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 1-17,23,34-35 are pending. Claims 1-17,23,34-35 are rejected herein. Claims 18-22,24-33 are cancelled, either through this action or a previous action.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 05 February 2026 has been entered.
Priority
This application claims priority to applications PCT/US22/20590 and provisional application #63/161,660 and has an effective filing date equivalent to 16 March 2021.
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 1-17,23 and 34-35 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claims 1,12,23 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
The claim recites a method, a system, and a computer product for clinical decision support, which are within a statutory category (or are interpreted to be within a statutory category for subject matter eligibility analysis purposes).
Step 2A1
The limitations of (claim 1 being representative) reading genomic information of a patient from a datastore […]; determining one or more variant of the genomic information, the one or more variant being associated with a disease state; identifying each of the one or more variant as a medically actionable variant or as a gene of uncertain significance, generating a list of one or more phenotypic features related to other one or more variant of the genomic information; reading an evaluation of the patient for a presence of the one or more phenotypic features on the list; and providing a diagnosis and patient management information associated with the one or more phenotypic features and the disease state to a healthcare provider as drafted, is a process that, under the broadest reasonable interpretation, covers certain methods of organizing human activity (i.e., managing personal behavior including following rules or instructions) but for recitation of generic computer components. That is, other than reciting a system comprising a datastore, a computing node, a non-transitory computer readable storage medium and a computer program product and a processor the claimed invention amounts to managing personal behavior or interaction between people. For example, but for these generic computer parts, this claim encompasses a person reading genomic information of a patient from a datastore, determining one or more variant of the genomic information, the variant being associated with a disease state, identifying each of the one or more variant as a medically actionable variant or as a gene of uncertain significance, generating a list of one or more phenotypic features related to the one or more variant of the genomic information; reading an evaluation of the patient for a presence of the one or more phenotypic features on the list; and providing a diagnosis and patient management information associated with the one or more phenotypic features and the disease state to the healthcare provider in the manner described in the identified abstract idea, supra. The Examiner notes that certain “method[s] of organizing human activity” includes a person’s interaction with a computer (see MPEP 2106.04(a)(2)(II)). If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior or interactions between people but for the recitation of generic computer components, then it falls within the “certain methods of organizing human activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A2
This judicial exception is not integrated into a practical application. In particular, the claim recites the additional element of a system comprising a datastore, a computing node, a non-transitory computer readable storage medium and a computer program product and a processor that implements the identified abstract idea. The system comprising a datastore, a computing node, a non-transitory computer readable storage medium and a computer program product and a processor are not described by the applicant and is recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Step 2B
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a system comprising a datastore, a computing node, a non-transitory computer readable storage medium and a computer program product and a processor to perform the noted steps amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept (“significantly more”).
Claims 2-11,13-17 and 34-35 are similarly rejected because they either further define/narrow the abstract idea and/or do not further limit the claim to a practical application or provide as inventive concept such that the claims are subject matter eligible even when considered individually or as an ordered combination. Claim(s) 2 merely describe(s) that reading the genomic information of the patient comprises accessing a certain type of record. Claim 3 merely describes reading the genomic information of the patient comprises accessing a certain provider. Claim 4 merely describes determining the one or more variant comprises accessing a datastore containing associations between variants and disease states. Claim 5 merely describes generating the list of the one or more phenotypic features comprises accessing a datastore containing associations between variants and phenotypes. Claim 6 merely describes generating the list of the one or more phenotypic features comprises accessing a datastore containing certain associations. Claim 7 merely describes generating the list of the one or more phenotypic features. Claim 8 merely describes providing a diagnosis and patient management information comprising displaying the one or more phenotypic features. Claim 9 merely describes receiving the healthcare provider an evaluation of the one or more phenotypic features in the patient. Claim 10 merely describes training the learning system. Claim 11 merely describes storing phenotypic features. Claim 13 merely describes wherein reading the genomic information of the patient comprises accessing a certain record. Claim 14 merely describes wherein reading the genomic information of the patient comprises accessing a certain provider. Claim 15 merely generating the list of the one or more variant comprises comparing the genomic information of the patient to a certain sequence. Claim 16 merely describes generating the list of the one or more variant comprises accessing a certain datastore containing association between variants and disease states. Claim 17 merely describes generating the list of the one or more phenotypic features comprises accessing a datastore containing associations between variants and phenotypes. Claim 34 merely describes prompting the healthcare provider to request a report about the one or more variant. Claim 35 merely describes the evaluation does not include any evidence for the one or more phenotypic features present in the patient, and further comprising storing the evaluation.
