DETAILED ACTION
Status of Claims
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This action is in reply to an application filed 15 December 2023, which is a national stage entry of an application with an international filing date of 16 June 2022, which claims domestic priority to a provisional application filed 16 June 2021.
Claims 1-35 were originally filed.
Claims 1, 3, 9 and 14 have been amended by preliminary amendment.
Claims 4, 7, 8, 10-13, 15, 21-23, 28 and 33-35 have been canceled.
Claims 1-3, 5, 6, 9, 14, 16-20, 24-27 and 29-32 are currently pending and have been examined.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 3 June 2024 and 5 March 2024 have been considered by the Office to the extent indicated.
Drawings
New corrected drawings in compliance with 37 CFR 1.121(d) are required in this application because the drawings contain lines of insufficient weight, text of insufficient size and/or shading that make the drawings illegible, see Figs. 3A-32. Applicant is advised to employ the services of a competent patent draftsperson outside the Office, as the U.S. Patent and Trademark Office no longer prepares new drawings. The corrected drawings are required in reply to the Office action to avoid abandonment of the application. The requirement for corrected drawings will not be held in abeyance.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), first paragraph:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-3, 5, 6, 9, 14, 16-20, 24-27, 29, 30 and 32 are rejected under 35 U.S.C. 112, first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claims 1 and 32 recite the steps of applying a trajectory model to the processed patient data to identify a likelihood of an adverse outcome of the patient. The patent application does not provide an adequate formula or algorithm explaining how the model is applied to identity a likelihood of an adverse outcome. For example, the specification, in paragraph [01110] states that the system can compute a score based on the likelihood. The specification does not, however, disclose an adequate formula or algorithm for applying a trajectory model to the processed patient data to identify a likelihood of an adverse outcome of the patient. Therefore, one skilled in the art of healthcare intervention, upon reading the specification, would not conclude that the inventor had possession of the claimed inventions on the day the application was filed.
To the extent that other claims rely on claims that are rejected under 35 USC 112 and fail to correct the deficiencies of the claims they rely on, those other claims are rejected for the same reasons as the claims they rely on. Appropriate correction is required.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claims 1-3, 5, 6, 9, 14, 16-20, 24-27 and 29-32 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), as being indefinite for failing to particularly point out and distinctly claim the subject matter which applicant regards as the invention.
Regarding claims 1, 25, 31 and 32, the phrase "such that" renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
To the extent that other claims rely on claims that are rejected under 35 USC 112 and fail to correct the deficiencies of the claims they rely on, those other claims are rejected for the same reasons as the claims they rely on. Appropriate correction is required.
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 1-3, 5, 6, 9, 14, 16-20, 24-27 and 29-32 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.
Step 1
Claims 1-3, 5, 6, 9, 14, 16-20, 24-27 and 29-32 are within the four statutory categories. Claims 1-3, 5, 6, 9, 14, 16-20, 24-27, 29 and 31 are drawn to a method, which is within the four statutory categories (i.e. process). Claim 32 is drawn to a system for predicting a patient medical event, which is within the four statutory categories (i.e. machine).
Prong 1 of Step 2A
Claim 1 recites: A method comprising:
obtaining, by one or more processors, patient data, wherein the patient data includes clinical laboratory results of a patient with a disease state;
processing, by the one or more processors, the patient data such that the clinical laboratory results are normalized by patient-specific baseline levels or cohort-specific baseline levels of the clinical laboratory results; and
applying, by the one or more processors, a trajectory model to the processed patient data to identify a likelihood of an adverse outcome of the patient, in which the trajectory model characterizes the disease state by a recovery trajectory in a phase-plane of one or more variables and is configured to:
compare the processed patient data to the recovery trajectory; and
output, based on the comparing, the likelihood of the adverse outcome of the patient.
Claim 31 recites: A method comprising:
obtaining, by one or more processors, training patient data, wherein the training patient data includes clinical laboratory results of a plurality of patients with one or more disease states;
processing, by the one or more processors, the training patient data such that the clinical laboratory results of the plurality of patients are normalized by patient- specific or cohort-specific baseline levels;
identifying, by the one or more processors, one or more variables to be used in a phase plane; and
fitting a trajectory model, by the one or more processors and using the one or more variables, to the plurality of training patient data, in which the trajectory model characterizes the one or more disease states by a recovery trajectory in the phase plane.
