DETAILED ACTION
The Applicant’s filing, received 12 May 2022 has been fully considered. The following rejections and/or objections 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 .
Status of the Claims
Claims 1-20 are pending.
Claims 1-20 are rejected.
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Claims 1-20 are given the benefit of Applicant’s claim for foreign priority based on applications EPO 19383010.6, filed 15 November 2019; and EPO 20164353.3, filed 19 March 2020.
Therefore, the effective filing date of the claimed invention is 15 November 2019.
Information Disclosure Statement
The information disclosure statement (IDS) received on 12 May 2022 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement has been considered by the examiner.
Claim Objections
Applicant is advised that should claim 11 be found allowable, claim 18 will be objected to under 37 CFR 1.75 as being a substantial duplicate thereof. When two claims in an application are duplicates or else are so close in content that they both cover the same thing, despite a slight difference in wording, it is proper after allowing one claim to object to the other as being a substantial duplicate of the allowed claim. See MPEP § 608.01(m).
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 8, 16, 17, and 20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 8 recites the limitation "the symptoms" in line three. There is insufficient antecedent basis for this limitation in the claim.
Claim 16 recites the limitation "the value of a second measure of similarity" in line fifteen. There is insufficient antecedent basis for this limitation in the claim.
Claim 17 is indefinite for depending from claim 16 and for failing to remedy the indefiniteness of claim 16.
Claim 20 recites the limitation "the group of first individuals" in line six. There is insufficient antecedent basis for this limitation in the claim.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite: (a) mental processes, i.e., concepts performed in the human mind, (e.g., observation, evaluation, judgement, opinion); (b) mathematical concepts, (e.g., mathematical relationships, formulas or equations, mathematical calculations); and (c) a law of nature (e.g., naturally occurring relationships).
Subject matter eligibility evaluation in accordance with MPEP 2106.
Eligibility Step 1: Step 1 of the eligibility analysis asks: Is the claim to a process, machine, manufacture or composition of matter?
Claims 1-10 recite a method (i.e., a process); claims 11-17 recite a system (machine or manufacture); and claims 18-20 recite a system (machine or manufacture).
Therefore, these claims are encompassed by the categories of statutory subject matter, and thus, satisfy the subject matter eligibility requirements under step 1.
[Step 1: YES]
Eligibility Step 2A: First it is determined in Prong One whether a claim recites a judicial exception, and if so, then it is determined in Prong Two whether the recited judicial exception is integrated into a practical application of that exception.
Eligibility Step 2A Prong One: In determining whether a claim is directed to a judicial exception, examination is performed that analyzes whether the claim recites a judicial exception, i.e., whether a law of nature, natural phenomenon, or abstract idea is set forth or described in the claim.
Independent claim 1 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
analyzing, using one or more machine learning techniques, the gene expression profile in relation to the genetic data obtained from the at least one data source to determine one or more genes included in the gene expression profile that have at least a threshold amount of representation in at least one of the co-occurring condition genetic data, the phenotype classification genetic data, or the biological pathway genetic data (i.e., mental processes and mathematical concepts);
determining a therapeutic responders profile that includes a plurality of features, at least a portion of the plurality of features corresponding to the one or more genes (i.e., mental processes);
analyzing, using one or more additional machine learning techniques, information corresponding to a plurality of subgroups of individuals in which a neurodevelopmental condition is present to determine respective profiles corresponding to each of the subgroups, the respective subgroup profiles each indicating features of individuals included in the respective subgroups (i.e., mental processes and mathematical concepts);
determining an amount of overlap between the plurality of features included in the therapeutic responders profile and the features of individuals included in the respective subgroup profiles (i.e., mental processes);
determining a subgroup of the plurality of subgroups that has at least a threshold amount of overlap between the plurality of features included in the therapeutic responders profile and a number of features corresponding to individuals included in the subgroup profile (i.e., mental processes and mathematical concepts); and
determining a probability that the therapeutic is a candidate treatment for the neurodevelopmental condition with respect to the subgroup (i.e., mental processes and mathematical concepts).
Independent claim 11 recites a system that executes the abstract ideas recited in independent claim 1.
Independent claim 18 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
analyzing the target profile data and protein interaction data in relation to the genetic data obtained from the at least one data source to determine one or more genes included in the network of genes that have at least a threshold amount of representation in at least one of the co-occurring condition genetic data, the phenotype classification genetic data, or the biological pathway genetic data (i.e., mental processes and mathematical concepts);
determining a therapeutic responders profile that includes a plurality of features, at least a portion of the plurality of features corresponding to the one or more genes (i.e., mental processes);
analyzing, using one or more machine learning techniques, information corresponding to a plurality of subgroups of individuals in which a neurodevelopmental condition is present to determine respective subgroup profiles corresponding to each of the subgroups, the respective subgroup profiles each indicating features of individuals included in the respective subgroups (i.e., mental processes and mathematical concepts);
determining an amount of overlap between the plurality of features included in the therapeutic responders profile and the features of individuals included in the respective subgroup profiles (i.e., mental processes);
determining a subgroup of the plurality of subgroups that has at least a threshold amount of overlap between the plurality of features included in the therapeutic responders profile and a number of features corresponding to individuals included in the subgroup profile (i.e., mental processes and mathematical concepts); and
determining a probability that the therapeutic is a candidate treatment for the neurodevelopmental condition with respect to the subgroup (i.e., mental processes and mathematical concepts).