Claim(s) 7 also includes the additional element of “trained learning systems.” This merely represents saying “apply it” or equivalent to the abstract idea. MPEP 2106.04(d)(I) and MPEP2106.05(I)(A) indicate that merely saying “apply it” or equivalent to the abstract idea cannot provide a practical application or significantly more.
The dependent claims also includes the additional element of an “electronic health record interface” or “electronic health record” and a “short messaging service text message.” These additional elements generally link the judicial exception to a particular technological environment. Additional elements that generally link the judicial exception to a particular technological environment or field of use cannot serve to integrate the exception into a practical application or provide significantly more. See MPEP 2106.04(d)(l), Relevant Consideration for Evaluating Whether Additional Elements Integrate A Judicial Exception Into A Practical Application, and MPEP 2106.05(h).
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.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-17,23,34-35 is/are rejected under 35 U.S.C. 103 as being unpatentable over US-20220189581-A1 (hereafter Neville) in view of US 2015/0310163 A1 (hereafter Kingsmore).
Regarding Claim 1
Neville teaches:
A method comprising: reading genomic information of a patient from a datastore encoded in a non-transitory computer readable medium; [Neville teaches at the Abstract a method of classifying a genetic variant comprising receiving, at a first plurality of trained nodes of a hierarchical Bayesian Network, input data comprising data of a genetic variant of a patient…]
determining one or more variant of the genomic information, the one or more variant being associated with a disease state; [Neville teaches at the Abstract a method of classifying a genetic variant comprising receiving, at a first plurality of trained nodes of a hierarchical Bayesian Network, input data comprising data of a genetic variant of a patient… Neville teaches at Fig. 1A a list of genetic variants identified in the sample (e.g. in a VCF file format). Neville teaches at Fig. 1A molecular and clinical diagnosis (identification of disease-causing genetic variants and of the genetic disease responsible for the patient’s clinical signs and symptoms). This is determining one or more variant of the genomic information, the one or more variant being associated with a disease state.]
identifying each of the one or more variant as a medically actionable variant or as a gene of uncertain significance, [Neville teaches at Fig. 1A molecular and clinical diagnosis (identification of disease-causing genetic variants and of the genetic disease responsible for the patient’s clinical signs and symptoms). This teaches identifying each of the one or more variant as a medically actionable variant.]
generating a list of one or more phenotypic features related to the one or more variant of the genomic information; [Neville teaches at the Abstract a method of classifying a genetic variant comprising receiving, at a first plurality of trained nodes of a hierarchical Bayesian Network, input data comprising data of a genetic variant of a patient… Neville teaches at Fig. 1A a list of genetic variants identified in the sample (e.g. in a VCF file format). Neville teaches at Fig. 1A molecular and clinical diagnosis (identification of disease-causing genetic variants and of the genetic disease responsible for the patient’s clinical signs and symptoms). This is determining one or more variant of the genomic information, the one or more variant being associated with a disease state.]
Neville may not explicitly teach:
reading and evaluation of the patient for a presence of the one or more phenotypic features on the list;
and providing a diagnosis and patient management information associated with the one or more phenotypic features and the disease state to a healthcare provider.
Kingsmore teaches:
reading an evaluation of the patient for a presence of the one or more phenotypic features on the list; [Kingsmore teaches at Figure 2 variant detection/genotyping and using SSAGA-delimited or non-delimited variant interpretation. Kingsmore teaches at Figure 2 entering clinical findings into SSAGA. Kingsmore teaches at para. [0035] symptom and sign-assisted genome analysis (“SSAGA”) is a new clinic-pathological correlation tool that maps the clinical features of 591 well-established, recessive genetic diseases with pediatric presentations to corresponding phenotypes and genes known to cause symptoms. This teaches reading an evaluation of the patient for a presence of the one or more phenotypic features associated with the one or more variant. Kingsmore also teaches at Claim 1 (c) comparing said first phenotype associated gene data sets with a database of individualized genomic variations identified in said individual by sequencing a genome, an exome or part of a genome of said individual. Kingsmore teaches at Claim 1 (d) creating a prioritized list of phenotype-associated variations based on said comparisons and at Claim 1(e) comparing said phenotype-associated variation of said individual with a database of genetic disease to produce a prioritized list of probable diseases. Kingsmore teaches at para. [0215] the system analyzes the collected individual phenotypic information of the individual with one, two or three different databases of mapped causative genes for genetic diseases and associated phenotypes which results in three separate and distinct phenotype-associated gene data sets and teaches that these data sets are then combined to use for analysis.]