The underlined limitations as shown above, given the broadest reasonable interpretation, cover the abstract ideas of “mathematical concepts” and/or the abstract idea of a mental process and/or a certain method of organizing human activity because they recite a process that could be practically performed in the human mind (i.e. observations, evaluations, judgments, and/or opinions – in this case, the steps of using normalized patient data to apply to a trajectory model to characterize a patient disease state) or using a pen and paper, but for the recitation of generic computer components (i.e. the structural components of the computer) see MPEP 2106.04(a)(2). Any limitations not identified above as part of the abstract idea(s) are deemed “additional elements,” and will be discussed in further detail below.
Furthermore, the abstract idea for claims 1 and 32 are identical as the abstract idea for claims 1, because the only difference between claims 1 and 32 is that claim 1 recites a method, whereas claim 32 recites a system.
Dependent claims 2, 3, 5, 6, 9, 14, 16-20, 24-27 and 29 include other limitations, for example claims 2 and 3 provide details on treatment recommendations, claims 5, 6, 19, 26 and 29 provide further details on various data results and variables, claims 14, 16-18, 24 and 30 provides details on the trajectory model and recovery tractor, claim 20 describes imputing data and claim 25 is directed to training data, but these only serve to further narrow the abstract idea, and a claim may not preempt abstract ideas, even if the judicial exception is narrow, e.g. see MPEP 2106.04. Additionally, any limitations in dependent claims 2, 3, 5, 6, 9, 14, 16-20, 24-27 and 29 not addressed above are deemed additional elements to the abstract idea, and will be further addressed below. Hence dependent claims 2, 3, 5, 6, 9, 14, 16-20, 24-27 and 29 are nonetheless directed towards fundamentally the same abstract idea as independent claims 1.
Prong 2 of Step 2A
Claims 1, 31 and 32 are not integrated into a practical application because the additional elements (i.e. any limitations that are not identified as part of the abstract idea) amount to no more than limitations which:
amount to mere instructions to apply an exception – for example, the recitation of the structural components of the computer, which amounts to merely invoking a computer as a tool to perform the abstract idea, e.g. see paragraph 123 of the present Specification, see MPEP 2106.05(f); and/or
generally link the abstract idea to a particular technological environment or field of use – for example, the claim language limiting the data to healthcare data, which amounts to limiting the abstract idea to the field of healthcare, see MPEP 2106.05(h); and/or
adding insignificant extrasolution activity to the abstract idea, for example mere data gathering, selecting a particular data source or type of data to be manipulated, and/or insignificant application (e.g. see MPEP 2106.05(g)).
Additionally, dependent claims 2, 3, 5, 6, 9, 14, 16-20, 24-27 and 29 include other limitations, but these limitations also amount to generally linking the abstract idea to a particular technological environment or field of use (e.g. the types of data disclosed in dependent claims 2, 3, 5, 6, 9, 14, 16-20, 24-27 and 29), and/or do not include any additional elements beyond those already recited in independent claim 1, and hence also do not integrate the aforementioned abstract idea into a practical application.
Step 2B
Claims 1, 31 and 32 do not include additional elements that are sufficient to amount to “significantly more” than the judicial exception because the additional elements (i.e. the non-underlined limitations above – in this case, the dispensing device and the one or more processors), as stated above, are directed towards no more than limitations that amount to mere instructions to apply the exception, generally link the abstract idea to a particular technological environment or field of use, and/or add insignificant extra-solution activity to the abstract idea, wherein the insignificant extra-solution activity comprises limitations which:
amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, as demonstrated by:
The Specification expressly disclosing that the additional elements are well-understood, routine, and conventional in nature:
Paragraph 123 of the Specification discloses that the additional elements (i.e. the structural components of the computer) comprise a plurality of different types of generic computing systems that are configured to perform generic computer functions (i.e. receive and process data) that are well-understood, routine, and conventional activities previously known to the pertinent industry (i.e. healthcare);
Relevant court decisions: The following are examples of court decisions demonstrating well-understood, routine and conventional activities, e.g. see MPEP 2106.05(d)(II):
i. 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));
ii. 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.");
iii. Electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225, 110 USPQ2d 1984 (2014) (creating and maintaining "shadow accounts"); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log); and
iv. 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.