Independent claims 1, 11, and 18, and those claims dependent therefrom, further recite a law of nature by associating genomic data (e.g., at least one of co-occurring condition genetic data, phenotype classification genetic data, or biological pathway genetic data) with phenotypes (e.g., a therapeutic responders profile), i.e., a genotype-phenotype correlation (MPEP 2106.04(b)).
Dependent claims 2-10, 12-17, 19, and 20 further recite the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas, as noted below.
Dependent claim 2 further recites:
the co-occurring condition genetic data is related to a first number of genes that are over-expressed in a group of first individuals in which the neurodevelopmental condition and an additional biological condition are present and a second number of genes that are under-expressed in the group of first individuals in which the neurodevelopmental condition and the additional biological condition are present (i.e., mental processes);
the phenotype classification genetic data indicates one or more genes that correspond to at least one phenotype of a group of second individuals in which the neurodevelopmental condition is present (i.e., mental processes); and
the biological pathway genetic data indicates one or more genes that are expressed in relation to disruption of at least one biological pathway in a group of third individuals in which the neurodevelopmental condition is present (i.e., mental processes).
Dependent claim 3 further recites:
at least one first individual included in the group of first individuals is different from at least one second individual included in the group of second individuals and from at least one third individual included in the group of third individuals (i.e., mental processes); and
at least one additional second individual included in the group of second individuals is different from at least one additional third individual included in the group of third individuals (i.e., mental processes).
Dependent claim 4 further recites:
determining a first ranking of a gene included in the gene expression profile based on an amount of up-regulation of the gene in response to the therapeutic or an amount of down-regulation of the gene in response to the therapeutic (i.e., mental processes);
determining that the gene is present in at least one of the co-occurring condition genetic data, phenotype classification genetic data, or biological pathway genetic data (i.e., mental processes); and
generating an additional gene expression profile that includes the gene with the gene having a second ranking in the additional gene expression profile, the second ranking being based on the first ranking and the additional gene expression profile being included in the therapeutic responders profile (i.e., mental processes).
Dependent claim 5 further recites:
determining that an additional gene included in the gene expression profile is not present in at least one of the co-occurring condition genetic data, phenotype classification genetic data, or biological pathway genetic data (i.e., mental processes); and
determining that the additional gene is to be excluded from the additional gene expression profile (i.e., mental processes).
Dependent claim 6 further recites:
generating a further gene expression profile for the subgroup of the plurality of subgroups, the further gene expression profile indicating a third group of genes that are up-regulated in individuals included in the subgroup and a fourth group of genes that are down-regulated in individuals included in the subgroup (i.e., mental processes); and
determining a measure of similarity between the additional gene expression profile included in the therapeutic responders profile and the further gene expression profile for the subgroup, the measure of similarity corresponding to at least a portion of the amount of overlap between the plurality of features included in the therapeutic responders profile and the number of features corresponding to the individuals included in the subgroup (i.e., mental processes and mathematical concepts).
Dependent claim 7 further recites:
the therapeutic responders profile includes at least one of a biological pathway that is disrupted in individuals in which the neurodevelopmental condition is present, a co-occurring biological condition that is present in individuals in which the neurodevelopmental condition is present, a phenotype that is related to individuals in which the neurodevelopmental condition is present, levels of analytes present in individuals in which the neurodevelopmental condition is present, or a morphological condition that is present in individuals in which the neurodevelopmental condition is present (i.e., mental processes).
Dependent claim 8 further recites:
the probability that the therapeutic is a candidate treatment for the neurodevelopmental condition with respect to the subgroup corresponds to a probability that the therapeutic alleviates at least a portion of the symptoms of the subgroup with respect to the neurodevelopmental condition (i.e., mental processes and mathematical concepts).
Dependent claim 9 further recites:
determining a first number of genes of individuals included in a subgroup of the plurality of subgroups that are up-regulated (i.e., mental processes and mathematical concepts);
determining a second number of genes that are up-regulated by the therapeutic (i.e., mental processes and mathematical concepts); and
analyzing the first number of genes with respect to the second number of genes to determine a probability that the subgroup of the plurality of subgroups are adverse responders to the therapeutic (i.e., mental processes and mathematical concepts).
Dependent claim 10 further recites:
determining a first number of genes of individuals included in a subgroup of the plurality of subgroups that are down-regulated (i.e., mental processes and mathematical concepts);
determining a second number of genes that are down-regulated by the therapeutic (i.e., mental processes and mathematical concepts); and
analyzing the first number of genes with respect to the second number of genes to determine a probability that the subgroup of the plurality of subgroups are adverse responders to the therapeutic (i.e., mental processes and mathematical concepts).
Dependent claim 12 further recites:
generating a ranked list of genes based on respective amounts of up-regulation and respective amounts of down-regulation of a plurality of genes in response to the therapeutic (i.e., mental processes);
determining a first number of genes of the ranked list that have at least a threshold amount of up-regulation (i.e., mental processes and mathematical concepts); and
determining a second number of genes of the ranked list that have at least a threshold amount of down-regulation (i.e., mental processes and mathematical concepts); and
the first group of genes included in the gene expression profile includes the first number of genes and the second group of genes included in the gene expression profile includes the second number of genes (i.e., mental processes).
Dependent claim 13 further recites:
determining a first ranking of a gene included in the gene expression profile based on an amount of up-regulation of the gene in response to the therapeutic or an amount of down-regulation of the gene in response to the therapeutic (i.e., mental processes);
determining that the gene is present in at least one of the co-occurring condition genetic data, phenotype classification genetic data, or biological pathway genetic data (i.e., mental processes); and
generating an additional gene expression profile that includes the gene with the gene having a second ranking in the additional gene expression profile, wherein the second ranking is based on the first ranking, the additional gene expression profile is included in the therapeutic responders profile, and the additional gene expression profile indicates up-regulation of a third group of genes that includes at least a portion of the first group of genes and down-regulation of a fourth group of genes that includes at least a portion of the second group of genes (i.e., mental processes).
