DETAILED ACTION
Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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.
Claim 2 is 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.
The term “more recent” in claim 2 is a relative term which renders the claim indefinite. The term “more recent” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. Because the term “more” is comparative, but no standard for comparison has been provided within the claim or specification, it is thus unclear how recently a “more recent” past glucose level must be in order to meet the limitation. Appropriate clarification or correction is required.
Claim Rejections - 35 USC § 102
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-11 and 14-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Cinar (U.S. Pat. Pub. No. 2011/0106011 A1).
Regarding claim 1, Cinar discloses an insulin delivery device (device/automatically controlled insulin pump 20 – see Fig. 1, [0002], and [0028-0030]), comprising: a reservoir for storing insulin ([0038], ln 2-4); a non-transitory storage medium (recordable medium, which records past glucose levels of the user) for storing computer programming instructions and past glucose levels of a user of the insulin delivery device ([0035]); a processor for executing the computer programming instructions (Fig. 1, [0035], wherein controller 40 includes a processor in cooperation with the recordable medium, the processor implementing the algorithms of a prediction module 42, an update module 44, and a control module 46 of the controller 40) to cause the processor to: customize a glucose prediction model of the user for predicting future glucose levels of the user based on the past glucose level readings of the user (see Fig. 1, [0006], [0008], and [0036]); use the customized glucose prediction model in determining a basal insulin delivery dosage by the insulin delivery device (Fig. 1, [0007], [0037], [0039], and [0053], wherein controller 40 operates as part of a closed-loop system to maintain patient glucose levels within desired levels by providing an insulin infusion rate – i.e. a basal insulin delivery dosage for continuous, closed-loop treatment, rather than a bolus, which is administered reactionary to blood glucose spikes – to the insulin pump portion 50 as a function of predicted future glucose level); and cause the delivery of the determined basal insulin delivery dosage from the reservoir to the user (Fig. 1 and [0037], ln 1-3).
Regarding claim 2, Cinar further discloses that the processor is further configured to modify the glucose prediction model in view of recent past glucose levels of the user and use the modified glucose prediction model in determining a next basal insulin delivery dosage by the insulin delivery device (see [0006], ln 15-17 and [0040], wherein the glucose prediction model is recursively updated – i.e. modified -- at each sampling time in view of new information in order to dynamically capture the subject’s glucose variation, the updated glucose prediction model being used at each sampling time to determine a next basal insulin delivery dosage in the manner described above in re claim 1, and see [0045-0047], wherein a forgetting factor λ is applied to the recorded past glucose levels within the prediction model summation, with a small value of λ giving more weight to recent observations over older observations, thereby the glucose prediction model may be recursively updated in view of recent past glucose levels, with older levels having minimal influence on predicted glucose level or being discarded).
Regarding claim 3, Cinar further discloses that the processor is further configured to: update the customizing of the glucose prediction model based on glucose levels received since the customizing; use the updated customized glucose prediction model in determining a new basal insulin delivery dosage by the insulin delivery device; and cause the insulin delivery device to deliver the determined new basal insulin delivery dosage ([0006], ln 15-17, [0036-0037], and [0040], wherein the glucose prediction model is recursively updated – i.e. modified -- at each sampling time in view of new information in order to dynamically capture the subject’s glucose variation, the updated glucose prediction model being used at each sampling time to determine a next basal insulin delivery dosage in the manner described above in re claim 1).
Regarding claim 4, Cinar further discloses that the customizing of the glucose prediction model comprises calculating weight coefficient values used in the glucose prediction model (see [0045-0047] and associated equations, wherein a weighted recursive least squares method is used to recursively customize and update the glucose prediction model).
Regarding claim 5, Cinar further discloses that the customizing entails using linear regression analysis (see [0043-0047]) to calculate coefficient values (model parameters contained in matrix polynomials Ak(q-1) and residuals Ck(q-1) at sampling instant k) that substantially minimize an error (modelling error ek) between predicted glucose levels that are predicted from past glucose levels of the user (estimated ẏk) and corresponding actual glucose level readings of the user (yk) (see [0043-0047], wherein actual glucose level at sampling instant k is y1,k within the vector yk, and wherein estimated/predicted glucose level at sampling instant k is ẏ1,k within the vector ẏk).
Regarding claim 6, Cinar further discloses that the glucose prediction model is linear (see [0043-0047]; [0064], wherein a linear time-series model proved to be reliable for predicting future glucose levels; and see example embodiments of [0079] and [0083], in which linear modules are used).
Regarding claim 7, Cinar further discloses that the glucose prediction model may ignore how much insulin has been delivered to the user ([0039-0041], [0050], and [0085], wherein the glucose prediction model is based solely upon past glucose level and physiological signal data when operating as a hypoglycemia warning system).
