Status of the Claims
The status of the claims as of the response filed 11/13/2025 is as follows:
Claims 1,3-5, 9 and 11-13 are pending.
Claims 2, 6, 7, 8, 10, 14, 15, 16, and 17 are canceled.
The applicant has amended Claims 1, 3, 4, 5, 9, 11, 12, and 13 are amended and have
been considered below.
Request for Continued Examination
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 11/13/2025 has been entered.
Response to Arguments
35 U.S.C. § 101 Subject Matter Eligibility
Applicant's arguments, see page 8-14, filed 11/13/2025, with respect to amended Claims [1, 3-5, 9, 11-13] are amended. Claims 2, 6-8, 10, 14-17 are cancelled. The arguments have been fully considered and are not persuasive.
The applicant argues that the claims are integrated into a practical application because they solve a specific technological problem in medical monitoring through a "multi-modal, real-time data processing architecture" that improves clinical decision-making, analogous to the eligible claims in DDR Holdings and McRO.
The Examiner respectfully disagrees because the claimed "multi-modal architecture" relies on generic, off-the-shelf components (sensors, processors) to perform the abstract idea, rather than improving the computer's own functionality. Per MPEP § 2106.05(a), an improvement must be to the functioning of the computer or technical field, not merely an improvement to the abstract idea itself (i.e., better data analysis or faster mental calculations). The specification confirms the hardware is "generic" (Spec., para. [0039]) and "commercially sourced" (Spec., para. [0132]), and the claimed "processing" uses standard mathematical algorithms. Unlike McRO, where specific rules automated a task previously impossible for computers, here the computer is simply automating a mental diagnostic process using standard data collection, which does not constitute a technical improvement sufficient to integrate the exception.
The applicant argues that the system effects a "particular prophylaxis and clinical intervention" by generating alerts that lead to early intervention, thereby satisfying the "treatment/prophylaxis" integration criteria seen in Vanda Pharmaceuticals.
The Examiner respectfully disagrees because Claim 1 does not recite a positive step of applying a specific treatment or prophylaxis to the patient, but rather concludes with "generates and displays prioritized clinical alerts... that assists in clinical decision-making." Per MPEP § 2106.04(d)(2), to integrate an abstract idea via treatment, the claim must affirmatively recite the administration of a specific drug or a specific step of medical treatment. Providing data that "enables" a clinician to potentially act is distinct from the claim requiring that action; thus, the claim remains directed to the abstract concept of gathering and analyzing data (information gathering), which is not a practical application of treatment.
The applicant argues that the claims recite "significantly more" than the abstract idea because the specific combination of weighted scoring, dynamic prioritization, and bi-directional communication constitutes a non-conventional computational process.
The Examiner respectfully disagrees because the elements cited as "non-conventional" (weighted scoring, prioritization logic) are the abstract ideas themselves (Mathematical Concepts and Mental Processes). Per MPEP § 2106.05, an inventive concept must reside in the additional elements relative to the abstract idea. Once the abstract mathematical logic is removed, the remaining elements are generic computer components and sensors used for their standard function of collecting and processing data (Spec., para. [0068]). Merely automating the abstract idea using these generic components, even if the logic is complex, does not provide an inventive concept significantly more than the exception itself.
The applicant argues that converting raw sensor data into a digital biomarker score constitutes a "transformation" of a physical article into a different state.
Examiner respectfully disagrees because the Applicant incorrectly interprets the legal definition of "transformation." Per MPEP 2106.05(c), a "transformation" requires a physical change to a physical object or substance; it explicitly states that the mere manipulation of data or mathematical constructs such as converting sensor readings into a score does not constitute a transformation of an article. Data, whether "raw" or a "score," is intangible information, and processing it is considered an abstract idea, not a physical transformation. Therefore, the claim fails to satisfy the machine-or-transformation test or integrate the abstract idea into a practical application on this basis.
The applicant argues that the combination of sensors and processing elements in the claim amounts to a "particular machine" rather than a generic computer.
Examiner respectfully disagrees because the components recited (sensors, processor) are used merely as tools to perform the abstract idea of calculating the biomarker score. According to MPEP 2106.05(b), to qualify as a "particular machine," the machine must be integral to the claim or effectively a "special purpose computer" that improves technology; simply adding generic data-gathering components to a mathematical process does not limit the claim meaningfully. The elements are performing generic computer functions (collecting and analyzing data) which does not amount to "significantly more" than the abstract idea itself.