Dependent claim 14 further recites:
the information corresponding to the plurality of subgroups of individuals in which the neurodevelopmental condition is present includes genetic information of a plurality of individuals included in the plurality of subgroups (i.e., mental processes);
determining, based on the genetic information, up-regulation of a fifth group of genes in the plurality of individuals and down-regulation of a sixth group of genes in the plurality of individuals (i.e., mental processes); and
generating a subgroup gene expression profile that includes the fifth group of genes and the sixth group of genes, the subgroup gene expression profile being included in the subgroup profile (i.e., mental processes).
Dependent claim 15 further recites:
comparing individual genes selected from the third group of genes with individual genes included in the sixth group of genes (i.e., mental processes);
determining a number of first pairs of shared genes between the individual genes included in the third group of genes and the individual genes included in the sixth group of genes with each first pair of shared genes including one gene included in the third group of genes and an additional gene included in the sixth group of genes (i.e., mental processes and mathematical concepts);
determining a number of first pairs of differing genes between the individual genes included in the third group of genes and the individual genes included in the sixth group of genes with each first pair of differing genes including a gene included in the third group of genes and another gene included in the sixth group of genes (i.e., mental processes and mathematical concepts);
increasing a value of a first measure of similarity based on the number of first pairs of shared genes (i.e., mental processes and mathematical concepts); and
decreasing the value of the first measure of similarity based on the number of first pairs of differing genes (i.e., mental processes and mathematical concepts).
Dependent claim 16 further recites:
comparing individual genes selected from the fourth group of genes with individual genes included in the fifth group of genes (i.e., mental processes);
determining a number of second pairs of shared genes between the individual genes included in the fourth group of genes and the individual genes included in the fifth group of genes with each second pair of shared genes including one gene included in the fourth group of genes and an additional gene included in the fifth group of genes (i.e., mental processes and mathematical concepts);
determining a number of second pairs of differing genes between the individual genes included in the fourth group of genes and the individual genes included in the fifth group of genes with each second pair of differing genes including a gene included in the fourth group of genes and another gene included in the fifth group of genes (i.e., mental processes and mathematical concepts);
increasing the value of a second measure of similarity based on the number of second pairs of shared genes (i.e., mental processes and mathematical concepts); and
decreasing the value of the second measure of similarity based on the number of second pairs of shared genes (i.e., mental processes and mathematical concepts).
Dependent claim 17 further recites:
combining the first measure of similarity and the second measure of similarity to generate an overall measure of similarity between the additional gene expression profile and the subgroup gene expression profile, wherein the probability that the therapeutic is a candidate treatment for the neurodevelopmental condition with respect to the subgroup is based at least partly on the overall measure of similarity (i.e., mental processes and mathematical concepts).
Dependent claim 19 further recites:
the neurodevelopmental condition is autism spectrum disorder (i.e., mental processes).
Dependent claim 20 further recites:
analyzing at least one of deoxyribonucleic acid (DNA) sequencing information or ribonucleic acid (RNA) sequencing information of the group of first individuals to determine the one or more genes included in the plurality of features (i.e., mental processes); and
analyzing at least one of DNA sequencing information, RNA sequencing information, or metabolomic information of the subgroup to determine one or more biological pathways modified in response to the neurodevelopmental condition (i.e., mental processes).
The abstract ideas recited in the claims are evaluated under the broadest reasonable interpretation (BRI) of the claim limitations when read in light of and consistent with the specification. As noted in the foregoing section, the claims are determined to contain limitations that can practically be performed in the human mind with the aid of a pen and paper (e.g., determining a therapeutic responders profile that includes a plurality of features, at least a portion of the plurality of features corresponding to the one or more genes; and determining an amount of overlap between the plurality of features included in the therapeutic responders profile and the features of individuals included in the respective subgroup profiles), and therefore recite judicial exceptions from the mental process grouping of abstract ideas. Additionally, the recited limitations that are identified as judicial exceptions from the mathematical concepts grouping of abstract ideas (e.g., using one or more additional machine learning techniques; and determining a probability that the therapeutic is a candidate treatment for the neurodevelopmental condition with respect to the subgroup) are abstract ideas irrespective of whether or not the limitations are practical to perform in the human mind. Furthermore, a law of nature correlating a genotype-phenotype relationship is identified at Eligibility Step 2A Prong One.
Therefore, claims 1-20 recite an abstract idea and a law of nature.
[Step 2A Prong One: YES]
Eligibility Step 2A Prong Two: In determining whether a claim is directed to a judicial exception, further examination is performed that analyzes if the claim recites additional elements that when examined as a whole integrates the judicial exception(s) into a practical application (MPEP 2106.04(d)). A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. The claimed additional elements are analyzed to determine if the abstract idea is integrated into a practical application (MPEP 2106.04(d)(I); MPEP 2106.05(a-h)). If the claim contains no additional elements beyond the abstract idea, the claim fails to integrate the abstract idea into a practical application (MPEP 2106.04(d)(III)).
The judicial exceptions identified in Eligibility Step 2A Prong One are not integrated into a practical application because of the reasons noted below.
Dependent claims 2-8 and 19 do not recite any elements in addition to the judicial exception, and thus are part of the judicial exception.
