Office Action 4: Final Rejection (2024-06-26)
Rejection types: 103 - Obviousness

CLAIMS:
Amendments to the Claims:

The following Listing of Claims will replace all prior versions, and listings, of claims in the application:

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 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 patient-specific conversion factor;
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;
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 the conversion factor for converting the estimated protein value 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 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 patient-specific conversion factor;
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;
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 the conversion factor for converting the estimated protein value 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 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 patient-specific conversion factor;
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;
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 the conversion factor for converting the estimated protein value 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.

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 .
Acknowledgement of Amendments
This Office Action is responsive to the amendment filed 02/14/2024. 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 02/14/2024, with respect to the objections of claims 5, 14, and 20 have been fully considered and are persuasive.  The objections of claims 5, 14, and 20 have has been withdrawn.
Applicant’s arguments, see pg 10 - 11, filed 02/14/2024, with respect to the rejection(s) of claim(s) 1, 6 – 7, 10, 15 – 16, and 18 under 35 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 20090006129 A1 to Thukral, et al. (hereinafter Thukral).
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) 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over US 20090006129 A1 to Thukral, et al. (hereinafter Thukral) in view of US 20050187749 A1 to Singley (cited in previous Office Action).
Thukral teaches a system [abstract] comprising:
one or more processors (16, 34) [0063-0064] (Fig 2); and
one or more processor-readable storage media (78) storing instructions [0073] (Fig 3) which, when executed by the one or more processors, cause performance of:
obtaining an estimated protein value for a meal and an estimated carbohydrate value for the meal [0146];
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 patient-specific conversion factor ([0212 -0213], the estimated protein value is inherently converted to an equivalent carbohydrate amount using some sort of mathematical function taking into account the patient-specific conversion factor of their gut glucose absorption based on what type of meal the patient is eating);
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 (846) [0163, 0212-0213, 0236] (Fig 9); and
causing delivery of insulin to the patient (850), 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 [0163] (Fig 9).
However, Thukral does not teach 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 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 filing date of the claimed invention to modify Thukral to determine 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, Thukral in view of Singley teach the system of claim 1, and Thukral further teaches 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 [0212-0213]; 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 [0163, 0213] (Fig 9).
Regarding claim 3, Thukral in view of Singley teach the system of claim 2, and Thukral further teaches 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 ([0142 - 0144], basal insulin dosage delivered prior to an event such as a patient exercising or eating a meal), and wherein determining the bolus dosage is further based on the amount of the basal dosage of insulin ([0142-0144], bolus dosage compensation for an event such as exercising or eating a meal is based on a prior basal dosage of insulin to help a patient maintain a target basal glucose).
Regarding claim 4, Thukral in view of Singley teach the system of claim 2, and Thukral further teaches determining the bolus dosage comprises:
identifying a plurality of candidate dosages [0135, 0182];
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 [0135, 0182] (Fig 9); and
selecting a candidate dosage that results in a maximum amount of time within the target range ([0182], a candidate dosage is selected which best places the patient’s glucose levels in the target glucose zone).
Regarding claim 5, Thukral in view of Singley teach the system of claim 1, and Thukral further teaches determining the equivalent carbohydrate value comprises:
determining the conversion factor for converting the estimated protein value to a parameter approximating an effect of the protein on glucose levels of the patient [0212]; 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 [0212].
Regarding claim 6, Thukral in view of Singley teach the system of claim 5, and Thukral further teaches the conversion factor is determined based on historical meal data for the patient and further based on historical glucose level data for the patient ([0143 - 0144, 0147, 0153, 0212- 0213], meal compensator uses historical meal data and historical glucose level data to determine the glucose absorption/protein equivalent carbohydrate conversion for proteins for the current meal).
Regarding claim 7, Thukral in view of Singley teach the system of claim 5, and Thukral further teaches the conversion factor is determined based on a time of day that the patient consumes the meal [0172, 0212].
Regarding claim 8, Thukral in view of Singley teach the system of claim 5, and Thukral further teaches wherein the instructions, when executed by the one or more processors, cause performance of:
obtaining an estimated fat value for the meal [0212];
determining, based on the estimated fat value, a glucose absorption rate resulting from consumption of the meal [0212 -0213],
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 [0212 -0213].
Regarding claim 9, Thukral in view of Singley teach the system of claim 8, and Thukral further teaches determining the glucose absorption rate comprises:
determining an absorption rate tuning factor for approximating an effect of fat on the glucose absorption rate [0212- 0213]; and
determining the glucose absorption rate based on the estimated fat value for the meal and the absorption rate tuning factor [0212 -0213],
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 ([0143 - 0144, 0147, 0153, 0212- 0213], meal compensator uses historical meal data and historical glucose level data to determine the glucose absorption rate).
Regarding claim 10, Thukral teaches a processor-implemented method [abstract, 0063-0064] comprising:
obtaining an estimated protein value for a meal and an estimated carbohydrate value for the meal [0146];
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 patient-specific conversion factor ([0212 -0213], the estimated protein value is inherently converted to an equivalent carbohydrate amount using some sort of mathematical function taking into account the patient-specific conversion factor of their gut glucose absorption based on what type of meal the patient is eating);
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 (846) [0163, 0212-0213, 0236] (Fig 9); and
causing delivery of insulin to the patient (850), 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 [0163] (Fig 9).
However, Thukral does not teach 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 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 filing date of the claimed invention to modify Thukral to determine 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, Thukral in view of Singley teach the method of claim 10, and Thukral further teaches 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 [0212-0213]; 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 [0163, 0213] (Fig 9).
Regarding claim 12, Thukral in view of Singley teach the method of claim 11, and Thukral further teaches 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 ([0142 - 0144], basal insulin dosage delivered prior to an event such as a patient exercising or eating a meal), and wherein determining the bolus dosage is further based on the amount of the basal dosage of insulin ([0142-0144], bolus dosage compensation for an event such as exercising or eating a meal is based on a prior basal dosage of insulin to help a patient maintain a target basal glucose).
Regarding claim 13, Thukral in view of Singley teach the method of claim 11, and Thukral further teaches determining the bolus dosage comprises:
identifying a plurality of candidate dosages [0135, 0182];
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 [0135, 0182] (Fig 9); and
selecting a candidate dosage that results in a maximum amount of time within the target range ([0182], a candidate dosage is selected which best places the patient’s glucose levels in the target glucose zone).
Regarding claim 14, Thukral in view of Singley teach the method of claim 10, and Thukral further teaches determining the equivalent carbohydrate value comprises:
determining the conversion factor for converting the estimated protein value to a parameter approximating an effect of the protein on glucose levels of the patient [0212]; 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 [0212].
Regarding claim 15, Thukral in view of Singley teach the method of claim 14, and Thukral further teaches the conversion factor is determined based on historical meal data for the patient and further based on historical glucose level data for the patient ([0143 - 0144, 0147, 0153, 0212- 0213], meal compensator uses historical meal data and historical glucose level data to determine the glucose absorption/protein equivalent carbohydrate conversion for proteins for the current meal).
Regarding claim 16, Thukral in view of Singley teach the method of claim 14, and Thukral further teaches the conversion factor is determined based on a time of day that the patient consumes the meal [0172, 0212].
Regarding claim 17, Thukral in view of Singley teach the method of claim 10, and Thukral further teaches wherein the instructions, when executed by the one or more processors, cause performance of:
obtaining an estimated fat value for the meal [0212];
determining, based on the estimated fat value, a glucose absorption rate resulting from consumption of the meal [0212 -0213],
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 [0212 -0213].
Regarding claim 18, Thukral teaches one or more non-transitory processor-readable storage media storing instructions [0073] which, when executed by one or more processors [0063-0064], cause performance of:
obtaining an estimated protein value for a meal and an estimated carbohydrate value for the meal [0146];
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 patient-specific conversion factor ([0212 -0213], the estimated protein value is inherently converted to an equivalent carbohydrate amount using some sort of mathematical function taking into account the patient-specific conversion factor of their gut glucose absorption based on what type of meal the patient is eating);
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 (846) [0163, 0212-0213, 0236] (Fig 9); and
causing delivery of insulin to the patient (850), 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 [0163] (Fig 9).
However, Thukral does not teach 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 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 filing date of the claimed invention to modify Thukral to determine 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, Thukral in view of Singley teach the one or more non-transitory processor-readable storage media of claim 18, and Thukral further teaches 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 [0212-0213];
determining, based on the predicted amounts of glucose to be absorbed into the bloodstream, a bolus dosage of insulin to deliver to the patient [0163, 0213] (Fig 9); and
prior to determining the bolus dosage, obtaining an amount of a basal dosage of insulin previously delivered to the patient ([0142 - 0144], basal insulin dosage delivered prior to an event such as a patient exercising or eating a meal), and wherein determining the bolus dosage is further based on the amount of the basal dosage of insulin ([0142-0144], bolus dosage compensation for an event such as exercising or eating a meal is based on a prior basal dosage of insulin to help a patient maintain a target basal glucose).
Regarding claim 20, Thukral in view of Singley teach the one or more non-transitory processor-readable storage media of claim 18, and Thukral further teaches teaches determining the equivalent carbohydrate value comprises:
determining the conversion factor for converting the estimated protein value to a parameter approximating an effect of the protein on glucose levels of the patient [0212];
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 [0212],
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 ([0143 - 0144, 0147, 0153, 0212- 0213], meal compensator uses historical meal data and historical glucose level data to determine the glucose absorption/protein equivalent carbohydrate conversion for proteins for the current meal).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action.  Accordingly, THIS ACTION IS MADE FINAL.  See MPEP § 706.07(a).  Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action.  In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any 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 date of this final action.

