DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Election/Restrictions
Claims 21, 23, 24, and 53 are withdrawn from further consideration pursuant to 37 CFR 1.142(b), as being drawn to a nonelected Species B, C, E-G, and H, there being no allowable generic or linking claim.
The Applicant elected Species A, D, and I, directed to Claims 1-20, 22, 25, and 52 in the reply filed on 26 January 2026. The Applicant timely traversed the restriction requirement, wherein the traversal was on the grounds that there would be no burden. The Examiner disagrees with these arguments. Each of distinct Species A-C, Species D-G, and Species H-I are directed to different embodiments, with different modes of operation of the method with different outcomes, which would require different search strategies. Furthermore, Prior Art applicable to one Species would likely not be applicable to the other Species due to the distinct subject matter.
Therefore, Claims 1-20, 22, 25, and 52 are presently under consideration in this application. The Examiner will consider the possibility of rejoinder of non-elected Claims 21, 23, 24, and 53 if/when allowable subject matter has been indicated.
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 1-20, 22, 25, and 52 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Following is a summary of the subject matter eligibility analysis:
Step 1:
Claims 1-20, 22, 25, and 52 are directed to a method (process). Thus, they are directed to one of the four statutory categories of invention.
Step 2A, prong 1:
Claim 1 recites a method of post-operative risk mitigation in a patient with an implanted VAD comprising:
receiving a plurality of features
inputting at least some of the features into a multistate model
generating with the multistate model a daily prediction of a likelihood of the patient developing at least one of the conditions corresponding to a plurality of states
outputting on a user interface an indicator of the likelihood of the patient developing the at least one of the conditions in the predetermined time period so as to manage post-operative risk from VAD implantation
These limitations, under their broadest reasonable interpretations, recite performing mathematical calculations (processing and mathematically analyzing the data) and forming mathematical relationships (a relationship/correlation for prediction of a likelihood of the patient developing at least one of the conditions corresponding to a plurality of states using a model), and as such, the claims recite limitations which may also fall within the 'mathematical concepts' grouping of abstract ideas. See MPEP 2106.4(a)(2). ‘‘[A] scientific truth, or the mathematical expression of it, is not patentable invention[.]’’ See, e.g., Benson, 409 U.S. at 65, 175 USPQ2d at 674; Flook, 437 U.S. at 589, 198 USPQ2d at 197; Mackay Radio & Telegraph Co. v. Radio Corp. of Am., 306 U.S. 86, 94, 40 USPQ 199, 202 (1939).
Furthermore, the performed method as drafted in Claim 1, under the broadest reasonable interpretation, is merely a mental process than can be performed by a person mentally and/or using a pen and paper, because these are steps are akin to having a doctor or other human actor performing a diagnosis based on data and mathematically evaluating sensed/input data, and then providing output (e.g. drawing, calculating, diagnosing, etc.) based on the data. Therefore, these steps may be performed mentally by a human actor and implemented by drawing objects/graphs/output or performing calculations based on the evaluation mentally or by hand using a pen and paper, such as a doctor performing a diagnosis based on analyzing data of the patient of the implanted VAD. 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. Therefore, if claim limitations, under their broadest reasonable interpretation covers the performance of the limitations within the human mind or by a human using a pen and paper, then it falls within “mental processes” grouping of abstract ideas. See MPEP 2106.04(a)(2)(III).
Claims 2-20, 22, 25, and 52 depend from Claim 1, and merely recite additional processing and analyzing steps, and therefore are also considered to cover concepts that are performing mathematical calculations and forming mathematical relationships, and may be considered mental processes as defined in MPEP 2106.04(a) and MPEP 2106.04(b).
Step 2A, prong 2:
The judicial exception is not integrated into a practical application.
These elements merely use generic computer components to evaluate sensed signals/input data. It is noted that no direct therapy or treatment initiation is explicitly claimed, particularly in independent Claim 1.