The additional elements in independent claim 1 include:
a computing system including one or more hardware processors and memory;
obtaining genetic data from at least one data source including at least one of co-occurring condition genetic data, phenotype classification genetic data, or biological pathway genetic data; and
obtaining a gene expression profile corresponding to a therapeutic, the gene expression profile indicating a first group of genes that are up-regulated in response to the therapeutic and a second group of genes that are down-regulated in response to the therapeutic.
The additional elements in independent claim 11 include:
one or more hardware processors;
one or more non-transitory computer-readable storage media storing computer readable instructions;
obtaining genetic data from at least one data source including at least one of co-occurring condition genetic data, phenotype classification genetic data, or biological pathway genetic data; and
obtaining a gene expression profile corresponding to a therapeutic, the gene expression profile indicating a first group of genes that are up-regulated in response to the therapeutic and a second group of genes that are down-regulated in response to the therapeutic.
The additional elements in independent claim 18 include:
one or more hardware processors;
one or more non-transitory computer-readable storage media storing computer readable instructions;
obtaining genetic data from at least one data source including at least one of co-occurring condition genetic data, phenotype classification genetic data, or biological pathway genetic data; and
obtaining target profile data of a therapeutic and human protein interaction data indicating a group of genes in a network of genes that are regulated in response to the therapeutic and interactions between the group of genes with proteins in a population of humans.
The additional elements in dependent claims 9, 10, 12-17, and 20 include:
a computing system (claims 9 and10);
one or more non-transitory computer-readable storage media store additional computer readable instructions (claims 12-17 and 20); and
one or more hardware processors (claims 12-17 and 20).
The additional elements of a computing system (claims 1, 9, and 10); one or more hardware processors (claims 1, 11, 12-17, 18, and 20); memory (claim 1); and one or more non-transitory computer-readable storage media store additional computer readable instructions (claims 11, 12-17, 18, and 20); invoke a computer merely as a tool for use in the claimed process, and therefore are not an improvement to computer functionality itself, or an improvement to any other technology or technical field, and thus, does not integrate the judicial exceptions into a practical application (see MPEP 2106.04(d)(1)).
The additional element of obtaining data (claims 1, 11, and 18) is merely a pre-solution activity of gathering data for use in the claimed process – a nominal addition to the claims that does not meaningfully limit the claims, and therefore does not add more than insignificant extra-solution activity to the judicial exceptions (MPEP 2106.05(g)).
Thus, the additionally recited elements merely invoke a computer and/or computer related components as tools; and/or amount to insignificant extra-solution activity; and as such, when all limitations in claims 1-20 have been considered as a whole, the claims are deemed to not recite any additional elements that would integrate a judicial exception into a practical application, and therefore claims 1-20 are directed to an abstract idea (MPEP 2106.04(d)).
[Step 2A Prong Two: NO]
Eligibility Step 2B: Because the claims recite an abstract idea, and do not integrate that abstract idea into a practical application, the claims are probed for a specific inventive concept. The judicial exception alone cannot provide that inventive concept or practical application (MPEP 2106.05). Identifying whether the additional elements beyond the abstract idea amount to such an inventive concept requires considering the additional elements individually and in combination to determine if they amount to significantly more than the judicial exception (MPEP 2106.05A i-vi).
The claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception(s) because of the reasons noted below.
Dependent claims 2-8 and 19 do not recite any elements in addition to the judicial exception(s).
The additional elements recited in independent claims 1, 11, and 18 and dependent claims 9, 10, 12-17, and 20 are identified above, and carried over from Step 2A Prong Two along with their conclusions for analysis at Step 2B. Any additional element or combination of elements that was considered to be insignificant extra-solution activity at Step 2A Prong Two was re-evaluated at Step 2B, because if such re-evaluation finds that the element is unconventional or otherwise more than what is well-understood, routine, conventional activity in the field, this finding may indicate that the additional element is no longer considered to be insignificant; and all additional elements and combination of elements were evaluated to determine whether any additional elements or combination of elements are other than what is well-understood, routine, conventional activity in the field, or simply append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, per MPEP 2106.05(d).
The additional elements of a computing system (claims 1, 9, and 10); one or more hardware processors (claims 1, 11, 12-17, 18, and 20); memory (claim 1); and one or more non-transitory computer-readable storage media store additional computer readable instructions (claims 11, 12-17, 18, and 20); and obtaining data (claims 1, 11, and 18); are conventional computer components and/or functions (see MPEP at 2106.05(b) and 2106.05(d)(II) regarding conventionality of computer components and computer processes).
Therefore, when taken alone, all additional elements in claims 1-20 do not amount to significantly more than the above-identified judicial exception(s). Even when evaluated as a combination, the additional elements fail to transform the exception(s) into a patent-eligible application of that exception. Thus, claims 1-20 are deemed to not contribute an inventive concept, i.e., amount to significantly more than the judicial exception(s) (MPEP 2106.05(II)).
[Step 2B: NO]
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
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 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Zhao et al. (“Genotype Combinations Linked to Phenotype Subgroups in Autism Spectrum Disorders.” 2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), Siena, Italy, 09-11 July 2019, pp. 1-8.), Narain et al. (WO 2013/134315) and Athey et al. (US 2019/0172584).
Zhao et al. explores genotype combinations linked to phenotype subgroups in autism spectrum disorders (Title) and investigates a computational model that allows for systematic comparison of phenotype data with genotype (single nucleotide polymorphisms (SNPs)) data based on machine learning techniques to identify discriminant genotype markers associated with the phenotypic subgroups (Abstract).
