DETAILED ACTION
For this Office action, Claims 1-20 are pending.
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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 18 November 2025 has been entered.
Response to Arguments
Applicant’s arguments with respect to claims 1-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. Applicant has amended independent Claims 1, 8 and 15 in a manner that has overcome the teachings of the prior art cited in the previous Office action; therefore, upon further consideration, the grounds of rejection have been withdrawn. However, further search and consideration of the prior art yields new grounds of rejection under 35 U.S.C. 103 using Coulter et al. (herein referred to as “Coulter”, US Pat Pub. 2010/0305966) as a secondary reference. Since the arguments do not address this reference and the only claim limitations challenged in the arguments are addressed by Coulter, the arguments are now considered moot and will not be addressed further at this time.
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 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Gerber et al. (herein referred to as “Gerber”, US Pt Pub. 2018/0043075) in view of Coulter et al. (herein referred to as “Coulter”, US Pat Pub. 2010/0305966).
Regarding instant Claim 1, Gerber discloses a computing device configured to automatically adjust a patient’s treatment (Paragraph [0090]; Paragraph [0095]; dialysis machine with computing device 120 configured to adjust operational parameters such as concentrate amounts or pump operation) comprising: one or more processors (Abstract; Paragraph [0052]; Paragraph [0095]; see processors distributed throughout system and computing device 120); and one or more hardware-based memory devices having instructions which, when executed by one or more processors (Abstract; Figures 1-2; Paragraph [0095]; computing device 120 with processors 122 and memory 124), provide, by the computing device, an initial treatment to the patient (Paragraphs [0090]-[0093]; treatment provided by dialysis system); gather, by one or more sensors operably connected to the computing device, information about the initial treatment associated with the computing device or the patient (Figure 1; Paragraph [0087]; Paragraphs [0091]-[0095]; sensors 106-106h delivers information to computing device 120); and receive, at the computing device, at least one of an adjustment to an operation of the computing device (Figure 1; Paragraph [0087]; Paragraphs [0090]-[0093]; information allows for adjustment by computing device 120 to keep ion patients ion concentration within normal range for said patient), a suggested adjustment to an operation of the computing device (Figure 1; Paragraph [0087]; Paragraphs [0090]-[0094]; adjustment to concentration/treatment is first suggested, also see output of information to user, such as via notification), or a notification about the computing device or the patient associated with the computing device (Figure 1; Paragraph [0095]; notification), wherein the adjustment, suggested adjustment, or notification is from an artificial intelligence (AI) engine based on treatment data derived from treatments other than the initial treatment to the patient at the computing device (Paragraph [0087]; Paragraph [0095]; device uses machine learning to arrive at more precise concentrations of solute than originally capable).
However, while Gerber does disclose the use of an artificial intelligence engine based on treatment data derived from treatments other than the initial treatment to the patient at the computing device, such treatment data including treatment data involving one or more different patients or the one or more different patients’ associated computing devices.
Coulter discloses robotic management of patient care logistics in the same field of endeavor as the instant application, as it solves the mutual problem of using artificial intelligence in the dialysis field adjustment of treatment (Abstract; Paragraph [0033]; Paragraph [0062]; Paragraph [0245]; see list of queue tasks and use of machine learning predictions and operational metrics). Coulter further discloses the use of an artificial intelligence engine based on treatment data, such treatment data involving one or more different patients or the one or more different patients’ associated computing devices in order to apply higher level learning across different facilities to assist in the machine learning of the AI engine (Abstract; Paragraph [0033]; Paragraph [0062]; Paragraph [0120]; Paragraph [0245]; see that data between different facilities or an integrated facility is supported).
It would have been obvious to one or ordinary skill in the art at the time the invention was filed to modify the treatment data of the artificial intelligence engine of Gerber to further comprise such treatment data including treatment data involving one or more different patients or the one or more different patients’ associated computing devices as taught by Coulter because Coulter discloses such treatment data applies higher level learning across different facilities to assist in the machine learning of the AI engine (Coulter, Abstract; Paragraph [0033]; Paragraph [0062]; Paragraph [0120]; Paragraph [0245]).
Regarding instant Claim 2, Claim 1, upon which Claim 2 is dependent, has been rejected above. Gerber further discloses wherein the computing device associated with the patient includes a medical device providing treatment to the patient (Abstract; Figure 1; Paragraph [0086]; system for dialysis).
Regarding instant Claim 3, Claim 2, upon which Claim 3 is dependent, has been rejected above. Gerber further discloses wherein the medical device is a dialysis machine (Abstract; Figure 1; Paragraph [0086]; system for dialysis).
Regarding instant Claim 4, Claim 1, upon which Claim 4 is dependent, has been rejected above. Gerber further discloses wherein the one or more sensors monitor the computing device itself (Paragraph [0091]; duplicated sensors allow for calibration and quality analysis of sensors and computing device 120).