Regarding claim 8, Cinar discloses a method performed by a processor of an electronic device (see in re claim 1), comprising: determining values of weights (estimated model parameters θk) for past glucose levels (actual glucose levels y1,k within the vector yk) of a user of an insulin delivery device based on a glucose history of the user (see [0043-0047] and [0055-0056], wherein a weighted recursive least squares method is used to determine estimated model parameters θk for past sample times k); applying the determined weights to the past glucose levels to produce weighted past glucose levels and determining a predicted glucose level (ẏ1,k within the vector ẏk) for a user at a given time (sample time k) as a sum of the weighted past glucose levels (see [0043-0049] and [0055-0056], wherein for each past sample time k, estimated model parameters/weights from θk may be applied to preceding glucose levels y1,k-i in the same manner as described by equations 1-5, wherein model parameters/weights from matrix Ai,k are applied to past glucose levels, in order to thereby obtain a predicted glucose level ẏ1,k at each sample time k by summation of the weighted past glucose levels preceding the given sample time k, as shown in equation 1); and using the predicted glucose level of the user to control delivery of insulin to the user by the insulin delivery device (see [0048] and [0057], wherein upon calculation of all predicted glucose levels for past sample times, predicted glucose levels for future sample times k+n may be calculated, and see [0035-0037] and [0058-0061], wherein the rate/amount of insulin delivered to the user by the insulin delivery device may be controlled in response to the predicted glucose levels for future sample times).
Regarding claim 9, Cinar further discloses that the determining the values of the weights for the past glucose levels of the user of the insulin delivery device based on the glucose history of the user comprises: for selected ones of the glucose levels (actual glucose levels y1,k within the vector yk) in the glucose history that includes glucose levels and associated times at which the glucose levels were sensed (sample times k), calculating predicted glucose levels (ẏ1,k within the vector ẏk) from weighted glucose levels in the glucose history for times that immediately precede the times of the selected ones of the glucose levels (sample times k-i) in the glucose history (see [0043-0047] and [0055-0056], wherein for each sample time k, estimated model parameters/weights from θk may be applied to preceding glucose levels y1,k-i in the same manner as described by equations 1-5, wherein model parameters/weights from matrix Ai,k are applied to past glucose levels, in order to thereby obtain a predicted glucose level ẏ1,k at each sample time k by summation of the weighted past glucose levels preceding the given sample time k, as shown in equation 1).
Regarding claim 10, Cinar further discloses that the determining of the values of the weights entails performing least squares regression analysis with the past glucose levels and predicted glucose levels that are predicted from the past glucose levels (see [0045] and [0056], wherein a weighted recursive least squares method is used to determine estimated model parameters θk for past sample times k).
Regarding claim 11, Cinar further discloses that a given one of the predicted glucose levels (ẏ1,k at given sample time k) is calculated as a sum of the weighted glucose levels in the glucose history for times that immediately precede a time of the given one of the predicted glucose levels (see [0043-0047] and [0055-0056], wherein for each sample time k, estimated model parameters/weights from θk may be applied to preceding glucose levels y1,k-i in the same manner as described by equations 1-5, wherein model parameters/weights from matrix Ai,k are applied to past glucose levels, in order to thereby obtain a predicted glucose level ẏ1,k at each sample time k by summation of the weighted past glucose levels preceding the given sample time k, as shown in equation 1).
Regarding claim 14, Cinar further discloses comparing the predicted glucose level to a low glucose level threshold; and where the predicted glucose level falls below the low glucose level threshold, taking corrective action ([0049], wherein a future predicted glucose level is compared against an assigned threshold of 60 mg/dl, and if it falls below the assigned threshold, a warning alarm/alert/notification is issued to the patient).
Regarding claim 15, Cinar further discloses that the corrective action comprises outputting an alert to the user ([0049]).
Regarding claim 16, Cinar discloses an electronic device (device/automatically controlled insulin pump 20 – see Fig. 1, [0002], and [0028-0030]) comprising: a storage (recordable medium, which records past glucose levels of the user) for storing computer programming instructions for controlling operation of an insulin delivery device ([0035]); a processor for executing the computer programming instructions (Fig. 1, [0035], wherein controller 40 includes a processor in cooperation with the recordable medium, the processor implementing the algorithms of a prediction module 42, an update module 44, and a control module 46 of the controller 40), the computer programming instruction for causing the processor to: use a glucose prediction model to predict future glucose levels of a user of the insulin delivery device (see [0035-0036], wherein prediction module 42 uses the model described in [0043-0061] to predict the future blood glucose level of the user based upon recorded past glucose levels); customize the glucose prediction model of the user based on past glucose levels of the user (see Fig. 1, [0006], [0008], and [0036], wherein the model/algorithm for predicting future glucose level is based upon recorded past glucose levels and physiological data of the user, and therefore is customized to the user, and see implementation details of [0043-0061], wherein such is apparent); use the customized glucose prediction model to predict future glucose levels of the user (see Fig. 1, [0035-0036], [0048], and [0057]); and use at least one of the predicted future glucose levels in determining a basal delivery dosage of insulin to be delivered to the user from the insulin delivery device (Fig. 1, [0007], [0037], [0039], and [0053], wherein controller 40 operates as part of a closed-loop system to maintain patient glucose levels within desired levels by providing an insulin infusion rate – i.e. a basal insulin delivery dosage for continuous, closed-loop treatment, rather than a bolus, which is administered reactionary to blood glucose spikes – to the insulin pump portion 50 as a function of predicted future glucose level).