Narain et al. is directed to compositions and methods for diagnosis and treatment of pervasive developmental disorders (Title; and Abstract), including autism spectrum disorders (page 1, para. 3), and shows that certain proteins are modulated, e.g., upregulated or downregulated, in cells derived from a subject afflicted with autism, as compared to normal, control cells, e.g., cells derived from a subject that is not afflicted with autism (page 2, para. 3).
Athey et al. is directed to an individual and cohort pharmacological phenotype prediction platform (Title) for patients who exhibit or may exhibit primary or comorbid disease, and shows that a machine learning engine may generate a statistical model based on training data from training patients to predict pharmacological phenotypes, including drug response and dosing, drug adverse events, disease and comorbid disease risk, drug-gene, drug-drug, and polypharmacy interactions, and then the model may be applied to data for new patients to predict their pharmacological phenotypes, and enable decision making in clinical and research contexts, including drug selection and dosage (Abstract).
Regarding independent claims 1, 11, and 18, Zhao et al. shows:
obtaining an autism spectrum disorder (ASD) study sample containing phenotype and genotype data (Section II., paras. 1-2; and Fig. 1);
a computational model that allows for systematic comparison of phenotype data with genotype (single nucleotide polymorphisms (SNPs)) data based on machine learning techniques to identify discriminant genotype markers associated with the phenotypic subgroups using autism spectrum disorder sample data (Abstract);
six phenotype markers were selected to cluster the sample in a hexagonal lattice format yielding five multidimensional subgroups based on extremities of the phenotype markers (Abstract);
the SNP selection model includes random subspace selection of SNPs in conjunction with feature selection algorithms to determine which set of SNPs were discriminant among these five subgroups (Abstract);
clinical evaluation and statistical description of lattice based phenotypic subgroups (Section IV. A., para. 1; and Fig. 2; and Tables III and IV);
Regarding independent claims 1, 11, and 18, Zhao et al. does not show:
obtaining a gene expression profile corresponding to a therapeutic, the gene expression profile indicating a first group of genes that are up-regulated in response to the therapeutic and a second group of genes that are down-regulated in response to the therapeutic;
the gene expression profile in relation to the genetic data obtained from the at least one data source to determine one or more genes included in the gene expression profile that have at least a threshold amount of representation in at least one of the co-occurring condition genetic data, the phenotype classification genetic data, or the biological pathway genetic data;
determining a therapeutic responders profile that includes a plurality of features, at least a portion of the plurality of features corresponding to the one or more genes;
determining an amount of overlap between the plurality of features included in the therapeutic responders profile and the features of individuals included in the respective subgroup profiles; or
determining a probability that the therapeutic is a candidate treatment for the neurodevelopmental condition with respect to the subgroup.
Narain et al. shows that the terms “marker” or “biomarker” are used interchangeably to mean a substance that is used as an indicator of a biologic state, e.g., genes, messenger RNAs, and proteins, or portions thereof (page 21, para. 4); the term “modulation” refers to upregulation (i.e., activation or stimulation), downregulation (i.e., inhibition or suppression) of a response, or the two in combination or apart (page 25, para. 6); and identifying a modulator of a disease process, e.g., pervasive development disorder, by:
obtaining a first data set representing expression levels of a plurality of genes in the disease related cells;
obtaining a second data set representing a functional activity or a cellular response of the disease related cells; generating a consensus causal relationship network among the expression levels of the plurality of genes and/or the functional activity or cellular response; and
identifying, from the consensus causal relationship network, a causal relationship unique in the disease process (e.g., pervasive developmental disorder), wherein a gene associated with the unique causal relationship is identified as a modulator of the disease process (page 11, para. 1);
determining clinical biomarkers that determine which patients will respond to a given treatment regimen (page 37, para. 2); and
administering to the subject in need thereof a therapeutically effective amount of a pharmaceutical composition comprising an agent the modulates expression or activity of one or more of the identified biomarkers (page 8, para. 8).
Athey et al. shows:
a pharmacological phenotype prediction model that may be applied to data for new patients to predict their pharmacological phenotypes, and enable decision making in clinical contexts including drug selection and dosage (Abstract);
the pharmacological phenotype prediction model, based on statistical analysis, may determine likelihoods or other semi-quantitative or quantitative measures indicating overall ratings of predicted responses to various drugs, and cause the likelihoods to be displayed on a user interface for a health care provider to review, wherein each likelihood may be presented as a probability, a percentage, a category from a set of categories, and/or in any other suitable manner (para. [0073]); and
the pharmacological phenotype prediction model may obtain indications of illnesses or disorders from which the current patient is suffering to identify an optimal drug to treat each illness, and the illnesses or disorders from which the current patient is suffering may also include autism spectrum disorders (para. [0058]).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method shown by Zhao et al. by incorporating methods for identifying causal relationships among the expression levels of a plurality of genes and the functional activity and/or a cellular response of the disease related cells, as shown by Narain et al., and discussed above. One of ordinary skill in the art would have been motivated to combine the methods of Zhao et al. with the methods of Narain et al., because Narain et al. shows methods for identifying a causal relationship unique in the disease process (e.g., autism spectrum disorders), wherein a gene associated with the unique causal relationship is identified as a modulator (i.e., an inhibitor or a stimulator of the disease process, through downregulation or upregulation, respectively, of genes) of the disease process. This modification would have had a reasonable expectation of success given that both Zhao et al. and Narain et al. disclose methods to identify discriminant genotype markers associated with phenotypes of autism spectrum disorders for the purpose of examining their potential clinical significance.