Regarding instant Claim 5, Claim 1, upon which Claim 5 is dependent, has been rejected above. Gerber further discloses wherein the one or more sensors monitor patient information (Paragraph [0093]; sensors may at least determine flow and solute concentration within dialysate removed from patient).
Regarding instant Claim 6, Claim 1, upon which Claim 6 is dependent, has been rejected above. Gerber further discloses wherein the adjustment, suggested adjustment, or notification is generated by a distinct computing device from the computing device providing the initial treatment to the patient (Paragraph [0086]; Paragraph [0095]; computing device may be remote from dialysis machine in communication via the internet).
Regarding instant Claim 7, Claim 1, upon which Claim 7 is dependent, has been rejected above. Gerber further discloses wherein the adjustment, suggested adjustment, or notification is verified with a treatment plan or guidelines associated with the patient (Paragraph [0087]; Paragraph [0090]; machine operates to ensure that dialysate values are within a predetermined threshold of expected values).
Regarding instant Claim 8, Gerber discloses a method performed by a computing device (Paragraph [0090]; Paragraph [0095]; method of operation of a computing device 120 with a dialysis machine), comprising: providing, by the computing device, an initial treatment to the patient (Paragraphs [0090]-[0093]; treatment provided by dialysis system); gathering, by one or more sensors operably connected to the computing device, information about the initial treatment associated with the computing device or the patient (Figure 1; Paragraph [0087]; Paragraphs [0091]-[0095]; sensors 106-106h delivers information to computing device 120); and receiving, at the computing device, at least one of an adjustment to an operation of the computing device (Figure 1; Paragraph [0087]; Paragraphs [0090]-[0093]; information allows for adjustment by computing device 120 to keep ion patients ion concentration within normal range for said patient), a suggested adjustment to an operation of the computing device (Figure 1; Paragraph [0087]; Paragraphs [0090]-[0094]; adjustment to concentration/treatment is first suggested, also see output of information to user, such as via notification), or a notification about the computing device or the patient associated with the computing device (Figure 1; Paragraph [0095]; notification), wherein the adjustment, suggested adjustment, or notification is from an artificial intelligence (AI) engine based on treatment data derived from treatments other than the initial treatment to the patient at the computing device (Paragraph [0087]; Paragraph [0095]; device uses machine learning to arrive at more precise concentrations of solute than originally capable).
However, while Gerber does disclose the use of an artificial intelligence engine based on treatment data derived from treatments other than the initial treatment to the patient at the computing device, such treatment data including treatment data involving one or more different patients or the one or more different patients’ associated computing devices.
Coulter discloses robotic management of patient care logistics in the same field of endeavor as the instant application, as it solves the mutual problem of using artificial intelligence in the dialysis field adjustment of treatment (Abstract; Paragraph [0033]; Paragraph [0062]; Paragraph [0245]; see list of queue tasks and use of machine learning predictions and operational metrics). Coulter further discloses the use of an artificial intelligence engine based on treatment data, such treatment data involving one or more different patients or the one or more different patients’ associated computing devices in order to apply higher level learning across different facilities to assist in the machine learning of the AI engine (Abstract; Paragraph [0033]; Paragraph [0062]; Paragraph [0120]; Paragraph [0245]; see that data between different facilities or an integrated facility is supported).
It would have been obvious to one or ordinary skill in the art at the time the invention was filed to modify the treatment data of the artificial intelligence engine of Gerber to further comprise such treatment data including treatment data involving one or more different patients or the one or more different patients’ associated computing devices as taught by Coulter because Coulter discloses such treatment data applies higher level learning across different facilities to assist in the machine learning of the AI engine (Coulter, Abstract; Paragraph [0033]; Paragraph [0062]; Paragraph [0120]; Paragraph [0245]).
Regarding instant Claim 9, Claim 8, upon which Claim 9 is dependent, has been rejected above. Gerber further discloses wherein the computing device associated with the patient includes a medical device providing treatment to the patient (Abstract; Figure 1; Paragraph [0086]; system for dialysis).
Regarding instant Claim 10, Claim 9, upon which Claim 10 is dependent, has been rejected above. Gerber further discloses wherein the medical device is a dialysis machine (Abstract; Figure 1; Paragraph [0086]; system for dialysis).
Regarding instant Claim 11, Claim 8, upon which Claim 11 is dependent, has been rejected above. Gerber further discloses wherein the one or more sensors monitor the computing device itself (Paragraph [0091]; duplicated sensors allow for calibration and quality analysis of sensors and computing device 120).
Regarding instant Claim 12, Claim 8, upon which Claim 12 is dependent, has been rejected above. Gerber further discloses wherein the one or more sensors monitor patient information (Paragraph [0093]; sensors may at least determine flow and solute concentration within dialysate removed from patient).
Regarding instant Claim 13, Claim 8, upon which Claim 13 is dependent, has been rejected above. Gerber further discloses wherein the adjustment, suggested adjustment, or notification is generated by a distinct computing device from the computing device providing the initial treatment to the patient (Paragraph [0086]; Paragraph [0095]; computing device may be remote from dialysis machine in communication via the internet).
