DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Status
Claims 1-21 are pending.
Claims 1-2, 4, 6 and 9-21 are examined on the merits.
Claims 3, 5, 7 and 8 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected invention, there being no allowable generic or liking claim.
Priority
This patent application is a continuation of United States Patent Application No. 18/298,371, filed April 11, 2023, which is a continuation of United States Patent Application No. 16/771,451, which claims the benefit of priority of United States Provisional patent application No. 62/902,950, filed 09/19/2019 and is a U.S. national stage patent application, filed pursuant to 35 U.S.C. § 371, of International patent application No. PCT/US2019/056713, filed on October 17, 2019, which claims the benefit of priority of United States Provisional patent application No. 62/746,997, filed October 17, 2018. Accordingly, the effective filing data of the claimed invention is 10/17/2018.
Withdrawn Rejections/Objections
Rejections and/or objections not reiterated from previous office actions are hereby
withdrawn in view of the amendments filed 06/30/2026.
The objection to specification is withdrawn in view of amendments received 06/30/2026 specifically by removing hyperlinks from the specification.
The 35 U.S.C. 102(a)(2) rejections to claims 1, 4, 6, 9-11, and 20 in the office action filed 12/08/2023 has been withdrawn in view of amendments received 06/30/2026. New rejections are applied.
The following rejections and/or objections are either maintained or newly applied. They constitute the complete set presently being applied to the instant application.
Specification
The amendments to the specification filed 06/30/2026 is accepted.
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 1-2, 4, 6 and 9-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
The Supreme Court has established a two-step framework for this analysis, wherein a claim does not satisfy § 101 if (1) it is “directed to” a patent-ineligible concept, i.e., a law of nature, natural phenomenon, or abstract idea, and (2), if so, the particular elements of the claim, considered “both individually and as an ordered combination,” do not add enough to “transform the nature of the claim into a patent-eligible application.” Elec. Power Grp., LLC v. Alstom S.A., 830 F.3d 1350, 1353 (Fed. Cir. 2016) (quoting Alice, 134 S. Ct. at 2355). Applicant is also directed to MPEP 2106.
Step 1: The instantly claimed invention (claim(s) 1-20 being representative) is directed to a system, and (claim(s) 21 being representative) is directed to a method. Therefore, the instantly claimed invention falls into one of the four statutory categories. [Step 1: YES]
Step 2A: First it is determined in Prong One whether a claim recites a judicial exception, and if so, then it is determined in in Prong Two if the recited judicial exception is integrated into a practical application of that exception.
Step 2A, Prong 1: Under the MPEP § 2106.04, the Step 2A (Prong 1) analysis requires determining whether a claim recites an abstract idea, law of nature, or natural phenomenon.
Claims 1-2, 4, 6 and 9-21 recite the following steps which fall under the mathematical concepts, mental processes, and/or certain methods of organizing human activity groupings of abstract ideas:
Claims 1, 20, and 21 recite C) mapping the first genomic sequencing data to corresponding locations in a reference human genome; D) mapping the second genomic sequencing data to corresponding locations in the reference human genome; the limitation mapping to a reference genome falls into mathematical concepts groupings of abstract ideas, since mapping is performed using a mathematical algorithm (see specification [0293] “FASTQ files were aligned against the human reference genome using BWA”).
Claims 1, 20, and 21 further recite determining an absence or presence of at least a first genomic alteration, from among a plurality of predefined genomic alterations, in the blood sample based on at least (i) the second genomic sequencing data, and (ii) the locations in the reference human genome to which the second genomic sequencing data has been mapped; the limitation determining absence or presence of alteration based on first and second data can be practically performed in human mind (mental process), for example by using a pen and paper, since human mind is capable of interpreting data based on known information.
Claims 1, 20, and 21 further recite assessment of the cancer treatment efficacy for the human subject responsive to at least the plurality of epigenetic patterns of cell free DNA within the blood sample and the absence or presence of at least the first genomic alteration in the blood sample; the limitation assessment of the cancer treatment efficacy can be practically performed in human mind (mental process), for example by using a pen and paper, since human are capable of assessing data.
Claim 9 recites verifying that each genomic alteration in the plurality of predefined genomic alterations is a somatic genomic alteration (mental process of data verification).
Claim 10 recites determining whether the respective genomic alteration is germline or somatic (mental process of determining based on the result of an analysis).
Claim 11 recites storing the structured data report in a subject data store (mental process of storing structured data, for example, a table, using a pen and paper).
Claim 12 recites retrieving health data associated with the human subject, and augmenting the structured data report with the health data (mental processes regaining and appending data).
Claims 13 and 14 recite including the cancer type in the data report (mental process of adding data to a report, for example, by using a pen and paper).