and providing a diagnosis and patient management information associated with the one or more phenotypic features and the disease state to a healthcare provider. [Kingsmore teaches at Figure 5 Iterative Human-Computer Interaction, involves physician patient encounter wherein the physician enters an initial set of observed symptoms, signs, test values: SxO1-SxOn. Kingsmore teaches at Figure 5 iterative human computer interaction a rank ordered differential diagnosis. This is interpreted to mean displaying a rank ordered differential diagnosis in the interaction. This is interpreted as providing a diagnosis and patient management information associated with the one or more phenotypic features and the disease state to a healthcare provider. Kingsmore also teaches at para. [0019] this system uses the patient’s symptoms, signs and/or laboratory values (Sx), and/or suspected mode of inheritance, obtained by a physician or there healthcare provider (such as a nurse or genetic counselor) and the patient’s genomic variations as data inputs, with dynamic prompts by the system, which concomitantly performs comprehensive, multinomial probabilistic classification, assisted by comprehensive databases of known mappings of genome sequence variations and known associated genes and known associated genetic diseases and known associated symptoms to provide an integrated, computer assisted probabilistic classification (or interpretation) of the clinical picture and the corresponding genomic variants in order to reach a Dx that is the likely cause of the patients symptoms and signs and genetic disease. Kingsmore teaches at para. [0008] that after the information is processed by the system, the system can display the results and/or possible list of diseases in the web based portal.]
Therefore, it would have been prima facie obvious to one of ordinary skill in the art of healthcare, at the time of filing, to modify the method and apparatus for classification and/or prioritization of genetic variants of Neville to the system for genome analysis and genetic disease diagnosis of Kingsmore with the motivation of addressing acutely ill neonates with genetic diseases who are often discharged or deceased before a diagnosis is made (Kingsmore at para. [0002]).
Regarding Claim 12 and 23
Due to their similarity to Claim 1, Claim 12 and 23 are similarly analyzed and rejected in a manner consistent with the rejection of Claim 1.
Regarding Claim 2
Neville/Kingsmore teach the method of claim 1. Neville/Kingsmore further teach:
wherein reading the genomic information of the patient comprises accessing an electronic health record of the patient. [Kingsmore at Figure 3 teaches accessing an electronic health record of the patient.]
Regarding Claim 3
Neville/Kingsmore teach the method of claim 1. Neville/Kingsmore further teach:
wherein reading the genomic information of the patient comprises accessing a sequencing provider. [Kingsmore teaches at Figure 2 next gen. sequencing, interpreted to be a “sequencing provider” there being no criteria other than literally providing the sequence.]
Regarding Claim 4
Neville/Kingsmore teach the method of claim 1. Neville/Kingsmore further teach:
wherein determining the one or more variant comprises comparing the genomic information of the patient to a reference sequence. [Kingsmore teaches at para. [0144] variants are compared to the reference gene and transcript annotation to determine the transcript-specific effects of a variant. Kingsmore teaches at Figure 2 entering clinical findings into SSAGA. Kingsmore teaches at para. [0035] symptom and sign-assisted genome analysis (“SSAGA”) is a new clinic-pathological correlation tool that maps the clinical features of 591 well-established, recessive genetic diseases with pediatric presentations to corresponding phenotypes and genes known to cause symptoms. This teaches wherein determining the one or more variant comprises comparing the genomic information of the patient to a reference sequence.]
Regarding Claim 5
Neville/Kingsmore teach the method of claim 1. Neville/Kingsmore further teach:
wherein generating the list of the one or more variant comprises accessing a datastore containing associations between variants and disease states. [Kingsmore teaches at Figure 2 variant detection/genotyping and using SSAGA-delimited or non-delimited variant interpretation. Kingsmore teaches at Figure 2 entering clinical findings into SSAGA. Kingsmore teaches at para. [0035] symptom and sign-assisted genome analysis (“SSAGA”) is a new clinic-pathological correlation tool that maps the clinical features of 591 well-established, recessive genetic diseases with pediatric presentations to corresponding phenotypes and genes known to cause symptoms. Kingsmore teaches at Table S1 a table containing associations between variants and disease, which is interpreted to be the phenotype or disease states.]