The applicant argues the claims are patent-eligible because they are similar to USPTO Subject Matter Eligibility Example 42.
Examiner respectfully disagrees because the comparison to Example 42 is factually distinguishable. Example 42 describes a specific technical improvement to the functioning of a computer network (changing how digital packets are transmitted to improve security/efficiency), whereas the current claims are directed to the gathering and analysis of information (calculating a health score). As detailed in MPEP 2106.05(a), an improvement in the abstract idea itself (e.g., a better mathematical model for a score) is not an improvement to computer functionality; thus, the analogy to Example 42 fails.
35 U.S.C. § 103 Obviousness
Applicant's arguments, see page 15-24, filed [11/13/2025], with respect to amended Claims 1, 3-5, 9, 11-13 are amended. Claims 2, 6-8, 10, 14-17 are cancelled. The arguments have been fully considered and are not persuasive.
The applicant argues that Tran teaches away from the claimed invention because it is limited to molecular-level analysis (genomic sequencing) and does not disclose "real-time" determination of deviations in "digital biomarkers" derived from "wearable sensors" like heart rate or bioimpedance.
The Examiner respectfully disagrees because the applicant's characterization of Tran as being limited to genomic sequencing is factually incorrect when the reference is considered as a whole. Tran explicitly discloses a "patient monitoring system" par. 0552, describing "wearable patient monitoring appliances such as wrist-watches" par. 0555, that include sensors for "ECG, EKG, blood pressure... [and] accelerometer" (Tran, para. [0556]). Furthermore, Tran describes using these sensors for "continuous, beat-to-beat... measurements" (Tran, para. [0556]) and processing this data to flag "potentially dangerous conditions" based on deviations from established ranges (Tran, para. [0556]). These disclosures directly teach the "real-time determination of deviations" in physiological data (digital biomarkers) from wearable sensors as claimed. Therefore, the limitation is disclosed by Tran.
The applicant argues that Tran does not teach the specific "system-generated score" calculated using a weighting model that integrates three distinct data types: (a) physiological deviation, (b) manual patient input (fluid/food), and (c) cognitive test results.
The Examiner respectfully disagrees because Tran expressly discloses an "aggregated score" par. 0294, or "composite" score derived from multiple input types, including physiological metrics, "medication use," and "mental well-being" (Tran, para. [0290], [0436]). Specifically, Tran teaches:
Physiological Data: Monitoring vital signs like BP and ECG (Tran, para. [0556]).
Manual Input: A user interface for entering "food intake... [and] symptoms" (Tran, para. [0448], [0504]).
Mental Function: Detecting "emotional health" and "mental acuity" via sensor/phone usage patterns (Tran, para. [0436], [0397]). Tran further teaches assigning "greater or less weight" to these metrics to generate a score that triggers alerts (Tran, para. [0290], [0292]). Thus, the structural and functional elements of the claimed multi-modal weighting model are present in the primary reference.
The applicant argues that combining Tran (genomics/IoT) and Smith (imaging-based liver staging) relies on impermissible hindsight because there is no motivation to combine disparate technical fields to achieve a wearable cirrhosis monitoring system.
The Examiner respectfully disagrees because the combination is based on the predictable use of known elements for their primary function, not hindsight. Tran provides a versatile platform for remote patient monitoring and disease management (Tran, para. [0003]), while Smith identifies a specific clinical need: the early detection of cirrhosis decompensation (ascites, hepatic encephalopathy) (Smith, para. [0003], [0083]). A Person Having Ordinary Skill in the Art (PHOSITA) would be motivated to utilize Tran's "continuous, real-time" monitoring capabilities (Tran, para. [0063]) to solve the problem of "difficult to diagnose" decompensation identified by Smith (Smith, para. [0008]). Integrating the disease-specific risk factors of Smith (ascites, HE) into the general monitoring architecture of Tran is a simple substitution of one set of health parameters for another to enhance patient care, which is a predictable result under KSR v. Teleflex. The 35 U.S.C 103 rejection clearly delineates this rationale, citing Smith for the specific "cirrhosis decompensation" limitation that is plugged into Tran's "decision support system" (Tran, para. [0372]).
