DETAILED ACTION
Notice to Applicant
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This communication is in response to the amendment filed 7/25/25. Claims 1-6, 10-11, 13-14, 16-17, and 20-21 are pending.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 3/26/26 has been entered.
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 1-6, 10-11, 13-14, 16-17, and 20-21 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.
35 USC 101 enumerates four categories of subject matter that Congress deemed to be appropriate subject matter for a patent: processes, machines, manufactures and compositions of matter. As explained by the courts, these “four categories together describe the exclusive reach of patentable subject matter. If a claim covers material not found in any of the four statutory categories, that claim falls outside the plainly expressed scope of Section 101 even if the subject matter is otherwise new and useful.” In re Nuijten, 500 F.3d 1346, 1354, 84 USPQ2d 1495, 1500 (Fed. Cir. 2007). Step 1 of the eligibility analysis asks: Is the claim to a process, machine, manufacture or composition of matter? Applicant’s claims fall within at least one of the four categories of patent eligible subject matter because claims 1-6, and 10 are drawn to a method; claims 11, 13-14, 16-17, and 20 are drawn to a system; claim 21 is drawn to a product (article of manufacture, storing instructions to perform a method)
Determining that a claim falls within one of the four enumerated categories of patentable subject matter recited in 35 USC 101 (i.e., process, machine, manufacture, or composition of matter) in Step 1 does not complete the eligibility analysis. Claims drawn only to an abstract idea, a natural phenomenon, and laws of nature are not eligible for patent protection. As described in MPEP 2106, subsection III, Step 2A of the Office’s eligibility analysis is the first part of the Alice/Mayo test, i.e., the Supreme Court’s “framework for distinguishing patents that claim laws of nature, natural phenomena, and abstract ideas from those that claim patent-eligible applications of those concepts.” Alice Corp. Pty. Ltd. v. CLS Bank Int'l,134 S. Ct. 2347, 2355, 110 USPQ2d 1976, 1981 (2014) (citing Mayo, 566 U.S. at 77-78, 101 USPQ2d at 1967-68).
In 2019, the United States Patent and Trademark Office (USPTO) prepared revised guidance (2019 Revised Patent Subject Matter Eligibility Guidance) for use by USPTO personnel in evaluating subject matter eligibility. The framework for this revised guidance, which sets forth the procedures for determining whether a patent claim or patent application claim is directed to a judicial exception (laws of nature, natural phenomena, and abstract ideas), is described in MPEP sections 2106.03 and 2106.04.
As explained in MPEP 2106.04(a)(2), the 2019 Revised Patent Subject Matter Eligibility Guidance explains that abstract ideas can be grouped as, e.g., mathematical concepts, certain methods of organizing human activity, and mental processes. Moreover, this guidance explains that a patent claim or patent application claim that recites a judicial exception is not ‘‘directed to’’ the judicial exception if the judicial exception is integrated into a practical application of the judicial exception. A claim that recites a judicial exception, but is not integrated into a practical application, is directed to the judicial exception under Step 2A and must then be evaluated under Step 2B (inventive concept) to determine the subject matter eligibility of the claim.
Step 2A asks: Does the claim recite a law of nature, a natural phenomenon (product of nature) or an abstract idea? If so, is the judicial exception integrated into a practical application of the judicial exception? A claim recites a judicial exception when a law of nature, a natural phenomenon, or an abstract idea is set forth or described in the claim. While the terms “set forth” and “describe” are thus both equated with “recite”, their different language is intended to indicate that there are different ways in which an exception can be recited in a claim. For instance, the claims in Diehr set forth a mathematical equation in the repetitively calculating step, while the claims in Mayo set forth laws of nature in the wherein clause, meaning that the claims in those cases contained discrete claim language that was identifiable as a judicial exception. The claims in Alice Corp., however, described the concept of intermediated settlement without ever explicitly using the words “intermediated” or “settlement.” A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception.
In the instant case, claims 1-6,10-11, 13-14, 16-17, and 20-21 recite(s) a method, system, and article of manufacture drawn to mathematical concepts, which is subject matter that falls within the enumerated groupings of abstract ideas described in MPEP 2106.04 (2019 Revised Patent Subject Matter Eligibility Guidance) The recited method and system are drawn to receiving graphical data, performing analysis on received data, developing an optimized mathematical model, and developing a model predicting an optimal clinical outcome; predicting an optimal clinical outcomes based on the data received.