Regarding Claim 6
Neville/Kingsmore teach the method of claim 1. Neville/Kingsmore further teach:
wherein generating the list of the one or more phenotypic features comprises accessing a datastore containing associations between variants and phenotypes. [Kingsmore teaches at Figure 2 variant detection/genotyping and using SSAGA-delimited or non-delimited variant interpretation. Kingsmore teaches at Figure 2 entering clinical findings into SSAGA. Kingsmore teaches at para. [0035] symptom and sign-assisted genome analysis (“SSAGA”) is a new clinic-pathological correlation tool that maps the clinical features of 591 well-established, recessive genetic diseases with pediatric presentations to corresponding phenotypes and genes known to cause symptoms. Kingsmore teaches at Table S1 a table containing associations between variants and disease, which is interpreted here to be the phenotype.]
Regarding Claim 7
Neville/Kingsmore teach the method of claim 1. Neville/Kingsmore further teach:
wherein generating the list of the one or more phenotypic features comprises providing the one or more variant to a trained learning systems, and obtaining therefrom the one or more phenotypic features. [Kingsmore teaches at para. [0182] furthermore, a feature of the disclosed system of the present invention is continuous self-learning, meaning that the data from each patient for whom the system is used is anonymously applied to further “train” or update the clinical feature to disease to gene to variant classifiers or mappings. Kingsmore teaches at Figure 2 entering clinical findings into SSAGA. Kingsmore teaches at Figure 2 variant detection/genotyping and using SSAGA-delimited or non-delimited variant interpretation Kingsmore teaches at para. [0035] symptom and sign-assisted genome analysis (“SSAGA”) is a new clinic-pathological correlation tool that maps the clinical features of 591 well-established, recessive genetic diseases with pediatric presentations to corresponding phenotypes and genes known to cause symptoms.]
Regarding Claim 8
Neville/Kingsmore teach the method of claim 1. Neville/Kingsmore further teach:
wherein providing a diagnosis and patient management information comprises displaying the one or more phenotypic features in an electronic health record interface. [Kingsmore teaches this system uses the patient’s symptoms, signs, and/or laboratory values (Sx), an/or suspected mode of inheritance, obtained by a physician or other healthcare provider (such as a nurse or genetic counselor) and the patient’s genomic variations and known associated genetic diseases and known associated symptoms to provide an integrated, computer-assisted probabilistic classification (or interpretation) of the clinical picture and the corresponding genomic variants in order to reach a Dx that is the likely cause of the patient’s symptoms and signs and genetic disease. Kingsmore teaches at Figure 2 an electronic medical record and producing a final report with primary and secondary findings. Kingsmore teaches at Figure 2 a web interface. These teach prompting the healthcare provider and displaying the one or more phenotypic features in an electronic health record interface. Kingsmore teaches at Figure 2 entering clinical findings into SSAGA.]
Regarding Claim 9
Neville/Kingsmore teach the method of claim 1. Neville/Kingsmore further teach:
further comprising: receiving from the healthcare provider an evaluation of the one or more phenotypic features in the patient. [Kingsmore teaches at Figure 5 a physician patient encounter wherein the physician enters an initial set of observed symptoms, signs and tests values. The observed symptoms and signs are interpreted to be phenotypic features in the patient. Kingsmore teaches this system uses the patient’s symptoms, signs, and/or laboratory values (Sx), an/or suspected mode of inheritance, obtained by a physician or other healthcare provider (such as a nurse or genetic counselor) and the patient’s genomic variations and known associated genetic diseases and known associated symptoms to provide an integrated, computer-assisted probabilistic classification (or interpretation) of the clinical picture and the corresponding genomic variants in order to reach a Dx that is the likely cause of the patient’s symptoms and signs and genetic disease.]
Regarding Claim 10
Neville/Kingsmore teach the method of claim 9. Neville/Kingsmore further teach:
further comprising: providing the one or more variant and the evaluation of the one or more phenotypic features to a learning system, thereby training the learning system to associate the one or more variant and the one or more phenotypic features. [Kingsmore teaches at para. [0182] furthermore, a feature of the disclosed system of the present invention is continuous self-learning, meaning that the data from each patient for whom the system is used is anonymously applied to further “train” or update the clinical feature to disease to gene to variant classifiers or mappings. Kingsmore teaches at Figure 2 entering clinical findings into SSAGA. Kingsmore teaches at para. [0035] symptom and sign-assisted genome analysis (“SSAGA”) is a new clinic-pathological correlation tool that maps the clinical features of 591 well-established, recessive genetic diseases with pediatric presentations to corresponding phenotypes and genes known to cause symptoms.]