It would have been further prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method shown by Zhao et al. by incorporating methods for obtaining individual/cohort and population panomic data and pharmacometabolomic data and identifying their respective correlations with pharmacological phenotypes, as shown by Athey et al. (e.g., para. [0092]), and discussed above. One of ordinary skill in the art would have been motivated to combine the methods of Zhao et al. with the methods of Athey et al., because Athey et al. shows methods for training and using a machine learning model to classify a cohort or population of training patients having at least some of or any suitable combination of identified SNPs, genes, and genomic regions as either having or not having the particular pharmacological phenotype based on the phenomic data for each training patient in the cohort or population, and further distinguish between the data for the subset of training patients having the particular pharmacological phenotype and the subset of training patients not having the particular pharmacological phenotype. This modification would have had a reasonable expectation of success given that both Zhao et al. and Athey et al. disclose methods to identify subsets of candidate variants (i.e., SNPs) for the purpose of examining their potential clinical significance to autism spectrum disorders (e.g., Athey et al. at paras. [0058] & [0109]).
Regarding dependent claim 19, Zhao et al. further shows the neurodevelopmental condition is autism spectrum disorder (Title; and Abstract).
Regarding dependent claim 2, Zhao et al. further shows:
genotype data associated with autism spectrum disorder and specific subgroups (clusters) defined for the sample that are based on a set of phenotype measures (Section I., col. 2, bottom).
Regarding dependent claim 2, Zhao et al. does not show:
first, second, or third groups of individuals; genes that are over-expressed and/or under-expressed; and the biological pathway genetic data indicates one or more genes that are expressed in relation to disruption of at least one biological pathway in a group of third individuals in which the neurodevelopmental condition is present.
Regarding dependent claim 2, Narain et al. further shows:
identifying proteins commonly modulated, e.g., upregulated or downregulated, in samples from autism disease patients as compared to samples from normal, unafflicted individuals (page 204, para. 4); a model for identifying novel proteins/pathways driving the pathogenesis of the disorder (page 41, para. 2); and identification of one or more determinative cellular cross-talk differentials (e.g., an increase or decrease in activity of a biological pathway, or key members of the pathway, or key regulators to members of the pathway) associated with the external stimulus component (page 31, para. 4).
Regarding dependent claim 2, Athey et al. further shows:
utilizing machine learning and statistical techniques to predict drug response phenotypes for patients, and stratified cohorts of patients, based on their biological, ancestry, demographic, clinical, sociological, and environmental characteristics (page 1, para. [0002]).
Therefore, it would have been further prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method shown by Zhao et al. by incorporating the methods of Narain et al. and Athey et al., for the reasons given in the motivation statement provided above.
Regarding dependent claim 3, Zhao et al. further does not show:
wherein at least one first individual included in the group of first individuals is different from at least one second individual included in the group of second individuals and from at least one third individual included in the group of third individuals; and at least one additional second individual included in the group of second individuals is different from at least one additional third individual included in the group of third individuals.
Regarding dependent claim 3, Athey et al. further shows:
utilizing machine learning and statistical techniques to predict drug response phenotypes for patients, and stratified cohorts of patients, based on their biological, ancestry, demographic, clinical, sociological, and environmental characteristics (page 1, para. [0002]).
Therefore, it would have been further prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method shown by Zhao et al. by incorporating the methods of Athey et al., because of the reasons given in the motivation statement provided above.
Regarding dependent claims 4 and 13, Zhao et al. further shows:
a filter-based ranking technique that ranks each SNP based on its overall level of Pearson correlation to each subgroup (page with Table II, col. 2, para. 2).
Regarding dependent claims 4 and 13, Zhao et al. further does not show:
determining rankings based on an amount of up-regulation of the gene in response to the therapeutic or an amount of down-regulation of the gene in response to the therapeutic; or generating an additional gene expression profile that includes the gene with the gene having a second ranking in the additional gene expression profile, the second ranking being based on the first ranking and the additional gene expression profile being included in the therapeutic responders profile.
Regarding dependent claims 4 and 13, Narain et al. further shows identifying proteins commonly modulated, e.g., upregulated or downregulated, in samples from autism disease patients as compared to samples from normal, unafflicted individuals (page 204, para. 4); a model for identifying novel proteins/pathways driving the pathogenesis of the disorder (page 41, para. 2); and identification of one or more determinative cellular cross-talk differentials (e.g., an increase or decrease in activity of a biological pathway, or key members of the pathway, or key regulators to members of the pathway) associated with the external stimulus component (page 31, para. 4).
Therefore, it would have been further prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method shown by Zhao et al. by incorporating the methods of Narain et al., because of the reasons given in the motivation statement provided above.
Regarding dependent claim 5, Zhao et al. further does not show:
determining that an additional gene included in the gene expression profile is not present in at least one of the co-occurring condition genetic data, phenotype classification genetic data, or biological pathway genetic data; and determining that the additional gene is to be excluded from the additional gene expression profile.
Regarding dependent claim 5, Athey et al. further shows:
the panomic data may include genomic data, epigenomic data, transcriptomic data, proteomic data, chromosomic data, metabolomic data, and/or biological networks, and that SNPs, genes, and genomic regions may be identified as related to a particular pharmacological phenotype, and the patient’s cells may be assayed for the identified SNPs, genes, and genomic regions related to the particular set of pharmacological phenotypes (para. [0050]).
Therefore, it would have been further prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method shown by Zhao et al. by incorporating the methods of Athey et al., because of the reasons given in the motivation statement provided above.