Regarding claim 17, Cinar further discloses that the electronic device is a closed-loop, integrated system comprising an insulin delivery device (insulin pump portion 50) and a management device for the insulin delivery device (controller 40) (see Fig. 1 and [0035-0037]).
Regarding claim 18, Cinar further discloses that the computer programming instructions include instructions for causing the processor to update the customizing of the glucose prediction model based on recent glucose levels of the user (see in re claim 2).
Regarding claim 19, Cinar further discloses that the computer programming instructions include instructions for causing the processor to adjust the predicted glucose levels of the user to account for noise (see [0047] and [0087], wherein the forgetting factor λ is variable, and may be modified or maintained to be at a large value in order to reduce the model’s sensitivity to noise by giving equal weight to recent and older data, such as by not reducing at the first instant of change; and see example embodiment of [0093], ln 1-4, wherein measured and recorded past glucose level data may be smoothed using a low-pass filter to reduce noise in the data prior to being used within the predictive model).
Regarding claim 20, Cinar further discloses that the glucose prediction model does not account for insulin delivered to the user in predicting the future glucose levels of the user (see in re claim 7).
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.
Claim(s) 12-13 are rejected under 35 U.S.C. 103 as being unpatentable over Cinar in view of Reifman (U.S. Pat. Pub. No. 2011/0160555 A1) and Bidet (U.S. Pat. Pub. No. 2021/0068669 A1).
Regarding claim 12, Cinar discloses the method of claim 8. While Cinar teaches comparing the predicted glucose level to a low glucose level threshold, and where the predicted glucose level falls below the low glucose level threshold, taking corrective action (see in re claim 14), Cinar fails to teach comparing the predicted glucose level to a high glucose level threshold; and where the predicted glucose level exceeds the high glucose level threshold, taking corrective action. Such a concept, however, follows naturally from the example of Cinar and from the well understood fact within the art that excessively high glucose levels (hyperglycemia) may be equally damaging to a patient’s health (see Bidet, [0012]). It is thus well understood within the art that there is a need for a warning system that can predict hyperglycemic events in the same manner that Cinar does for hypoglycemic events (see Bidet, [0021]). Further, such a method step is known within the art. Reifman exhibits a system and method for predicting future glucose levels of a patient based upon measured and recorded glucose level measurements of the patient, similar to that of Cinar (see Fig 1-2B, [0005-0008], and [0037-0045]). Reifman teaches the method step of comparing a predicted glucose level to a high glucose level threshold; and where the predicted glucose level exceeds the high glucose level threshold, taking corrective action by outputting an alert to the user (see Fig. 1, method step 140, [0008], and [0045]). Based on the teachings and example of Reifman, and because it is well understood within the art that there is a need for a warning system that can predict hyperglycemic events in the same manner that Cinar does for hypoglycemic events, as taught by Bidet, it would have been obvious to one of ordinary skill in the art prior to the filing date of the claimed invention to modify the method of Cinar to include comparing the predicted glucose level to a high glucose level threshold; and where the predicted glucose level exceeds the high glucose level threshold, taking corrective action in the form of outputting an alert to the user, as taught by Reifman, in addition to the similar process already performed by Cinar for low glucose levels, thereby aiding the user in avoiding damaging high glucose level (hyperglycemic) events.
Regarding claim 13, Cinar as modified by Reifman and Bidet exhibits that the corrective action comprises outputting an alert to the user (see in re claim 12).
Pertinent Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. This art includes
Cinar ‘543 (U.S. 2016/0354543 A1) describes a system and method for predicting future glucose levels of a patient based upon measured and recorded glucose level measurements of the patient and for controlling an insulin delivery device according to predicted future glucose levels, as well as for providing hypoglycemia and hyperglycemia early warning predictions.
Finan (U.S. Pat. Pub. No. 2014/0180240 A1) describes a system and method for predicting future glucose levels of a patient based upon measured and recorded glucose level measurements of the patient and for controlling an insulin delivery device according to at least one predicted future glucose level.
Palerm (U.S. Pat. Pub. No. 2015/0165119 A1) describes a system and method for predicting future glucose levels of a patient based upon measured and recorded glucose level measurements of the patient and for controlling an insulin delivery device according to at least one predicted future glucose level.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Eric A Lange whose telephone number is (571)272-9202. The examiner can normally be reached on M-F 8:30am-noon and 1pm-5:30pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Chelsea Stinson can be reached on (571) 270-1744. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ERIC A LANGE/Examiner, Art Unit 3783
/CHELSEA E STINSON/Supervisory Patent Examiner, Art Unit 3783