Claim 15 recites augmenting the data report comprises including the diagnosis, date of recurrence, the treatment incurred by the human subject, or an outcome of treatment in the data report (mental process of appending data).
Claim 19 recites publishing the locations in the reference human genome to which the second genomic sequencing data have been mapped to a lake database (mental process of writing a location).
Claim 19 further recites adding a first data alert or first event to a data alerts list (mental process of adding data to a list).
Claim 19 further recites determining upon the adding of the first data alert or first event to a data alerts list, wherein the E) determining obtains the locations in the reference human genome to which the second genomic sequencing data have been mapped from the lake database (mental process of determining a location based on known data).
Claims 2, 4, 6, and 16-18 provide further information about the recited judicial exceptions.
Additionally, claims 1-2, 4, 6 and 9-20 recite a correlation between cell-free DNA and presence or absence of alterations, and as such, falls into judicial exception of Laws of nature and natural phenomena. See MPEP 2106(b) I.
The identified claims recite a law of nature, a natural phenomenon (product of nature) or fall into one of the groups of abstract ideas of mathematical concepts, mental processes, and/or certain methods of organizing human activity for the reasons set forth above. See MPEP 2106.04 (a)(2) III and MPEP 2106.04 (b) I. Therefore, claims are directed to one or more judicial exception(s) and require further analysis in Prong Two. [Step 2A, Prong 1: YES]
Step 2A: Prong 2: Under MPEP 2106.04, the Step 2A, Prong 2 analysis requires identifying whether there are any additional elements recited in the claim beyond the judicial exception(s) and evaluating those additional elements to determine whether they integrate the exception into a practical application of the exception. This judicial exception is not integrated into a practical application for the following reasons.
The additional elements of claims 1-2, 4, 6 and 9-21 include the following.
Claims 1, 20, and 21 recite a computer system comprising one or more processors, and a memory, storing instructions, obtaining first and second sequencing data, and communicating through a network connection; storing the structured data report in a data store; authenticating a clinician user based on login credentials; display a patient-list interface; receiving a selection of patient cells; display a report interface.
Claim 20 further recites a non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions.
Claim 2 recites interfacing with a cloud service platform.
Claim 19 recites a first and a second microservice.
The additional elements of a system comprising one or more processors, a memory, a non-transitory computer readable storage medium, one or more program, a first and second microservice (software/program), storing structured data, authenticating a clinician user, displaying a patient-list, and displaying a report are generic computer components and/or processes. There are no limitations that indicate that the processor, input module, processing module, or output module in the computer-implemented system require anything other than generic computing systems. The courts have found the use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general-purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Furthermore, the additional element of interfacing with a cloud service platform amounts to generally linking the use of a judicial exception to a particular technological environment or field of use, which the courts have identified as limitations that do not integrate a judicial exception into a practical application. See MPEP 2106.04 (d) I.
Furthermore, the additional element of obtaining first and second sequencing data, receiving data, and receiving cells amount to nothing more than gathering the data necessary to perform the abstract idea, and as such, considered insignificant extra-solution activity. The courts have identified limitations that merely gather data as insignificant extra-solution activities that do not integrate the judicial exception into a practical application. See MPEP 2106.05(g).
Therefore, the additionally recited elements amount to generic computer components and/or insignificant extra-solution activity and, as such, the claims as a whole do no integrate the abstract idea into practical application. See MPEP 2106.05(g). Thus, claims 1-2, 4, 6 and 9-20 are directed to an abstract idea. [Step 2A, Prong 2: NO]
Step 2B: In the second step it is determined whether the claimed subject matter includes additional elements that amount to significantly more than the judicial exception. An inventive concept cannot be furnished by an abstract idea itself. See MPEP § 2106.05.
The claims do not include any additional steps appended to the judicial exception that are sufficient to amount to significantly more than the judicial exception.
The additional elements of claims 1-2, 4, 6 and 9-2 include the following.
Claims 1, 20, and 21 recite a computer system comprising one or more processors, and a memory, storing instructions, obtaining first and second sequencing data, and communicating through a network connection; storing the structured data report in a data store; authenticating a clinician user based on login credentials; display a patient-list interface; receiving a selection of patient cells; display a report interface.
Claim 20 further recites a non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions.
Claim 2 recites interfacing with a cloud service platform.
Claim 19 recites a first and second microservice.
The additional elements of a system comprising one or more processors, a memory, a non-transitory computer readable storage medium, one or more program, a first and second microservice (software/program), storing structured data, authenticating a clinician user, displaying a patient-list, and displaying a report are conventional computer components and/or processes. The courts have found the use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general-purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TU Communications LLC v. AV Auto, LLC, 823 F.3d 607,613,118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit).
