Office Action 2: Final Rejection (2023-06-02)
Rejection types: 103 - Obviousness

CLAIMS:
AMENDMENTS TO THE CLAIMS

This listing of claims will replace all prior versions and listings of claims in the application.

Listing of Claims:

Claim 1 (Currently Amended): A system comprising:
one or more processors; and
one or more processor-readable storage media storing instructions which, when executed by the one or more processors, cause performance of:
obtaining an estimated protein value for a meal;
determining an equivalent carbohydrate value for the meal based on converting the estimated protein value into a corresponding carbohydrate value;
determining, based on the equivalent carbohydrate value for the meal, an amount of insulin to deliver to a patient to counteract a glucose level increase caused by consumption of the meal; and
causing delivery of insulin to the patient, with an insulin delivery device, based on generating an output indicative of the amount of insulin to counteract the glucose level increase caused by consumption of the meal.

Claim 2 (Original): The system of claim 1, wherein determining the amount of insulin to deliver to the patient comprises:
predicting, based on the equivalent carbohydrate value for the meal, amounts of glucose to be absorbed into a bloodstream of the patient over a duration of time due to consumption of the meal; and
determining, based on the predicted amounts of glucose to be absorbed into the bloodstream, a bolus dosage of insulin to deliver to the patient.

Claim 3 (Original): The system of claim 2, wherein determining the amount of insulin to deliver to the patient comprises:
prior to determining the bolus dosage, obtaining an amount of a basal dosage of insulin previously delivered to the patient, and wherein determining the bolus dosage is further based on the amount of the basal dosage of insulin.

Claim 4 (Original): The system of claim 2, wherein determining the bolus dosage comprises:
identifying a plurality of candidate dosages;
for each candidate dosage of the plurality of candidate dosages, predicting a respective amount of time within a target range for the patient's glucose levels; and
selecting a candidate dosage that results in a maximum amount of time within the target range.

Claim 5 (Currently Amended): The system of claim 1, wherein determining the equivalent carbohydrate value comprises:
determining a conversion factor for converting protein to a parameter approximating an effect of the protein on glucose levels of the patient; and
determining the equivalent carbohydrate for the meal based on converting the estimated protein value for the meal into the corresponding carbohydrate value using the conversion factor .

Claim 6 (Original): The system of claim 5, wherein the conversion factor is determined based on historical meal data for the patient and further based on historical glucose level data for the patient.

Claim 7 (Original): The system of claim 5, wherein the conversion factor is determined based on a time of day that the patient consumes the meal.

Claim 8 (Original): The system of claim 5, wherein the instructions, when executed by the one or more processors, cause performance of:
obtaining an estimated fat value for the meal;
determining, based on the estimated fat value, a glucose absorption rate resulting from consumption of the meal, wherein determining the amount of insulin to deliver to the patient is based on the equivalent carbohydrate value for the meal and is further based on the glucose absorption rate resulting from consumption of the meal.

Claim 9 (Original): The system of claim 8, wherein determining the glucose absorption rate comprises:
determining an absorption rate tuning factor for approximating an effect of fat on the glucose absorption rate; and
determining the glucose absorption rate based on the estimated fat value for the meal and the absorption rate tuning factor, wherein the absorption rate tuning factor is determined based on historical meal data for the patient and further based on historical glucose level data for the patient.

Claim 10 (Currently Amended): A processor-implemented method comprising:
obtaining an estimated protein value for a meal;
determining an equivalent carbohydrate value for the meal based on converting the estimated protein value into a corresponding carbohydrate value;
determining, based on the equivalent carbohydrate value for the meal, an amount of insulin to deliver to a patient to counteract a glucose level increase caused by consumption of the meal; and
causing delivery of insulin to the patient, with an insulin delivery device, based on generating an output indicative of the amount of insulin to counteract the glucose level increase caused by consumption of the meal.

Claim 11 (Original): The method of claim 10, wherein determining the amount of insulin to deliver to the patient comprises:
predicting, based on the equivalent carbohydrate value for the meal, amounts of glucose to be absorbed into a bloodstream of the patient over a duration of time due to consumption of the meal; and
determining, based on the predicted amounts of glucose to be absorbed into the bloodstream, a bolus dosage of insulin to deliver to the patient.

Claim 12 (Original): The method of claim 11, wherein determining the amount of insulin to deliver to the patient comprises:
prior to determining the bolus dosage, obtaining an amount of a basal dosage of insulin previously delivered to the patient, and wherein determining the bolus dosage is further based on the amount of the basal dosage of insulin.

Claim 13 (Original): The method of claim 11, wherein determining the bolus dosage comprises:
identifying a plurality of candidate dosages;
for each candidate dosage of the plurality of candidate dosages, predicting a respective amount of time within a target range for the patient's glucose levels; and
selecting a candidate dosage that results in a maximum amount of time within the target range.

Claim 14 (Currently Amended): The method of claim 10, wherein determining the equivalent carbohydrate value comprises:
determining a conversion factor for converting protein to a parameter approximating an effect of the protein on glucose levels of the patient; and
determining the equivalent carbohydrate for the meal based on converting the estimated protein value for the meal into the corresponding carbohydrate value using the conversion factor .

Claim 15 (Original): The method of claim 14, wherein the conversion factor is determined based on historical meal data for the patient and further based on historical glucose level data for the patient.

Claim 16 (Original): The method of claim 14, wherein the conversion factor is determined based on a time of day that the patient consumes the meal.

Claim 17 (Original): The method of claim 10, further comprising:
obtaining an estimated fat value for the meal;
determining, based on the estimated fat value, a glucose absorption rate resulting from consumption of the meal, wherein determining the amount of insulin to deliver to the patient is based on the equivalent carbohydrate value for the meal and is further based on the glucose absorption rate resulting from consumption of the meal.

Claim 18 (Currently Amended): One or more non-transitory processor-readable storage media storing instructions which, when executed by one or more processors, cause performance of:
obtaining an estimated protein value for a meal;
determining an equivalent carbohydrate value for the meal based on converting the estimated protein value into a corresponding carbohydrate value;
determining, based on the equivalent carbohydrate value for the meal, an amount of insulin to deliver to a patient to counteract a glucose level increase caused by consumption of the meal; and
causing delivery of insulin to the patient, with an insulin delivery device, based on generating an output indicative of the amount of insulin to counteract the glucose level increase caused by consumption of the meal.

Claim 19 (Original): The one or more non-transitory processor-readable storage media of claim 18, wherein determining the amount of insulin to deliver to the patient comprises:
predicting, based on the equivalent carbohydrate value for the meal, amounts of glucose to be absorbed into a bloodstream of the patient over a duration of time due to consumption of the meal;
determining, based on the predicted amounts of glucose to be absorbed into the bloodstream, a bolus dosage of insulin to deliver to the patient; and
prior to determining the bolus dosage, obtaining an amount of a basal dosage of insulin previously delivered to the patient, and wherein determining the bolus dosage is further based on the amount of the basal dosage of insulin.