Dependent claims 2, 3, 5, 6, 9, 14, 16-20, 24-27 and 29 include other limitations, but none of these limitations are deemed significantly more than the abstract idea because, as stated above, the aforementioned dependent claims do not recite any additional elements not already recited in independent claim 1, and/or the additional elements recited in the aforementioned dependent claims similarly amount to generally linking the abstract idea to a particular technological environment or field of use (e.g. the types of data disclosed in dependent claims 2, 3, 5, 6, 9, 14, 16-20, 24-27 and 29), and hence do not amount to “significantly more” than the abstract idea.
Thus, taken alone, the additional elements do not amount to significantly more than the abstract idea identified above. Furthermore, looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually, and there is no indication that the combination of elements improves the functioning of a computer or improves any other technology, and their collective functions merely provide conventional computer implementation.
Therefore, whether taken individually or as an ordered combination, claims 1-3, 5, 6, 9, 14, 16-20, 24-27 and 29-32 are nonetheless rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
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 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 of this title, 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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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.
Claims 1-3, 5, 6, 9, 14, 19, 31 and 32 are rejected under 35 U.S.C. 103 as being obvious over Clark et al. (WIPO Pub 2021/034770 A1), hereinafter Clark, further in view of Kurtz et al. (U.S. PG-Pub 2022/0392605 A1), hereinafter Kurtz.
As per claims 1, 6 and 32, Clark discloses a method and a system comprising:
one or more processors and one or more storage devices storing instructions that are operable, when executed by the one or more processors, to cause the one or more processors to perform operations (Clark discloses use of computer structure, see paragraph 696.) comprising:
obtaining, by one or more processors, patient data, wherein the patient data includes clinical laboratory results of a patient with a disease state (Clark, patient data processed to obtain a model representing temporal measures among neuromelanin concentration in a subject, see paragraph 112.);
processing, by the one or more processors, the patient data such that the clinical laboratory results are normalized by patient-specific baseline levels or cohort- specific baseline levels of the clinical laboratory results (Study subject scans of patients are normalized, paragraph 173.); and
applying, by the one or more processors, a trajectory model to the processed patient data to identify a likelihood of an adverse outcome of the patient (Clark, generalized linear mixed-effects model was used to predict neuromelanin tissue concentration, see paragraph 184.),
in which the trajectory model characterizes the disease state by a recovery trajectory in a phase-plane of one or more variables (Baseline MRI would predict LDOPA-induced improvements, Clark paragraph 602.) and is configured to:
compare the processed patient data to the recovery trajectory (Increase in neuromelanin volume compared to a control is proportional to the improvement and/or efficacy of Parkinson’s disease progression and or treatment, see Clark paragraph 121.); and
output, based on the comparing, the likelihood of adverse outcome of the patient (Parkinson’s disease predicted, see Clark, paragraphs 92, 143, 146, 283.).
Clark fails to explicitly disclose:
a likelihood of adverse outcome of the patient; and
6. wherein the disease state comprises an acute inflammatory response.
Kurtz teaches that it was old and well known in the art of healthcare communications before the effective filing date of the claimed invention to provide a likelihood of adverse outcome of the patient and wherein the disease state comprises an acute inflammatory response (Kurtz, Abstract, paragraphs 104, 105, 112, 127, 154-159 and 167.) in order to provide “diagnostics and treatments based upon updated probabilities of an individual's clinical outcome” (Kurtz, paragraph 3.).
Therefore, it would have been obvious to one of ordinary skill in the art of healthcare communications before the effective filing date of the claimed invention to modify the healthcare modeling method of Clark to include providing a likelihood of adverse outcome of the patient and wherein the disease state comprises an acute inflammatory response, as taught by Kurtz, in order to arrive at a healthcare modeling method that provides “diagnostics and treatments based upon updated probabilities of an individual's clinical outcome” (Kurtz, paragraph 3.).