Furthermore, the additional element of interfacing with a cloud service platform amounts to generally linking the use of a judicial exception to a particular technological environment or field of use, which the courts have identified as limitations that do not amount to significantly more. See MPEP 2106.05 I. A.
Furthermore, the additional element of obtaining first and second sequencing data, receiving data, and receiving cells amount to nothing more than gathering the data necessary to perform the abstract idea, and as such, considered insignificant extra-solution activity. The courts have identified limitations that merely gather data as insignificant extra-solution activities that do not amount to significantly more. See MPEP 2106.05(g).
Therefore, these additional elements are not sufficient to amount to significantly more than the judicial exception. See MPEP 2106.05(g).
Taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception(s). Even when viewed as a combination, the additional elements fail to transform the exception into a patent-eligible application of that exception. Thus, the claims as a whole do not amount to significantly more than the exception itself. [Step 2B: NO]
Therefore, the instantly rejected claims are not drawn to eligible subject matter as they are directed to an abstract idea without significantly more.
Response to Arguments
Applicant's arguments filed 06/30/2026 have been considered but they are not yet persuasive.
Applicant states (pg. 13, para. 1) that:
The rejection improperly abstracts individual limitations away from the claim as a whole. USPTO guidance requires the Office to identify the specific claim limitation allegedly reciting a judicial exception and to determine whether the identified limitation falls within a recognized abstract-idea grouping. If the claim does not recite a judicial exception, or if any alleged exception is integrated into a practical application, the claim is eligible. The current USPTO guidance also cautions that the mental-process grouping should not be expanded to limitations that cannot practically be performed in the human mind and that the claim must be analyzed as a whole.
Indeed, Federal Circuit precedent cautions against oversimplifying claims and supports eligibility where claims recite specific computer-implemented data structures, rules, or user- interface operations rather than merely claiming an abstract result. Enfish held claims not abstract where they recited a specific database improvement, McRO emphasized that claims must be considered as an ordered combination without ignoring specific requirements, and Core Wireless held eligible claims directed to a particular manner of displaying and accessing limited information in a user interface.
These arguments are not yet persuasive. Applicant remarks are directed to Step 2A Prong One of 101 analysis, specifically that whether the claims recite a judicial exception.
Instant claims are directed to judicial exception of evaluating a treatment efficacy and recite multiple judicial exceptions for at least the steps of mapping data, determining an absence or presence of a genomic alterations, and assessment of the cancer treatment efficacy.
If the claim recites a judicial exception (i.e., an abstract idea enumerated in MPEP § 2106.04(a), a law of nature, or a natural phenomenon), the claim requires further analysis in Prong Two (MPEP 2106.04 II. A. 1).
Instant claims recite the additional elements of a system comprising one or more processors, a memory, a non-transitory computer readable storage medium, one or more program, a first and second microservice (software/program), storing structured data, authenticating a clinician user, displaying a patient-list, and displaying, which are generic computer components and processes that do not integrate the judicial exception into a practical application. these limitations equate to mere instructions to implement the abstract idea on a generic computer that the courts have stated does not integrate a recited judicial exception into a practical application in Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984.
Furthermore, the additional element of obtaining data, receiving data, and receiving cells are considered insignificant extra-solution activities. The courts have identified limitations that merely gather data or stores data as insignificant extra-solution activity that does not integrate the abstract idea into a practical application (see MPEP 2106.05(g)).
With regards to Applicant referring to Enfish, the disputed claims in Enfish were patent-eligible because they were "directed to a specific improvement to the way computers operate, embodied in [a] self-referential table." Enfish, 822 F.3d at 1336. The court found that the "plain focus of the claims" there was an improvement to computer functionality itself-a self-referential table for a computer database, designed to improve the way a computer carries out its basic functions of storing and retrieving data- not on a task for which a computer is used in its ordinary capacity. Id. at 1335-36.
Here, in contrast, Applicant does not purport to have invented a data structure analogous to Enfish's self-referential table. And Applicant fails to explain sufficiently and persuasively how instantly claimed invention is directed to an improvement in the way computers operate analogous to the case in Enfish. Instant claims merely use generic computer components (e.g., a processor and storage device) that operate in their normal, expected manner.
With regards to Applicant referring to McRo, in McRO, "[t]he claimed improvement was to how the physical display operated (to produce better quality images)." SAP Am. v. InvestPic, LLC, 898 F.3d 1161, 1167 (Fed. Cir. 2018). The claims in McRO recited a step of applying the data sets generated using the specific claimed rules to a sequence of animated characters to produce lip synchronization and facial expression control of those animated characters. McRO, 837 F.3d at 1308. Thus, the claims were directed to an improvement in computer animation and used rules to automate a subjective task of humans to create a sequence of synchronized, animated characters. Id. at 1314-15.
In the claims at issue here, there is no such application of specifically claimed rules to produce an improved technological result.