Respond to Amendments
35 U.S.C. § 112 Written Description
Applicant's arguments, see page 8, filed 11/13/2025, with respect to amended Claims 1, 3-5, 9, 11-13 are amended. Claims 2, 6-8, 10, 14-17 are cancelled. The arguments have been fully considered and are persuasive.
The applicant argues that the amended claims overcome the written description rejection because the features of "patient specific digital biomarkers," "deviations," and risk scoring find support in the original specification.
The Examiner agrees that the amendments and the specification provide sufficient written description support for the claimed subject matter. Therefore, the 35 U.S.C. § 112(a) rejection is withdrawn.
Statutory Category of Claim 11
Applicant's arguments, see page 8, filed 11/13/2025, with respect to amended Claim 11 are fully considered and are persuasive regarding the statutory category.
The applicant argues that Claim 11 has been amended from a "computer program product" to a "computer implemented method for…, thereby overcoming the rejection that the claim was directed to non-statutory.
The Examiner agrees that the amendment to Claim 11 overcomes the rejection regarding statutory category (Step 1 of the eligibility analysis). Therefore, the rejection based on the claim being "software per se" is withdrawn.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 11-13 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 12-13 recites the element "the processor". There is insufficient antecedent basis for this limitation in the claim.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Subject Matter eligibility Rejection 35 U.S.C 101
Claims 1,3-5, 9 and 11-13 are rejected under 35 U.S.C. § 101 because the claimed subject matter is directed to a judicial exception (an abstract idea) without reciting elements that integrate the exception into a practical application or provide an inventive concept amounting to significantly more than the exception itself.
Step 1: Statutory Categories Analysis
The claims are directed to statutory subject matter, encompassing the following statutory categories:
Machine (Claims 1, 3-5, 9): The language reciting a "computer-implemented medical monitoring system" comprising a "processor," "memory," and "sensor or wearable devices" describes a concrete thing consisting of hardware parts, aligning with the definition of a machine in MPEP § 2106.03.
Process (Claims 11-13): The language reciting "A computer implemented method for…" defines a series of acts or steps, aligning with the definition of a process in MPEP § 2106.03.
Having confirmed the claims are directed to statutory subject matter, the analysis proceeds to Step 2A Prong One.
Step 2A, Prong One: Judicial Exception Analysis
Step 2A, Prong One determines whether the claims recite a judicial exception (MPEP § 2106.04).
The whole invention is related to "a system for assessing decompensated cirrhosis" which operates by "collecting first patient data... receive a manual input of second patient data... and process the said patient data to detect signs" (Spec., para. [0022]-[0024]).
More specifically, the claims 1, 3-5, 9, and 11-13 are directed to a judicial exception because they recite Mental Processes (evaluating patient deviations), Mathematical Concepts (computing scores), and Certain Methods of Organizing Human Activity (prioritizing alerts). Under Broadest Reasonable Interpretation (BRI), the claims describe collecting medical data, performing calculations on that data, and presenting the results to a clinician to assist in their decision-making.
Independent Claims Recites the following non-bold abstract parts:
Claim 1.
A computer-implemented medical monitoring system configured for real-time determination of a plurality of deviations in patient data from patient-specific digital biomarkers values and prioritization of the plurality of deviations based on a system generated score to assist a clinician for early detection of cirrhosis decompensation in a cirrhosis patient, wherein the system comprises:
a processor;
and a memory storing instructions executable by the processor, wherein the processor that acquires, in real-time, first patient data associated with the cirrhosis patient from one or more sensor or wearable devices selected from the group comprising temperature, a heart rate, a heart-rate-variability, a blood pressure, an electrocardiogram, a physical activity, a sleep status, a weight, a body fluid composition, a bioimpedance, or a combination thereof, and;
receives second patient data associated with the cirrhosis patient, via an user interface of a patient device, wherein said second patient data comprises at least one of fluid intake, perceived well-being, symptoms, food intake by the cirrhosis patient;
executes, at least one higher mental function test, on the user interface of the patient device, to generate third patient data related to hepatic encephalopathy assessment of the cirrhosis patient;
determines, for each digital biomarker, a plurality of deviations in the first patient data from the patient-specific digital biomarkers values derived from previously stored digital biomarkers values associated with the cirrhosis patient;
computes, for each deviation, a system-generated score using a weighting model stored in a processing database, wherein the system-generated score is determined based on (a) variation of a current biomarker value from the patient specific digital biomarker values weighted by clinical relevance, (b) the second patient data, and (c) the third patient data;
prioritizes the plurality of deviations based on the system generated score to identify deviations indicative of potential cirrhosis decompensation;
generates and displays prioritized clinical alerts, on a practitioner device, that assists in clinical decision-making for early detection of cirrhosis decompensation, by to a predefined risk threshold indicative of cirrhosis decompensation, wherein the clinical alert comprises an interpretation of the deviation and its corresponding risk;
Note: The bolded portions represent additional elements evaluated in Prong Two and Step 2B. The non-bolded portions represent the abstract idea. Referenced applicant language comes from public application number.