Claim 20 (Currently Amended): The one or more non-transitory processor-readable storage media of claim 18, wherein determining the equivalent carbohydrate value comprises:
determining a conversion factor for converting protein to a parameter approximating an effect of the protein on glucose levels of the patient; and
determining the equivalent carbohydrate for the meal based on converting the estimated protein value for the meal into the corresponding carbohydrate value using the conversion factor , wherein the conversion factor is determined based on historical meal data for the patient and further based on historical glucose level data for the patient.
2 3 4 5 6 7

OFFICE ACTION:
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
Applicant’s arguments, see pg. 8-12 of remarks, filed March 1st, 2023, with respect to the rejection(s) of claim(s) 1-3, 5-12, and 14-20 under 35 U.S.C. 102(a)(1) have been fully considered and are persuasive.  Therefore, the rejection has been withdrawn.  However, upon further consideration, a new ground(s) of rejection is made in view of Thukral (US 20090006061 A1).  Thukral teaches an explicit conversion of protein content to equivalent carbohydrates (Paragraph 0213:  “Proteins and fat are converted to an equivalent carbohydrate amount”).
The amendment adding the use of an insulin device also helped overcome the outstanding 101 rejection.
Claim Rejections - 35 USC § 103
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 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.
Claims 1-3, 5-12, and 14-20 are rejected under 35 U.S.C. 103 as being unpatentable over Weinert (US 20070179434 A1) in view of Thukral (US 20090006061 A1).
Regarding claims 1, 10, and 18, Weinert teaches a system/method/non-transitory processor-readable media storing instructions (Paragraph 0001:  “systems for determining insulin administration information based on a user input of user-related feed forward information”) comprising:
one or more processors (Paragraph 0003:  “a processor”); and
one or more processor-readable storage media storing instructions which, when executed by the one or more processors (Paragraph 0065:  “one or more suitable data and/or program storage devices”), cause performance of:
obtaining an estimated protein value for a meal (Paragraph 0010:  “meal size values for each of the fat amount, protein amount and carbohydrate amount”);
determining, based on the equivalent carbohydrate value for the meal, an amount of insulin to deliver to a patient to counteract a glucose level increase caused by consumption of the meal (Paragraph 0023:  “The drug may be a blood glucose lowering drug. The drug may be, for example, insulin. The first parameter may correspond to carbohydrate content of a meal and the second parameter may correspond to an expected speed of overall glucose absorption from the meal by the user”); and
causing delivery of insulin to the patient, with an insulin delivery device (Paragraph 0069:  “the insulin pump is configured to wirelessly transmit information relating to insulin delivery to the handheld device 12”), based on generating an output indicative of the amount of insulin to counteract the glucose level increase caused by consumption of the meal (Paragraph 0020:  “The method may further include displaying at least some of the drug administration information on a display unit”).
Weinert fails to explicitly teach determining an equivalent carbohydrate value for the meal based on converting the estimated protein value into a corresponding carbohydrate value.
Thukral teaches determining an equivalent carbohydrate value for the meal based on converting the estimated protein value into a corresponding carbohydrate value (Paragraph 0213:  “Proteins and fat are converted to an equivalent carbohydrate amount”).  I would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the equivalent carbohydrate calculation of Weinert to incorporate the explicit conversion of protein value to equivalent carbohydrates taught by Thukral, because it helps to find the best and most accurate values for insulin to counter the gut glucose concentration (Paragraph 0214 of Thukral).
Regarding claims 2 and 11, Weinert teaches wherein determining the amount of insulin to deliver to the patient (Paragraph 0023:  “The drug may be a blood glucose lowering drug. The drug may be, for example, insulin. The first parameter may correspond to carbohydrate content of a meal and the second parameter may correspond to an expected speed of overall glucose absorption from the meal by the user”) comprises:
predicting, based on the equivalent carbohydrate value for the meal, amounts of glucose to be absorbed into a bloodstream of the patient over a duration of time due to consumption of the meal (Paragraph 0077:  “the estimate of the expected speed of overall glucose absorption parameter, the shape and duration of the glucose absorption profile may be mapped to the composition of the meal”); and
determining, based on the predicted amounts of glucose to be absorbed into the bloodstream, a bolus dosage of insulin to deliver to the patient (Paragraph 0023:  “The drug may be a blood glucose lowering drug. The drug may be, for example, insulin. The first parameter may correspond to carbohydrate content of a meal and the second parameter may correspond to an expected speed of overall glucose absorption from the meal by the user”).
Regarding claims 3 and 12, Weinert teaches wherein determining the amount of insulin to deliver to the patient comprises: prior to determining the bolus dosage, obtaining an amount of a basal dosage of insulin previously delivered to the patient (Paragraph 0121:  “Information is entered into a database … In such cases, the other bolus-related information may include, for example, but should not be limited to, number of meal compensation or correction boluses administered, amount of each bolus administered, time between administered boluses and time of administration of first bolus”), and wherein determining the bolus dosage is further based on the amount of the basal dosage of insulin (Paragraph 0157:  “ Any such stored information may be evaluated immediately or in the future, and/or may be re-evaluated when new entries or updates are made to the database and/or to the one or more system control algorithms. Examples of user feedback entered into the system 10 include, but are not limited to, any of the information illustrated in FIG. 13”:  the prior bolus dose is a database entry which is used in the system algorithms used for bolus control).
Regarding claim 5 and 14, Weinert teaches wherein determining the equivalent carbohydrate value comprises:
determining a conversion factor for converting protein to a parameter approximating an effect of the protein on glucose levels of the patient (Paragraph 0082); and
determining the equivalent carbohydrate for the meal (Paragraph 0081-0083).
Weinert fails to explicitly converting the estimated protein value for the meal into the corresponding carbohydrate value using the conversion factor.
Thukral teaches converting the estimated protein value for the meal into the corresponding carbohydrate value using the conversion factor  (Paragraph 0213 and Paragraphs 0200-0230:  “Proteins and fat are converted to an equivalent carbohydrate amount”:  see equations and conversion inherently requires a factor).  I would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the equivalent carbohydrate calculation of Weinert to incorporate the explicit conversion of protein value to equivalent carbohydrates taught by Thukral, because it helps to find the best and most accurate values for insulin to counter the gut glucose concentration (Paragraph 0214 of Thukral).
Regarding claims 6 and 15, Weinert teaches wherein the conversion factor is determined based on historical meal data for the patient (Paragraph 0100:  “a suitable graphical user interface can be defined based on the patient's recorded dietary habits, the outcome of the third process module is a graphical user interface that maps user-selectable feed forward information to insulin delivery information”) and further based on historical glucose level data for the patient (Paragraph 0121 and Fig. 13:  previous glucose levels used).