With regards to Applicant referring to Core Wireless, in Core Wireless Licensing v. LG Electronics, Inc., the court noted several benefits, such as an improvement in the speed of a user's navigation through views and windows, a reduction in the number of steps to reach desired data or functionality, and the ability of a user to identify data or functionality of an application without actually opening the application. The court held that the claims were directed to an improvement in the functioning of computers, particularly those with small screens, and were not directed to an abstract idea.
In contrast to Core Wireless, Applicant fails to explain sufficiently and persuasively how instantly claimed invention is directed to an improvement in the way computers operate analogous to the case in Core Wireless. Instant claims merely use generic computer components (e.g., a processor and storage device) that operate in their normal, expected manner.
Taken as a whole, the claims are interpreted as being directed to an abstract idea of evaluating treatment efficacy, which merely uses a general-purpose computer as a tool to perform the process. As such, the rejection of claims under U.S.C. 101 is maintained.
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.
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.
Claims 1-2, 4, 6, 9-19 and 20-21 are rejected under 35 U.S.C. 103 as being unpatentable over Eltoukhy et al. (US 11756655) in view of Andry et al. (PAPAyA: A Highly Scalable Cloud-based Framework for Genomic Processing, In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2016) - Volume 3: BIOINFORMATICS, pages 198-206).
Regarding claims 1, 20, and 21, Eltoukhy discloses systems and methods for generating a therapeutic response predict or detecting a disease, by: using a genetic analyzer to generate genetic information; receiving into computer memory a dataset comprising, for each of a plurality of individuals having a disease, (1) genetic information from the individual generated at first time point and (2) treatment response of the individual to one or more therapeutic interventions determined at a second, later, time point; and implementing a machine learning algorithm using the dataset to generate at least one computer implemented classification algorithm, wherein the classification algorithm, based on genetic information from a subject, predicts therapeutic response of the subject to a therapeutic intervention (abstract).
Eltoukhy further discloses that the data is sent by the DNA sequencers over a direct connection or over the internet to a computer for processing and that the data processing aspects of the system can be implemented in digital electronic circuitry, or in computer hardware, firmware, software, or in combinations of them. Eltoukhy further discloses that the data processing apparatus of the invention can be implemented in a computer program product tangibly embodied in a machine-readable storage device for execution by a programmable processor. Eltoukhy further discloses one or more computer programs that are executable on a programmable system including at least one programmable processor coupled to receive data and instructions from and to transmit data and instructions to a data storage system (col. 28, L.1-35); reading on limitations of a computer system for evaluating a cancer treatment efficacy for a human subject that is undergoing, or has completed, a cancer treatment for a cancer, the computer system comprising one or more processors, and a memory, wherein the memory stores instructions for performing a method using the one or more processors (in claim 1), and non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions that, when executed by an electronic device with one or more processors and a memory, cause the electronic device to perform a method for evaluating a cancer treatment efficacy for a human subject that is undergoing, or has completed, a cancer treatment for a cancer (in claim 20).
Eltoukhy further discloses an exemplary process to generate genetic reports, including a tumor response map and associated summary of alterations: The process first captures genetic information by collecting body fluid samples as sources of genetic material (e.g., blood) (for example, second genomic sequencing data) and then the process sequences the materials (polynucleotides in a sample can be sequenced, producing a plurality of sequence reads) and then the tumor burden is estimated (implicit: Tumor burden is estimated after mapping raw sequencing data to the human reference genome) (col. 11, L. 45-67). Eltoukhy further discloses that the genetic information comprises sequence or abundance data from one or more genetic loci in cell-free DNA from the individuals (col. 12, L. 9-11). Eltoukhy further discloses processing genetic information (for example, second genomic sequencing data), identifying genetic variants including copy number variants, single nucleotide polymorphism, abnormal changes in nucleic acid chemical modifications, abnormal changes in epigenetic patterns and abnormal changes in nucleic acid methylation (for example, first genomic sequencing data) (col. 12, L. 14-25). Eltoukhy further discloses that cell free polynucleotides taken from a subject can include polynucleotides derived from normal cells (for example, second genomic sequencing data), as well as polynucleotides derived from diseased cells (for example, first genomic sequencing data), such as cancer cells. Polynucleotides from cancer cells may bear genetic variants (col. 12, L. 60-65); reading on limitations of A) obtaining, from an electronic data store, first genomic sequencing data from cell free DNA drawn from a blood sample of the human subject, wherein the first genomic sequencing data comprises a plurality of epigenetic patterns of cell free DNA within the blood sample; B) obtaining, from an electronic data store, second genomic sequencing data from cell free DNA drawn from the blood sample, wherein the second genomic sequencing data comprises sequence data of cell free DNA within the blood sample.