In the instant case, claims 1-6,10-11, 13-14, 16-17, and 20-21 recite(s) a method and system for certain methods of organizing human activities, which is subject matter that falls within the enumerated groupings of abstract ideas described in MPEP 2106.04 (2019 Revised Patent Subject Matter Eligibility Guidance) Certain methods of organizing human activities includes fundamental economic practices, like insurance; commercial interactions (i.e. legal obligations, marketing or sales activities or behaviors, and business relations). Organizing human activity also encompasses managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions.) The recited method and system are drawn to analyzing clinical data comparing individual treatment pathways and similar treatments; and predicting an optimal clinical outcome for a patient. ( i.e. managing personal behavior or relationships)
In particular, claims 1, 11, and 21 recite a method, system and CRM to:
receive a state transition graph… multiple aligned and merged individual treatment pathways;
performing an analysis, by the one or more computing devices, on the state transition graph and clinical data obtained from the individual treatment pathways, wherein the state transition graph comprises one or more edges that correspond to treatments of a similar nature;
generating,…based on the performed analysis, an optimal statistical model configured to that predicts an optimal clinical outcome based on the state transition graph and the clinical data, … based on analysis of the influence of the one or more edges on a categorical or quantitative trait, and wherein the categorical or quantitative trait includes at least one of a dynamic categorical trait or a dynamic quantitative trait;
predicting an optimal clinical outcome for a patient
It is noted that claims 1, 11, and 21 further recite “wherein the dynamic categorical trait or a dynamic quantitative trait comprises a value that changes after traversing at least one of the one or more edges.” Claims 1, 11, and 21 have been also amended to recite: each comprising two or more similar overlapping edges, wherein edge similarity is defined by a user-defined similarity criteria and measure, and wherein two or more similar edges are merged only if their effects on a clinical outcome are in a same direction and a resultant p value or effect measure is stronger than an individual edge. The additional limitations further define the abstract idea, but fail to add significantly more. As such, the claims are not patient eligible.
MENTAL PROCESS-ANALYSIS
Moreover, the language of claims 1, 11, and 21 encompasses performance of the limitations(s) in the mind, but for the recitation of generic computer components.
In the instant case, the limitation of determining the amount of use of each icon over a predetermined period of time, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “by one or more computer devices,” nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “by one or more computer devices” language, receiving, performing an analysis; generating a model; and predicting in the context of this claim encompasses the user manually reading the state graph with aligned and merged treatment pathways; analyzing the information; rendering a prediction regarding the optimal outcome.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas.
As explained in MPEP 2106.04(a)(2)(III), the courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). (emphasis added) As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[M]ental processes[] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978).
Accordingly, the "mental processes" abstract idea grouping is defined as concepts performed in the human mind, and examples of mental processes include observations, evaluations, judgments, and opinions.
The courts do not distinguish between mental processes that are performed entirely in the human mind and mental processes that require a human to use a physical aid (e.g., pen and paper or a slide rule) to perform the claim limitation. See, e.g., Benson, 409 U.S. at 67, 65, 175 USPQ at 674-75, 674 (noting that the claimed "conversion of [binary-coded decimal] numerals to pure binary numerals can be done mentally," i.e., "as a person would do it by head and hand."); Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1139, 120 USPQ2d 1473, 1474 (Fed. Cir. 2016) (holding that claims to a mental process of "translating a functional description of a logic circuit into a hardware component description of the logic circuit" are directed to an abstract idea, because the claims "read on an individual performing the claimed steps mentally or with pencil and paper").
Moreover, courts do not distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer. As the Federal Circuit has explained, "[c]ourts have examined claims that required the use of a computer and still found that the underlying, patent-ineligible invention could be performed via pen and paper or in a person’s mind." Versata Dev. Group v. SAP Am., Inc., 793 F.3d 1306, 1335, 115 USPQ2d 1681, 1702 (Fed. Cir. 2015). See also Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1318, 120 USPQ2d 1353, 1360 (Fed. Cir. 2016) (‘‘[W]ith the exception of generic computer-implemented steps, there is nothing in the claims themselves that foreclose them from being performed by a human, mentally or with pen and paper.’’); Mortgage Grader, Inc. v. First Choice Loan Servs. Inc., 811 F.3d 1314, 1324, 117 USPQ2d 1693, 1699 (Fed. Cir. 2016) (holding that computer-implemented method for "anonymous loan shopping" was an abstract idea because it could be "performed by humans without a computer").
This judicial exception is not integrated into a practical application because the claim language does not recite any improvements to the functioning of a computer, or to any other technology or technical field (See MPEP 2106.04(d)(1); see also MPEP 2106.05(a)(I-II)). Moreover, the claims do not integrate the judicial exception into a practical application because the claimed invention does not: apply the judicial exception with, or by use of, a particular machine (see MPEP 2106.05(b)); effect a transformation or reduction of a particular article to a different state or thing (see MPEP 2106.05(c)); or apply or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment see MPEP 2106.05(e). (Considerations for integration into a practical application in Step 2A, prong two and for recitation of significantly more than the judicial exception in Step 2B).