Recording data sensed from a mammal is a well-known and conventional technique that uses some type of generic sensors to record data from a mammal. This analysis includes merely acquiring a signal/data from a patient using a generic sensor component and is considered an insignificant pre-solution activity of gathering data for use in a claimed process (see MPEP 2106.05(g)). This pre-solution activity of data gathering and then performing calculations/analyses is well-known and typical in the field of medical sensing and computing technology.
Additionally, processing with a machine learning model is considered as a well-known technique in the field, with neural networks being trained to process information and identify/classify certain traits being a concept used to process received data and other physiological signals. Further, this limitation comprises processing the data to estimate a health index and/or prediction of patient outcome. This limitation amount to mere instructions to apply an exception (MPEP 2106.05(f)), wherein the exception is a natural phenomena where a correlation between data analysis diagnosis exists and a neural network/machine modeling is simply added as a computer function/trained set of instructions to “apply”/find the exception. As found in MPEP 2106.05(f), “the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words “apply it”.”
Furthermore, outputting an alert or diagnosis (e.g. Claims 1, 16, 18) is a well-known and typical limitation. In the medical field, the ability to present data to a clinician on a GUI is a well established activity. Therefore, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Dependent Claims 10 and 11 recite, “generating a control signal affecting an operating parameter of the VAD” and “wherein the operating attribute of the VAD comprises at least one of: a pump pulsatility index; a pump power; and a pump speed” respectively, and Claim 17 recites “generating a modified treatment regime based on the change in the one of the at least one trendline”. However, these limitations are considered generic treatment and are therefore considered that the method is not integrated into a practical application. Treatment and/or prophylaxis must be specific, and the claim limitation in question must affirmatively recite an action that effects a particular treatment or prophylaxis for a disease or medical condition. The application or use of the judicial exception in this manner meaningfully limits the claim by going beyond generally linking the use of the judicial exception to a particular technological environment, and thus transforms a claim into patent-eligible subject matter. See MPEP 2106.04(d)(2).
Claims 2-9, 12-16, 18-20, 22, 25, and 52 depend from Claim 1, and merely recite additional processing and analyzing steps/details, and therefore are also considered to not be integrated into a practical application for the same reasons as Claim 1.
By the above reasoning, none of the above amount to integrating the mathematical concepts or mental processes into practical application.
Step 2B :
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
As discussed with respect to Step 2A - Prong Two, the additional elements in the claim amount to no more than insignificant extra solution activity and mere instructions to apply the exception using generic computer/processing components and sensors. The same analysis applies here in 2B and does not provide an inventive concept. The data gathering of Claim 1 amounts to no more than mere pre-solution activity of data processing, and this pre-solution activity of processing data using known sensors is well-understood, routine, and conventional in the field of computing and medical technology.
Furthermore, the only structural elements provided in the claims relate to computer modeling/analyzing. These are well-understood, routine, and conventional systems in the field of computing and medical technology. For example, see Liu et al. (US Publication No. 2019/0192753), described in detail below. Although the claims also recite “a ventricular assist device (VAD)”, this is also a pre-solution activity component which only provides the data for the method steps, since implantation/manipulation of the VAD is not explicitly recited in the claims.
Further, dependent Claims 2-20, 22, 25, and 52 are rejected on the same grounds as Claim 1. These dependent claims do not add significantly more to the judicial exceptions and merely recite additional analysis/mathematical steps. Therefore, the evaluations steps of Claims 1-20, 22, 25, and 52 do not recite any additional structural elements or limitations on practical applications (e.g. specific treatment). Although dependent Claims 10 and 11 recite, “generating a control signal affecting an operating parameter of the VAD” and “wherein the operating attribute of the VAD comprises at least one of: a pump pulsatility index; a pump power; and a pump speed” respectively, and Claim 17 recites “generating a modified treatment regime based on the change in the one of the at least one trendline”. However, these limitations are considered generic treatment and are therefore considered that the method is not integrated into a practical application. Treatment and/or prophylaxis must be specific, and the claim limitation in question must affirmatively recite an action that effects a particular treatment or prophylaxis for a disease or medical condition. The application or use of the judicial exception in this manner meaningfully limits the claim by going beyond generally linking the use of the judicial exception to a particular technological environment, and thus transforms a claim into patent-eligible subject matter. See MPEP 2106.04(d)(2).
