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 .
Response to Arguments
Rejection Under 112
Applicant's arguments filed 05/26/2026 have been fully considered. Applicant argues that the specification at [0030] and [0041]-[0042] support the claimed feature. In response to Applicant’s argument, the argument is persuasive and the rejection is withdrawn.
Rejection Under 101
Applicant's arguments filed 05/26/2026 have been fully considered. Applicant argues that:
The amended claims are not directed to organizing human activity because the recited limitations are directed to improvements in machine learning technology itself. Desjardins explained that adjusting parameter values of machine learning models to optimize performance improved the machine learning model operations rather than reciting an abstract idea. Similarly, the amended claims are directed to modifying model parameters.
In response to Applicant’s argument, the additional elements do not amount to a practical application since they merely amount to invoking the use of a computer to carry out the abstract idea and amount to insignificant extrasolution activity. See the updated rejection in light of the amendments. The claims recite already existing machine learning for the particular purpose of the missed bolus dose. Thus the machine learning is merely being used to carry out the abstract idea. Additionally, the Desjardins case was directed to machine learning improvements whereas here the machine learning is merely being used to carry out the abstract idea, which is further evidenced by Applicant’s specification at [0002] that states the invention’s technical field is directed to detecting missed bolus doses related to insulin therapy, not machine learning. The specification in the background section merely identifies patient healthcare problems that the claimed invention is directed toward. See spec. [0003]-[0006]. Therefore, machine learning is merely being invoked to carry out the abstract idea. Following steps to determine if there is a missed bolus dose for insulin management, the claim is classified under organizing human activity and therefore recites an abstract idea.
The claims recite a practical application by improving the field of glucose monitoring for diabetes management. The ordered combination of training a missed bolus classifier on therapy data…, provides a technical solution to the specific problem of missed bolus detection which is supported by the specification (see recited spec. paragraphs, Remarks pg. 15). The outcome of Desjardins supports the conclusion that the training of a model was held to be directed to an improvement and thus integrates the abstract idea into a practical application.
In response to Applicant’s argument, the additional elements are considered individually and as a whole and do not amount to a practical application since they merely amount to invoking the use of a computer to carry out the abstract idea and amount to insignificant extrasolution activity. The claims recite already existing machine learning for the particular purpose of the missed bolus dose. Thus the machine learning is merely being used to carry out the abstract idea. Additionally, as previously discussed, the Desjardins case was directed to machine learning improvements whereas here the machine learning is merely being used to carry out the abstract idea. The specification in the background section merely identifies patient healthcare problems that the claimed invention is directed toward. See spec. [0003]-[0006]. Thus, the claims do not recite an improvement to the machine learning and do not integrate the abstract idea into a practical application.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 3, 5-13, 15, 17-19, 21-34 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., an abstract idea) without significantly more.
Step 1 of the Alice/Mayo Test
Claims 1, 3, 5-10, 23-29, 32-34 are drawn to a method, which is within the four statutory categories (i.e. process). Claims 11-13, 15, 17-19, 21-22 are drawn to a system, which is within the four statutory categories (i.e. apparatus). Claim 30 is drawn to a computer-readable storage medium storing instructions, which is within the four statutory categories (i.e. manufacture). Claim 31 is drawn to a computer program product comprising a non-transitory computer-readable storage medium having computer-readable instructions embodied thereon, which is within the four statutory categories (i.e. manufacture).