Regarding Claim 11
Neville/Kingsmore teach the method of claim 1. Neville/Kingsmore further teaches:
further comprising: storing the phenotypic features of the patient in an electronic health record of the patient. [Kingsmore teaches at para. [0091] “The Variant Warehouse” is a relational database and accompanying lightweight web application that stores characterization results and makes them available through a simple query and display interface.]
Regarding Claim 13
Neville/Kingsmore teach the system of claim 12. Neville/Kingsmore further teach:
wherein reading the genomic information of the patient comprises accessing an electronic health record of the patient. [Kingsmore teaches at Figure 2 on the left hand side accessing the electronic medical record for an ill patient.]
Regarding Claim 14
Neville/Kingsmore teaches the system of claim 12. Neville/Kingsmore further teach:
wherein reading the genomic information of the patient comprises accessing a sequencing provider. [Kingsmore teaches at Figure 2 next gen. sequencing, interpreted to be a “sequencing provider” there being no criteria other than literally providing the sequence.]
Regarding Claim 15
Neville/Kingsmore teach the system of claim 12. Neville/Kingsmore further teach:
wherein generating the list of the one or more variants comprises comparing the genomic information of the patient to a reference sequence. [Kingsmore teaches at para. [0144] that variants are compared to the reference gene and transcript annotation to determine the transcript specific effects of a variant. This teaches determining the one or more variant comprises comparing the genomic information of the patient to a reference sequence. ]
Regarding Claim 16
Neville/Kingsmore teach the system of claim 12. Neville/Kingsmore further teach:
wherein generating the list of the one or more phenotypic features comprises accessing a datastore containing associations between variants and disease states. [Kingsmore teaches at Figure 2 variant detection/genotyping and using SSAGA-delimited or non-delimited variant interpretation. Kingsmore teaches at para. [0035] symptom and sign-assisted genome analysis (“SSAGA”) is a new clinic-pathological correlation tool that maps the clinical features of 591 well-established, recessive genetic diseases with pediatric presentations to corresponding phenotypes and genes known to cause symptoms. This teaches wherein determining the one or more phenotypic features comprises accessing a datastore containing associations between variants and disease states.]
Regarding Claim 17
Neville/Kingsmore teach the system of claim 12. Neville/Kingsmore further teach:
wherein generating the list of the one or more phenotypic features comprises accessing a datastore containing associations between variants and phenotypes. [Kingsmore teaches at Figure 2 variant detection/genotyping and using SSAGA-delimited or non-delimited variant interpretation. Kingsmore teaches at para. [0035] symptom and sign-assisted genome analysis (“SSAGA”) is a new clinic-pathological correlation tool that maps the clinical features of 591 well-established, recessive genetic diseases with pediatric presentations to corresponding phenotypes and genes known to cause symptoms. This teaches wherein determining the one or more phenotypic features comprises accessing a datastore containing associations between variants and phenotypic states.]
Regarding Claim 34
Neville/Kingsmore teach the method of claim 1. Neville/Kingsmore further teach:
further comprising: prompting the healthcare provider to request a report about the one or more variant. [Reid teaches at para. [0123] the method will further comprise receiving a request for a genetic profile of the one or more de-identified medical records, transmitting the request, wherein the request comprises an identifier for each of the one or more de-identified medical records, and receiving, the genetic profile from a remote computing device. The request for a genetic profile of the one or more de-identified medical records is prompting the healthcare provider to request a report about the one or more variant.]
Regarding Claim 35
Neville/Kingsmore teach the method of claim 34. Neville/Kingsmore further teach:
wherein the evaluation does not include any evidence for the one or more phenotypic features present in the patient, [Reid teaches at para. [0067] the medical information can comprise, for example, medical history, medical professional observations and remarks, laboratory reports, diagnoses, doctors’ orders, prescriptions, vital signs, fluid balance, respiratory function, blood parameters, electrocardiograms, x-rays, CT scans, MRI data, laboratory test results, diagnoses, prognoses, evaluations, admission and discharge notes, and patient registration information.]
and further comprising storing the evaluation. [Reid teaches at para. [0067 the one or more computing devices will be used to store, process, analyze, output and/or visualize biological data.]
Response to Arguments
Request for Interview
Currently, the Application is not in condition for Allowance and more than superficial or minor matters remain. The request for interview is granted. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
35 U.S.C. 101
Applicant argues against the Office Action’s characterization of the material as a certain method of organizing human activity. Applicant argues that actual performance of managing personal behavior is not recited in the claims.