Thus, the claims are not patent eligible.
Therefore, Claims 1-20, 22, 25, and 52 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. It is recommended by the Examiner that explicit tangible output or treatment/therapy steps based on the analysis, or explicit non-generic structure, be added to independent Claim 1 in order to overcome the rejections under 35 USC 101. It is noted that any amendment must be fully supported by the Specification/Drawings as originally filed.
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.
Claims 1-5, 10-20, 22, and 25 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Liu et al. (US Publication No. 2019/0192753).
Regarding Claim 1, Liu et al. discloses a method of post-operative risk mitigation in a patient with an implanted Ventricular Assist Device (ventricular assist device/LVAD, Paragraph 0006, 0007; predictive modeling to forecast patient outcome over time, see Fig. 15; Claim 1, Paragraph 0004, 0053), the method comprising:
receiving a plurality of features, each of the features relating to an attribute associated with the patient having received the implanted VAD (acquiring data from sensors, Paragraph 0024, 0027, e.g. pressure, Paragraph 0011, lactate concentration, Paragraph 0014, cardiac power output, Paragraph 0027, 0099-0101);
inputting at least some of the features into a multistate model (predictive modeling with machine learning, Paragraph 0019, 0055, 0029; see features of Fig. 9), the multistate model comprising a plurality of states each of the states corresponding to a condition of the patient (Paragraph 0019, 0024, 0048-0049; different patient states, Paragraph 0053, 0057, 0063, 0069 (e.g., death/survival; decline in health, ICU necessity, 0021, 0051, 0073, 0091));
generating with the multistate model a daily prediction of a likelihood of the patient developing at least one of the conditions corresponding to the plurality of states in a predetermined time period (predictive modeling of patient states/outcomes over time periods based on input data to the model, Paragraph 0019, 0027, 0028, 0031; daily time periods, Paragraph 0012, 0021, 0028);
and outputting on a user interface an indicator of the likelihood of the patient developing the at least one of the conditions in the predetermined time period so as to manage post- operative risk from VAD implantation (alert/alarms or graphical displays of health status for post-operative risk management or time periods, Paragraph 0012, 0021, 0053, 0059, 0062).
Regarding Claim 2, Liu et al. discloses the method further wherein generating with the multistate model the daily prediction of the likelihood of the patient developing at least one of the conditions corresponding to the plurality of states in the predetermined time period (predictive modeling of patient states/outcomes over time periods based on input data to the model, Paragraph 0019, 0027, 0028, 0031; daily time periods, Paragraph 0012, 0021, 0028) comprises generating with the multistate model the daily prediction of the likelihood of the patient developing a first set of conditions corresponding to a first set of states (Paragraph 0019, 0024, 0048-0049; different patient states, Paragraph 0053, 0057, 0063, 0069 (e.g., death/survival; decline in health, ICU necessity, 0021, 0051, 0073, 0091)); and wherein outputting the indicator of the likelihood of the patient developing the at least one of the conditions in the predetermined time period comprises outputting the indicator (alert/alarms or graphical displays of health status for post-operative risk management, Paragraph 0021, 0053, 0059, 0062) of the likelihood of the patient developing a second set of conditions corresponding to a second set of states in the predetermined time period (Paragraph 0019, 0024, 0048-0049; multiple different patient states, Paragraph 0053, 0057, 0063, 0069 (e.g., death/survival; decline in health, health index, ICU necessity, 0021, 0051, 0073, 0091)).
Regarding Claims 3 and 4, Liu et al. discloses the method further wherein the first set of conditions corresponding to the first set of states is greater or less than the second set of conditions corresponding to the second set of states (multiple different patient states, Paragraph 0053, 0057, 0063, 0069 (e.g., death/survival; decline in health, health index, ICU necessity, 0021, 0051, 0073, 0091), each of which may be greater than or less than other condition states depending on model data/input).