Eltoukhy further discloses a data storage system (for example, an electronic data store) (col. 28, L. 15-20). Eltoukhy further discloses that clinical information is stored in a database array, for example, the system can store patient information from physicians and test labs in this database and that genome sequence is also captured and histology reports for each patient (col. 8, L. 10-20).
Eltoukhy further discloses mapping sequence reads derived from the sequencing onto a reference sequence; identifying a subset of mapped sequence reads that align with a variant of the reference sequence at each mappable base position; for each mappable base position, calculating a ratio of (a) a number of mapped sequence reads that include a variant as compared to the reference sequence, to (b) a number of total sequence reads for each mappable base position (col. 3, L. 53-67); reading on limitations of C) mapping the first genomic sequencing data to corresponding locations in a reference human genome; D) mapping the second genomic sequencing data to corresponding locations in the reference human genome.
Eltoukhy further discloses determining specific gene alterations (col. 17, L. 55-60; FIG. 2A). Eltoukhy further discloses detecting abnormal cellular activities by sequencing of cell-free nucleic acid with a genetic analyzer, e.g., a DNA sequencer; and detecting the presence or absence of genetic alteration and/or amount of genetic variation in an individual based on the diagnostic confidence indication of the sequence read (col. 2, L. 14-25). Eltoukhy further discloses that the genomic fragment reads that meet a specified quality score thresholds are mapped to a reference genome, or a reference sequence that is known not to contain mutations. After mapping alignment, sequence reads are assigned a mapping score. A mapping score may be a representation or reads mapped back to the reference sequence indicating whether each position is or is not uniquely mappable (col. 22, L. 39-48-53); reading on limitations of E) determining an absence or presence of at least a first genomic alteration, from among a plurality of predefined genomic alterations, in the blood sample based on at least (i) the second genomic sequencing data, and (ii) the locations in the reference human genome to which the second genomic sequencing data has been mapped.
Eltoukhy further discloses generating a genetic report/diagnosis col. 13, L. 10) and predicting therapeutic response of the subject to a therapeutic intervention (abstract, FIG 2B). Eltoukhy further discloses determining the efficacy of a particular treatment option. In one example, successful treatment options may actually increase the amount of copy number variation or mutations detected in subject's blood if the treatment is successful as more cancers may die and shed DNA (col. 14, L. 50-55); reading on limitations of F) securely communicating, through a network connection, a structured data report that provides an assessment of the cancer treatment efficacy for the human subject responsive to at least the plurality of epigenetic patterns of cell free DNA within the blood sample and the absence or presence of at least the first genomic alteration in the blood sample.
Eltoukhy further discloses storing reports in patient data store (FIG 2A-3B); reading on limitations of storing data report in a subject data store comprising a plurality of structured data reports.
Eltoukhy further discloses that the healthcare provider or practice includes medical services providers, such as doctors, nurses, home health aides, technicians and physician's assistants, and the practice is any medical care facility staffed with healthcare providers (col. 11, para. 1); reading on limitations of the clinician user is different from an ordering physician for the human subject.
Eltoukhy further discloses displaying patient information associated with reports selected by one or more providers (FIG 2C-2I). Eltoukhy further discloses that in order to provide for interaction with a user, the invention can be implemented using a computer system having a display device such as a monitor or LCD (liquid crystal display) screen for displaying information to the user and input devices by which the user can provide input to the computer system such as a keyboard, a two-dimensional pointing device such as a mouse or a trackball, or a three-dimensional pointing device such as a data glove or a gyroscopic mouse. The computer system can be programmed to provide a graphical user interface through which computer programs interact with users. The computer system can be programmed to provide a virtual reality, three-dimensional display interface (col. 28, para. 2); reading on limitations of causing the computing device of the clinician user to display a patient-list interface comprising a patient cell corresponding to the human subject and associated with the structured data report; receiving, from the clinician user, a selection of the patient cell: in response to the selection, causing the computing device to display a reports interface comprising a list of one or more reports associated with the human subject, wherein the one or more reports includes the structured data report.
Further regarding claims 1, 20, and 21, Eltoukhy do not disclose authenticating a clinician user at a computing device based on login credentials. This limitation is taught by Andry.
Andry discloses PAPAyA platform to ingest, store and process in silico large genomics datasets using analysis algorithms based on pre-defined knowledge databases with the goal to offer personalized therapy guidance to physicians in particular for cancers and infectious diseases.
Andry further discloses that the platform comprises user management; user registration (register a new user account, update profile information, change and reset password information), authenticate a user and validate user access token (pg. 203, col. 1, section: 4 Architecture).