Both Clark and Kurtz are directed to the electronic processing of patient healthcare data and specifically to the diagnosis and treatment based thereon. Moreover, merely adding a well-known element into a well-known system, to produce a predictable result to one of ordinary skill in the art, does not render the invention patentably distinct over such combination (see MPEP 2141).
As per claim 31, the majority of the limitations presented in claim 31 are present in claim 1. Therefore, claim 31 is rejected over Clark in view of Kurtz for at least the same reasons as claim 1, with the same motivation. Clark also discloses the following remaining limitations of Claim 31:
identifying, by the one or more processors, one or more variables to be used in a phase plane (Increase in neuromelanin volume compared to a control is proportional to the improvement and/or efficacy of Parkinson’s disease progression and or treatment, see Clark paragraph 121.); and
fitting a trajectory model, by the one or more processors and using the one or more variables (Increase in neuromelanin volume compared to a control is proportional to the improvement and/or efficacy of Parkinson’s disease progression and or treatment, see Clark paragraph 121.).
As per claims 2, 3, 5, 9, 14 and 19, Clark/Kurtz discloses claim 1, discussed above. Clark also discloses:
2. providing, by the one or more processors and based on the likelihood of adverse outcome of the patient, information indicative of a recommended treatment (Clark discloses a guide for selection of treatment, see paragraph 627.);
3. wherein the recommended treatment comprises a recommendation to continue a current treatment regimen or to modify the current treatment regimen (Clark, paragraph 45.);
5. wherein the clinical laboratory results are indicative of at least one of a blood count, a metabolic panel measurement, or a vital sign measurement (Clark, paragraph 499.);
9. wherein the one or more variables are selected from the group consistent of: a white blood cell count, a white blood cell count and a platelet count, a white blood cell count and a blood urea nitrogen level, and a white blood cell count and a red blood cell distribution width (Clark considers white blood cell measurements, see paragraphs 85 and 445.);
14. wherein the trajectory model is predictive of the adverse outcome, and wherein the adverse outcome comprises at least one outcome selected from the group consisting of: a complication and mortality (Increase in neuromelanin volume compared to a control is proportional to the improvement and/or efficacy of Parkinson’s disease progression and or treatment, see Clark paragraph 121.);
19. identifying, for the patient, the patient-specific or the cohort-specific baseline levels of the clinical laboratory results (Clarke discloses comparing baseline measurements in a specific patient of either symptom-specific or disease-specific voxels, or neuromelanin concentrations, or neuromelanin volumes of specific regions against future measurements of these value s in the same patient, see paragraph 141.), wherein the baseline levels of the clinical laboratory results represent levels of the one or more variables before the patient is diagnosed with the disease state (Patient is determined to have Parkinson’s when the total amount of neuromelanin on serial scans has decreased to less then about 30% of patient’s baseline neuromelanin, see paragraph 225.).
Claim 16 is rejected under 35 U.S.C. 103 as being obvious over Clark/Kurtz et al. (WIPO Pub 2021/034770 A1) further in view of Zhang, JinFei, et al. "Platelet‐to‐white blood cell ratio: a novel and promising prognostic marker for HBV‐associated decompensated cirrhosis." Journal of Clinical Laboratory Analysis 34.12 (2020): e23556, hereinafter Zhang.
As per claim 16, Clark/Kurtz discloses claim 1, discussed above. Clark fails to explicitly disclose but Kurtz teaches that it was old and well known in the art of healthcare communications before the effective filing date of the claimed invention to provide wherein the recovery trajectory comprises an exponential decay of white blood cell count and a linear increase in platelet count (Zhang discloses model for end stage liver disease score and platelet to white blood cell ratio for predicting 30 day mortality in patient, see page 4, Fig. 2.).
Therefore, it would have been obvious to one of ordinary skill in the art of healthcare communications before the effective filing date of the claimed invention to modify the modeling method of Clark/Kurtz to include wherein the recovery trajectory comprises an exponential decay of white blood cell count and a linear increase in platelet count, as taught by Zhang, in order to arrive at a healthcare modeling method that models 30 day mortality in patients (Zhang, page 4, Fig. 2.). Both Clark and Zhang are directed to the processing of patient healthcare data and specifically to the diagnosis and treatment based thereon. Moreover, merely adding a well-known element into a well-known system, to produce a predictable result to one of ordinary skill in the art, does not render the invention patentably distinct over such combination (see MPEP 2141).