Claim Abstract Classification Rational
Under their Broadest Reasonable Interpretation (MPEP § 2111), the independent claims 1 and 11 abstract idea recite collecting medical data, calculating a risk score, and evaluating that score to alert a doctor. This process aligns with the following abstract idea categories:
Mental Process (MPEP § 2106.04(a)(2)(III)): The independent claims recite "determines... a plurality of deviations," "prioritizes the plurality of deviations," and "assists in clinical decision-making". Under BRI, these terms require observing inputs, evaluating thresholds, and forming a judgment about the data's relevance. This parallels cognitive steps performed by a doctor evaluating test results. The specification confirms this assistance to human cognition: "The management system assists the clinician in the interpretation of the remotely acquired signs" (Spec., para. [0040]). This sentence directly supports the claim limitations as reflecting an assistance to human mental work, rather than a technical improvement.
Mathematical Concepts (MPEP § 2106.04(a)(2)(I)): The independent claims recite "computes, for each deviation, a system-generated score using a weighting model". Under BRI, the "computes" and "weighting model" language clearly describes an algebraic calculation, which falls under the definition of a mathematical calculation. The specification elaborates on this abstract idea: "The platform S1 (or practitioner application module) process the data with CirrhoCare's algorithms [unique combination of (a) standard deviation... (b) weightage... and (c) patient inputted data ]" (Spec., para. [0083-0084]). This supports that the core invention resides in a specific formula or algorithm, which is an abstract idea.
Certain Method of Organizing Human Activity (MPEP § 2106.04(a)(2)(II)): The independent claims 1 and 11 recite "to assist a clinician for early detection" and "generates and displays prioritized clinical alerts". This describes a managed workflow of interaction, which falls under the sub-category of Managing Personal Behavior or Relationships. The claim organizes the interaction between patient data collection and the clinician's diagnostic workflow by prioritizing information for review. The specification supports this, stating: "The clinical user dashboard D connects to the patient application A preferably via the platform S1 interface" (Spec., para. [0098]). This establishes the claimed limitations as defining the organizational rules for patient-to-clinician interaction.
Manual Replication Scenario (Human Equivalence)
The abstract nature of the claims is reinforced because the nature of the steps—determining deviations, computing scores, and prioritizing—corresponds to fundamental mental and mathematical activities. While the claim recites "real-time" and "digital biomarkers," the underlying steps are concepts that can be performed in the human mind or with pen and paper. The computer merely automates this mental process to add speed, but utilizing a computer to perform an abstract idea more quickly does not render the claim eligible. The core logic remains an abstract calculation and evaluation, regardless of the automation.
Dependent Claims Analysis
The dependent claims 3, 4, 5, 9, and 12-13 are also directed to an abstract idea.
Claims 3: These claims recite under BRI "processing the first patient data with the processing algorithms based on a combination of (a) standard deviation... and (b) weightage...," which is a Mathematical Concept. This merely specifies the exact type of mathematical and statistical calculations used, narrowing the abstract idea rather than adding a non-abstract element.
Claims 4 and 5 and 12-13: These claims recite under BRI "enables communication between the cirrhosis patient and a practitioner" and "provides, to a practitioner, alerts... that require a response from the practitioner to modify or adjust a patient's management plan" which is a Certain Method of Organizing Human Activity. This describes the outcome of an organizational scheme and the delivery of information to a human professional.