MPEP 2106.04(a)(2) Abstract Idea Groupings indicates that the phrase “methods of organizing human activity is used to describe concepts related to:
fundamental economic principles or practices (including hedging, insurance, mitigating risk);
commercial or legal interactions (including agreements in the form of contracts, legal obligations, advertising, marketing or sales activities or behaviors, and business relations); and
managing personal behavior or relationships or interactions between people, (including social activities, teaching, and following rules or instructions).
To paraphrase, the claims themselves recite reading genomic information of a patient from a datastore […]; determining one or more variant of the genomic information, the one or more variant being associated with a disease state; identifying each of the one or more variant as a medically actionable variant or as a gene of uncertain significance, generating a list of one or more phenotypic features related to other one or more variant of the genomic information; reading an evaluation of the patient for a presence of the one or more phenotypic features on the list; and providing a diagnosis and patient management information associated with the one or more phenotypic features and the disease state to a healthcare provider. The abstract idea was determined to be managing personal behavior or relationships or interactions between people including social activities. The sub-groupings encompass both activity of a single person and activity that involves multiple people. Moreover, the MPEP indicates that certain activity between a person and a computer may fall within the "certain methods of organizing human activity" grouping. Please the rejection above. Note that the claims recite giving the disease information to the healthcare provider. Note also, the mental processes abstract idea groupings could be used to categorize the recited material (despite the impracticality of dealing with genetic information that Applicant has suggested elsewhere). The MPEP requires that the Examiner point out at least one identified Abstract idea. The Examiner has now done so twice.
Applicant argues that the claims do not actually recite the performance of a person reading any genomic information, for example, or instruct a person to read genomic information. Further, it would be impracticable for a person to reach genomic information in any practical manner. Genomic information comprises tens of thousands of protein-coding genes. For a person to read the entirety of the genomic information alone would take days or week. The amount of time for a person to read the entirety of the genomic information and then to determine one or more variant within the genomic information would be impracticable for any useful result-this process would take an undue amount of time for a person to complete.
See above. Whether the process is practical or not is beside the point. That a person could execute the abstract idea to perform genetic diagnosis and generate patient management data and give it to the healthcare provider in the manner recited in the abstract idea, which involves certain methods of organizing human activity, is pertinent. Moreover, as described above, the MPEP indicates that interaction with a person and a computer may fall within the "certain methods of organizing human activity" grouping. Besides the various mentions of generic computer parts, the Abstract idea itself could be executed by a person interacting with a healthcare provider (…providing a diagnosis and patient management information associated with the one or more phenotypic features and the disease state to a healthcare provider). The sub-groupings encompass both activity of a single person and activity that involves multiple people. Moreover, the MPEP indicates that certain activity between a person and a computer may fall within the "certain methods of organizing human activity" grouping.
Further, the claims do not actually recite the performance of instructions. The claims do not actually recite the performance of managing a person’s interaction with a computer. Applicant submits that the interpretation of the instant claims of reciting such language is overtly broad.
The Examiner disagrees. The claims recite “…reading genomic information of a patient from a datastore encoded in a non-transitory computer readable medium;…” and later “…providing a diagnosis and patient management information associated with the one or more phenotypic features and the disease state to a healthcare provider.” Regardless of the form that the information is provided in (how the interaction occurs, whether it is a screen, spoken, passed verbally by another individual or whether the reading, determining, identifying etc. is completed entirely by a computer up until providing the diagnosis and patient management information to the healthcare provider), the claim requires information from the genomic datastore encoded in the non-transitory computer readable medium to ultimately be read, to inform an analysis and diagnosis, and for that diagnosis and analysis to be literally provided to the healthcare professional. As such the healthcare professional has mandated interaction with information derived from a computer and therefore the claims do actually recite the performance of managing a person’s interaction with a computer. Please see the relevant response above for an explanation of how the claims fall within a certain method of organizing human activity.
If it were to be argued that the claims, in reciting steps for providing a diagnosis and patient management information associated with the one or more phenotype features and the disease state to a healthcare provider, relate to actually performing a certain method of organizing human activity, or related to actually performing certain method of organizing human activity, this is not sufficient to trigger an eligibility issue. The MPEP states that if a claim is based on or involves an abstract idea, but does not recite it, then the claim is not directed to an abstract idea (MPEP 2106.04(a)(1)). The 2019 PEG further stipulates that “only when a claim recites a judicial exception does the claim require further analysis in order to determine its eligibility.”