Regarding dependent claim 6, Zhao et al. further shows:
genotype data associated with autism spectrum disorder and specific subgroups (clusters) defined for the sample that are based on a set of phenotype measures (Section I., col. 2, bottom);
clinical evaluation and statistical description of lattice based phenotypic subgroups (Section IV. A., para. 1; and Fig. 2; and Tables III and IV); and
a filter-based ranking technique that ranks each SNP based on its overall level of Pearson correlation to each subgroup (page with Table II, col. 2, para. 2).
Regarding dependent claim 6, Zhao et al. does not show:
generating a further gene expression profile for the subgroup of the plurality of subgroups, the further gene expression profile indicating a third group of genes that are up-regulated in individuals included in the subgroup and a fourth group of genes that are down-regulated in individuals included in the subgroup.
Regarding dependent claim 6, Athey et al. further shows:
utilizing machine learning and statistical techniques to predict drug response phenotypes for patients, and stratified cohorts of patients, based on their biological, ancestry, demographic, clinical, sociological, and environmental characteristics (page 1, para. [0002]).
Therefore, it would have been further prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method shown by Zhao et al. by incorporating the methods of Athey et al., because of the reasons given in the motivation statement provided above.
Regarding dependent claim 7, Zhao et al. does not show:
wherein the therapeutic responders profile includes at least one of a biological pathway that is disrupted in individuals in which the neurodevelopmental condition is present, a co-occurring biological condition that is present in individuals in which the neurodevelopmental condition is present, a phenotype that is related to individuals in which the neurodevelopmental condition is present, levels of analytes present in individuals in which the neurodevelopmental condition is present, or a morphological condition that is present in individuals in which the neurodevelopmental condition is present.
Regarding dependent claim 7, Narain et al. further shows:
identifying proteins commonly modulated, e.g., upregulated or downregulated, in samples from autism disease patients as compared to samples from normal, unafflicted individuals (page 204, para. 4); a model for identifying novel proteins/pathways driving the pathogenesis of the disorder (page 41, para. 2); and identification of one or more determinative cellular cross-talk differentials (e.g., an increase or decrease in activity of a biological pathway, or key members of the pathway, or key regulators to members of the pathway) associated with the external stimulus component (page 31, para. 4).
Therefore, it would have been further prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method shown by Zhao et al. by incorporating the methods of Narain et al., because of the reasons given in the motivation statement provided above.
Regarding dependent claim 8, Zhao et al. further shows:
genotype data associated with autism spectrum disorder and specific subgroups (clusters) defined for the sample that are based on a set of phenotype measures (Section I., col. 2, bottom).
Regarding dependent claim 8, Zhao et al. does not show:
the probability that the therapeutic is a candidate treatment for the neurodevelopmental condition with respect to the subgroup corresponds to a probability that the therapeutic alleviates at least a portion of the symptoms of the subgroup with respect to the neurodevelopmental condition.
Regarding dependent claim 8, Athey et al. further shows:
the pharmacological phenotype prediction model, based on statistical analysis, may determine likelihoods or other semi-quantitative or quantitative measures indicating overall ratings of predicted responses to various drugs, and cause the likelihoods to be displayed on a user interface for a health care provider to review, wherein each likelihood may be presented as a probability, a percentage, a category from a set of categories, and/or in any other suitable manner (para. [0073]); and
a treatment selection may refer to pharmacological and/or non-pharmacological treatment(s) to alleviate, neutralize, or improve a patients’ condition (para. [0041]).
Therefore, it would have been further prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method shown by Zhao et al. by incorporating the methods of Athey et al., because of the reasons given in the motivation statement provided above.
Regarding dependent claim 9 and 10, Zhao et al. does not show:
determining a first number of genes of individuals included in a subgroup of the plurality of subgroups that are up-regulated or down-regulated; determining a second number of genes that are up-regulated or down-regulated by the therapeutic; and analyzing the first number of genes with respect to the second number of genes to determine a probability that the subgroup of the plurality of subgroups are adverse responders to the therapeutic.
Regarding dependent claims 9 and 10, Narain et al. further shows:
identifying, from the consensus causal relationship network, a causal relationship unique in the disease process (e.g., pervasive developmental disorder), wherein a gene associated with the unique causal relationship is identified as a modulator (i.e., of upregulation or downregulation) of the disease process (p. 11, para. 1).
Regarding dependent claims 9 and 10, Athey et al. further shows:
utilizing machine learning and statistical techniques to predict drug response phenotypes for patients, and stratified cohorts of patients, based on their biological, ancestry, demographic, clinical, sociological, and environmental characteristics (page 1, para. [0002]);
the pharmacological phenotype prediction model, based on statistical analysis, may determine likelihoods or other semi-quantitative or quantitative measures indicating overall ratings of predicted responses to various drugs, and cause the likelihoods to be displayed on a user interface for a health care provider to review, wherein each likelihood may be presented as a probability, a percentage, a category from a set of categories, and/or in any other suitable manner (para. [0073]); and
an initial treatment response may refer to a stable condition, lack of response, improved clinical response, or adverse events resulting from pharmacological treatment (para. [0042]).
Therefore, it would have been further prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method shown by Zhao et al. by incorporating the methods of Narain et al. and Athey et al., because of the reasons given in the motivation statement provided above.