While abstract ideas, natural phenomena, and laws of nature are not eligible for patenting by themselves, claims that integrate these exceptions into an inventive concept are thereby transformed into patent-eligible inventions. Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 134 S. Ct. 2347, 2354, 110 USPQ2d 1976, 1981 (2014) (citing Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66, 71-72, 101 USPQ2d 1961, 1966 (2012)). Thus, the second part of the Alice/Mayo test is often referred to as a search for an inventive concept. Id. An “inventive concept” is furnished by an element or combination of elements that is recited in the claim in addition to (beyond) the judicial exception, and is sufficient to ensure that the claim as a whole amounts to significantly more than the judicial exception itself. Alice Corp., 134 S. Ct. at 2355, 110 USPQ2d at 1981 (citing Mayo, 566 U.S. at 72-73, 101 USPQ2d at 1966). Although the courts often evaluate considerations such as the conventionality of an additional element in the eligibility analysis, the search for an inventive concept should not be confused with a novelty or non-obviousness determination. See Mayo, 566 U.S. at 91, 101 USPQ2d at 1973 (rejecting “the Government’s invitation to substitute Sections 102, 103, and 112 inquiries for the better established inquiry under Section 101”). As made clear by the courts, the “‘novelty’ of any element or steps in a process, or even of the process itself, is of no relevance in determining whether the subject matter of a claim falls within the Section 101 categories of possibly patentable subject matter.” Intellectual Ventures I v. Symantec Corp.,838 F.3d 1307, 1315, 120 USPQ2d 1353, 1358 (Fed. Cir. 2016) (quoting Diamond v. Diehr, 450 U.S. at 188–89, 209 USPQ at 9).
As described in MPEP 2106.05, Step 2B of the Office’s eligibility analysis is the second part of the Alice/Mayo test, i.e., the Supreme Court’s “framework for distinguishing patents that claim laws of nature, natural phenomena, and abstract ideas from those that claim patent-eligible applications of those concepts.” Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. _, 134 S. Ct. 2347, 2355, 110 USPQ2d 1976, 1981 (2014) (citing Mayo, 566 U.S. 66, 101 USPQ2d 1961 (2012)). Step 2B asks: Does the claim recite additional elements that amount to significantly more than the judicial exception? The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 1 recites additional limitation(s), including: by one or more computing devices. Similarly, claim 11 recites “a processor configured to…..” Claim 21 additionally recites “a non-transitory, machine-readable medium storing instructions…” These additional claim limitations do not amount to significantly more, and merely include generic computer elements performing generic computer functions/activities, that amount to no more than implementing the abstract idea with a computerized system.
The generic nature of the computer system used to carryout steps of the recited method is underscored by the system description in the instant application, which discloses: “When implemented at least partially in hardware, the modules, models, engines, processors, and other information generating, processing, or calculating features may be, for example, any one of a variety of integrated circuits including but not limited to an application-specific integrated circuit, a field-programmable gate array, a combination of logic gates, a system-on-chip, a microprocessor, or another type of processing or control circuit" (par. 96-Emphasis added) The disclosure also states: “A non-transitory machine-readable storage medium may include any mechanism for storing information in a form readable by a machine, such as a personal or laptop computer, a server, or other computing device. Thus, a non-transitory machine-readable storage medium may include read-only memory (ROM), random-access memory (RANI), magnetic disk storage media, optical storage media, flash-memory devices, and similar storage media.” (par. 98) The description of broad range of known computer components used to implement the method underscores that the applicant's perceived invention/ novelty focuses on the computerized implementation of the abstract idea, not the underlying structure of the additional (generic) components.
Furthermore, the courts have recognized certain computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (See MPEP 2106.05 (d) (II)). These include:
- Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014) ("Unlike the claims in Ultramercial, the claims at issue here specify how interactions with the Internet are manipulated to yield a desired result‐‐a result that overrides the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink." (emphasis added));
- Performing repetitive calculations, Flook, 437 U.S. at 594, 198 USPQ2d at 199 (recomputing or readjusting alarm limit values); Bancorp Services v. Sun Life, 687 F.3d 1266, 1278, 103 USPQ2d 1425, 1433 (Fed. Cir. 2012) ("The computer required by some of Bancorp’s claims is employed only for its most basic function, the performance of repetitive calculations, and as such does not impose meaningful limits on the scope of those claims.");
- Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93;
Because Applicant’s claimed invention recites a judicial exception that is not integrated into a practical application and does not include additional elements that are sufficient to amount to significantly more than the judicial exception itself, the claimed invention is not patent eligible.