Please see the relevant response above for an explanation of how the claims fall within a certain method of organizing human activity. The claim recited a certain method of organizing human activity and so required further analysis.
Applicant argues that when considered as a whole, the claims are clearly integrated into a practical application. It is difficult to imagine that the phrase “integrated into a practical application” could have any substantiative meaning if the claim language below were not considered to be “integrated into the practical application.”
The Examiner disagrees. MPEP 2106.04(d) Integration of a Judicial Exception Into a Practical Application teaches that limitations the courts have found indicative that an additional element (or combination of elements) may have integrated the exception into a practical application include:
An improvement in the functioning of a computer, or an improvement to other technology or technical field, as discussed in MPEP §§ 2106.04(d)(1) and 2106.05(a);
Applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, as discussed in MPEP § 2106.04(d)(2);
Implementing a judicial exception with, or using a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, as discussed in MPEP § 2106.05(b);
Effecting a transformation or reduction of a particular article to a different state or thing, as discussed in MPEP § 2106.05(c); and
Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception, as discussed in MPEP § 2106.05(e).
The Examiner maintains that none of these currently apply to the as amended claims. The additional elements have a nominal or insignificant relationship to the recited subject matter and serve primarily to facilitate the implementation of the method onto a computer, such that the computer is a mere tool used to facilitate the method and to improve (as Applicant has stated elsewhere) the practicality of the implementation of the method. For example, the implementation with the computer serves to speed up the use of the abstract idea only without any, or with perhaps with negative (in terms of performance, we do not know), impact on the computer itself. As recited, the additional elements cannot serve to integrate the judicial exception into a practical application of the exception at Step 2A prong two at Step 2B of the Alice/Mayo Subject Matter Eligibility inquiry. As another example relevant to MPEP § 2106.04(d)(2), the claims fail to integrate a specific treatment or prophylaxis into the claims and suggest only “…providing a diagnosis and patient management information associated with the one or more phenotypic features and the disease state to a healthcare provider.”
Every limitation is integrated into the specific practical application, specifically the practical application of a medical decision support system employing reverse phenotyping. The claims very clearly “use the judicial exception in a manger that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception.” (2019 PEG, at 11). For example, the limitation of “providing a diagnosis and patient management information associated with the one or more phenotypic features and the disease state to a healthcare provider” is clearly providing a practical application of the claimed method.
Note that “providing a diagnosis and patient management information associated with the one or more phenotypic features and the disease state to a healthcare provider” was one limitation that was part of the Abstract idea. As recited, the additional elements cannot serve to integrate the judicial exception into a practical application of the exception at Step 2A prong two at Step 2B of the Alice/Mayo Subject Matter Eligibility inquiry. As another example relevant to MPEP § 2106.04(d)(2), the claims fail to integrate a specific treatment or prophylaxis into the claims and suggest only “…providing a diagnosis and patient management information associated with the one or more phenotypic features and the disease state to a healthcare provider.”
35 U.S.C. 103
Applicant has amended independent claims 1,12 and 23 to recite, among other things, the steps of “identifying each of the one or more variant as a medically actionable variant as a gene of uncertain significance,” “reading and evaluation of the patient for a presence of the one or more phenotypic features on the list,” and “providing a potential disease diagnosis and patient management information associated with the one or more phenotypic features and a disease state to a healthcare provider.” Applicant submits that neither Kingsmore nor Reid, alone or in combination, disclose at least these features of Applicant’s Amended Independent Claims.
“identifying each of the one or more variant as a medically actionable variant as a gene of uncertain significance,” Neville teaches at Fig. 1A molecular and clinical diagnosis (identification of disease-causing genetic variants and of the genetic disease responsible for the patient’s clinical signs and symptoms). This teaches identifying each of the one or more variant as a medically actionable variant.