Regarding claims 7 and 16, Weinert teaches wherein the conversion factor is determined based on a time of day that the patient consumes the meal (Paragraph 00120, 00130-00132:  meal time and type is used to adjust the maps).
Regarding claims 8 and 17, Weinert teaches wherein the instructions, when executed by the one or more processors, cause performance of:
obtaining an estimated fat value for the meal (Paragraph 0010:  “meal size values for each of the fat amount, protein amount and carbohydrate amount”);
determining, based on the estimated fat value, a glucose absorption rate resulting from consumption of the meal, wherein determining the amount of insulin to deliver to the patient is based on the equivalent carbohydrate value for the meal and is further based on the glucose absorption rate resulting from consumption of the meal (Paragraph 0077).
Regarding claim 9, Weinert teaches wherein determining the glucose absorption rate comprises:
determining an absorption rate tuning factor for approximating an effect of fat on the glucose absorption rate (Fig. 4/5 and Paragraph 0081-0083:  amount of fat is tuned based on meal composition and details); and
determining the glucose absorption rate based on the estimated fat value for the meal and the absorption rate tuning factor (Fig. 4/5 and Paragraphs 0081-0083), wherein the absorption rate tuning factor is determined based on historical meal data for the patient (Paragraph 0100:  “a suitable graphical user interface can be defined based on the patient's recorded dietary habits, the outcome of the third process module is a graphical user interface that maps user-selectable feed forward information to insulin delivery information”) and further based on historical glucose level data for the patient (Paragraph 0121 and Fig. 13:  previous glucose levels used).
Regarding claim 19, Weinert teaches wherein determining the amount of insulin to deliver to the patient (Paragraph 0023:  “The drug may be a blood glucose lowering drug. The drug may be, for example, insulin. The first parameter may correspond to carbohydrate content of a meal and the second parameter may correspond to an expected speed of overall glucose absorption from the meal by the user”) comprises:
predicting, based on the equivalent carbohydrate value for the meal, amounts of glucose to be absorbed into a bloodstream of the patient over a duration of time due to consumption of the meal (Paragraph 0077:  “the estimate of the expected speed of overall glucose absorption parameter, the shape and duration of the glucose absorption profile may be mapped to the composition of the meal”);
determining, based on the predicted amounts of glucose to be absorbed into the bloodstream, a bolus dosage of insulin to deliver to the patient (Paragraph 0023:  “The drug may be a blood glucose lowering drug. The drug may be, for example, insulin. The first parameter may correspond to carbohydrate content of a meal and the second parameter may correspond to an expected speed of overall glucose absorption from the meal by the user”); and
prior to determining the bolus dosage, obtaining an amount of a basal dosage of insulin previously delivered to the patient (Paragraph 0121:  “Information is entered into a database … In such cases, the other bolus-related information may include, for example, but should not be limited to, number of meal compensation or correction boluses administered, amount of each bolus administered, time between administered boluses and time of administration of first bolus”), and wherein determining the bolus dosage is further based on the amount of the basal dosage of insulin (Paragraph 0157:  “ Any such stored information may be evaluated immediately or in the future, and/or may be re-evaluated when new entries or updates are made to the database and/or to the one or more system control algorithms. Examples of user feedback entered into the system 10 include, but are not limited to, any of the information illustrated in FIG. 13”:  the prior bolus dose is a database entry which is used in the system algorithms used for bolus control).
Regarding claim 20, Weinert teaches wherein determining the equivalent carbohydrate value comprises:
determining a conversion factor for converting protein to a parameter approximating an effect of the protein on glucose levels of the patient (Paragraph 0082); and
wherein the conversion factor is determined based on historical meal data for the patient (Paragraph 0100:  “a suitable graphical user interface can be defined based on the patient's recorded dietary habits, the outcome of the third process module is a graphical user interface that maps user-selectable feed forward information to insulin delivery information”) and further based on historical glucose level data for the patient (Paragraph 0121 and Fig. 13:  previous glucose levels used).
Weinert fails to explicitly converting the estimated protein value for the meal into the corresponding carbohydrate value using the conversion factor.
Thukral teaches converting the estimated protein value for the meal into the corresponding carbohydrate value using the conversion factor  (Paragraph 0213 and Paragraphs 0200-0230:  “Proteins and fat are converted to an equivalent carbohydrate amount”:  see equations and conversion inherently requires a factor).  I would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the equivalent carbohydrate calculation of Weinert to incorporate the explicit conversion of protein value to equivalent carbohydrates taught by Thukral, because it helps to find the best and most accurate values for insulin to counter the gut glucose concentration (Paragraph 0214 of Thukral).
Claims 4 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Weinert and Thukral as applied to claims 1 and 10 above, and further in view of Mazlish (US 20180200439 A1).
Regarding claim 4 and 13, Weinert and Thukral fail to teach wherein determining the bolus dosage comprises: identifying a plurality of candidate dosages; for each candidate dosage of the plurality of candidate dosages, predicting a respective amount of time within a target range for the patient's glucose levels; and selecting a candidate dosage that results in a maximum amount of time within the target range.
Mazlish teaches wherein determining the bolus dosage comprises:
identifying a plurality of candidate dosages (Paragraph 20:  “ For example, such personalization may include generating multiple insulin delivery profiles and projected blood glucose levels for each of the insulin delivery profiles, and selecting the profile that closely tracks towards a target blood glucose level”);
for each candidate dosage of the plurality of candidate dosages, predicting a respective amount of time within a target range for the patient's glucose levels (Paragraph 0022:  “Methods and systems provided herein can use a model to predict multiple future blood glucose levels for multiple different basal insulin delivery profiles or basal insulin delivery rates, and select one of the basal insulin delivery profiles or basal insulin delivery rates based on prediction of which profile or rate will approximate a target blood glucose level, or more specifically, select the profile that minimizes the differences between the predicted future blood glucose values and one or more target blood glucose values”); and
selecting a candidate dosage that results in a maximum amount of time within the target range (Paragraph 0022:  “In some cases, the profile that minimizes, lessens, or lowers variations from one or more target blood glucose levels in the future may be selected”).  It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system/method of Weinert and Thukral to incorporate the multiple candidate dosages of Mazlish, because it allows for the best and most optimal treatment to be given to a patient to control their blood glucose level (Paragraph 0022 of Mazlish).
Conclusion
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 extension fee 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.