Claim 17 is rejected under 35 U.S.C. 103 as being obvious over Clark/Kurtz further in view of Fahey, Marion, et al. "Development and validation of clinical prediction models for mortality, functional outcome and cognitive impairment after stroke: a study protocol." BMJ open 7.8 (2017): e014607, hereinafter Fahey.
As per claim 17, Clark/Kurtz discloses claim 1, discussed above. Clark also discloses wherein comparing the processed patient data to the recovery trajectory as shown above. Clark fails to explicitly disclose but Fahey teaches that it was old and well known in the art of healthcare communications before the effective filing date of the claimed invention to provide identifying positions of the processed patient data relative to the recovery trajectory in the phase plane (Subgroup analysis used to assess deviations from predicted recovery trajectories, see Fahey, page 3, right column, middle paragraph.); and determining a degree to which the positions of the processed patient data deviate from the recovery trajectory at any given time point and over serial time points (Assess deviations of predicted curves, Fahey page 2, left column, bottom paragraph.).
Therefore, it would have been obvious to one of ordinary skill in the art of healthcare communications before the effective filing date of the claimed invention to modify the modeling method of Clark/Kurtz to include imputing, based on the second patient data, missing values in the clinical laboratory results of the patient and wherein the trajectory model further outputs a likelihood of a full and healthy recovery of the patient, as taught by Fahey, in order to arrive at a healthcare modeling method that to generate a scoring system that classifies risks (Fahey, page 2, left column, bottom paragraph.).
Both Clark and Fahey are directed to the processing of patient healthcare data and specifically to the diagnosis and treatment based thereon. Moreover, merely adding a well-known element into a well-known system, to produce a predictable result to one of ordinary skill in the art, does not render the invention patentably distinct over such combination (see MPEP 2141).
Claims 20 and 24 are rejected under 35 U.S.C. 103 as being obvious over Clark/Kurtz further in view of Mori, Makoto, et al. "Protocol for project recovery after cardiac surgery: a single-center cohort study leveraging digital platform to characterise longitudinal patient-reported postoperative recovery patterns." BMJ open 10.9 (2020): e036959, hereinafter Mori.
As per claims 20 and 24, Clark/Kurtz discloses claim 1, discussed above. Clark also discloses:
20. obtaining second patient data of a plurality of patients (Patient data from multiple studies, paragraph 591), wherein the plurality of patients does not include the patient (Patient data compared to second non-patient population, see Clark, paragraph 223.), and the plurality of patients and the patient share patient attributes (Multiple studies using same attributes, see paragraph 591.).
Clark fails to explicitly disclose but Mori teaches that it was old and well known in the art of healthcare communications before the effective filing date of the claimed invention to provide
20. imputing, based on the second patient data, missing values in the clinical laboratory results of the patient (Imputing missing data, see Mori, page 6, left column, bottom paragraph.); and
24. wherein the trajectory model further outputs a likelihood of a full and healthy recovery of the patient (Recovery scale, page 3, right column, top paragraph).
Therefore, it would have been obvious to one of ordinary skill in the art of healthcare communications before the effective filing date of the claimed invention to modify the modeling method of Clark/Kurtz to include imputing, based on the second patient data, missing values in the clinical laboratory results of the patient and wherein the trajectory model further outputs a likelihood of a full and healthy recovery of the patient, as taught by Mori, in order to arrive at a healthcare modeling method that fills missing data and provides more relevant outputs.
Both Clark and Mori are directed to the processing of patient healthcare data and specifically to the diagnosis and treatment based thereon. Moreover, merely adding a well-known element into a well-known system, to produce a predictable result to one of ordinary skill in the art, does not render the invention patentably distinct over such combination (see MPEP 2141).
Claim 18 is rejected under 35 U.S.C. 103 as being obvious over Clark/Kurtz/Zhang further in view of Mori.