Regarding Claim 5, Liu et al. discloses the method further wherein the multistate model generates the daily prediction for conditions corresponding to a greater number of states than are output via the indicator of the user interface (multiple different patient states, Paragraph 0053, 0057, 0063, 0069; output clinically relevant data (e.g. ‘score’), alert/alarms or graphical displays of health status for post-operative risk management, Paragraph 0021, 0053, 0059, 0062).
Regarding Claim 10, Liu et al. discloses the method further comprising generating a control signal affecting an operating attribute of the VAD (changing operation parameters, Paragraph 0109; Claim 16, 17).
Regarding Claim 11, Liu et al. discloses the method further wherein the operating attribute of the VAD comprises at least one of: a pump pulsatility index; a pump power; and a pump speed (pump parameters, Paragraph 0018, 0026, 0109).
Regarding Claim 12, Liu et al. discloses the method further wherein the daily prediction is generated each day for a plurality of days (daily time periods, Paragraph 0012, 0021, 0028, 0030).
Regarding Claim 13, Liu et al. discloses the method further comprising outputting, with the user interface: at least one trendline based on an aggregate of generated daily predictions (graphical displays of health status trendlines by day, Paragraph 0021, 0053, 0059, 0062; see Figs. 4-7).
Regarding Claim 14, Liu et al. discloses the method further wherein the at least one trendline comprises one trendline associated with one of the at least one of the conditions corresponding to one of the plurality of states (multiple different patient states and trends, Paragraph 0053, 0057, 0063, 0069; alert/alarms or graphical displays of health status trends for post-operative risk management, Paragraph 0021, 0053, 0059, 0062).
Regarding Claim 15, Liu et al. discloses the method further wherein the one trendline indicates a change in risk with respect to time for the one of the at least one of the conditions corresponding to one of the plurality of states associated with the one trendline (multiple different patient states and trends, Paragraph 0053, 0057, 0063, 0069; alert/alarms or graphical displays of health status trends for post-operative risk management, Paragraph 0021, 0053, 0059, 0062).
Regarding Claim 16, Liu et al. discloses the method further comprising determining a change in one of the at least one trendline, the change indicating an increased risk; and generating an alert based on the change in the one of the at least one trendline (multiple different patient states and trends, Paragraph 0053, 0057, 0063, 0069; alert/alarms or graphical displays of health status trends for post-operative risk management based on changes in trends over time and detecting changes, Paragraph 0021, 0053, 0059, 0062).
Regarding Claim 17, Liu et al. discloses the method further comprising generating a modified treatment regime based on the change in the one of the at least one trendline (modifying treatment/pump parameters based on changes in trends, Paragraph 0030, 0073, 0098; Claims 16-19).
Regarding Claim 18, Liu et al. discloses the method further comprising determining a change in one of the at least one trendline, the change indicating a decreased risk (modifying treatment/pump parameters based on changes in trends, including increase/decrease in risk, Paragraph 0030, 0073, 0098; Claims 16-19); and generating an alert based on the change in the trendline (alert/alarms or graphical displays of health status trends for post-operative risk management, Paragraph 0021, 0053, 0059, 0062).
Regarding Claim 19, Liu et al. discloses the method further comprising determining that at least some of the received plurality of features are aged (non-trustable data, Paragraph 0063); and generating replacement features for at least some of the aged plurality of features (replacement data, Paragraph 063); and wherein the features inputted into the multistate model include the replacement features and non-aged features (replacement of non-trustable/bad data inputs with new data, Paragraph 0063).
Regarding Claim 20, Liu et al. discloses the method further wherein generating replacement features comprises: selecting a replacement model for generating the replacement features; and generating replacement features with the replacement model (replacement of non-trustable/bad data inputs with new data, Paragraph 0063).
Regarding Claim 22, Liu et al. discloses the method further wherein the replacement model selects a most recent value for use as replacement data (replacement of non-trustable/bad data inputs with most recent data, Paragraph 0063).
Regarding Clam 25, Liu et al. discloses the method further wherein the multistate model utilizes logistic regression to estimate transition probability (logistic regression, Paragraph 0055, 0056; Claim 11).
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 6-9 are rejected under 35 U.S.C. 103 as being unpatentable over Liu et al. (US Publication No. 2019/0192753) in view of Hettrick et al. (US Publication No. 2020/0405244).