Step 2A of the Alice/Mayo Test - Prong One
The independent claims recite an abstract idea. For example, independent claim 30 (and substantially similar with independent claim 1, 11, 23, 29, 31) recites:
A computer-readable storage medium storing instructions which, when executed by a processor of a computer in communication with an insulin management system, cause the computer to perform operations comprising:
receiving therapy data associated with an insulin-based management of a person with diabetes over a period of time, wherein the therapy data comprises glucose data of the person with diabetes collected from an in vivo glucose monitoring device, the in vivo glucose monitoring device comprising:
a glucose sensor configured to be placed in contact with interstitial fluid of the person with diabetes and monitor glucose levels of the person with diabetes: and
sensor electronics coupled to the glucose sensor and configured to wirelessly transmit glucose data of the person with diabetes;
training, by the processor, a missed-bolus classifier based on the therapy data of the person with diabetes, wherein the training comprises:
generating a feature set having one or more features of the therapy data;
determining a predictive ability of the trained missed-bolus classifier; and
improving the predictive ability of the trained missed-bolus classifier by changing weighting factors for features of the feature set:
identifying a retrospective time period of the period of time;
performing a trained missed-bolus classification process utilizing the trained missed-bolus classifier on at least a part of the therapy data that corresponds to the retrospective time period, wherein the trained missed-bolus classification process is based on a supervised machine learning model;
obtaining a classification result responsive to the performed trained missed-bolus classification process;
assigning a label to the retrospective time period responsive to the classification result, wherein the label is assigned by a trained missed-bolus classifier engine, wherein the label comprises a missed-bolus dose label or a no missed-bolus dose label;
outputting a report comprising the labeled retrospective time period and one or more insights about the person with diabetes based at least in part on the labeled retrospective time period,
wherein the one or more insights comprises a probability the person with diabetes will miss a bolus dose.
Any differences between the independent claims and not shown in the exemplary claim above, for example the aggregation limitation or managing therapy settings limitation of claim 23, should be included in the abstract idea.
These underlined elements recite an abstract idea that can be categorized, under its broadest reasonable interpretation, to cover the management of personal behavior or interactions (i.e., following rules or instructions to assign a label to a detected bolus classification) but for the recitation of generic computer components. For example, but for computer-readable storage medium storing instructions which, when executed by a processor of a computer, cause the computer to perform operations, an in vivo glucose monitoring device, glucose sensor, sensor electronics, missed-bolus classifier, the limitations of this claim encompass following steps to determine if a missed bolus is detected in order to assign a label to the classification result to output reports with insights about the patient with diabetes. If a claim limitation, under its broadest reasonable interpretation, covers management of personal behavior or interactions but for the recitation of generic computer components, then the limitations fall within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. See MPEP § 2106.04(a).
Dependent claims recite additional subject matter which further narrows or defines the abstract idea embodied in the claims (such as claims 3, 5-10, 12-13, 15, 17-19, 24-28, 32-34 reciting particular aspects of the abstract idea).
Step 2A of the Alice/Mayo Test - Prong Two
For example, independent claim 30 (and substantially similar with independent claim 1, 11, 23, 29, 31) recites:
A computer-readable storage medium storing instructions which, when executed by a processor of a computer in communication with an insulin management system, cause the computer to perform operations comprising: (merely invokes use of computer and other machinery as a tool as noted below, see MPEP 2106.05(f))
receiving therapy data associated with an insulin-based management of a person's diabetes over a period of time, wherein the therapy data comprises glucose data of the person with diabetes collected from an in vivo glucose monitoring device, the in vivo glucose monitoring device comprising: (merely invokes use of computer and other machinery as a tool as noted below, see MPEP 2106.05(f))
a glucose sensor configured to be placed in contact with interstitial fluid of the person with diabetes and monitor glucose levels of the person with diabetes: and (merely invokes use of computer and other machinery as a tool as noted below, see MPEP 2106.05(f))
sensor electronics coupled to the glucose sensor and configured to wirelessly transmit glucose data of the person with diabetes; (merely invokes use of computer and other machinery as a tool as noted below, see MPEP 2106.05(f))
training, by the processor, a missed-bolus classifier based on the therapy data of the person with diabetes, wherein the training comprises: (merely invokes use of computer and other machinery as a tool as noted below, see MPEP 2106.05(f))
generating a feature set having one or more features of the therapy data;
determining a predictive ability of the trained missed-bolus classifier; and
improving the predictive ability of the trained missed-bolus classifier by changing weighting factors for features of the feature set:
identifying a retrospective time period of the period of time;
performing a trained missed-bolus classification process utilizing the trained missed-bolus classifier on at least a part of the therapy data that corresponds to the retrospective time period, wherein the trained missed-bolus classification process is based on a supervised machine learning model;
obtaining a classification result responsive to the performed trained missed-bolus classification process;
assigning a label to the retrospective time period responsive to the classification result, wherein the label is assigned by a trained missed-bolus classifier engine, wherein the label comprises a missed-bolus dose label or a no missed-bolus dose label;
outputting a report comprising the labeled retrospective time period and one or more insights about the person with diabetes based at least in part on the labeled retrospective time period, (merely insignificant extrasolution activity steps as noted below, see MPEP 2106.05(g))
wherein the one or more insights comprises a probability the person with diabetes will miss a bolus dose.
