQG Inc, or Intellectual Ventures I v. Symantec Corp, with decisions that did not identify an improvement to the technology, such as Alice Corp, Versata Dev. Group, Inc. v. SAP AM. Inc, or TLI Communications.
The computer elements of the claims do not utilize a particular machine. MPEP 2106.05(b): contrasting decisions wherein a particular machine was identified, such as MacKay Radio & Tel. Co. v. Radio Corp. of America, Eibel Process Co. v. Minn. & Ont. Paper Co., with decisions where a general-purpose computer does not qualify as a particular machine, such as Ultramercial, Inc. v. Hulu, LLC, TLI communications, or Eon Corp. IP holdings LLC v. AT&T Mobility LLC.
Hence, these are mere instructions to apply the JE using a computer, and therefore the claim does not recite integrate that JE into a practical application.
Dependent claim(s) 36-45, 47-50 recite(s) an abstract limitation to the JE reciting additional mathematic concepts, or mental processes. Additional abstract limitations cannot provide a practical application of the JE as they are a part of that JE.
In combination, the limitations of data gathering, for the purpose of carrying out the JE, using a general-purpose computer merely provide extra-solution activity, and fail to integrate the JE into a practical application.
With respect to step 2B: NO, the claims do not provide a specific inventive concept. The judicial exception alone cannot provide that inventive concept or practical application. MPEP 2106.05(I):
“… an "inventive concept" is furnished by an element or combination of elements that is recited in the claim in addition to (beyond) the judicial exception, and is sufficient to ensure that the claim, as a whole, amounts to significantly more than the judicial exception itself. Alice Corp…”
With respect to claim(s) 30-35, 46: The limitation(s) identified above as non-abstract elements (EIA) related to data gathering do not rise to the level of significantly more than the judicial exception.
The genotypic and phenotypic data of plant populations, cited in the preamble, used for the purpose of predicting a trait or phenotype is disclosed by:
Cooper et al. (WO2016/069078 A1: cited in specification) provides genotypic and phenotypic data for plant populations to improve molecular breeding methods.
Barbier, D. (WO2015/100236 A1: cited in specification) provides genotypic and phenotypic data for plant populations to improve molecular breeding methods.
Oppenheim et al. (US 2019/0130999 A1 filed 10/25/2018) discloses the collection of plant genotypic and phenotypic data, for use in generating latent space representations.
Aguilar-Rodrigues (2018) discloses the collection of plant genotypic and phenotypic data for the purpose of generating a genotype-phenotype representation.
Johnson (US 2010/0037342 A1) discloses the collection of plant genotype and phenotype data for the purpose of improving yield gain through improved breeding.
These elements meet the BRI of the identified data gathering limitations. As such, the prior art recognizes that this data gathering element is routine, well understood and conventional in the art MPEP 2106.05(d): “If, however, the additional element (or combination of elements) is no more than well-understood, routine, conventional activities previously known to the industry, which is recited at a high level of generality, then this consideration does not favor eligibility.”
The genotype and phenotype data of plant populations, obtained in the preamble, is described at a high level of generality, having no particular aspects or requirements. Obtaining genotype and phenotype data of plant populations, for similar uses (trait prediction) was shown to be well known in the prior art, conventional in bioinformatics and genetics technology, and routinely available from a variety of sources. The data gathering limitation does not provide an unconventional step as was found in DDR Holdings, LLC. V. Hotels.com, L.P. or CellzDirect.
Carrying over the analysis from step 2A-prong 2:
Data gathering steps are not an abstract idea, they are extra-solution activity, as they collect the data necessary to carry out the JE. MPEP 2106.05(g).
The data gathering does not impose any meaningful limitation on the JE, or how the JE is performed. MPEP 2106.05(g).
The additional limitation (data gathering) must have more than a nominal or insignificant relationship to the identified judicial exception to provide an inventive concept. (MPEP 2106.05(g) citing Mayo, PerkinElmer, Inc. v. Interna Ltd, Intellectual Ventures LLC v. Erie Indem. Co., Electric Power Group LLC v. Alstom S.A.)
The data gathering steps constitute a general link to a technological environment: the trait prediction methods are intended to be applied to plant populations. (MPEP 2106.05(h), citing Mayo, Bilski, electric Power Group, Genetic Techs Ltd v Merial LLC.)
Therefore, simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception are insufficient to provide significantly more (as discussed in Alice Corp.,).