Claims 1-6, and10 are dependent from Claim 1 and include(s) all the limitations of claim(s) 1. However, the additional limitations of the claims 1-6, and10 fail to recite significantly more than the abstract idea. Therefore, claim(s) 1-6, and10 are also rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claims 13-14, 16-17 and 20 are dependent from Claim 11 and include(s) all the limitations of claim(s) 11. However, the additional limitations of the claims 12-20 fail to recite significantly more than the abstract idea. Therefore, claim(s) 12-20 are also rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-6, and 10; and 21 is/are rejected under 35 U.S.C. 102(a)(1)as being anticipated by Aggarwal et al (US 20100125462 A1).
Claim 1 Aggarwal teaches a computer implemented(par. 195-196) a method for graph-based predictive modeling of optimal clinical outcomes comprising:
receiving, by one or more computing devices, a state transition graph representing multiple aligned and merged individual treatment pathways (Fig. 3; par. 12- the analytics engine uses a state-transition graph to represent the current state of the patient. Furthermore, the user views this state-transition graph through the GUI. Each vertex of the state-transition graph represents the state of the patient at each stage of the treatment protocol. Hence, by moving from one vertex to another, the user can view the entire state-transition graph for a particular disease (and the treatment protocols that are included in the system for this disease; par. 26) comprising: one or more qualifying events; one or more response states to the one or more qualifying events; one or more reversible or collapsible events (par. 26-treatment data; par. 64-complications/ health issues)
performing analysis, by the one or more computing devices, on the state transition graph and clinical data obtained from the individual treatment pathways, (par. 26-analytics engine 104 performs statistical and computational analysis based on the input parameters and generates (as well as regularly updates) a state-transition graph representing the different stages of different treatment protocols along with potential outcomes; par. 32-33- analysis module), wherein the state transition graph comprises one or more edges that correspond to treatments of a similar nature. (par. 33- The state-transition graph has vertices and directed edges… The directed edges originating from a vertex indicate different options that are available at a particular stage of the treatment protocol.)
and
automatically generating, by the one or more computing devices based on the performed analysis, an optimal statistical model configured to predict an optimal clinical outcome based on the state transition graph and the clinical data. (Figs. 2-4; par. 24-27; par. 62-63; par. 188-194; See also-par. 45-50),
wherein the optimal predictive model is generated based on analysis of the influence of the one or more edges on a categorical or quantitative trait, (par. 33- 35: The state-transition graph has vertices and directed edges… The directed edges originating from a vertex indicate different options that are available at a particular stage of the treatment protocol; See [0012], [0049]-[0050], wherein arc = edge, vertex = node; [0043]: fitting of weights; [0009], [0016]: analysis may be in real-time and therefore dynamic ) and wherein the categorical or quantitative trait includes at least one of a dynamic categorical trait or a dynamic quantitative trait. (par. 26-28)
predicting, using the generated optimal statistical model, an optimal outcome for a patient. (par. 43; par. 63; par. 188-194-output)
Claim 1 has been further amended to recite: each comprising two or more similar overlapping edges, wherein edge similarity is defined by a user-defined similarity criteria and measure, and wherein two or more similar edges are merged only if their effects on a clinical outcome are in a same direction and a resultant p value or effect measure is stronger than an individual edge “; “wherein the dynamic categorical trait or a dynamic quantitative trait comprises a value that changes after traversing at least one of the one or more edges” and
Aggrawal does not expressly teach the specific data recited in the claim (i.e. each comprising two or more similar overlapping edges, wherein edge similarity is defined by a user-defined similarity criteria and measure, and wherein two or more similar edges are merged only if their effects on a clinical outcome are in a same direction and a resultant p value or effect measure is stronger than an individual edge; wherein the dynamic categorical trait or a dynamic quantitative trait comprises a value that changes after traversing at least one of the one or more edges). These differences are only found in the non-functional descriptive material and are not functionally involved in any manipulative steps of the invention nor do they alter any recited structural elements; therefore, such differences do not effectively serve to patentably distinguish the claimed invention over the prior art. Any manipulative steps of the invention would be performed the same regardless of the specific data (i.e. the actively recited step is “automatically generating, by the one or more computing devices based on the performed analysis, an optimal statistical model.”) Further, any structural elements remain the same regardless of the specific data. Thus, this descriptive material will not distinguish the claimed invention from the prior art in terms of patentability as the claimed invention fails to present a new and unobvious functional relationship between the descriptive material and the substrate, see In re Gulack, 703 F.2d 1381, 1385, 217 USPQ 401, 404 (Fed. Cir. 1983); In re Lowry, 32 F.3d 1579, 32 USPQ2d 1031 (Fed. Cir. 1994); In re Ngai, 367 F.3d 1336, 1336, 70 USPQ2d 1862, 1863-64 (Fed. Cir. 2004). Another indication of the existence of non-functional descriptive material is that the content of the material is merely “directed towards conveying a message or meaning to a human reader independent of the supporting product.” Please see MPEP § 2111.05(I)(B).