As per claim 18, Clark/Kurtz/Fahey discloses claim 17, discussed above. Clark fails to explicitly disclose but Mori teaches that it was old and well known in the art of healthcare communications before the effective filing date of the claimed invention to provide wherein determining the degree to which the positions of the processed patient data deviate from the recovery trajectory comprises computing a direction or angle between the positions of the processed patient data and the recovery trajectory in the phase-plane (Mori discloses sensitivity analysis to compare trajectories, page 6, left column, bottom paragraph.).
Therefore, it would have been obvious to one of ordinary skill in the art of healthcare communications before the effective filing date of the claimed invention to modify the modeling method of Clark/Kurtz to include computing a direction angle, as taught by Mori, in order to arrive at a healthcare modeling method that fills missing data and provides more relevant outputs. Moreover, merely adding a well-known element into a well-known system, to produce a predictable result to one of ordinary skill in the art, does not render the invention patentably distinct over such combination (see MPEP 2141).
Claims 25 and 26 are rejected under 35 U.S.C. 103 as being obvious over Clark/Kurtz further in view of Visweswaran, Shyam, and Gregory F. Cooper. "Patient-specific models for predicting the outcomes of patients with community acquired pneumonia." AMIA Annual Symposium Proceedings. Vol. 2005. 2005.
As per claims 25 and 26, Clark/Kurtz discloses claim 1, discussed above. Clark also discloses:
26. wherein the clinical laboratory results comprise measurements of at least one parameter selected from the group consisting of: anion gap, blood-urea nitrogen, creatinine, hematocrit, glucose, platelet count, red cell distribution width, and white blood cell count (Clark considers white blood cell measurements, see paragraphs 85 and 445.).
Clark fails to explicitly disclose but Visweswaran teaches that it was old and well known in the art of healthcare communications before the effective filing date of the claimed invention to provide:
25. obtaining training patient data, wherein the training patient data includes clinical laboratory results of a plurality of patients with one or more disease states (Visweswaran discloses trained the models on a set of 1601 patient cases; page abstract, see variables page 2, left column.); processing the training patient data such that the clinical laboratory results of the plurality of patients are normalized by the patient-specific or cohort-specific baseline levels (Visweswaran discloses Bayesian patient specific model, page 2, right column.); identifying the one or more variables to be used in the phase plane; and fitting the trajectory model, using the one or more variables, to the plurality of training patient data (Visweswaran discloses variables, see page 2 let column middle paragraph, and fitting the model thereon.).
Therefore, it would have been obvious to one of ordinary skill in the art of healthcare communications before the effective filing date of the claimed invention to modify the modeling method of Clark/Kurtz to include obtaining training data to normalize patient baseline levels and fitting the model based on identified variables, as taught by Visweswaran, in order to arrive at a healthcare modeling method that benefits of using patient-specific models for making clinical predictions.
Both Clark and Visweswaran are directed to the processing of patient healthcare data and specifically to the diagnosis and treatment based thereon. Moreover, merely adding a well-known element into a well-known system, to produce a predictable result to one of ordinary skill in the art, does not render the invention patentably distinct over such combination (see MPEP 2141).
Claims 27 and 29 are rejected under 35 U.S.C. 103 as being obvious over Clark/Kurtz/ Visweswaran in view of Alashwal, Hany, et al. "The application of unsupervised clustering methods to Alzheimer’s disease." Frontiers in computational neuroscience 13 (2019): 31, hereinafter Alashwal, further in view of Ultsch, Alfred, and Jörn Lötsch. "Machine-learned cluster identification in high-dimensional data." Journal of biomedical informatics 66 (2017): 95-104, hereinafter Ultsch.
As per claims 27 and 29, Clark/Kurtz/Visweswaran discloses claim 25, discussed above.
Clark also discloses:
29. for a different set of the one or more variables: computing a significance of a generalized linear model predicting the adverse outcome (Clark discloses a generalized linear model using data across all grid sections and specimens, paragraph 184, used to predict an adverse outcome, paragraph 283.).
Clark fails to explicitly disclose but Alashwal teaches that it was old and well known in the art of healthcare communications before the effective filing date of the claimed invention to provide:
27. wherein identifying the one or more variables comprises: identifying, by applying unsupervised clustering to the plurality of training patient data, high-dimensional clusters (Alashwal uses unsupervised clustering to the patient data, page 3, left column, middle paragraph.); reducing dimensionality of the high-dimensional clusters; and identifying the one or more variables that are significantly associated with the one or more disease states (Merge identified pair after removing clusters from distance matrix until reduced, page 5, left column, middle paragraph.).