With respect to claims 51, 52: the limitations identified above as non-abstract elements (EIA) related to general-purpose computer systems do not rise to the level of significantly more than the judicial exception.
Each of Cooper, Barbier, Oppenheim, Aguilar-Rodriguez and Johnson cited above disclose computer systems or computing elements which meet the BRI of the claimed computer system or computer system elements, comprising input, output/ display, a processor, and memory.
The computer system elements and the non-transitory computer readable storage media are recited at a high level of generality, having no particular aspects or requirements. The use of general-purpose computer systems, and non-transitory computer readable media was shown to be routine in the technology of genetics, bioinformatics, and plant trait prediction.
Carrying over the analysis from Step 2A-prong 2:
The claims do not provide any details of how specific structures of the computer elements are used to implement the JE. MPEP 2106.05(a), contrasting decisions identifying how the computer implements an abstract idea, such as in McRo to decisions which found no specific interaction with the computer, such as in Affinity Labs of Tex v. DirecTV, LLC.
The computer elements of the claims do not provide improvements to the functioning of the computer itself. MPEP 2106.05(a) I, contrasting decisions indicating an improvement to the computer, such as DDR Holdings, LLC v. Hotels.com LP, with decisions that did not identify an improvement to the computer, such as FairWarning IP, LLC v. Iatrix Sys.
The computer elements of the claims do not provide improvements to any other technology or technical field. MPEP 2106.05(a) II: contrasting decisions indicating an improvement to the technology, such as Diamond v. Diehr, Trading Techs. Int’l v. CQG Inc, or Intellectual Ventures I v. Symantec Corp, with decisions that did not identify an improvement to the technology, such as Alice Corp, Versata Dev. Group, Inc. v. SAP AM. Inc, or TLI Communications.
The computer elements of the claims do not utilize a particular machine. MPEP 2106.05(b): contrasting decisions wherein a particular machine was identified, such as MacKay Radio & Tel. Co. v. Radio Corp. of America, Eibel Process Co. v. Minn. & Ont. Paper Co., with decisions where a general-purpose computer does not qualify as a particular machine, such as Ultramercial, Inc. v. Hulu, LLC, TLI communications, or Eon Corp. IP holdings LLC v. AT&T Mobility LLC.
Hence, these are mere instructions to apply the JE using a computer, and therefore the claim does not provide significantly more.
Dependent claim(s) 36-45, 47-50 each recite a limitation requiring additional mathematic concepts or mental processes. Additional abstract limitations cannot provide significantly more than the JE as they are a part of that JE (MPEP 2106.05).
In combination, the data gathering steps providing the information required to be acted upon by the JE, performed in a generic computer or generic computing environment fail to rise to the level of significantly more than that JE. The data gathering steps provide the data for the JE, which is carried out by the general-purpose computers. No non-routine step or element has clearly been identified.
The claims have all been examined to identify the presence of one or more judicial exceptions. Each additional limitation in the claims has been addressed, alone and in combination, to determine whether the additional limitations integrate the judicial exception into a practical application. Each additional limitation in the claims has been addressed, alone and in combination, to determine whether those additional limitations provide an inventive concept which provides significantly more than those exceptions. For these reasons, the claims, when the limitations are considered individually and as a whole, are rejected under 35 USC § 101 as being directed to non-statutory subject matter.
Applicant’s arguments:
The Examiner notes she erroneously characterized claim 30 as reciting computer system-related components. While the claim may imply the use of a computer, or computer system, claim 30 does not specifically recite any computer system specific elements, nor is it specifically computer-implemented.
Applicant’s arguments have been carefully considered but are not completely persuasive.
Applicant argues the categorization or identification of abstract ideas, and/or a natural law in the claims. The Examiner has specifically identified each limitation in the claim, and what category of judicial exception is encompassed. The abstract ideas identified in the independent claims are the same as those identified as mathematic correlations, mathematic calculations, and mathematical relationships or as mental processes, concepts performed in the human mind including observations, evaluations, judgements and opinions, in MPEP 2106.04.
The improvement provided by the claims, an improvement in the representation of genotype/phenotype data, “to impute or predict a genotype and/or a phenotype,” is provided by the steps identified as the abstract idea/ judicial exception. According to the guidance set forth in MPEP 2106, this is an improvement to the judicial exception itself, and is not reflected back into a specific technological environment or practically applied process.