Claim 9: These claims recite under BRI "one or more wearable or sensor devices comprise a smart watch and/or a blood pressure device". These claims specify the tools used to gather the input data for the abstract mental and mathematical processes defined in the independent claim, inheriting the abstract idea.
The claims recite judicial exceptions, requiring further analysis under Step 2A, Prong Two.
Step 2A, Prong Two: Integration into a Practical Application
Step 2A, Prong Two evaluates whether the claim as a whole integrates the recited judicial exception into a practical application (MPEP § 2106.04(d)). The claims' additional elements do not overcome Prong Two because they merely implement the abstract mental processes and mathematical calculations on generic computer components and sensors without effecting a technical improvement or specific treatment.
Evaluation of Independent Claim 1 Additional Elements
The independent claims 1 and 11 fail to integrate the abstract idea because the additional elements, when analyzed by group, do not provide a practical application:
Generic Computer Components:
The "processor," "memory," "user interface," "processing database," and "practitioner device" are invoked merely as tools to automate the abstract mental and mathematical steps. Per MPEP § 2106.05(f), these are mere instructions to implement the abstract idea on a computer. The specification confirms these are generic "computerized unit[s]" (Spec., para. [0073, 0077, 0048, 0132]) running a "smartphone application" (Spec., para. [0073, 0095, 0044]), demonstrating no technical improvement to computer functionality under MPEP § 2106.05(a). Limiting their use to a "medical monitoring system" for a "cirrhosis patient" is a mere field-of-use limitation under MPEP § 2106.05(h).
Data Gathering Hardware:
The "sensor or wearable devices" are used solely for data acquisition, per MPEP § 2106.05(a), the specification admits these are "generic" devices (Spec., para. [0068]) with no technical improvements. Their inclusion merely links the abstract idea to the technological environment of medical sensing, which is insufficient for integration under MPEP § 2106.05(h).
Combination Analysis: When viewed as a whole, the combination of these elements does not integrate the abstract idea. The claim describes a generic arrangement performing the abstract analysis (data collection -> calculation -> alert), which does not transform the abstract idea into an eligible application but rather uses standard technology to automate the mental process of a clinician.
Dependent Claims Analysis
The dependent claims (Claims 3, 4, 5, 9, 12, 13) recite additional elements that generally relate to specific algorithms, communication features, or particular types of monitoring devices (e.g., smart watches, blood pressure devices). However, these additional elements merely introduce more generic devices or standard tools for their intended use. For instance, specifying a "smart watch" or "blood pressure device" only narrows the source of data to a particular type of commercially available hardware, which the specification itself identifies as "commercially sourced" (Spec., para. 0132) Consequently, these elements do not overcome prong two as they rely on standard, off-the-shelf technology.
When viewed as a whole, the combination of these elements in the dependent and independent claims does not integrate the abstract idea. The claims amount to using off-the-shelf medical sensors to gather data for a computer to analyze using mathematical statistics.
Because the claims are directed to an abstract idea without integrating it into a practical application, the analysis proceeds to Step 2B.
Step 2B: Inventive Concept Analysis
Step 2B determines whether the additional elements, individually or in an ordered combination, provide an inventive concept that amounts to "significantly more" than the judicial exception itself (MPEP § 2106.05). The additional elements in these claims do not overcome Step 2B because they represent mere instructions to implement the abstract idea on generic components, or insignificant extra-solution activity.
Evaluation of Independent Claims 1 and 11 Additional Elements
Generic Computer Components Elements: "processor," "memory," "user interface," "processing database," "practitioner device"
The claim relies on generic computing elements (processor, memory, devices) solely to automate the abstract idea of determining a weighted score and prioritizing alerts. Per MPEP § 2106.05(f), using generic computer components to execute an abstract idea amounts to nothing more than generic instructions to apply the exception. The specification reinforces this lack of specificity by identifying the application platform as running on a standard "computerized unit" (Spec., para. 0048)
Data Gathering Hardware Elements: "sensor or wearable devices,"
The data gathering hardware, including "sensor or wearable devices," is employed only for the preliminary step of gathering input data for the abstract calculation, making it insignificant extra-solution activity under MPEP § 2106.05(g). The specification confirms that these elements offer no technical solution beyond standard capability, admitting they are "generic" (Spec., para. 0068) and "commercially sourced" (Spec., para. 0132). Therefore, these elements do not contribute an inventive concept.