The judicial exception is not integrated into a practical application. In particular, the additional elements do not integrate the abstract idea into a practical application, other than the abstract idea per se, because the additional elements amount to no more than limitations, which:
amount to mere instructions to apply an exception (such as recitations of a computer-readable storage medium storing instructions which, when executed by a processor of a computer, cause the computer to perform operations, an in vivo glucose monitoring device, glucose sensor, sensor electronics, missed-bolus classifier, thereby invoking computers as a tool to perform the abstract idea, see applicant’s specification [0025]-[0029], [0040], [0042], [0064]-[0070], see MPEP 2106.05(f))
add insignificant extra-solution activity to the abstract idea (such as recitation of outputting a report with insights about the person with diabetes amounts to insignificant extrasolution activity, see MPEP 2106.05(g))
Dependent claims recite additional subject matter which amount to limitations consistent with the additional elements in the independent claims (such as claims 3, 5-10, 12-13, 15, 17-19, 24-28, 32-34 recite additional limitations which amount to invoking computers as a tool to perform the abstract idea, and claims 3, 5-10, 12-13, 15, 17-19, 24-28, 32-34 additional limitations which generally link the abstract idea to a particular technological environment or field of use). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation and do not impose a meaningful limit to integrate the abstract idea into a practical application.
Step 2B of the Alice/Mayo Test for Claims
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to discussion of integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply an exception and adding insignificant extrasolution activity to the abstract idea. Additionally, the additional elements, other than the abstract idea per se, amount to no more than elements which:
amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields (such as using a computer-readable storage medium storing instructions which, when executed by a processor of a computer, cause the computer to perform operations, an in vivo glucose monitoring device, glucose sensor, sensor electronics, missed-bolus classifier, e.g., Applicant’s spec describes the computer system with it being well-understood, routine, and conventional because it describes in a manner that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such elements to satisfy 112a. (See Applicant’s Spec. [0025]-[0029], [0040], [0042], [0064]-[0070]); a computer-readable storage medium storing instructions which, when executed by a processor of a computer, cause the computer to perform operations, processor, classifier, e.g., merely adding a generic computer, generic computer components, or a programmed computer to perform generic computer functions, Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 134 S. Ct. 2347, 2358-59, 110 USPQ2d 1976, 1983-84 (2014).
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. The following represent examples that courts have identified as insignificant extrasolution activities (e.g. see MPEP 2106.05(g)): outputting a report with insights about the person with diabetes, e.g., outputting or providing access to the information, Symantec, 838 F.3d at 1321 and MPEP 2106.05(g)(3)).
Dependent claims recite additional subject matter which, as discussed above with respect to integration of the abstract idea into a practical application, amount to invoking computers as a tool to perform the abstract idea, and are generally linking the abstract idea to a particular field of environment. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. Therefore, the claims are not patent eligible, and are rejected under 35 U.S.C. § 101.
Subject Matter Free of Prior Art
Claims 1, 3, 5-13, 15, 17-19, 21-34 are free of prior art over Estes (US 2013/0053819) in view of Blomquist et al. (US 2019/0350501) and Agrawal et al. (US 2013/0345663). The prior art references, or reasonable combination thereof, could not be found to disclose, or suggest all of the limitations found in the independent claims. The closest prior art is Estes (US 2013/0053819), which teaches an infusion pump system and method with alarms to indicate that a meal or bolus was missed in response to a blood glucose characteristic. Blomquist et al. (US 2019/0350501) teaches a pump with information about the user to initiate drug delivery. Agrawal et al. (US 2013/0345663) teaches a diabetes therapy management system using an insulin infusion device and identifying bolus calculator event data from glucose data and detected event occurrences. The references taken solely, or in combination, fail to provide the required limitations, and modification of any complementary combination of the references of record would be impermissible hindsight and not provide any advantages over their present application. The dependent claims are also free of prior art due to their corresponding dependency of the independent claims.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
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/AMANDA R. COVINGTON/Examiner, Art Unit 3686 /RACHELLE L REICHERT/Primary Examiner, Art Unit 3686
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