Regarding claim 2, Eltoukhy discloses that reports are submitted and accessed electronically via the internet (col. 15, L. 60-61). Eltoukhy further discloses that sequencing may be performed using any nucleic acid sequencing platforms known in the art (col. 22, L. 30-31) and that the data is sent by the DNA sequencers over a direct connection or over the internet to a computer for processing. Eltoukhy further discloses that the data processing aspects of the invention can be implemented advantageously in one or more computer programs that are executable on a programmable system including at least one programmable processor coupled to receive data and instructions from and to transmit data and instructions to a data storage system (col. 28, L. 1-60).
Further regarding claim 2, Eltoukhy does not expressly disclose interfacing with a cloud service platform to perform at least one of the A) to F) steps.
Andry discloses PAPAyA platform to ingest, store and process in silico large genomics datasets using analysis algorithms based on pre-defined knowledge databases with the goal to offer personalized therapy guidance to physicians in particular for cancers and infectious diseases. Andry further discloses that the framework is deployed on a cloud-based digital health platform that provides generic provisioning and hosting services, identity and access management, workflow orchestration, device cloud capabilities, notifications, scheduling, logging, auditing, metering as well as specific patient demographic, clinical and wellness data services that can be combined with the genomics analytics result (abstract, FIG. 1, FIG. 2).
Regarding claim 4, Eltoukhy discloses that the plurality of predefined genomic alterations consists of mutations in the EGFR gene (FIG. 2D. 2E, 2F, 2G, 2H, 2I).
Regarding claim 6, Eltoukhy discloses that the first genomic alteration is a single nucleotide polymorphism in a gene (col. 9, L. 40-45). See also identification of single nucleotide polymorphisms (col. 12, L. 14-25).
Regarding claim 9, Eltoukhy discloses measure of each of a plurality of somatic mutants among the polynucleotides in each sample (col. 6, L. 27-35); reading on limitations of verifying that each genomic alteration in the plurality of predefined genomic alterations is a somatic genomic alteration.
Regarding claim 10, Eltoukhy discloses that using the systems and methods described useful in monitoring residual disease or recurrence of disease (col. 14, L. 60-63). Eltoukhy further discloses using a feature-based classifier trained on validated somatic mutation samples while benefiting from other available information such as base quality, mapping quality, strand bias and tail distance. Given paired normal/tumor bam files, the embodiment will output the 60 probability of each candidate site being somatic. Through the systems and methods described herein, the present disclosure provides a way to classify treatment responses to therapeutic interventions, and subsequently determine whether a given individual falls into a particular classification (e.g., responsive to treatment, nonresponsive to treatment, or a particular level of responsiveness such as fully responsive or partially responsive) (col. 8, L. 55-67); reading on limitations of the assessment of the cancer treatment is in the form of a molecular residual disease status or a cancer recurrence status for the human subject, and wherein the method further comprises determining, for each respective genomic alteration determined to be present in the determining E), whether the respective genomic alteration is germline or somatic, and wherein when the respective genomic alteration is determined to be germline, suppressing use of the respective genomic alteration in providing the molecular residual disease (MRD) status or the cancer recurrence status for the human subject.
Regarding claim 11, Eltoukhy discloses that clinical information is stored in a database array. For example, the system can store patient information from physicians and test labs in this database. Text data 220 such as genome sequence is also captured and histology reports for each patient. For example, data can come from cBio Cancer Genomics Portal (FIG. 1B, 210); reading on limitations of the structured data report in a subject data store.
Regarding claim 12, Eltoukhy discloses that the report generator system can be a central data processing system configured to establish communications directly with: a remote data site or lab, a medical practice/healthcare provider (treating professional) and/or a patient/subject through communication links. Eltoukhy further discloses that the lab can be medical laboratory, diagnostic laboratory, medical facility, medical practice, point-of-care testing device, or any other remote data site capable of generating subject clinical information. Subject clinical information includes but it is not limited to laboratory test data, X-ray data, examination and diagnosis. Eltoukhy further discloses that the clinical information 210 is stored in a database array and extracted by extractor 240 (for example, data augmentation) (col. 8, L. 10-12). Eltoukhy further discloses that the process generates genetic Report/Diagnosis. First, the process retrieves Prior Treatment from the Population with Similar Genetic Profile (78). The process includes generating genetic graph for a plurality of measurements showing mutation trend (79) and generating report showing treatment results and options (col. 13, L. 10-15). Additionally, Andry discloses that Demographic and clinical data from EMRs and other various clinical systems, including pathology and radiology data from the patient (in HSDP done via a VHR and an associated EMPI), is imported, reconciled and associated with biological sequencing data (pg. 201, col. 1, subsection 3.1.2); reading on limitation of retrieving health data associated with the human subject, and augmenting the structured data report with the health data.