APPLICANT REBUTTAL: REMARKS
Claims 1, 5, 10, 14, 18, and 20 are amended. Accordingly, upon entry of this
amendment, claims 1-20 will remain pending. Applicant respectfully requests reconsideration in view of the remarks presented below.
Claim Rejections Under 35 U.S.C.
§
Claims 1-3, 5-12, and 14-20 were rejected under 35 U.S.C. 103 as allegedly being
unpatentable over Weinert U.S. Patent Application Publication No. 2007/0179434 (hereinafter, "Weinert") in view of Thukral U.S. Patent Application Publication No. 2009/006061 (hereinafter, "Thukral"). Claims 4 and 13 were rejected under 35 U.S.C. 103 as allegedly being unpatentable over Weinert and Thukral, and further in view of Mazlish U.S. Patent Application Publication No. 2018/0200439 (hereinafter, "Mazlish").
Without conceding in the basis of the rejections, and solely to expedite prosecution of this Application, independent claims 1, 10, and 18 have been amended to recite, inter alia: obtaining an estimated protein value for a meal and an estimated carbohydrate value for the meal;
converting the estimated protein value into a corresponding carbohydrate value by applying the estimated
protein value to a mathematical function or by dividing the
estimated protein value by a conversion factor;
[and]
determining an equivalent carbohydrate value for the meal
by adding the estimated carbohydrate value for the meal to the
corresponding carbohydrate value associated with the
estimated protein value.
(Claim 1 as amended; claims 10 and 18 have been amended to recite similar features).
Applicant notes that portions of the amendments made herein to claims 1, 10, and 18 were previously recited in dependent claim 5, prior to the current amendments. In rejecting dependent claim 5, the Office conceded that Weinert does not disclose or suggest "converting the estimated protein value into a corresponding carbohydrate value using the conversion factor." The Office asserted that Thukral discloses this feature, citing paragraph [0213] and stating that the equations in paragraphs [0200]-[0230] inherently require "a factor." (Office Action, page 6).
Paragraph [0213] of Thukral states "proteins and fat are converted to an equivalent
carbohydrate amount." However, Thukral does not disclose or suggest "converting the estimated
protein value into a corresponding carbohydrate value
by applying the estimated protein value to a mathematical function or by dividing the estimated protein value by a conversion factor."
Applicant respectfully submits that the equations of paragraphs [0200]-[0230] do not correspond to converting the estimated protein value into a corresponding carbohydrate value, let alone by
"applying the estimated protein value to a mathematical function or dividing the estimated protein value by a conversion factor,"
as recited in Applicant's claims 1, 10, and 18 as amended. Rather, these equations relate to, e.g., an insulin nullified vector (see paragraph [0203]), glucose drop due to insulin utilization (see paragraphs [0206]-[0208]), estimated insulin remaining (see paragraphs [0219]-[0221]), and other parameters that are
not related to converting the estimated protein value into a corresponding carbohydrate value.
Applicant respectfully submits independent claims 1, 10, and 18 are allowable for at least a second reason. In rejecting independent claim 1, the Office conceded Weinert does not disclose or suggest "determining an equivalent carbohydrate value for the meal based on converting the estimated protein value into a corresponding carbohydrate value." However, the Office asserted that Thukral discloses this feature, citing paragraph [0213] of Thukral. (Office Action, page 4). As discussed above, Thukral states "proteins and fat are converted to an equivalent carbohydrate amount," however, Thukral makes no mention of
how
the equivalent carbohydrate amount is determined. Accordingly, Thukral does not disclose or suggest "determining an equivalent carbohydrate value for the meal
by adding the estimated carbohydrate value for the meal to the corresponding carbohydrate value associated with the estimated protein value,"
as recited in amended claims 1, 10, and 18.
For at least these reasons, Applicant respectfully submits independent claims 1, 10, and 18 are allowable. Moreover, 2-9, 11-17, 19, and 20, each of which depend from one of independent claims 1, 10, or 18 are allowable for at least the same reasons corresponding independent claims 1, 10, and 18 are allowable.
For at least these reasons, applicant respectfully requests reconsideration and withdrawal of the rejections of the claims under 35 U.S.C. § 103.
Conclusion