claims 2 Aggarwal teaches a system/method wherein the one or more qualifying events comprises one or more treatment regimens. (par. 25-27- The user may provide input parameters related to historical information of a patient and one or more treatment protocols that may be used for the treatment of the patient.)
claims 3 Aggarwal teaches a method/system , wherein the one or more treatment regimens is selected from the group consisting of a drug regimen, a surgical protocol, a collection of eligible interventions, or combinations thereof. (par. 33; par. 87-92; par. 93-116-drugs and treatments)
claims 4 Aggarwal teaches the method/system, wherein the one or more response states is selected from the group consisting of a response status after a treatment; and a subtype of the patient based on a specific gene signature. (par. 10-11; par. 27-28)
claims 5. Aggarwal teaches the method/system, wherein the one or more response states is linked to one or more reports selected from the group consisting of a clinical report, a radiology report, a pathology report, a genomics report, or combinations thereof. (Fig. 3; par. 33; par. 47-49; par. 76-92)
claims 6 Aggarwal discloses the method/system wherein the one or more response states is linked to one or more genomics reports.(par. 86-oncotype genetic markers)
claims 10 Aggarwal discloses a method/system of claim 8, wherein the method for evaluating the influence of the one or more edges is selected from the group consisting of a relative risk test, an odds ratio test, a Chi-Square Test of Independence, a Fisher's Exact Test of Independence, a McNemar's Test of Homogeneity of Marginal Distributions and a Dependent T-Test for Paired Samples. (par. 32 analytics engine 104 performs the analysis by using classical statistical techniques and by using artificial neural networks)
Claim 21 Aggarwal teaches a system comprising a processor (par. 195-196) and a non-transitory computer readable medium storing instructions (par. 196) for performing a method for graph-based predictive modeling of optimal clinical outcomes comprising:
receiving, by one or more computing devices, a state transition graph representing multiple aligned and merged individual treatment pathways (Fig. 3; par. 12- the analytics engine uses a state-transition graph to represent the current state of the patient. Furthermore, the user views this state-transition graph through the GUI. Each vertex of the state-transition graph represents the state of the patient at each stage of the treatment protocol. Hence, by moving from one vertex to another, the user can view the entire state-transition graph for a particular disease (and the treatment protocols that are included in the system for this disease; par. 26) comprising: one or more qualifying events; one or more response states to the one or more qualifying events; one or more reversible or collapsible events (par. 26-treatment data; par. 64-complications/ health issues)
performing analysis, by the one or more computing devices, on the state transition graph and clinical data obtained from the individual treatment pathways, (par. 26-nalytics engine 104 performs statistical and computational analysis based on the input parameters and generates (as well as regularly updates) a state-transition graph representing the different stages of different treatment protocols along with potential outcomes; par. 32-33- analysis module), wherein the state transition graph comprises one or more edges that correspond to treatments of a similar nature. (par. 33- The state-transition graph has vertices and directed edges… The directed edges originating from a vertex indicate different options that are available at a particular stage of the treatment protocol.) and
automatically generating, by the one or more computing devices, based on the performed analysis an optimal statistical model configured to predict an optimal clinical outcome based on the state transition graph and the clinical data (Figs. 2-4; par. 24-27; par. 62-63; par. 188-194; See also-par. 45-50);
wherein the optimal predictive model is generated based on analysis of the influence of the one or more edges on a categorical or quantitative trait, (par. 33- 35: The state-transition graph has vertices and directed edges… The directed edges originating from a vertex indicate different options that are available at a particular stage of the treatment protocol; See [0012], [0049]-[0050], wherein arc = edge, vertex = node; [0043]: fitting of weights; [0009], [0016]: analysis may be in real-time and therefore dynamic) and wherein the categorical or quantitative trait includes at least one of a dynamic categorical trait or a dynamic quantitative trait. (par. 26-28)
predicting, using the generated optimal statistical model, an optimal outcome for a patient. (par. 43; par. 63; par. 188-194-output)
Claim 21 has been further amended to recite: each comprising two or more similar overlapping edges, wherein edge similarity is defined by a user-defined similarity criteria and measure, and wherein two or more similar edges are merged only if their effects on a clinical outcome are in a same direction and a resultant p value or effect measure is stronger than an individual edge “; “wherein the dynamic categorical trait or a dynamic quantitative trait comprises a value that changes after traversing at least one of the one or more edges” and