29. wherein identifying the one or more variables that are significantly associated with the one or more disease states (Alashwal, clusters linked to targe tvariable, page 7, right column, top paragraph.) comprises: … using the one or more variables in the plurality of training patient data; and determining that the significance meets a threshold (Examine patient subgroup with variable trajectories using extrapyramidal burden cluster had greater patients diagnosed with dementia, page 3, left column, bottom paragraph.)
Therefore, it would have been obvious to one of ordinary skill in the art of healthcare communications before the effective filing date of the claimed invention to modify the modeling method of Clark/Kurtz/Visweswaran to include processing of disease states, as taught by Alashwal, in order to arrive at a healthcare modeling method that fills provides further unbiased results.
Neither Clark nor Alashwal disclose wherein the clusters are associated with the one or more disease states. Ultsch teaches that it was old and well known in the art of healthcare communications before the effective filing date of the claimed invention to provide wherein the clusters are associated with the one or more disease states (Ultsch, page 95, Abstract.)
Therefore, it would have been obvious to one of ordinary skill in the art of healthcare communications before the effective filing date of the claimed invention to modify the modeling method of Clark/Kurtz/Visweswaran/Alashwal to include wherein the clusters are associated with the one or more disease states, as taught by Ultsch, in order to arrive at a healthcare modeling method that fills provides more relevant outputs.
Clark, Alashwal and Ultsh are directed to the processing of patient healthcare data and specifically to the diagnosis and treatment based thereon. Moreover, merely adding a well-known element into a well-known system, to produce a predictable result to one of ordinary skill in the art, does not render the invention patentably distinct over such combination (see MPEP 2141).
Claim 30 is rejected under 35 U.S.C. 103 as being obvious over Clark/Kurtz/Visweswaran further in view of Santimone, Iolanda, et al. "White blood cell count, sex and age are major determinants of heterogeneity of platelet indices in an adult general population: results from the MOLI-SANI project." haematologica 96.8 (2011): 1180, hereinafter Santimone.
As per claim 30, Clark/Kurtz/Visweswaran discloses claim 25, discussed above. Clark fails to explicitly disclose but Santimone teaches that it was old and well known in the art of healthcare communications before the effective filing date of the claimed invention to provide wherein fitting the trajectory model comprises: fitting an exponential decay of white blood cell count using the plurality of training data; and fitting a linear increase in platelet count using the plurality of training data (Various parameters are negatively correlated with white blood cell count, see page 1182, right column, middle paragraph.)
Therefore, it would have been obvious to one of ordinary skill in the art of healthcare communications before the effective filing date of the claimed invention to modify the modeling method of Clark/Kurtz/Visweswaran to include wherein fitting the trajectory model comprises: fitting an exponential decay of white blood cell count using the plurality of training data; and fitting a linear increase in platelet count using the plurality of training data, as taught by Santimone, in order to arrive at a healthcare modeling method that benefit of underlining the relation between platelets and inflammation (Santimone, page 1180, Abstract.).
Both Clark and Santimone are directed to the processing of patient healthcare data and specifically to the diagnosis and treatment based thereon. Moreover, merely adding a well-known element into a well-known system, to produce a predictable result to one of ordinary skill in the art, does not render the invention patentably distinct over such combination (see MPEP 2141).
Conclusion
The following uncited references are relevant to the current claims:
Jain et al. (U.S. PG-Pub 2024/0395419 A1), hereinafter Jain.
Any inquiry of a general nature or relating to the status of this application or concerning this communication or earlier communications from the Examiner should be directed to Mark Holcomb, whose telephone number is 571.270.1382. The Examiner can normally be reached on Monday-Friday (8-5). If attempts to reach the Examiner by telephone are unsuccessful, the Examiner’s supervisor, Kambiz Abdi, can be reached at 571.272.6702.
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/MARK HOLCOMB/
Primary Examiner, Art Unit 3685
19 December 2025