NEXT OFFICE ACTION: 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 .
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 July 19, 2023 has been entered.
Acknowledgement of Amendments
This Office Action is responsive to the amendment filed July 19, 2023. The examiner acknowledges the amendments to claims 1, 5, 10, 14, 18, and 20. Claims 1-20 are subject to examination hereinbelow.
Response to Arguments
Applicant’s arguments, see pg 9, filed October 23, 2023, with respect to the rejection(s) of claim(s) 1, 10, and 18 under USC 103 have been fully considered and are persuasive.  Therefore, the rejection has been withdrawn.  However, upon further consideration, a new ground(s) of rejection is made in view of US 20050187749 A1 to Singley.
Claim Objections
Claims 5, 14, and 20 are objected to because of the following informalities: converting protein to a parameter should be amended to --converting the estimated protein value to a parameter--.  Appropriate correction is required.
Claim Rejections - 35 USC § 103
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 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.
Claim(s) 1-3, 5, 7-12, 14, and 16-20 are rejected under 35 U.S.C. 103 as being unpatentable over Weinert (US 20070179434 A1) (cited in previous Office Action) in view of US 20050187749 A1 to Singley.
Regarding claim 1, Weinert teaches a system [abstract] comprising:
one or more processors (Paragraph 0003:  “a processor”); and
one or more processor-readable storage media storing instructions which, when executed by the one or more processors (Paragraph 0065:  “one or more suitable data and/or program storage devices”), cause performance of:
obtaining an estimated protein value for a meal and an estimated carbohydrate value for the meal (Paragraph 0010:  “meal size values for each of the fat amount, protein amount and carbohydrate amount”);
determining, based on the equivalent carbohydrate value for the meal, an amount of insulin to deliver to a patient to counteract a glucose level increase caused by consumption of the meal (Paragraph 0023:  “The drug may be a blood glucose lowering drug. The drug may be, for example, insulin. The first parameter may correspond to carbohydrate content of a meal and the second parameter may correspond to an expected speed of overall glucose absorption from the meal by the user”); and
causing delivery of insulin to the patient, with an insulin delivery device (Paragraph 0069:  “the insulin pump is configured to wirelessly transmit information relating to insulin delivery to the handheld device 12”), based on generating an output indicative of the amount of insulin to counteract the glucose level increase caused by consumption of the meal (Paragraph 0020:  “The method may further include displaying at least some of the drug administration information on a display unit”).
However, Weinert does not teach converting the estimated protein value into a corresponding carbohydrate value by applying the estimated protein value to a mathematical function or by dividing the estimated protein value by a conversion factor; and
determining an equivalent carbohydrate value for the meal by adding the estimated carbohydrate value for the meal to the corresponding carbohydrate value associated with the estimated protein value.
Singley teaches converting an estimated protein value into a corresponding carbohydrate value by applying the estimated protein value to a mathematical function (shown in step 208) or by dividing the estimated protein value by a conversion factor (CFP multiplier) [0025] (Fig 2); and determining an equivalent carbohydrate value for the meal by adding the estimated carbohydrate value for the meal to the corresponding carbohydrate value associated with the estimated protein value (step 210) [0026] (Fig 2).
It would have been obvious to one of ordinary skill before the effective filling date of the claimed invention to modify the processor-readable storage media storing instructions of Weinert to cause converting the estimated protein value into a corresponding carbohydrate value by applying the estimated protein value to a mathematical function or by dividing the estimated protein value by a conversion factor; and determining an equivalent carbohydrate value for the meal by adding the estimated carbohydrate value for the meal to the corresponding carbohydrate value associated with the estimated protein value, because doing so would help calculate a bolus of insulin for a meal based on both the carbohydrate and protein content of a meal, as recognized by Singley [0027].
Regarding claim 2, Weinert in view of Singley teach the system of claim 1, and Weinert further teaches wherein determining the amount of insulin to deliver to the patient (Paragraph 0023:  “The drug may be a blood glucose lowering drug. The drug may be, for example, insulin. The first parameter may correspond to carbohydrate content of a meal and the second parameter may correspond to an expected speed of overall glucose absorption from the meal by the user”) comprises:
predicting, based on the equivalent carbohydrate value for the meal, amounts of glucose to be absorbed into a bloodstream of the patient over a duration of time due to consumption of the meal (Paragraph 0077:  “the estimate of the expected speed of overall glucose absorption parameter, the shape and duration of the glucose absorption profile may be mapped to the composition of the meal”); and
determining, based on the predicted amounts of glucose to be absorbed into the bloodstream, a bolus dosage of insulin to deliver to the patient (Paragraph 0023:  “The drug may be a blood glucose lowering drug. The drug may be, for example, insulin. The first parameter may correspond to carbohydrate content of a meal and the second parameter may correspond to an expected speed of overall glucose absorption from the meal by the user”).
Regarding claim 3, Weinert in view of Singley teach the system of claim 2, and Weinert further teaches wherein determining the amount of insulin to deliver to the patient comprises:
prior to determining the bolus dosage, obtaining an amount of a basal dosage of insulin previously delivered to the patient (Paragraph 0121:  “Information is entered into a database … In such cases, the other bolus-related information may include, for example, but should not be limited to, number of meal compensation or correction boluses administered, amount of each bolus administered, time between administered boluses and time of administration of first bolus”), and wherein determining the bolus dosage is further based on the amount of the basal dosage of insulin (Paragraph 0157:  “ Any such stored information may be evaluated immediately or in the future, and/or may be re-evaluated when new entries or updates are made to the database and/or to the one or more system control algorithms. Examples of user feedback entered into the system 10 include, but are not limited to, any of the information illustrated in FIG. 13”:  the prior bolus dose is a database entry which is used in the system algorithms used for bolus control).
Regarding claim 5, Weinert in view of Singley teach the system of claim 1, however Weinert does not teach determining the equivalent carbohydrate value comprises:
determining the conversion factor for converting protein to a parameter approximating an effect of the protein on glucose levels of the patient; and
determining the equivalent carbohydrate for the meal based on converting the estimated protein value for the meal into the corresponding carbohydrate value using the conversion factor.
Singley teaches determining the equivalent carbohydrate value comprises:
determining the conversion factor for converting protein to a parameter approximating an effect of the protein on glucose levels of the patient [0025]; and
determining the equivalent carbohydrate for the meal based on converting the estimated protein value for the meal into the corresponding carbohydrate value using the conversion factor [0025 – 0027].
It would have been obvious to one of ordinary skill before the effective filling date of the claimed invention to modify the processor-readable storage media storing instructions of Weinert to cause the determining the equivalent carbohydrate value by:
determining the conversion factor for converting protein to a parameter approximating an effect of the protein on glucose levels of the patient; and
determining the equivalent carbohydrate for the meal based on converting the estimated protein value for the meal into the corresponding carbohydrate value using the conversion factor, because doing so would help calculate a bolus of insulin for a meal based on both the carbohydrate and protein content of a meal, as recognized by Singley [0027].
Regarding claim 7, Weinert in view of Singley teach the system of claim 5, however Weinert does not teach the conversion factor is determined based on a time of day that the patient consumes the meal.
Singley teaches the conversion factor is determined based on a time of day that the patient consumes the meal [0025, 0027, 0061] (Fig 3).
It would have been obvious to one of ordinary skill before the effective filling date of the claimed invention to modify the processor-readable storage media storing instructions of Weinert to determine the conversion factor based on a time of day that the patient consumes the meal, because doing so would help track a patient’s meal times, as recognized by Singley [0061].
Regarding claim 8, Weinert in view of Singley teach the system of claim 5, and Weinert further teaches wherein the instructions, when executed by the one or more processors, cause performance of:
obtaining an estimated fat value for the meal (Paragraph 0010:  “meal size values for each of the fat amount, protein amount and carbohydrate amount”);
determining, based on the estimated fat value, a glucose absorption rate resulting from consumption of the meal, wherein determining the amount of insulin to deliver to the patient is based on the equivalent carbohydrate value for the meal and is further based on the glucose absorption rate resulting from consumption of the meal (Paragraph 0077).
Regarding claim 9, Weinert in view of Singley teach the system of claim 8, and Weinert teaches wherein determining the glucose absorption rate comprises:
determining an absorption rate tuning factor for approximating an effect of fat on the glucose absorption rate (Fig. 4/5 and Paragraph 0081-0083:  amount of fat is tuned based on meal composition and details); and