MPEP 2106.05(a): “… it is important to keep in mind that an improvement in the abstract idea itself (e.g. a recited fundamental economic concept) is not an improvement in technology. For example, in Trading Technologies Int’l v. IBG, 921 F.3d 1084, 1093-94, 2019 USPQ2d 138290 (Fed. Cir. 2019), the court determined that the claimed user interface simply provided a trader with more information to facilitate market trades, which improved the business process of market trading but did not improve computers or technology.”
An improvement in the judicial exception itself is not an improvement in the technology. For example, in In re Board of Trustees of Leland Stanford Junior University, 989 F.3d 1367, 1370, 1373 (Fed. Cir. 2021) (Stanford I), Applicant argued that the claimed process was an improvement over prior processes because it ‘‘yields a greater number of haplotype phase predictions,’’ but the Court found it was not ‘‘an improved technological process’’ and instead was an improved ‘‘mathematical process.’’ The court explained that such claims were directed to an abstract idea because they describe ‘‘mathematically calculating alleles’ haplotype phase,’’ like the ‘‘mathematical algorithms for performing calculations’’ in prior cases. Notably, the Federal Circuit found that the claims did not reflect an improvement to a technological process, which would render the claims eligible (FR89 no.137, p58137, 7/17/2024).
Here, Applicant has provided an improved mathematical process for analyzing genotype and phenotype data in plants, using mathematic transformation of data into vectors, applying the vectors to a machine learning autoencoder/ decoder framework, and imputing the genotype or phenotype of the test data. The step of “selection” of a plant does not apply that result to any particular action, or practically applied process.
The improvement in the prediction of a genotype or phenotype in a plant population test dataset (carried out by the judicial exception) does not provide an improvement in the technology of receiving exogenous data. The collection of exogenous data is carried out, unchanged, whether or not the judicial exception is applied. (Cleveland Clinic Foundation: using well-known or standard laboratory techniques is not sufficient to show an improvement (MPEP2106.05(a))
The improvement in the prediction of genotypes or phenotypes in plant population test data (achieved by the judicial exception) does not require a non-conventional interaction with a specific element of a computer as was required in Enfish. The disputed claims in Enfish were patent-eligible because they were "directed to a specific improvement to the way computers operate, embodied in [a] self-referential table." Enfish, 822 F.3d at 1336. The court found that the "plain focus of the claims" there was on an improvement to computer functionality itself-a self-referential table for a computer database, designed to improve the way a computer carries out its basic functions of storing and retrieving data- not on a task for which a computer is used in its ordinary capacity. Id. at 1335-36. The court noted that the specification identified additional benefits conferred by the self-referential table (e.g., increased flexibility, faster search times, and smaller memory requirements), which further supported the court's conclusion that the claims were directed to an improvement of an existing technology. Id. at 1337 (citation omitted).
The improvement in the prediction of genotypes or phenotypes in plant population test data (carried out by the judicial exception) does not improve the functionality of the computer itself as in Finjan, Visual Memory, or SRI Int’l. In Finjan, claims to virus scanning were found to be an improvement in computer technology. In Visual Memory, claims to an enhanced computer memory system were found to be directed to an improvement in computer capabilities. In SRI Int'l, claims to detecting suspicious activity by using network monitors and analyzing network packets were found to be an improvement in computer network technology.
The improvement in the prediction of genotypes or phenotypes in plant population test data does not provide an improvement in computer animation and use rules to automate a subjective task of humans to create a sequence of synchronized, animated characters as in McRo. In McRO, it was not the mere presence of unconventional rules that led to patent eligibility. In McRO, "[t]he claimed improvement was to how the physical display operated (to produce better quality images)." SAP Am. v. InvestPic, LLC, 898 F.3d 1161, 1167 (Fed. Cir. 2018). The claims in McRO recited a step of applying the data sets generated using the specific claimed rules to a sequence of animated characters to produce lip synchronization and facial expression control of those animated characters. McRO, 837 F.3d at 1308. Thus, the claims were directed to an improvement in computer animation and used rules to automate a subjective task of humans to create a sequence of synchronized, animated characters. Id. at 1314--15.
In the claims at issue here, there is no such application of specifically claimed rules to produce an improved technological result. The process of prediction of genotypes or phenotypes in plant population test data is not a technological process; it is information evaluation.
With respect to the arguments that the claims provide an improvement to the computer or to a technology, these arguments are not persuasive. “It is important to note that in order for a method claim to improve computer functionality, the broadest reasonable interpretation of the claim must be limited to computer implementation.” (MPEP 2106.05(a)).