Aggrawal does not expressly teach the specific data recited in the claim (i.e. each comprising two or more similar overlapping edges, wherein edge similarity is defined by a user-defined similarity criteria and measure, and wherein two or more similar edges are merged only if their effects on a clinical outcome are in a same direction and a resultant p value or effect measure is stronger than an individual edge; wherein the dynamic categorical trait or a dynamic quantitative trait comprises a value that changes after traversing at least one of the one or more edges). These differences are only found in the non-functional descriptive material and are not functionally involved in any manipulative steps of the invention nor do they alter any recited structural elements; therefore, such differences do not effectively serve to patentably distinguish the claimed invention over the prior art. Any manipulative steps of the invention would be performed the same regardless of the specific data (i.e. the actively recited step is “automatically generating, by the one or more computing devices based on the performed analysis, an optimal statistical model.”) Further, any structural elements remain the same regardless of the specific data. Thus, this descriptive material will not distinguish the claimed invention from the prior art in terms of patentability as the claimed invention fails to present a new and unobvious functional relationship between the descriptive material and the substrate, see In re Gulack, 703 F.2d 1381, 1385, 217 USPQ 401, 404 (Fed. Cir. 1983); In re Lowry, 32 F.3d 1579, 32 USPQ2d 1031 (Fed. Cir. 1994); In re Ngai, 367 F.3d 1336, 1336, 70 USPQ2d 1862, 1863-64 (Fed. Cir. 2004). Another indication of the existence of non-functional descriptive material is that the content of the material is merely “directed towards conveying a message or meaning to a human reader independent of the supporting product.” Please see MPEP § 2111.05(I)(B).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 11, 13-14, 16-17; and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Aggarwal et al (US 20100125462 A1) in view of Dastmalchi et al (US 20130275153 A1)
Claim 11 Aggarwal teaches a system comprising a processor (par. 195-196) and a non-transitory computer readable medium storing instructions (par. 196) for predicting optimal clinical outcomes, comprising:
a processor configured to:
receive a state transition graph representing multiple aligned and merged individual treatment pathways (Fig. 3; par. 12- the analytics engine uses a state-transition graph to represent the current state of the patient. Furthermore, the user views this state-transition graph through the GUI. Each vertex of the state-transition graph represents the state of the patient at each stage of the treatment protocol. Hence, by moving from one vertex to another, the user can view the entire state-transition graph for a particular disease (and the treatment protocols that are included in the system for this disease; par. 26) comprising:
one or more qualifying events, wherein the one or more qualifying events comprises one or more treatment regimens. (par. 25-27- The user may provide input parameters related to historical information of a patient and one or more treatment protocols that may be used for the treatment of the patient.)
one or more response states to the one or more qualifying events, wherein the one or more response states is linked to one or more genomics report; .(par. 86-oncotype genetic markers)
one or more reversible or collapsible events (par. 26-treatment data; par. 64-complications/ health issues)
perform analysis on the state transition graph and clinical data obtained from the individual treatment pathways, (par. 26-nalytics engine 104 performs statistical and computational analysis based on the input parameters and generates (as well as regularly updates) a state-transition graph representing the different stages of different treatment protocols along with potential outcomes; par. 32-33- analysis module), wherein the state transition graph comprises one or more edges that correspond to treatments of a similar nature. (par. 33- The state-transition graph has vertices and directed edges… The directed edges originating from a vertex indicate different options that are available at a particular stage of the treatment protocol.) and
automatically generate, based on performed analysis, an optimal statistical model configured to predict an optimal clinical outcome based on the state transition graph and the clinical data. (Figs. 2-4; par. 24-27; par. 62-63; par. 188-194; See also-par. 45-50 )
wherein the processor is configured to automatically generate an optimal predictive model by analyzing the influence of the one or more edges on a categorical or quantitative trait, (par. 33- 35: The state-transition graph has vertices and directed edges… The directed edges originating from a vertex indicate different options that are available at a particular stage of the treatment protocol; See [0012], [0049]-[0050], wherein arc = edge, vertex = node; [0043]: fitting of weights; [0009], [0016]: analysis may be in real-time and therefore dynamic) and wherein the categorical or quantitative trait includes at least one of a dynamic categorical trait or a dynamic quantitative trait. (par. 26-28), wherein the categorical or quantitative trait is a static categorical or quantitative trait or a dynamic categorical or quantitative trait. (par. 26-28; par. 33- The state-transition graph has vertices and directed edges… The directed edges originating from a vertex indicate different options that are available at a particular stage of the treatment protocol; See [0012], [0049]-[0050], wherein arc = edge, vertex = node; [0043]: fitting of weights; [0009], [0016]: analysis may be in real-time and therefore dynamic )
predicting, using the generated optimal statistical model, an optimal outcome for a patient. (par. 43; par. 63; par. 188-194-output)
Claim 11 has been further amended to recite: “each comprising two or more similar overlapping edges, wherein edge similarity is defined by a user-defined similarity criteria and measure, and wherein two or more similar edges are merged only if their effects on a clinical outcome are in a same direction and a resultant p value or effect measure is stronger than an individual edge “; “wherein the dynamic categorical trait or a dynamic quantitative trait comprises a value that changes after traversing at least one of the one or more edges” and