determining the glucose absorption rate based on the estimated fat value for the meal and the absorption rate tuning factor (Fig. 4/5 and Paragraphs 0081-0083), wherein the absorption rate tuning factor is determined based on historical meal data for the patient (Paragraph 0100:  “a suitable graphical user interface can be defined based on the patient's recorded dietary habits, the outcome of the third process module is a graphical user interface that maps user-selectable feed forward information to insulin delivery information”) and further based on historical glucose level data for the patient (Paragraph 0121 and Fig. 13:  previous glucose levels used).
Regarding claim 10, Weinert teaches a processor-implemented method [abstract, 0015] comprising:
obtaining an estimated protein value for a meal and an estimated carbohydrate value for the meal (Paragraph 0010:  “meal size values for each of the fat amount, protein amount and carbohydrate amount”);
determining, based on the equivalent carbohydrate value for the meal, an amount of insulin to deliver to a patient to counteract a glucose level increase caused by consumption of the meal (Paragraph 0023:  “The drug may be a blood glucose lowering drug. The drug may be, for example, insulin. The first parameter may correspond to carbohydrate content of a meal and the second parameter may correspond to an expected speed of overall glucose absorption from the meal by the user”); and
causing delivery of insulin to the patient, with an insulin delivery device (Paragraph 0069:  “the insulin pump is configured to wirelessly transmit information relating to insulin delivery to the handheld device 12”), based on generating an output indicative of the amount of insulin to counteract the glucose level increase caused by consumption of the meal (Paragraph 0020:  “The method may further include displaying at least some of the drug administration information on a display unit”).
However, Weinert does not teach converting the estimated protein value into a corresponding carbohydrate value by applying the estimated protein value to a mathematical function or by dividing the estimated protein value by a conversion factor; and
determining an equivalent carbohydrate value for the meal by adding the estimated carbohydrate value for the meal to the corresponding carbohydrate value associated with the estimated protein value.
Singley teaches converting an estimated protein value into a corresponding carbohydrate value by applying an estimated protein value to a mathematical function (shown in step 208) or by dividing the estimated protein value by a conversion factor (CFP multiplier) [0025] (Fig 2); and determining an equivalent carbohydrate value for the meal by adding the estimated carbohydrate value for the meal to the corresponding carbohydrate value associated with the estimated protein value (step 210) [0026] (Fig 2).
It would have been obvious to one of ordinary skill before the effective filling date of the claimed invention to modify the method of Weinert to include steps comprising converting the estimated protein value into a corresponding carbohydrate value by applying the estimated protein value to a mathematical function or by dividing the estimated protein value by a conversion factor; and determining an equivalent carbohydrate value for the meal by adding the estimated carbohydrate value for the meal to the corresponding carbohydrate value associated with the estimated protein value, because doing so would help calculate a bolus of insulin for a meal based on both the carbohydrate and protein content of a meal, as recognized by Singley [0027].
Regarding claim 11, Weinert in view of Singley teach the method of claim 10, and Weinert further teaches wherein determining the amount of insulin to deliver to the patient (Paragraph 0023:  “The drug may be a blood glucose lowering drug. The drug may be, for example, insulin. The first parameter may correspond to carbohydrate content of a meal and the second parameter may correspond to an expected speed of overall glucose absorption from the meal by the user”) comprises:
predicting, based on the equivalent carbohydrate value for the meal, amounts of glucose to be absorbed into a bloodstream of the patient over a duration of time due to consumption of the meal (Paragraph 0077:  “the estimate of the expected speed of overall glucose absorption parameter, the shape and duration of the glucose absorption profile may be mapped to the composition of the meal”); and
determining, based on the predicted amounts of glucose to be absorbed into the bloodstream, a bolus dosage of insulin to deliver to the patient (Paragraph 0023:  “The drug may be a blood glucose lowering drug. The drug may be, for example, insulin. The first parameter may correspond to carbohydrate content of a meal and the second parameter may correspond to an expected speed of overall glucose absorption from the meal by the user”).
Regarding claim 12, Weinert in view of Singley teach the method of claim 11, and Weinert further teaches wherein determining the amount of insulin to deliver to the patient comprises:
prior to determining the bolus dosage, obtaining an amount of a basal dosage of insulin previously delivered to the patient (Paragraph 0121:  “Information is entered into a database … In such cases, the other bolus-related information may include, for example, but should not be limited to, number of meal compensation or correction boluses administered, amount of each bolus administered, time between administered boluses and time of administration of first bolus”), and wherein determining the bolus dosage is further based on the amount of the basal dosage of insulin (Paragraph 0157:  “ Any such stored information may be evaluated immediately or in the future, and/or may be re-evaluated when new entries or updates are made to the database and/or to the one or more system control algorithms. Examples of user feedback entered into the system 10 include, but are not limited to, any of the information illustrated in FIG. 13”:  the prior bolus dose is a database entry which is used in the system algorithms used for bolus control).
Regarding claim 14, Weinert in view of Singley teach the method of claim 10, however Weinert does not teach determining the equivalent carbohydrate value comprises:
determining the conversion factor for converting protein to a parameter approximating an effect of the protein on glucose levels of the patient; and
determining the equivalent carbohydrate for the meal based on converting the estimated protein value for the meal into the corresponding carbohydrate value using the conversion factor.
Singley teaches determining the equivalent carbohydrate value comprises:
determining the conversion factor for converting protein to a parameter approximating an effect of the protein on glucose levels of the patient [0025]; and
determining the equivalent carbohydrate for the meal based on converting the estimated protein value for the meal into the corresponding carbohydrate value using the conversion factor [0025 – 0027].
It would have been obvious to one of ordinary skill before the effective filling date of the claimed invention to modify the steps of Weinert to cause the determining the equivalent carbohydrate value by:
determining the conversion factor for converting protein to a parameter approximating an effect of the protein on glucose levels of the patient; and
determining the equivalent carbohydrate for the meal based on converting the estimated protein value for the meal into the corresponding carbohydrate value using the conversion factor, because doing so would help calculate a bolus of insulin for a meal based on both the carbohydrate and protein content of a meal, as recognized by Singley [0027].
Regarding claim 16, Weinert in view of Singley teach the method of claim 14, however Weinert does not teach the conversion factor is determined based on a time of day that the patient consumes the meal.
Singley teaches the conversion factor is determined based on a time of day that the patient consumes the meal [0025, 0027, 0061] (Fig 3).
It would have been obvious to one of ordinary skill before the effective filling date of the claimed invention to modify the steps Weinert to determine the conversion factor based on a time of day that the patient consumes the meal, because doing so would help track a patient’s meal times, as recognized by Singley [0061].
Regarding claim 17, Weinert in view of Singley teach the system of claim 10, and Weinert further teaches wherein the instructions, when executed by the one or more processors, cause performance of:
obtaining an estimated fat value for the meal (Paragraph 0010:  “meal size values for each of the fat amount, protein amount and carbohydrate amount”);
determining, based on the estimated fat value, a glucose absorption rate resulting from consumption of the meal, wherein determining the amount of insulin to deliver to the patient is based on the equivalent carbohydrate value for the meal and is further based on the glucose absorption rate resulting from consumption of the meal (Paragraph 0077).
Regarding claim 18, Weinert teaches one or more non-transitory processor-readable storage media storing instructions, which, when executed by one or more processors [abstract, 0015], cause performance of:
obtaining an estimated protein value for a meal and an estimated carbohydrate value for the meal (Paragraph 0010:  “meal size values for each of the fat amount, protein amount and carbohydrate amount”);
determining, based on the equivalent carbohydrate value for the meal, an amount of insulin to deliver to a patient to counteract a glucose level increase caused by consumption of the meal (Paragraph 0023:  “The drug may be a blood glucose lowering drug. The drug may be, for example, insulin. The first parameter may correspond to carbohydrate content of a meal and the second parameter may correspond to an expected speed of overall glucose absorption from the meal by the user”); and
causing delivery of insulin to the patient, with an insulin delivery device (Paragraph 0069:  “the insulin pump is configured to wirelessly transmit information relating to insulin delivery to the handheld device 12”), based on generating an output indicative of the amount of insulin to counteract the glucose level increase caused by consumption of the meal (Paragraph 0020:  “The method may further include displaying at least some of the drug administration information on a display unit”).
However, Weinert does not teach converting the estimated protein value into a corresponding carbohydrate value by applying the estimated protein value to a mathematical function or by dividing the estimated protein value by a conversion factor; and
determining an equivalent carbohydrate value for the meal by adding the estimated carbohydrate value for the meal to the corresponding carbohydrate value associated with the estimated protein value.
Singley teaches converting an estimated protein value into a corresponding carbohydrate value by applying the estimated protein value to a mathematical function (shown in step 208) or by dividing the estimated protein value by a conversion factor (CFP multiplier) [0025] (Fig 2); and