Regarding instant Claim 14, Claim 8, upon which Claim 14 is dependent, has been rejected above. Gerber further discloses wherein the adjustment, suggested adjustment, or notification is verified with a treatment plan or guidelines associated with the patient (Paragraph [0087]; Paragraph [0090]; machine operates to ensure that dialysate values are within a predetermined threshold of expected values).
Regarding instant Claim 15, Gerber discloses one or more hardware-based memory devices having executable instructions which, when executed by one or more processors disposed in a computing device (Paragraph [0090]; Paragraph [0095]; dialysis machine with computing device 120, memory 124 and processors 122 configured to adjust operational parameters such as concentrate amounts or pump operation) causes the computing device to: provide, by the computing device, an initial treatment to the patient (Paragraphs [0090]-[0093]; treatment provided by dialysis system); gather, by one or more sensors operably connected to the computing device, information about the initial treatment associated with the computing device or the patient (Figure 1; Paragraph [0087]; Paragraphs [0091]-[0095]; sensors 106-106h delivers information to computing device 120); and receive, at the computing device, at least one of an adjustment to an operation of the computing device (Figure 1; Paragraph [0087]; Paragraphs [0090]-[0093]; information allows for adjustment by computing device 120 to keep ion patients ion concentration within normal range for said patient), a suggested adjustment to an operation of the computing device (Figure 1; Paragraph [0087]; Paragraphs [0090]-[0094]; adjustment to concentration/treatment is first suggested, also see output of information to user, such as via notification), or a notification about the computing device or the patient associated with the computing device (Figure 1; Paragraph [0095]; notification), wherein the adjustment, suggested adjustment, or notification is from an artificial intelligence (AI) engine based on treatment data derived from treatments other than the initial treatment to the patient at the computing device (Paragraph [0087]; Paragraph [0095]; device uses machine learning to arrive at more precise concentrations of solute than originally capable).
However, while Gerber does disclose the use of an artificial intelligence engine based on treatment data derived from treatments other than the initial treatment to the patient at the computing device, such treatment data including treatment data involving one or more different patients or the one or more different patients’ associated computing devices.
Coulter discloses robotic management of patient care logistics in the same field of endeavor as the instant application, as it solves the mutual problem of using artificial intelligence in the dialysis field adjustment of treatment (Abstract; Paragraph [0033]; Paragraph [0062]; Paragraph [0245]; see list of queue tasks and use of machine learning predictions and operational metrics). Coulter further discloses the use of an artificial intelligence engine based on treatment data, such treatment data involving one or more different patients or the one or more different patients’ associated computing devices in order to apply higher level learning across different facilities to assist in the machine learning of the AI engine (Abstract; Paragraph [0033]; Paragraph [0062]; Paragraph [0120]; Paragraph [0245]; see that data between different facilities or an integrated facility is supported).
It would have been obvious to one or ordinary skill in the art at the time the invention was filed to modify the treatment data of the artificial intelligence engine of Gerber to further comprise such treatment data including treatment data involving one or more different patients or the one or more different patients’ associated computing devices as taught by Coulter because Coulter discloses such treatment data applies higher level learning across different facilities to assist in the machine learning of the AI engine (Coulter, Abstract; Paragraph [0033]; Paragraph [0062]; Paragraph [0120]; Paragraph [0245]).
Regarding instant Claim 16, Claim 15, upon which Claim 16 is dependent, has been rejected above. Gerber further discloses the computing device associated with the patient includes a medical device providing treatment to the patient (Abstract; Figure 1; Paragraph [0086]; system for dialysis).
Regarding instant Claim 17, Claim 15, upon which Claim 17 is dependent, has been rejected above. Gerber further discloses wherein the medical device is a dialysis machine (Abstract; Figure 1; Paragraph [0086]; system for dialysis).
Regarding instant Claim 18, Claim 16, upon which Claim 18 is dependent, has been rejected above. Gerber further discloses wherein the one or more sensors monitor the computing device itself (Paragraph [0091]; duplicated sensors allow for calibration and quality analysis of sensors and computing device 120).
Regarding instant Claim 19, Claim 15, upon which Claim 19 is dependent, has been rejected above. Gerber further discloses wherein the one or more sensors monitor patient information (Paragraph [0093]; sensors may at least determine flow and solute concentration within dialysate removed from patient).
Regarding instant Claim 20, Claim 15, upon which Claim 20 is dependent, has been rejected above. Gerber further discloses wherein the adjustment, suggested adjustment, or notification is generated by a distinct computing device from the computing device providing the initial treatment to the patient (Paragraph [0086]; Paragraph [0095]; computing device may be remote from dialysis machine in communication via the internet).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RICHARD C GURTOWSKI whose telephone number is (571)272-3189. The examiner can normally be reached 10:00 am-6:30pm CT.
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/RICHARD C GURTOWSKI/Primary Examiner, Art Unit 1773 12/03/2025