Aggrawal does not expressly teach the specific data recited in the claim (i.e. each comprising two or more similar overlapping edges, wherein edge similarity is defined by a user-defined similarity criteria and measure, and wherein two or more similar edges are merged only if their effects on a clinical outcome are in a same direction and a resultant p value or effect measure is stronger than an individual edge; wherein the dynamic categorical trait or a dynamic quantitative trait comprises a value that changes after traversing at least one of the one or more edges). These differences are only found in the non-functional descriptive material and are not functionally involved in any manipulative steps of the invention nor do they alter any recited structural elements; therefore, such differences do not effectively serve to patentably distinguish the claimed invention over the prior art. Any manipulative steps of the invention would be performed the same regardless of the specific data (i.e. the actively recited step is “automatically generating, by the one or more computing devices based on the performed analysis, an optimal statistical model.”) Further, any structural elements remain the same regardless of the specific data. Thus, this descriptive material will not distinguish the claimed invention from the prior art in terms of patentability as the claimed invention fails to present a new and unobvious functional relationship between the descriptive material and the substrate, see In re Gulack, 703 F.2d 1381, 1385, 217 USPQ 401, 404 (Fed. Cir. 1983); In re Lowry, 32 F.3d 1579, 32 USPQ2d 1031 (Fed. Cir. 1994); In re Ngai, 367 F.3d 1336, 1336, 70 USPQ2d 1862, 1863-64 (Fed. Cir. 2004). Another indication of the existence of non-functional descriptive material is that the content of the material is merely “directed towards conveying a message or meaning to a human reader independent of the supporting product.” Please see MPEP § 2111.05(I)(B).
Claim 11 further recites:
multiple aligned and merged individual treatment pathways for a plurality of patients,
the one or more response states comprising subtypes of the plurality of patients in the state transition graph based on specific gene signatures,
Aggarwal discloses a system substantially as claimed but does not expressly disclose “multiple aligned and merged individual treatment pathways for a plurality of patients.” Dastmalchi discloses a system configured to receive data that includes multiple aligned and merged individual treatment pathways for a plurality of patients. (Fig. 8-10; par. 69-72)
Aggarwal discloses response states and use of genetic signatures in determining treatment options and tumor typing (par. 79-81; par. 86-oncotyping), but does not expressly disclose the one or more response states comprising subtypes of the plurality of patients in the state transition graph ( based on specific genesignatures). Dastmalchi discloses one or more response states comprising subtypes of the plurality of patients in the state transition graph (par. 61-62-cohort data: “identify a set of events of interest, compute the health correlation graph for all events of interest for all patients in the system to be optimized and then compute a global figure of merit for the system. The figure of merit can be any function of the impact value and time, computed over the entire patient cohort…” “suggest actions which optimize over expected future outcomes for the individual and the cohort, conditioned upon the likelihood that the action will be taken and will have the desired effect”)
At the time of filing, it would have been obvious to one of ordinary skill in the art to modify the system of Aggarwal with the teaching of Dastmalchi to include the additional features with the motivation of increasing medical care efficiency and care quality (Dastmalchi: par. 7)
claims 13 Aggarwal teaches a method/system , wherein the one or more treatment regimens is selected from the group consisting of a drug regimen, a surgical protocol, a collection of eligible interventions, or combinations thereof. (par. 33; par. 87-92; par. 93-116-drugs and treatments)
claims 14 Aggarwal teaches the method/system, wherein the one or more response states further comprises a response status after a treatment (par. 27-28; par. 37-38; par. 191-tumor response rates). Aggarwal further discloses response states and use of genetic signatures in determining treatment options and tumor typing (par. 79-81; par. 86-oncotyping subtype of the patient based on a specific gene signature.
claims 16 Aggarwal discloses the method/system wherein the one or more response states is linked to one or more genomics reports.(par. 86-oncotype genetic markers)
claims 17 Aggarwal teaches a method/ system, wherein the state transition graph comprises one or more edges that correspond to treatments of a similar nature. (par. 33- The state-transition graph has vertices and directed edges… The directed edges originating from a vertex indicate different options that are available at a particular stage of the treatment protocol.)
claims 20 Aggarwal discloses a method/system of claim 11, wherein the method for evaluating the influence of the one or more edges is selected from the group consisting of, but not restricted to, a relative risk test, an odds ratio test, a Chi-Square Test of Independence, a Fisher's Exact Test of Independence, a McNemar's Test of Homogeneity of Marginal Distributions and a Dependent T-Test for Paired Samples. (par. 32 analytics engine 104 performs the analysis by using classical statistical techniques and by using artificial neural networks)
Response to Arguments
Applicant's arguments filed 3/26/26 have been fully considered but they are not persuasive.