determining an equivalent carbohydrate value for the meal by adding the estimated carbohydrate value for the meal to the corresponding carbohydrate value associated with the estimated protein value (step 210) [0026] (Fig 2).
It would have been obvious to one of ordinary skill before the effective filling date of the claimed invention to modify the processor-readable storage media storing instructions of Weinert to cause converting the estimated protein value into a corresponding carbohydrate value by applying the estimated protein value to a mathematical function or by dividing the estimated protein value by a conversion factor; and
determining an equivalent carbohydrate value for the meal by adding the estimated carbohydrate value for the meal to the corresponding carbohydrate value associated with the estimated protein value, because doing so would help calculate a bolus of insulin for a meal based on both the carbohydrate and protein content of a meal, as recognized by Singley [0027].
Regarding claim 19, Weinert in view of Singley teach the limitations of claim 18, and Weinert further teaches wherein determining the amount of insulin to deliver to the patient comprises:
prior to determining the bolus dosage, obtaining an amount of a basal dosage of insulin previously delivered to the patient (Paragraph 0121:  “Information is entered into a database … In such cases, the other bolus-related information may include, for example, but should not be limited to, number of meal compensation or correction boluses administered, amount of each bolus administered, time between administered boluses and time of administration of first bolus”), and wherein determining the bolus dosage is further based on the amount of the basal dosage of insulin (Paragraph 0157:  “ Any such stored information may be evaluated immediately or in the future, and/or may be re-evaluated when new entries or updates are made to the database and/or to the one or more system control algorithms. Examples of user feedback entered into the system 10 include, but are not limited to, any of the information illustrated in FIG. 13”:  the prior bolus dose is a database entry which is used in the system algorithms used for bolus control).
Regarding claim 20, Weinert in view of Singley teach the limitations of claim 18, however Weinert does not teach determining the equivalent carbohydrate value comprises:
determining the conversion factor for converting protein to a parameter approximating an effect of the protein on glucose levels of the patient; and
determining the equivalent carbohydrate for the meal based on converting the estimated protein value for the meal into the corresponding carbohydrate value using the conversion factor.
Singley teaches determining the equivalent carbohydrate value comprises:
determining the conversion factor for converting protein to a parameter approximating an effect of the protein on glucose levels of the patient [0025]; and
determining the equivalent carbohydrate for the meal based on converting the estimated protein value for the meal into the corresponding carbohydrate value using the conversion factor [0025 – 0027].
It would have been obvious to one of ordinary skill before the effective filling date of the claimed invention to modify the steps of Weinert to cause the determining the equivalent carbohydrate value by:
determining the conversion factor for converting protein to a parameter approximating an effect of the protein on glucose levels of the patient; and
determining the equivalent carbohydrate for the meal based on converting the estimated protein value for the meal into the corresponding carbohydrate value using the conversion factor, because doing so would help calculate a bolus of insulin for a meal based on both the carbohydrate and protein content of a meal, as recognized by Singley [0027].
Claim(s) 4 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Weinert in view of Singley as applied to claims 2 and 11 above, and further in view of Mazlish (US 20180200439 A1) (cited in previous Office Action).
Regarding claim 4, Weinert in view of Singley teach the system of claim 2, however they fail to teach wherein determining the amount of insulin to deliver to the patient comprises:
identifying a plurality of candidate dosages; for each candidate dosage of the plurality of candidate dosages, predicting a respective amount of time within a target range for the patient's glucose levels; and selecting a candidate dosage that results in a maximum amount of time within the target range.
Mazlish teaches wherein determining an amount of insulin to deliver to the patient comprises:
identifying a plurality of candidate dosages (Paragraph 20:  “ For example, such personalization may include generating multiple insulin delivery profiles and projected blood glucose levels for each of the insulin delivery profiles, and selecting the profile that closely tracks towards a target blood glucose level”);
for each candidate dosage of the plurality of candidate dosages, predicting a respective amount of time within a target range for the patient's glucose levels (Paragraph 0022:  “Methods and systems provided herein can use a model to predict multiple future blood glucose levels for multiple different basal insulin delivery profiles or basal insulin delivery rates, and select one of the basal insulin delivery profiles or basal insulin delivery rates based on prediction of which profile or rate will approximate a target blood glucose level, or more specifically, select the profile that minimizes the differences between the predicted future blood glucose values and one or more target blood glucose values”); and
selecting a candidate dosage that results in a maximum amount of time within the target range (Paragraph 0022:  “In some cases, the profile that minimizes, lessens, or lowers variations from one or more target blood glucose levels in the future may be selected”).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Weinert in view of Singley to incorporate the multiple candidate dosages of Mazlish, because it allows for the best and most optimal treatment to be given to a patient to control their blood glucose level (Paragraph 0022 of Mazlish).
Regarding claim 13, Weinert in view of Singley teach the method of claim 11, however they fail to teach wherein determining the amount of insulin to deliver to the patient comprises:
identifying a plurality of candidate dosages; for each candidate dosage of the plurality of candidate dosages, predicting a respective amount of time within a target range for the patient's glucose levels; and selecting a candidate dosage that results in a maximum amount of time within the target range.
Mazlish teaches wherein determining an amount of insulin to deliver to the patient comprises:
identifying a plurality of candidate dosages (Paragraph 20:  “ For example, such personalization may include generating multiple insulin delivery profiles and projected blood glucose levels for each of the insulin delivery profiles, and selecting the profile that closely tracks towards a target blood glucose level”);
for each candidate dosage of the plurality of candidate dosages, predicting a respective amount of time within a target range for the patient's glucose levels (Paragraph 0022:  “Methods and systems provided herein can use a model to predict multiple future blood glucose levels for multiple different basal insulin delivery profiles or basal insulin delivery rates, and select one of the basal insulin delivery profiles or basal insulin delivery rates based on prediction of which profile or rate will approximate a target blood glucose level, or more specifically, select the profile that minimizes the differences between the predicted future blood glucose values and one or more target blood glucose values”); and
selecting a candidate dosage that results in a maximum amount of time within the target range (Paragraph 0022:  “In some cases, the profile that minimizes, lessens, or lowers variations from one or more target blood glucose levels in the future may be selected”).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Weinert in view of Singley to incorporate the multiple candidate dosages of Mazlish, because it allows for the best and most optimal treatment to be given to a patient to control their blood glucose level (Paragraph 0022 of Mazlish).
Claim(s) 6 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Weinert in view of Singley as applied to claim 5 and 14 above, and further in view of US 5836312 A to Moore.
Regarding claim 6, Weinert in view of Singley teach the system of claim 5, however they do not teach the conversion factor is determined based on historical meal data for the patient and further based on historical glucose level data for the patient.
Moore teaches a conversion factor is determined based on historical meal data and further based on historical glucose level data for the patient [abstract; col 7, ln 57 – col 8, ln 15; col 8, ln 35 – col 9, ln 2].
It would have been obvious to one of ordinary skill before the effective filling date of the claimed invention to modify the system of Weinert and Singley to determine the conversion factor based on historical meal data for the patient and historical glucose level data for the patient, because doing so would help adjust the conversion factor according to a plurality of physiological measurements, as recognized by Moore [col 6, ln 24 – col 7, ln 22].
Regarding claim 15, Weinert in view of Singley teach the method of claim 14, however they do not teach the conversion factor is determined based on historical meal data for the patient and further based on historical glucose level data for the patient.
Moore teaches a conversion factor is determined based on historical meal data and further based on historical glucose level data for the patient [abstract; col 7, ln 57 – col 8, ln 15; col 8, ln 35 – col 9, ln 2].
It would have been obvious to one of ordinary skill before the effective filling date of the claimed invention to modify the system of Weinert and Singley to determine the conversion factor based on historical meal data for the patient and historical glucose level data for the patient, because doing so would help adjust the conversion factor according to a plurality of physiological measurements, as recognized by Moore [col 6, ln 24 – col 7, ln 22].
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US 5836312 A, US 20080294373 A1, and US 20200268968 A1 are mentioned because they disclose systems and methods for determining glycose level changes and insulin needs based on carbohydrate and protein intake. US 20120315609 A1 and US 20210205534 A1 are mentioned because they disclose systems and methods for monitoring food intake.