When viewed as a whole, the combination of these generic hardware elements performing routine data acquisition and basic computational automation of an abstract mental process does not transform the abstract idea into a patent-eligible invention, and therefore lacks an inventive concept.
Dependent Claims Analysis
The dependent claims (Claims 3, 4, 5, 9, 12, 13) recite additional elements that generally relate to specific algorithms, communication features, or particular types of monitoring devices (e.g., smart watches, blood pressure devices). However, these additional elements merely introduce more generic devices or standard tools for their intended use. For instance, specifying a "smart watch" or "blood pressure device" only narrows the source of data to a particular type of commercially available hardware, which the specification itself identifies as "commercially sourced" (Spec., para. 0132) Consequently, these elements do not add significantly more to the judicial exception as they rely on standard, off-the-shelf technology to perform routine functions.
The dependent claims merely narrow the abstract idea or recite insignificant extra-solution activity using generic technology. Viewed as a whole, the combination of these limitations fails to transform the abstract idea into patent-eligible subject matter.
The claims are directed to an abstract idea and lack an inventive concept. Therefore, Claims 1, 3-5, 9, and 11-13 are rejected under 35 U.S.C. § 101.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 3-5, and 9 and 11-13 are rejected under 35 U.S.C. § 103 as being unpatentable over US20200251213A1-Tran in combination with US20150148658A1-Smith.
Claim 1. Tran Teaches:
A computer-implemented medical monitoring system configured for real-time determination of a plurality of deviations in patient data from patient-specific digital biomarkers values and prioritization of the plurality of deviations based on a system generated score to assist a clinician for early detection of : a processor;
(Tran, paragraphs [0002-0003], [0054], [0185], [0295], [0320]-[0324],[0328], [0372], [397],[0340], [0486], [0512], [0289], [0303],[0549-0556])
Tran discloses a general-purpose medical monitoring system with a processor that functions as a decision support system (DSS) to alert a doctor. The system works by detecting a trend in patient data over time (determining deviations) and using a prediction scoring engine to assign a score for prioritizing actions.
Tran ties monitoring inputs to real-time data sources: EMRs “store real-time or near real-time patient… information, such as wearable, bedside, or in-home patient monitors” . Tran also discloses algorithms that analyze “data reported in real-time” and an automated analysis that is “capable of providing real-time feedback to patients and/or healthcare providers.”
and a memory storing instructions executable by the processor, wherein the processor that acquires, in real-time, first patient data associated with the cirrhosis patient from one or more sensor or wearable devices selected from the group comprising temperature, a heart rate, a heart-rate-variability, a blood pressure, an electrocardiogram, a physical activity, a sleep status, a weight, a body fluid composition, a bioimpedance, or a combination thereof, and; (Tran, paragraphs [0303], [0045], [0063], [0551-0552], [0556]).
Tran discloses a system with a processor and a memory to store computer instructions. The system performs continuous monitoring using wearable devices and portable physiological transducers for realtime feedback. The taught sensors explicitly include a heart rate monitor, weight scale, thermometer...single or multiple lead electrocardiograph (ECG)...a body fat monitor...an accelerometer coupled to the body to detect acceleration.
receives second patient data associated with the ; (Tran, paragraphs [0300-0301], [0395], [0397], [0475], [0504]).
Tran describes a system where a patient uses a user interface on a smart phone or PDA to manually enter data. This data explicitly includes food intake, symptoms, and perceived sensations (perceived well-being), and the system further includes a Medication compliance agent to monitor medication adherence and compliance.
executes, at least one higher mental function test, on the user interface of the patient device, to generate third patient data related to ; (Tran, paragraphs [0300-0302], [0057], [0166], [0397], [0436])
Tran's system performs a cognitive assessment by detecting emotional health and mental acuity through monitoring of a patient's everyday communications and sensor data on their smart phone. This constitutes a form of remote cognitive monitoring.
determines, for each digital biomarker, a plurality of deviations in the first patient data from the patient-specific digital biomarkers values derived from previously stored digital biomarkers values associated with the cirrhosis patient; (Tran, paragraphs [0181-0185], [0291-0292],[0288-0289], [0302], [0547-0549]).
