Prosecution Insights
Last updated: August 18, 2026
Application No. 18/739,444

REAL-TIME INTRADIALYTIC HYPOTENSION PREDICTION

Final Rejection §101
Filed
Jun 11, 2024
Priority
Dec 20, 2019 — provisional 62/951,259 +1 more
Examiner
HOLCOMB, MARK
Art Unit
3685
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Fresenius SE & Co. KGaA
OA Round
2 (Final)
34%
Grant Probability
At Risk
3-4
OA Rounds
2y 2m
Est. Remaining
74%
With Interview

Examiner Intelligence

Grants only 34% of cases
34%
Career Allowance Rate
165 granted / 489 resolved
-18.3% vs TC avg
Strong +40% interview lift
Without
With
+40.5%
Interview Lift
resolved cases with interview
Typical timeline
4y 5m
Avg Prosecution
44 currently pending
Career history
537
Total Applications
across all art units

Statute-Specific Performance

§101
28.7%
-11.3% vs TC avg
§103
40.5%
+0.5% vs TC avg
§102
7.2%
-32.8% vs TC avg
§112
22.0%
-18.0% vs TC avg
Black line = Tech Center average estimate • Based on career data from 489 resolved cases

Office Action

§101
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 a response filed 22 May 2026, on an application filed 11 June 2024, which is a continuation of an application issued as U.S. Patent #12,040,092, which claims priority to a provisional application filed 20 December 2019. Claims 1, 5 and 9 have been amended. Claims 1-16 are currently pending and have been examined. Subject Matter Free of Prior Art The cited prior art of record fails to expressly teach or suggest, either alone or in combination, the features found within the independent claim. In particular, the cited prior art of record fails to expressly teach or suggest the combination of: predicting intradialytic hypotension (“IDH”) by training a machine learning model that determines the probability of a future IDH event by obtaining historical treatment data preceding IDH events and segmenting into multiple portions, wherein each portion is utilized differently and comprises different time event data and then applying real time hemodialysis data to the machine learning model. Information Disclosure Statement The information disclosure statements (IDS) submitted on 11 June 2024 has been considered by the Office to the extent indicated. Drawings The drawings were received on 22 May 2026. These drawings are accepted. Claim Rejections - 35 USC § 101 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1-16 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 1-16 are within the four statutory categories. Claims 1-4 and 15 are drawn to a non-transitory computer-readable media storing instructions that, when executed by one or more processors, predict one or more intradialytic hypotensive (IDH) events, which is within the four statutory categories (i.e. manufacture). Claims 5-8 and 16 are drawn to a system, which is within the four statutory categories (i.e. machine). Claims 9-14 are drawn to a method, which is within the four statutory categories (i.e. process). Prong 1 of Step 2A Claim 1 recites: One or more non-transitory computer-readable media storing instructions that, when executed by one or more processors, predict one or more intradialytic hypotensive (IDH) events by: using a machine learning model to determine the probability of a future IDH event occurring based on training of the machine learning model; and using the machine learning model to make a prediction that the future IDH event will occur in a preferred prediction time period based on the training of the machine learning model, the machine learning model being trained by: obtaining historical hemodialysis treatment data preceding one or more intradialytic hypotension (IDH) events, segmenting a first portion of the historical hemodialysis treatment data into a first set, the first portion of the historical hemodialysis treatment data being data corresponding to a first time period before the IDH events, segmenting a second portion of the historical hemodialysis treatment data into a second set, the second portion of the historical hemodialysis treatment data being data corresponding to a second time period before the IDH events and before the first time period, segmenting a third portion of the historical hemodialysis treatment data into a third set, the third portion of the historical hemodialysis treatment data being data corresponding to a third time period before the IDH events and after the first time period, and in a first stage, training the machine learning model to predict the occurrence of IDH events based on the first set, the machine learning model treating the first set as containing data indicative of a future IDH event occurring within the preferred prediction time period, and in a second stage, training the machine learning model to predict the occurrence of IDH events based on the second set, the machine learning model treating the second set as containing data not indicative of the future IDH event occurring within the preferred prediction time period; in a third stage, having the machine learning model disregard the third set such that the third set is neither indicative nor not indicative of a future IDH event occurring within the preferred prediction time period; and obtaining real-time hemodialysis data associated with a hemodialysis patient; and applying the real-time hemodialysis data to the machine learning model, to predict whether the probability of the future IDH event occurring within the preferred prediction time period is greater than a threshold probability for the hemodialysis patient. The underlined limitations as shown above, given the broadest reasonable interpretation, cover the abstract idea of a certain method of organizing human activity because they recite managing personal behavior or relationships or interactions between people (i.e. social activities, teaching, and following rules or instructions – in this case the step of training a model by segmenting data in order to predict the possibility of a future IDH event), e.g. 