Regarding Claims 6-9, Liu et al. discloses the method further wherein the plurality of features comprise at least a post-implantation feature indicative of a post-operative condition of the patient (acquiring data from sensors, Paragraph 0024, 0027, e.g. pressure, Paragraph 0011, lactate concentration, Paragraph 0014, cardiac power output, Paragraph 0027, 0099-0101), wherein the post-implantation feature is time-varying and identifies an operating attribute of the VAD including at least one of pump pulsatility index; a pump power; and a pump speed (Paragraph 0018, 0026, 0109). Liu et al. does not explicitly disclose wherein the plurality of features comprise at least a baseline feature indicating a pre-operative condition of the patient and an implantation feature indicating a condition of the patient during implantation of the VAD.
Hettrick et al. teaches a method of determining a health status of a patient with an implanted a cardiac medical device (Abstract, Paragraph 0009-0012), comprising receiving a plurality of features, each of the features relating to an attribute associated with the patient having received the cardiac medical device (sensed data to analyze health status, Paragraph 0006-0008, 0072), wherein the plurality of features comprise at least a baseline feature indicating a pre-operative condition of the patient (baseline features, Paragraph 0039, 0041, 0042) and an implantation feature indicating a condition of the patient during implantation of the cardiac medical device (e.g. during clinician visit/monitoring period, Paragraph 0010, 0012, 0014, 0042), and using a multistate model a daily prediction of a likelihood of the patient developing at least one condition (machine learning algorithms, Paragraph 0070, 0072, 0120), and adjusting parameters of an implanted cardiac medical device such as a VAD using the prediction (modifying parameter values, Paragraph 0012).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to configure the plurality of features to comprise at least a baseline feature indicating a pre-operative condition of the patient and an implantation feature indicating a condition of the patient during implantation, as taught by Hettrick et al., in the method disclosed by Liu et al., in order to provide predictive analyses in comparison to a known baseline during acute phases of the implantation/usage of the cardiac medical device, such that treatment and/or cardiac medical device operation parameters may be adjusted to improve patient outcome (see Hettrick et al., Paragraph 0012).
Claim 52 is rejected under 35 U.S.C. 103 as being unpatentable over Liu et al. (US Publication No. 2019/0192753) in view of Mainsah et al. (US Publication No. 2021/0370045).
Regarding Claim 52, Liu et al. discloses the method further including receiving a plurality of features, each of the features relating to an attribute associated with the patient having received the implanted VAD (acquiring data from sensors, Paragraph 0024, 0027, e.g. pressure, Paragraph 0011, lactate concentration, Paragraph 0014, cardiac power output, Paragraph 0027, 0099-0101); and inputting at least some of the features into a multistate model (predictive modeling with machine learning, Paragraph 0019, 0055, 0029; see features of Fig. 9), the multistate model comprising a plurality of states, wherein each of the states corresponding to a condition of the patient (Paragraph 0019, 0024, 0048-0049; different patient states, Paragraph 0053, 0057, 0063, 0069 (e.g., death/survival; decline in health, ICU necessity, 0021, 0051, 0073, 0091)). However, Liu et al. does not explicitly disclose wherein the plurality of states includes gastrointestinal bleeding.
Mainsah et al. teaches a method of determining a health status of a patient with an implanted VAD (Paragraph 0005-0007) using a multistate model comprising a plurality of states (Paragraph 0070), wherein the plurality of states includes gastrointestinal bleeding (Paragraph 0030), and predicting patient outcome based on the multistate model (Paragraph 0070).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include gastrointestinal bleeding as one of the plurality of states as taught by Mainsah et al., in the method disclosed by Liu et al., since gastrointestinal bleeding is a known common complication of implanted VADs (see Mainsah et al., Paragraph 0030) that may be adjusted for based on predictive algorithms, such as to improve patient outcome/health.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PAMELA M BAYS whose telephone number is (571)270-7852. The examiner can normally be reached 10:00am - 6:00pm EST.
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/PAMELA M. BAYS/Primary Examiner, Art Unit 3796
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