(A) Applicant argues that the claimed invention is not drawn to a mathematical concept or mathematical relationship.
In response, the examiner has updated the rejection under 35 USC 101 to remove the analysis of the invention as a mathematical concept. Applicant’s arguments regarding this analysis are moot.
The recited judicial exception is not integrated into a practical application because the claim language does not recite any improvements to the functioning of a computer, or to any other technology or technical field (See MPEP 2106.04(d)(1); see also MPEP 2106.05(a)(I-II)). Moreover, the claims do not integrate the judicial exception into a practical application because the claimed invention does not: apply the judicial exception with, or by use of, a particular machine (see MPEP 2106.05(b)); effect a transformation or reduction of a particular article to a different state or thing (see MPEP 2106.05(c)); or apply or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment see MPEP 2106.05(e). (Considerations for integration into a practical application in Step 2A, prong two and for recitation of significantly more than the judicial exception in Step 2B).
(B) Applicant argues that the Aggarwal reference fails to teach the use of a dynamic categorical and/or quantitative trait. Instead, Aggarwal discloses the inputting of parameters, such as "overall survival for a pre-defined number of years, disease free survival for a pre-defined number of years, tumor response rate, time to progression of symptoms, and quality of life after the treatment," but fails to disclose dynamic categorical and/or quantitative traits.
In response, the examiner disagrees. Applicant fails to define or recite any particular “categorical traits” or “quantitative traits.” Therefore the terms are given the broadest reasonable interpretation. It is not clear to the examiner how parameters, such as "overall survival for a pre-defined number of years, disease free survival for a pre-defined number of years, tumor response rate, time to progression of symptoms, and quality of life after the treatment" are different from the “categorical” or “quantitative” traits argued by the Applicant
Aggarwal also discloses developing a cost estimation engine, for predicting costs of different treatment pathways/ treatment protocol timelines. (See Figs. 2-4; par. 24-27; par. 62-63; par. 188-194; See also-par. 45-50 ) It is noted that while the claims recite “optimal statistical model” and “optimal clinical outcome,” the claims 1, 11, and 21 fail to define whether the optimized outcome is with regard to costs, length of treatment, 5-year survival rates, QOL, or any number of parameters.
Additionally, applicant’s arguments regarding the instant invention’s distinctions from the Aggarwal reference rely limitations which are not actively recited/performed in claimed invention. For example, “to predict an optimal clinical outcome based on the state transition graph and the clinical data” is an intended use of the model. Moreover, claims 1, 11, and 21 broadly recite performing an analysis on state transition graph data and clinical data, but provides no details regarding the type of analysis performed or used to generate the “optimal model,” other than saying it is based on the analysis.
As drafted, the current claim language is overly broad, and does not preclude or overcome the Aggarwal reference.
(C) Applicant argues that the Aggrawal and Dastmalchi references do not address claim limitations, because the Dastmalchi reference does not remedy the deficiencies of Aggrawal. Applicant further argues that the combination of the references is improper because there is no motivation to combine.
In response, the Examiner respectfully disagrees. Applicant’s arguments regarding the Aggrawal reference have been addressed in paragraph (B) of the response to arguments.
Additionally, in response to applicant’s argument that there is no teaching, suggestion, or motivation to combine the references, the examiner recognizes that obviousness may be established by combining or modifying the teachings of the prior art to produce the claimed invention where there is some teaching, suggestion, or motivation to do so found either in the references themselves or in the knowledge generally available to one of ordinary skill in the art. See In re Fine, 837 F.2d 1071, 5 USPQ2d 1596 (Fed. Cir. 1988), In re Jones, 958 F.2d 347, 21 USPQ2d 1941 (Fed. Cir. 1992), and KSR International Co. v. Teleflex, Inc., 550 U.S. 398, 82 USPQ2d 1385 (2007). In this case, the examiner has provided motivation from the secondary reference to support the motivation to make the proposed modifications.
While applicant may disagree the motivation set forth in the rejection, this does not negate fact that the examiner has provided a motivation to combine. The fact that the inventor has recognized another advantage which would flow naturally from following the suggestion of the prior art cannot be the basis for patentability when the differences would otherwise be obvious. See Ex parte Obiaya, 227 USPQ 58, 60 (Bd. Pat. App. & Inter. 1985).
Conclusion
Pertinent prior art:
De La Torre (US 20170277857 A1)
Hu et al (US 20180082025 A1)
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/Rachel L. Porter/Primary Examiner, Art Unit 3684