Regarding claim 13, Eltoukhy discloses that the systems and methods described herein may also be used to help characterize certain cancers. Genetic data produced from the system and methods of this disclosure may allow practitioners to help better characterize a specific form of cancer. Often times, cancers are heterogeneous in both composition and staging. Genetic profile data may allow characterization of specific sub-types of cancer that may be important in the diagnosis or treatment of that specific sub-type. This information may also provide a subject or practitioner clues regarding the prognosis of a specific type of cancer (col. 14, L. 27-38). Eltoukhy further discloses classifying the test sample into one or more classes of cancers (col. 9, L. 12-27). Additionally, Andry discloses cancer scenarios and subtyping in Table 1. reading on limitations of including the cancer type in the data report.
Regarding claim 14, Eltoukhy discloses specimen’s details in the report (see FIG. 2C, 2D). Additionally, Andry discloses the data augmentation of various data and extracting and repurposing data from multiple different EMR systems (pg. 201, col. 1, subsection 3.1.2); reading on limitations of the health data comprises details of a specimen collected from the human subject, and the augmenting the data report with the health data comprises including details of the specimen in the data report.
Regarding claim 15, Eltoukhy discloses that lab 22 can be medical laboratory, diagnostic laboratory, medical facility, medical practice, point-of-care testing device, or any other remote data site capable of generating subject clinical information. Subject clinical information includes but it is not limited to laboratory test data, X-ray data, examination and diagnosis, the results of laboratory tests, imaging or medical procedure directed towards the specific cancer that one of ordinary skill in the art can readily identify. The list of appropriate sources of clinical information for cancer includes but it is not limited to: a computed tomography (CT) scan, a magnetic resonance imaging (MRI) scan, ultrasound scan, bone scan, a positron emission tomography (PET Scan), bone marrow test, barium X-ray, endoscopy, lymphangiogram, IVU (Intravenous urogram) or IVP (IV pyelogram), lumbar puncture, cystoscopy, immunological tests (anti-malignin antibody screen), and cancer marker tests (col. 11, L. 13-24). Eltoukhy further discloses reporting on cancer test results and treatment options (col. 10, L. 60-63). Eltoukhy further discloses classifying treatment responses to therapeutic interventions, and subsequently determine whether a given individual falls into a particular classification (e.g., responsive to treatment, nonresponsive to treatment, or a particular level of responsiveness such as fully 65 responsive or partially responsive) (col. 8, L. 60-67); reading on limitations of the health data comprises a diagnosis, a recurrence, a medication, a surgery, a response to treatment incurred by the human subject, an adverse effect to treatment incurred by the human subject, or an organoid modeling result, and the augmenting the data report comprises including the diagnosis, date of recurrence, the treatment incurred by the human subject, or an outcome of treatment in the data report.
Regarding claim 16, Eltoukhy discloses that a central data processing system is configured to establish communications directly with: a remote data site or lab 22, a medical practice/healthcare provider (treating professional) 24 and/or a patient/subject 26 through communication links. The lab 22 can be medical laboratory, diagnostic laboratory, medical facility, medical practice, point-of-care testing device, or any other remote data site capable of generating subject clinical information (col. 10-11, L. 63-97, 1-3, respectively). Additionally, Andry discloses extracting and repurposing data from multiple different EMR systems (pg. 201, col. 1, subsection 3.1.2); reading on limitation of the health data is retrieved from an electronic medical record or an electronic health record associated with the human subject.
Regarding claim 17, Eltoukhy discloses that health data provide indication of status of lung cancer (col. 13, L. 38-60; FIG. 2E, 2H); reading on limitaions of the health data provides an indication of a status of a colorectal, ovarian, lung, or breast cancer for the human subject. Additionally, Andry discloses that examples of use cases include breast, prostate and lung cancer scenarios (pg. 199, col. 2, subsection 2; see also scenarios of Table 1).
Regarding claim 18, Eltoukhy discloses that in a cancer treatment embodiment, the subject may be afflicted with cancer, among others (col. 11, L. 11-12). Eltoukhy further discloses that the term "cancer" includes reast, prostate, lung and colon cancer (col. 13, L. 48-67); reading on limitations of the human subject is afflicted with colorectal, ovarian, lung, or breast cancer. Additionally, Andry discloses that examples of use cases include breast, prostate and lung cancer scenarios (pg. 199, col. 2, subsection 2; see also scenarios of Table 1).