“reading and evaluation of the patient for a presence of the one or more phenotypic features on the list,” Kingsmore teaches at Figure 2 variant detection/genotyping and using SSAGA-delimited or non-delimited variant interpretation. Kingsmore teaches at Figure 2 entering clinical findings into SSAGA. Kingsmore teaches at para. [0035] symptom and sign-assisted genome analysis (“SSAGA”) is a new clinic-pathological correlation tool that maps the clinical features of 591 well-established, recessive genetic diseases with pediatric presentations to corresponding phenotypes and genes known to cause symptoms. This teaches reading an evaluation of the patient for a presence of the one or more phenotypic features associated with the one or more variant. Kingsmore also teaches at Claim 1 (c) comparing said first phenotype associated gene data sets with a database of individualized genomic variations identified in said individual by sequencing a genome, an exome or part of a genome of said individual. Kingsmore teaches at Claim 1 (d) creating a prioritized list of phenotype-associated variations based on said comparisons and at Claim 1(e) comparing said phenotype-associated variation of said individual with a database of genetic disease to produce a prioritized list of probable diseases. Kingsmore teaches at para. [0215] the system analyzes the collected individual phenotypic information of the individual with one, two or three different databases of mapped causative genes for genetic diseases and associated phenotypes which results in three separate and distinct phenotype-associated gene data sets and teaches that these data sets are then combined to use for analysis.
“providing a potential disease diagnosis and patient management information associated with the one or more phenotypic features and a disease state to a healthcare provider.” [Kingsmore teaches at Figure 5 Iterative Human-Computer Interaction, involves physician patient encounter wherein the physician enters an initial set of observed symptoms, signs, test values: SxO1-SxOn. Kingsmore teaches at Figure 5 iterative human computer interaction a rank ordered differential diagnosis. This is interpreted to mean displaying a rank ordered differential diagnosis in the interaction. This is interpreted as providing a diagnosis and patient management information associated with the one or more phenotypic features and the disease state to a healthcare provider. Kingsmore also teaches at para. [0019] this system uses the patient’s symptoms, signs and/or laboratory values (Sx), and/or suspected mode of inheritance, obtained by a physician or there healthcare provider (such as a nurse or genetic counselor) and the patient’s genomic variations as data inputs, with dynamic prompts by the system, which concomitantly performs comprehensive, multinomial probabilistic classification, assisted by comprehensive databases of known mappings of genome sequence variations and known associated genes and known associated genetic diseases and known associated symptoms to provide an integrated, computer assisted probabilistic classification (or interpretation) of the clinical picture and the corresponding genomic variants in order to reach a Dx that is the likely cause of the patients symptoms and signs and genetic disease. Kingsmore teaches at para. [0008] that after the information is processed by the system, the system can display the results and/or possible list of diseases in the web based portal.]
Applicant argues that, as described in Kingsmore, the method is designed to integrate millions of variants into a health record, by the method does not include further breakdowns or classifications of variants within any downstream step. The Office Action further acknowledges that Kingsmore may not explicitly teach the previously recited step of “generating a list of medically actionable variants, genes of uncertain significance, and one or more phenotypic features related to the one or more variant of the genomic information.”
Please see the updated 35 U.S.C. 101 rejection. The amended limitation in question is “generating a list of one or more phenotypic features related to the one or more variant of the genomic information;” [Neville teaches at the Abstract a method of classifying a genetic variant comprising receiving, at a first plurality of trained nodes of a hierarchical Bayesian Network, input data comprising data of a genetic variant of a patient… Neville teaches at Fig. 1A a list of genetic variants identified in the sample (e.g. in a VCF file format). Neville teaches at Fig. 1A molecular and clinical diagnosis (identification of disease-causing genetic variants and of the genetic disease responsible for the patient’s clinical signs and symptoms). This is determining one or more variant of the genomic information, the one or more variant being associated with a disease state.]
Applicant argues that neither Kingsmore nor Reid teach or suggest the presently recited step of “identifying each of the one or more variant as a medically actionable variant or as a gene of uncertain significance.” Applicant argues that Kingsmore does not teach the limitation.
Neville teaches at Fig. 1A molecular and clinical diagnosis (identification of disease-causing genetic variants and of the genetic disease responsible for the patient’s clinical signs and symptoms). This teaches identifying each of the one or more variant as a medically actionable variant.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 2017/0286594 A1 (hereafter Reid) discusses methods and systems for generating and analyzing genetic variant-phenotype association results are disclosed.
Lin (A General Framework for Detecting Disease Associations with Rare Variants in Sequencing Studies) teaches a framework that considers the genotype variant to phenotype connection.
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 TRISTAN ISAAC EVANS whose telephone number is (571)270-5972. The examiner can normally be reached Mon-Thurs 8:00am-12:00pm & 1:00pm-7:00pm, off Fridays.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Robert Morgan can be reached on 571-272-6773. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/T.I.E./Examiner, Art Unit 3683
/CHRISTOPHER L GILLIGAN/Primary Examiner, Art Unit 3683