CITED REFERENCE SUMMARIES: Ref US20090006061A1: Claims:
A computerized system used by a user(s) to developing patient specific therapies for chronic disease management of a patient(s), the system comprising: a data collection module which enables the system to collect patient specific data according to a data collection protocol and performs integrity and quality checks on the patient specific data; a user interface which enables the user to select a patient model from a plurality of patient models provided by the system; a module validation module which enables the system to validate the selected patient model; an analyses module which enables the system to apply the patient specific data to the selected patient model to extract useful patient specific physiological information, and to use the extracted patient specific physiological information to develop one or more patient specific therapies for treating the chronic disease of the patient; a result validation and presentation module which enables the system to validate the one or more patient specific therapies and to present validated ones of the one or more patient specific therapies on the user interface for approval.
a data collection module which enables the system to collect patient specific data according to a data collection protocol and performs integrity and quality checks on the patient specific data;
a user interface which enables the user to select a patient model from a plurality of patient models provided by the system;
a module validation module which enables the system to validate the selected patient model;
an analyses module which enables the system to apply the patient specific data to the selected patient model to extract useful patient specific physiological information, and to use the extracted patient specific physiological information to develop one or more patient specific therapies for treating the chronic disease of the patient;
a result validation and presentation module which enables the system to validate the one or more patient specific therapies and to present validated ones of the one or more patient specific therapies on the user interface for approval.
The computerized system according to claim 1 wherein the data collection protocol dictates specific data to be collected, manner to be collected, and compliancy procedure.
The computerized system according to claim 1 wherein for the integrity and quality checks the data collection module enables the system to check for inconsistencies between collected patient specific data and the data collection protocol and time stamps, to determine whether collection performed over a required time period, and to determine for the collected patient data whether data values are in predefined ranges and provide a predetermined number of samples within a certain time window.
The computerized system according to claim 1 wherein the system provides the plurality of patient models from at least one of a client computer, a computer server, a portable memory device, computer storage, and a computer readable medium.
The computerized system according to claim 1 wherein the plurality of patient models each mathematically represents at least one aspect of human physiology, and provides mapping to different physiological states, conditions or parameters.
The computerized system according to claim 1 wherein the module validation module enables the system to perform on the selected patient model at least one of a Bayesian analysis, a cost function analysis, parameter estimation, statistical analysis, numeric analysis, range analysis, gain values analysis, test scenarios analysis, simulations, and modeling.
The computerized system according to claim 1 wherein the model validation module enables the system to determine model parameters which are then used to validate the selected patient model.
The computerized system according to claim 1 wherein the analyses module provides analysis tools which enables the system to perform at least one of simulations, statistical analysis, sensitivity analysis, visualizations, information extraction, optimizations, and to provide recommendations which include at least one of type, amount, and timing for dosing, exercise, and meals.
The computerized system according to claim 1 further comprising a rule/guideline sets module which governs the system in collection of the patient specific data according to the data collection protocol.
The computerized system according to claim 1 wherein the result validation and presentation module provides simulation tools which enable the system to test the one or more patient specific therapies for at least one of robustness, stability, sensitivity to parameter variation, and effectiveness, and to generate confidence intervals.
The computerized system according to claim 1 wherein the system is a client/server system.
A computerized system for developing patient-specific therapies based on dynamic modeling of patient-specific physiology, the system comprising a computer configured to provide access to a number of software modules stored in at least one database or other memory unit, the number of software modules including: a first software module configured to provide access via the computer to one or more data collection protocols defining at least a type of patient-specific data to be collected and a manner in which the patient-specific data is to be collected, a second software module configured to provide access via the computer to information which develop one or more patient-specific models configured to simulate one or more aspects of physiology of the patient, a third software module configured to provide access via the computer to one or more software tools that apply patient-specific data, collected according to the one or more data collection protocols, to the one or more developed patient specific models to determine therefrom one or more patient-specific therapies, and a fourth software module configured to provide access via the computer to one or more software validation tools that validate the patient-specific therapies and to present the one or more patient-specific therapies on the computer.
a first software module configured to provide access via the computer to one or more data collection protocols defining at least a type of patient-specific data to be collected and a manner in which the patient-specific data is to be collected,
a second software module configured to provide access via the computer to information which develop one or more patient-specific models configured to simulate one or more aspects of physiology of the patient,
a third software module configured to provide access via the computer to one or more software tools that apply patient-specific data, collected according to the one or more data collection protocols, to the one or more developed patient specific models to determine therefrom one or more patient-specific therapies, and
a fourth software module configured to provide access via the computer to one or more software validation tools that validate the patient-specific therapies and to present the one or more patient-specific therapies on the computer.
A computer implemented method of developing patient specific therapies for chronic disease management of a patient(s) on a computerized system, the method comprising: providing a data collection module which enables the system to collect patient specific data according to a data collection protocol and performs integrity and quality checks on the patient specific data; providing a user interface which enables the user to select a patient model from a plurality of patient models provided by the system; providing a module validation module which enables the system to validate the selected patient model; providing an analyses module which enables the system to apply the patient specific data to the selected patient model to extract useful patient specific physiological information, and to use the extracted patient specific physiological information to develop one or more patient specific therapies for treating the chronic disease of the patient; providing a result validation and presentation module which enables the system to validate the one or more patient specific therapies and to present validated ones of the one or more patient specific therapies on the user interface for approval.
providing a data collection module which enables the system to collect patient specific data according to a data collection protocol and performs integrity and quality checks on the patient specific data;
providing a user interface which enables the user to select a patient model from a plurality of patient models provided by the system;
providing a module validation module which enables the system to validate the selected patient model;
providing an analyses module which enables the system to apply the patient specific data to the selected patient model to extract useful patient specific physiological information, and to use the extracted patient specific physiological information to develop one or more patient specific therapies for treating the chronic disease of the patient;
providing a result validation and presentation module which enables the system to validate the one or more patient specific therapies and to present validated ones of the one or more patient specific therapies on the user interface for approval.
The computer implemented method according to claim 13 further comprises using the data collection protocol to dictate specific data to be collected, manner to be collected, and a compliancy procedure.
The computer implemented method according to claim 13 further comprises using the system to check for inconsistencies between collected patient specific data and the data collection protocol and time stamps, to determine whether collection performed over a required time period, and to determine for the collected patient data whether data values are in predefined ranges and provide a predetermined number of samples.
The computer implemented method according to claim 13 further comprises using the system to provide the plurality of patient models from at least one of a computer server, a portable memory device, computer storage, and a computer readable medium.
The computer implemented method according to claim 13 further comprises using the system to modify the selected patient model and add a new patient model which mathematically represent at least one aspect of human physiology, and which provides mapping to different physiological states, conditions or parameters.
The computer implemented method according to claim 13 further comprises using the system to perform on the selected patient model at least one of a Bayesian analysis, a cost function analysis, parameter estimation, statistical analysis, numeric analysis, range analysis, gain values analysis, test scenarios analysis, simulations, and modeling.
The computer implemented method according to claim 13 further comprises using the system to determine model parameters which are then used to validate the selected patient model.
The computer implemented method according to claim 13 further comprises using the system to perform at least one of simulations, statistical analysis, sensitivity analysis, visualizations, information extraction, optimizations, and to provide recommendations which include at least one of type, amount, and timing for dosing, exercise, and meals.
The computer implemented method according to claim 13 further comprising using a rule/guideline sets module which governs the system in collection of the patient specific data according to the data collection protocol.
The computer implemented method according to claim 13 further comprises using system to test the one or more patient specific therapies for at least one of robustness, stability, sensitivity to parameter variation, and effectiveness, and to generate confidence intervals.
The computer implemented method according to claim 13 further comprises providing the system as a client/server system.
A computer implemented method for developing patient-specific therapies based on dynamic modeling of patient-specific physiology on a computer, comprising: configuring the computer to provide access to a number of software modules stored in at least one database or other memory unit; configuring a first one of the software modules to provide access via the computer to one or more data collection protocols defining at least a type of patient-specific data to be collected and a manner in which the patient-specific data is to be collected, configuring a second one of the software modules to provide access via the computer to information which develop one or more patient-specific models configured to simulate one or more aspects of physiology of the patient, configuring a third one of the software modules to provide access via the computer to one or more software tools that apply patient-specific data, collected according to the one or more data collection protocols, to the one or more developed patient specific models to determine therefrom one or more patient-specific therapies, and configuring a fourth one of the software modules to provide access via the computer to one or more software validation tools that validate the patient-specific therapies and present the one or more patient-specific therapies on the computer.
configuring the computer to provide access to a number of software modules stored in at least one database or other memory unit;
configuring a first one of the software modules to provide access via the computer to one or more data collection protocols defining at least a type of patient-specific data to be collected and a manner in which the patient-specific data is to be collected,
configuring a second one of the software modules to provide access via the computer to information which develop one or more patient-specific models configured to simulate one or more aspects of physiology of the patient,
configuring a third one of the software modules to provide access via the computer to one or more software tools that apply patient-specific data, collected according to the one or more data collection protocols, to the one or more developed patient specific models to determine therefrom one or more patient-specific therapies, and
configuring a fourth one of the software modules to provide access via the computer to one or more software validation tools that validate the patient-specific therapies and present the one or more patient-specific therapies on the computer.
Ref US20070179434A1: Claims:
A system for determining drug administration information, the system comprising: an input device providing for user input of feed forward information having a first parameter component and a second parameter component, a data storage device having stored therein a map correlating values of the first and second parameter components to drug administration information, and a processor responsive to user input of the feed forward information to determine corresponding drug administration information according to the map.
an input device providing for user input of feed forward information having a first parameter component and a second parameter component,
a data storage device having stored therein a map correlating values of the first and second parameter components to drug administration information, and
a processor responsive to user input of the feed forward information to determine corresponding drug administration information according to the map.
The system of claim 1 further comprising a display unit, and wherein the processor is configured to display at least some of the corresponding drug administration information on the display unit.
and wherein the processor is configured to display at least some of the corresponding drug administration information on the display unit.
The system of claim 1 wherein the input device includes a display unit, and wherein the processor is configured to control the display unit to display a graphical user interface having a first axis defined by values of the first parameter component and a second axis defined by values of the second parameter component, the graphical user interface providing for the user input of feed forward information in the form of a single user selection of a corresponding pair of values of the first and second parameter components.
and wherein the processor is configured to control the display unit to display a graphical user interface having a first axis defined by values of the first parameter component and a second axis defined by values of the second parameter component, the graphical user interface providing for the user input of feed forward information in the form of a single user selection of a corresponding pair of values of the first and second parameter components.
The system of claim 3 wherein the graphical user interface includes a touch responsive interface providing for the single user selection of the corresponding pair of values of the first and second parameter components.
The system of claim 3 wherein the graphical user interface defines a grid-type user interface providing for the single user selection of discrete pairs of values of the first and second parameter components.
The system of claim 3 wherein the graphical user interface defines a continuous function of the first and second parameter components.
The system of claim 1 wherein the input device includes a display unit, and wherein the processor is configured to control the display unit to display a graphical user interface having a first axis defined by a plurality of identifiers of the first parameter component and a second axis defined by values of the second parameter component, the graphical user interface providing for the user input of feed forward information in the form of user selection of pairs of each of the plurality of identifiers of the first parameter component and corresponding values of the second parameter component.
and wherein the processor is configured to control the display unit to display a graphical user interface having a first axis defined by a plurality of identifiers of the first parameter component and a second axis defined by values of the second parameter component, the graphical user interface providing for the user input of feed forward information in the form of user selection of pairs of each of the plurality of identifiers of the first parameter component and corresponding values of the second parameter component.
The system of claim 7 wherein the graphical user interface includes a touch responsive interface providing for the user selection of the pairs of each of the plurality of identifiers of the first parameter component and corresponding values of the second parameter component.
The system of claim 7 wherein the graphical user interface defines a grid-type user interface providing for the user selection of discrete pairs of each of the plurality of identifiers of the first parameter component and corresponding values of the second parameter component.
The system of claim 1 wherein the drug is a blood glucose lowering drug.
The system of claim 10 wherein the drug is insulin.
The system of claim 11 wherein the input device is configured to provide for user input of feed forward information in the form of meal information having the first parameter component corresponding to carbohydrate content and the second parameter component corresponding to an expected speed of overall glucose absorption from the meal by the user.
The system of claim 12 wherein the input device includes a display unit, and wherein the processor is configured to control the display unit to display a graphical user interface having a first axis defined by values of the carbohydrate content values and a second axis defined by values of the expected speed of overall glucose absorption from the meal by the user, the
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