Tran teaches using a patient profile “stored in a database” to set patient-specific “reference values”/“target value(s)” , and analyzing incoming reported metrics such that values that “fall outside of those limits” are treated as deviation-triggering conditions , where the analysis uses real-time data together with “historical patient data such as previously-reported… metrics” including a set “previously reported and stored for a patient” —i.e., deviations in first patient data relative to patient-specific values derived from previously stored patient data.
computes, for each deviation, a system-generated score using a weighting model stored in a processing database, wherein the system-generated score is determined based on (a) variation of a current biomarker value from the patient specific digital biomarker values weighted by clinical relevance, (b) the second patient data, and (c) the third patient data; (Tran, [0220], [0288]-[0290], [0292]-[0295], [0395]-[0398])
Tran teaches a system that “compares … metrics” to “target value(s)” and flags values “outside … limits,” then assigns per-metric “greater or less weight” (patient “needs”) and generates a “composite or aggregated score,” while analyzing real-time data using auxiliary data “stored in a … database,” and incorporating patient lifestyle/symptom context plus additional test/sensor streams (including “EEG” mental acuity and other lab/EHR/omic test data) to support clinical decisions
Tran teaches database-backed analysis where patient-specific “reference values/target value(s)” are used so current reported metrics can be compared and evaluated over time , metrics can be “weigh[ed]” (equal/greater/less) , and incoming data is processed in an “analysis database” and “given a score” , with clinical relevance reflected by relationships “defined based on the clinical relevance” , while patient-entered inputs like “food intake … symptoms … perceived sensations” are transferred to the analyzer and scoring can include “mental well-being … cognitive functioning
prioritizes the plurality of deviations based on the system generated score to identify deviations indicative of potential ; (Tran, [0290]–[0292], [0295], [0398])
Tran uses patient metrics and changes that “may indicate a serious issue requiring immediate medical attention,” generates a “composite or aggregated score,” and uses score/threshold logic (score “compare[d] … with a predetermined threshold”) to single out the most urgent deviations—i.e., score-based prioritization to identify potentially serious deterioration (not expressly cirrhosis-specific)
generates and displays prioritized clinical alerts, on a practitioner device, that assists in clinical decision-making for early detection ; (Tran, [0288], [0290], [0297], [0298], [0304], [0330], [0372], [0375-0376], [0398], [0444],[0453], [0487])
Tran teaches thresholds where metrics “outside … limits trigger an alert” sent to “a healthcare provider,” assigns scores and compares “each score with a predetermined threshold,” then transmits an alert/recommended action “for display” on an output device where “the other device may belong to a healthcare provider,” with urgent alerts “indicating … need of immediate medical treatment”—supporting prioritized provider alerts and decision support.
Obvious Rational:
Trans describe all limitations except for the following element:
cirrhosis decompensation in a cirrhosis patient, however, Smith teaches the missing element cirrhosis decompensation in a cirrhosis patient, describing that "cirrhosis is difficult to diagnose unless it has decompensated and lead to clinically detectable signs of portal hypertension such as ascites or symptomatic varices," that staging uses "Child-Pugh...MELD," and that an LSN-based algorithm can "determine... a predicted likelihood of future... development of ascites [and] development of hepatic encephalopathy." (Smith, paras. 0008- 0010, 0083; claims 33, 36.)
It would have been obvious to a person of ordinary skill in the art to combine the teachings of Tran with Smith because both references are directed to the same purpose of using remote data analysis to predict and manage disease progression. Tran discloses a versatile technological platform for recommending lifestyle modification to mitigate...disease risks and biomarks (Tran, para. 0003, 0057), while Smith addresses the specific clinical problem of diagnosing and staging liver fibrosis and/or cirrhosis (Smith, para. 0016-0017). A person of ordinary skill in the art developing Tran's general health monitoring system would have looked to specific clinical applications, such as the one described by Smith, to enhance the system's utility and commercial value. Because, Tran identifies liver-related biomarkers and proteins indicative of conditions like inflammation and insulin resistance, which overlap with cirrhosis risk factors in Smith, creating a logical connection for integrating liver-specific monitoring.