Additionally, “To show that the involvement of a computer assists in improving the technology, the claims must recite the details regarding how a computer aids the method, the extent to which the computer aids the method, or the significance of a computer to the performance of the method. Merely adding generic computer components to perform the method is not sufficient. Thus, the claim must include more than mere instructions to perform the method on a generic component or machinery to qualify as an improvement to an existing technology.”
With respect to arguments directed to the presence of “a machine learning-based autoencoder framework”:
Ex parte Desjardins had claims drawn to the use of a machine learning model, trained on one task with a first set of data, and set parameter weights, then trained again using differing data on a different task, adjusting parameters and weights, while protecting performance of the first task. Further, in Desjardins, the retraining of the particular ML changed the structure of that ML in a way that provided "'[a]n improvement in the functioning of a computer, or an improvement to other technology or technical field,' as discussed in MPEP §§ 2106.04(d)(l) and 2106.05(a)."
The independent claim in Ex parte Desjardins contained specific limitations as to how at least some aspects of the asserted improvements are achieved:
"When evaluating the claim as a whole, we discern at least the following limitation of independent claim 1 that reflects the improvement: "adjust the first values of the plurality of parameters to optimize performance of the machine learning model on the second machine learning task while protecting performance of the machine learning model on the first machine learning task." We are persuaded that constitutes an improvement to how the machine learning model itself operates, and not, for example, the identified mathematical calculation." Ex parte Desjardins, p9
In contrast, the claims do not clearly set forth the link between the data gathered, any initial training of the ML, the structure of the ML, and how training or retraining affects the structure of how the ML itself operates to obtain the desired results or asserted improvement.
Further, with respect to the arguments regarding the alleged improvement, it is unclear that the independent claims recite all the necessary and sufficient steps required to achieve that improvement. MPEP 2106.05(a): “An important consideration in determining whether a claim improves technology is the extent to which the claim covers a particular solution to a problem or a particular way to achieve a desired outcome, as opposed to merely claiming the idea of a solution or outcome. McRO, 837 F.3d at 1314-15, 120 USPQ2d at 1102- 03; DDR Holdings, 773F.3d at 1259, 113 USPQ2d at 1107.”
The MPEP sets forth that “if the examiner concludes the disclosed invention does not improve technology, the burden shifts to applicant to provide persuasive arguments supported by any necessary evidence to demonstrate that one of ordinary skill in the art would understand that the disclosed invention improves technology. Any such evidence submitted under 37 CFR 1.132 must establish what the specification would convey to one of ordinary skill in the art and cannot be used to supplement the specification. See, e.g. MPEP § 716.09 on 37 CFR 1.132 practice with respect to rejections under 35 U.S.C. 112(a). For example, in response to a rejection under 35 U.S.C. 101, an applicant could submit a declaration under § 1.132 providing testimony on how one of ordinary skill in the art would interpret the disclosed invention as improving technology and the underlying factual basis for that conclusion.” Applicant’s arguments cannot take the place of evidence.
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 30-52 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-25 of U.S. Patent No. 11,174,522 B2. Although the claims at issue are not identical, they are not patentably distinct from each other because they recite nearly the same encoder and decoder structures for imputing a genotypic or phenotypic aspect of a plant or plant population. The patent states it uses “an encoder” while the application utilizes “autoencoders”. The application generates more than one latent space representation, however this is embraced by the claims of the patent. The patent and application both claim computer systems and computer program products.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. 17/905,861, to the same assignee, may be the subject of a future non-statutory double patenting rejection, depending on the direction of prosecution. The ‘861 provides the same method, with the exception of an additional “trained ML model” used for predicting the phenotype of interest.
Oppenheim (US 2019/0130999 A1) utilizes latent space representations of plant genetic data to predict phenotypic data, including yield [0062-0063]. Oppenheim particular utilizes kmers of genetic data, kmer frequency data, and kmer distribution data not specifically required for the rejected claims.
Rolfe (US 2019/0244680 A1) uses genetic data, including genotype and gene expression data, applied to autoencoder frameworks, to predict phenotypic data. Plant genetics is not specifically discussed beyond a token mention at [0179].
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARY K ZEMAN whose telephone number is 5712720723. The examiner can normally be reached on 8am-2pm M-F. Email may be sent to mary.zeman@uspto.gov if the appropriate permissions have been filed.
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/MARY K ZEMAN/ Primary Examiner, Art Unit 1686
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