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 5 and 9 are identical as the abstract idea for claim 1, because the only difference between claims 1, 5 and 9 is that claim 1 recites a non-transitory computer-readable media, whereas claim 5 recites a system and claim 9 recites a non-transitory computer-readable media. Dependent claims 2-4, 6-8 and 10-16 include other limitations, for example claims 2, 6, 10 and 13-16 provide further details on the prediction timeline, 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 2-4, 6-8 and 10-16 not addressed above are deemed additional elements to the abstract idea, and will be further addressed below. Hence dependent claims 2-4, 6-8 and 10-16 are nonetheless directed towards fundamentally the same abstract idea as independent claims 1, 5 and 9. Prong 2 of Step 2A Claims 1-16 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 paragraphs 74-82 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 hemodialysis treatment data and intradialytic hypotension events, 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 2-4, 6-8 and 10-16 include other limitations, but these limitations also amount to no more than mere instructions to apply the exception (e.g. the treatment adjustments of claims 3, 4, 7, 8, 11 and 12), and/or do not include any additional elements beyond those already recited in independent claims 1, 5 and 9, and hence also do not integrate the aforementioned abstract idea into a practical application. Step 2B Claims 1-16 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 structural components of the computer), 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: paragraphs [0059]-[0064] and [0066] 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): 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."); 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 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 2-4, 6-8 and 10-16 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 claims 1, 5 and 9, and/or the additional elements recited in the aforementioned dependent claims similarly amount to mere instructions to apply the exception (e.g. the treatment adjustments of claims 3, 4, 7, 8, 11 and 12), 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 1-16 are nonetheless rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter. Response to Arguments Applicant’s arguments filed 22 May 2026 concerning the rejection of all claims under 35 U.S.C. 103(a) have been fully considered and are persuasive in view of the amendments to the claims. Accordingly, the prior art rejection has been removed. Applicant’s arguments filed 22 May 2026 concerning the rejection of all claims under 35 U.S.C. 101 have been fully considered but they are not persuasive. With regard to the rejection of the claims under 35 USC 101, Applicant argues on pages 9-10 that the claims comprise statutory material because: A. Example 39 of the PEG2019 materials indicate that training AI comprises statutory subject matter; and B. the claims are not directed to an abstract idea; nor a method of organizing human activity as no humans are recited in the claims. The Office respectfully disagrees. Please see the statutory rejection, issued above, wherein the claims are shown to be directed to an abstract idea without significantly more. Regarding A., Example 39 indicates that claims comprising training a neural network for facial detection can comprise statutory material when there is no abstract idea in the claims. This is dissimilar to the present claimset, which recites a process that would be performed manually by a provider in order to learn how to predict IDH events. Regarding B., multip9le CAFC decisions that the Office has characterized as Certain Method of Organizing Human Activity did not actively recite a person or persons performing the steps of the claims (see, e.g., EPG, TLI communications, Ultramercial). Because whether a human is required to perform the step of the claim is not a requirement for claims to encompass certain method of organizing human activity, this argument is not persuasive. Accordingly, the rejection is upheld. Conclusion Unused but cited relevant prior art includes: Hatib et al. (U.S. PG-Pub 2021/0035023 A1) discloses a predictive risk model optimization system configured to identify a predictive set of parameters enabling prediction of future hypotensive events of the patient. THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. 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. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /MARK HOLCOMB/ Primary Examiner, Art Unit 3685 24 July 2026
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Prosecution Timeline

Jun 11, 2024
Application Filed
Feb 11, 2025
Response after Non-Final Action
Feb 25, 2026
Non-Final Rejection mailed — §101
May 22, 2026
Response Filed
Jul 28, 2026
Final Rejection mailed — §101 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
34%
Grant Probability
74%
With Interview (+40.5%)
4y 5m (~2y 2m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 489 resolved cases by this examiner. Grant probability derived from career allowance rate.

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