Furthermore, a person of ordinary skill in the art would have been motivated to integrate the cirrhosis specific diagnostic focus from Smith into the system of Tran to achieve the clear and articulated benefit of early, non-invasive detection of life-threatening complications. Smith teaches that its method is designed to screen for, diagnose, stage severity of, and evaluate response to therapy of liver fibrosis and/or cirrhosis in order to reduce or obviate the need for a liver biopsy (Smith, para. 0016, 0003). This provides a compelling reason to apply Tran's analytical engine to this specific clinical context.
Tran in combination with Smith teaches, Claim 3.
The computer-implemented medical monitoring system according
to claim 1, wherein the practitioner device processes the first patient data with the processing
algorithms based on a combination of (a) standard deviation of event specific digital
biomarkers values calculated over a period, (b) weightage of the event specific digital
biomarker and (c) the second patient data and the third patient data, to determine the cirrhosis
decompensation events including one or more of dehydration/acute kidney injury, new
accumulation of ascites, infection and/or hepatic encephalopathy. (Tran, paragraphs [0685], [0220], [0372], [0436], [0483], [0395]; Smith, paragraphs [Claim 3], [claim 36], [0059], [0073]).
The combination of prior art teaches a system where a practitioner device processes patient data using an algorithm that incorporates the claimed inputs to determine the claimed outputs. Smith explicitly teaches using the standard deviation of biomarker values (liver surface nodularity) to assess cirrhosis and to predict specific decompensation events, including ascites and hepatic encephalopathy. Tran teaches a general-purpose medical analysis system that uses a weighting model and aggregates all available data types-including manual inputs (second patient data) and mental state assessments (third patient data)-to predict disease risk.
Tran in combination with Smith teaches, Claim 4.
The computer-implemented medical monitoring system according
to claim 1, wherein the user interface of the patient device enables communication between
the cirrhosis patient and a practitioner and provides reminders relating to detected signs
related to decompensated cirrhosis, to the cirrhosis patient. (Tran, paragraphs [0300-0303], [0372], [0453]; Smith, paragraphs [0010], [0083], [0064)).
The combination of prior art teaches a system with a patient-facing user interface that facilitates both communication and automated reminders relevant to cirrhosis management. Tran discloses a user interface, smart phone that enables communication with patients and can automatically send messages using rule-based agents. Smith provides the specific clinical context, teaching a method for detecting signs related to cirrhosis decompensation, such as the predicted likelihood of...development of ascites, for] development of hepatic encephalopathy.
Tran in combination with Smith teaches, Claim 5.
The computer-implemented medical monitoring system according
to claim 1, wherein the practitioner device provides, to a practitioner, alerts relating to
detected signs related to decompensated cirrhosis and/or interpretations of patient data
implying signs related to decompensated cirrhosis that require a response from the
practitioner to modify or adjust a patient's management plan. (Tran, paragraphs [0300-0303], [0372], [0453]; Smith, paragraphs [0010], [0083], [0064]).
The combination of prior art teaches a system with a patient-facing user interface that facilitates both communication and automated reminders relevant to cirrhosis management. Tran discloses a user interface on a smart phone that enables communication with patients and can automatically send messages using rule-based agents. Smith provides the specific clinical context, teaching a method for detecting signs related to cirrhosis decompensation, such as the predicted likelihood of...development of ascites, [or] development of hepatic encephalopathy.
Tran in combination with Smith teaches, Claim 9.
The computer-implemented medical monitoring system according to claim 1, wherein the one or more wearable or sensor devices comprise a smart watch and/or a blood pressure device and/or bioimpedance smart scale and/or a thermometer. (Tran, paragraphs [0032-0033], [0072], [0551-0552]).
Tran explicitly discloses each of the devices recited in the Markush group as examples of sensors or wearable devices that can be integrated into its comprehensive remote patient monitoring system.
Note: Claims 11-13 are rejected with same analysis above of claims 1, 4 and 5.
Conclusion
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/JOSHUA DAMIAN RUIZ/Examiner, Art Unit 3684
/Shahid Merchant/Supervisory Patent Examiner, Art Unit 3684