Regarding claim 19, Eltoukhy discloses mapping sequence reads derived from the sequencing onto a reference sequence; identifying a subset of mapped sequence reads that align with a variant of the reference sequence at each mappable base position; for each mappable base position, calculating a ratio of (a) a number of mapped sequence reads that include a variant as compared to the reference sequence, to (b) a number of total sequence reads for each mappable base position; and comparing current sequence reads with prior sequence reads from at least on other time point and updating a diagnostic confidence indication accordingly (col. 2, L. 59-67). Eltoukhy further discloses detecting the presence or absence of genetic alteration and/or amount of genetic variation in an individual based on the diagnostic confidence indication of the sequence read (col. 2, L. 19-23). Eltoukhy further discloses the data processing aspects of the system can be implemented in digital electronic circuitry, or in computer hardware, firmware, software, or in combinations of them (col. 28, L. 1-13). Andry discloses that pipelines used in PAPAyA are defined as a sequence of standard jobs (i.e., series of steps embodying bioinformatics tools and commands) used to transform data (e.g. sequencing data in FASTQ format) from a raw state to a processed state in which various analyses can be performed on variant calling data in VCF format … Modules used in PAPAyA take this 'usable' data and apply custom algorithms as well as various knowledge-base-driven annotations to provide the user with what is the crux of our platform: providing clinically actionable information based on a person's genome or biome … The modules are implemented using univariate or multivariate statistical methods as well as various machine learning and computational biology algorithms. For example, cancer subtyping can be a specific module that leverages unsupervised learning capabilities of the analytics platform … modules include genomics-oriented analytics, as well as NLP-related analytics (pg. 201). Andry further discloses scheduling and running jobs as part of predefined workflows asynchronously, passing parameters and results that are output between jobs, checking the status and progress of jobs, canceling and retrying specific jobs (for example, one or more alerts). Andry further discloses dependable mechanisms for automatic, secure, quality assured acquisition of demographic, clinical and genomic data from healthcare organizations. Provide a reliable way to schedule and execute various pipelines such as those for detecting variants, mutations, copy number variation (CNV), differential gene expression and differential DNA methylation (pg. 199, col. 2, last two paragraphs). Andry further discloses that the framework provides workflow orchestration, device cloud capabilities, notifications, scheduling, logging, auditing, metering as well as specific patient demographic, clinical and wellness data services that can be combined with the genomics analytics results (abstract); reading on limitations of wherein the D) mapping is performed by a first microservice and the E) determining is performed by a second microservice, and wherein the method further comprises comprising: publishing, upon completion of the D) mapping, the locations in the reference human genome to which the second genomic sequencing data have been mapped to a lake database, adding a first data alert or first event to a data alerts list, and initiating the second microservice to perform the E) determining upon the adding of the first data alert or first event to a data alerts list, wherein the E) determining obtains the locations in the reference human genome to which the second genomic sequencing data have been mapped from the lake database.
Rationale for combining Eltoukhy and Andry:
In KSR Int 'l v. Teleflex, the Supreme Court, in rejecting the rigid application of the teaching, suggestion, and motivation test by the Federal Circuit, indicated that “The principles underlying [earlier] cases are instructive when the question is whether a patent claiming the combination of elements of prior art is obvious. When a work is available in one field of endeavor, design incentives and other market forces can prompt variations of it, either in the same field or a different one. If a person of ordinary skill can implement a predictable variation, § 103 likely bars its patentability.” KSR Int'l v. Teleflex lnc., 127 S. Ct. 1727, 1740 (2007).
Applying the KSR standard to Eltoukhy and Andry, the examiner concludes that the combination of Eltoukhy and Andry represents the use of known techniques to improve similar methods. Both Eltoukhy and Andry are directed to analyzing large genomics datasets using analysis algorithms based on pre-defined knowledge databases with the goal to offer guidance for cancers. Eltoukhy only disclosed data processing aspects of the invention can be implemented advantageously in one or more computer programs that are executable on a programmable system including at least one programmable processor coupled to receive data and instructions from and to transmit data and instructions to a data storage system and submitting and accessing the reports electronically via internet for generating a therapeutic response. In the same field of research, Andry disclosed a cloud-based platform that employs microservices that provides generic provisioning and hosting services, identity and access management, workflow orchestration, device cloud capabilities, notifications, scheduling, logging, auditing, metering as well as specific patient demographic, clinical and wellness data services that can be combined with the genomics analytics results of Eltoukhy. It would have been obvious to use the genomic analysis of Eltoukhy as one of the microservices of Andy and the results would have been predictable. One ordinary skilled in art before he effective filing data of the claimed invention would have had a reasonable expectation of success at combining the method of Eltoukhy and Andry. This combination would have been expected to have provided a more comprehensive assessment of cancer treatment efficacy. Therefore, the invention would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention, absent evidence to the contrary.
Response to Arguments
Applicants’ arguments filed 06/30/2026 have been considered but they are not yet persuasive. The amendments to claims necessitated new art rejections. As such, the combination of Eltoukhy and Andry teaches all the limitations of the claimed invention.
Conclusion
No claims are allowed.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/G.S./Examiner, Art Unit 1686
/LARRY D RIGGS II/Supervisory Patent Examiner, Art Unit 1686
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