Regarding dependent claims 14, 15, and 16, Zhao et al. shows:
genotype data associated with autism spectrum disorder and specific subgroups (clusters) defined for the sample that are based on a set of phenotype measures (Section I., col. 2, bottom);
clinical evaluation and statistical description of lattice based phenotypic subgroups (Section IV. A., para. 1; and Fig. 2; and Tables III and IV); and
a filter-based ranking technique that ranks each SNP based on its overall level of Pearson correlation to each subgroup (page with Table II, col. 2, para. 2).
Regarding dependent claims 14, 15, and 16, Zhao et al. does not show:
subgroups of individuals in which the neurodevelopmental condition is present includes genetic information of a plurality of individuals included in the plurality of subgroups; determining, based on the genetic information, up-regulation of a fifth group of genes in the plurality of individuals and down-regulation of a sixth group of genes in the plurality of individuals; and generating a subgroup gene expression profile that includes the fifth group of genes and the sixth group of genes, the subgroup gene expression profile being included in the subgroup profile (claim 14);
comparing individual genes selected from the third group of genes with individual genes included in the sixth group of genes; determining a number of first pairs of shared genes between the individual genes included in the third group of genes and the individual genes included in the sixth group of genes with each first pair of shared genes including one gene included in the third group of genes and an additional gene included in the sixth group of genes; determining a number of first pairs of differing genes between the individual genes included in the third group of genes and the individual genes included in the sixth group of genes with each first pair of differing genes including a gene included in the third group of genes and another gene included in the sixth group of genes; increasing a value of a first measure of similarity based on the number of first pairs of shared genes; and decreasing the value of the first measure of similarity based on the number of first pairs of differing genes (claim 15); or
comparing individual genes selected from the fourth group of genes with individual genes included in the fifth group of genes; determining a number of second pairs of shared genes between the individual genes included in the fourth group of genes and the individual genes included in the fifth group of genes with each second pair of shared genes including one gene included in the fourth group of genes and an additional gene included in the fifth group of genes; determining a number of second pairs of differing genes between the individual genes included in the fourth group of genes and the individual genes included in the fifth group of genes with each second pair of differing genes including a gene included in the fourth group of genes and another gene included in the fifth group of genes; increasing the value of a second measure of similarity based on the number of second pairs of shared genes; and decreasing the value of the second measure of similarity based on the number of second pairs of shared genes.
Regarding dependent claims 14, 15, and 16, Narain et al. shows:
identifying, from the consensus causal relationship network, a causal relationship unique in the disease process (e.g., pervasive developmental disorder), wherein a gene associated with the unique causal relationship is identified as a modulator (i.e., of upregulation or downregulation) of the disease process (p. 11, para. 1).
Regarding dependent claims 14, 15, and 16, Athey et al. shows:
utilizing machine learning and statistical techniques to predict drug response phenotypes for patients, and stratified cohorts of patients, based on their biological, ancestry, demographic, clinical, sociological, and environmental characteristics (page 1, para. [0002]).
Therefore, it would have been further prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method shown by Zhao et al. by incorporating the methods of Narain et al. and Athey et al., because of the reasons given in the motivation statement provided above.
Regarding dependent claim 17, Zhao et al. shows:
genotype data associated with autism spectrum disorder and specific subgroups (clusters) defined for the sample that are based on a set of phenotype measures (Section I., col. 2, bottom);
clinical evaluation and statistical description of lattice based phenotypic subgroups (Section IV. A., para. 1; and Fig. 2; and Tables III and IV); and
a filter-based ranking technique that ranks each SNP based on its overall level of Pearson correlation to each subgroup (page with Table II, col. 2, para. 2).
Regarding dependent claim 17, Zhao et al. does not show:
combining the first measure of similarity and the second measure of similarity to generate an overall measure of similarity between the additional gene expression profile and the subgroup gene expression profile, wherein the probability that the therapeutic is a candidate treatment for the neurodevelopmental condition with respect to the subgroup is based at least partly on the overall measure of similarity.
Regarding dependent claim 17, Athey et al. shows:
the pharmacological phenotype prediction model, based on statistical analysis, may determine likelihoods or other semi-quantitative or quantitative measures indicating overall ratings of predicted responses to various drugs, and cause the likelihoods to be displayed on a user interface for a health care provider to review, wherein each likelihood may be presented as a probability, a percentage, a category from a set of categories, and/or in any other suitable manner (para. [0073]).
Therefore, it would have been further prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method shown by Zhao et al. by incorporating the methods of Athey et al., because of the reasons given in the motivation statement provided above.
Regarding dependent claim 20, Zhao et al. shows:
genotype data associated with autism spectrum disorder and specific subgroups (clusters) defined for the sample that are based on a set of phenotype measures (Section I., col. 2, bottom).
Regarding dependent claim 20, Zhao et al. does not show:
analyzing at least one of DNA sequencing information, RNA sequencing information, or metabolomic information of the subgroup to determine one or more biological pathways modified in response to the neurodevelopmental condition.
Regarding dependent claim 20, Narain et al. shows:
identifying, from the consensus causal relationship network, a causal relationship unique in the disease process (e.g., pervasive developmental disorder), wherein a gene associated with the unique causal relationship is identified as a modulator (i.e., of upregulation or downregulation) of the disease process (p. 11, para. 1).
Therefore, it would have been further prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method shown by Zhao et al. by incorporating the methods of Narain et al., because of the reasons given in the motivation statement provided above.
Conclusion
No claims are allowed.
This Office action is a Non-Final action. A shortened statutory period for reply to this action is set to expire THREE MONTHS from the mailing date of this application.
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/S.W.B./Examiner, Art Unit 1687
/Joseph Woitach/Primary Examiner, Art Unit 1687