APPLICANT REBUTTAL: REMARKS
Claims 1, 5, 10, 14, 18, and 20 are amended. Claims 1-20 remain pending. Applicant respectfully requests reconsideration in view of the remarks presented below.
Interview Summary
Applicant thanks the Examiner for the telephonic interview conducted January 11, 2024. Participating in the interview were Examiner Raymond P. Dulman and Applicant's representative, Arthi Srinivasan (Reg. No. 73,675). During the interview, Applicant'srepresentative discussed the rejection of independent claim 1 under 35 U.S.C. § 103 in light of a proposed amendment to claim 1. The Examiner indicated that the proposed amendment would overcome the current rejection but that further search would be needed. Applicant notes similar amendments to those discussed during the interview have been made to the independent claims herein.
No agreement regarding allowability was reached.
The Objection to Claims 5,
14, and 20
Claims 5, 14, and 20 were objected to due to informalities. Applicant has amended these claims to recite "converting
the estimated
protein
value"
as requested by the Office.
Accordingly, Applicant respectfully requests that the objection be withdrawn.
Claim Rejections Under 35 U.S.C.
&
The Office Action rejected claims 1-3, 5, 7-12, 14, and 16-20 under 35 U.S.C. § 103 as
being unpatentable over Weinert (U.S. Publication No. 20070179434 Al, hereinafter WEINERT) in view of Singley (U.S. Publication No. 20050187749 A1, hereinafter STINGLEY). Claims 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, and further in view of Mazlish (U.S. Publication No. 20180200439 Al, hereinafter MAZLISH). Claims 6 and 15 are rejected under 35 U.S.C. § 103 as being unpatentable over WEINERT in view of SINGLEY as applied to claims 5 and 14, and further in view of Moore (U.S. Patent No. 5836312 A, hereinafter MOORE).
Without conceding in the basis of the rejection, and solely to expedite prosecution of this application, Applicant has amended independent claims 1, 10, and 18 to recite, inter alia,
"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
p
atient-s
p
ecific
conversion factor." Support for this amendment can be found in at least paragraph [0080] of the originally filed specification.
In rejecting independent claim 1, prior to the current amendments, the Office correctly acknowledged that Weinert 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 carbohydrate value." However, the Office asserted that Singley discloses this feature. (Office Action, page 5).
Singley states that "the grams of carbs from proteins can be calculated by taking the food weight of the food being weighed by the scale and multiplying it by a multiplier appropriate for the weight units being used to weigh the food. For example, it is known that 1 ounce of a 'protein food' (e.g., meat, poultry, etc.) equals 4.2 grams of carbs from protein. Thus, if we have
3 ounces of chicken, we can calculate that we have 12.6 grams carbs from that protein." (Singley, paragraph [0025]). In other words, Singley describes using a fixed carbs from protein value for a given food. Nowhere does Singley disclose or suggest using a
p
atient-s
p
ecific conversion factor
to "convert the estimated protein value into a corresponding carbohydrate value."
Moreover, Applicant notes that during the telephonic interview, the Examiner agreed the amendment to independent claims 1, 10, and 18 would overcome the current rejection over Weinert in view of Singley.
Accordingly, Applicant respectfully submits that independent claims 1, 10, and 18 are allowable. Moreover, Applicant respectfully submits that dependent claims 2-9, 11-17, 19, and 20, each of which depend from one of independent claims 1, 10, and 18 are allowable for at least the same reasons independent claims 1, 10, and 18 are allowable.
Dependent Claims 6 and
IS
Applicant respectfully submits dependent claims 6 and 15, which recite "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" are allowable for at least a second reason.
In rejecting dependent claims 6 and 15, the Office conceded that Weinert and Singley fail to disclose or suggest that the conversion factor is determined based on historical meal data and historical glucose level data, but asserted that Moore discloses this feature. (Office Action, page 21).
The cited portion of Moore describes "determining whether [an] information string
relates to a consumed item or measured physiological parameter," which is "stored along with time data coupled thereto in a subdirectory directed to the physiological measurement." In other words, the cited portion of Moore merely describes techniques for generating a log of items consumed and physiological data, and makes no mention of
"a conversion factor,"
let alone one used to "convert [an] estimated protein value into a corresponding carbohydrate value." The cited portion of Moore is entirely unrelated to converting an estimated protein value into a corresponding carbohydrate value, and accordingly cannot and does not disclose or suggest that a conversion factor for performing such a conversion is "determined based on historical meal data for the patient and further based on historical glucose level data for the patient."
Dependent Claims 7 and 16
Applicant respectfully submits that dependent claims 7 and 16, which recite "the
conversion factor is determined based on a time of day that the user consumes the meal," are allowable for at least a second reason.
In rejecting dependent claims 7 and 16, the Office asserted that Singley discloses this
feature. Singley states "[t]he tool can record the event with the following pieces of information: Time of meal, Foods and weights, Meal bolus computation, BG reading, time of BG reading (pre meal), meal type (Breakfast, lunch, dinner), HBG adjustment, & LBG adjustment (if any)." (Singley, paragraph [0061], cited by the Office).
Applicant respectfully submits that Singley merely states that time of day can be
recorded, and makes no mention of a
conversion factor being determined based on the time of
day
,
as recited in dependent claims 7 and 16.
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
1.	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
2.	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 25 September 2024 has been entered.
Response to Amendment
3.	According to the Amendment, filed 25 September 2024, the status of the claims is as follows:
Claims 1, 10, 18, and 20 are currently amended;
Claims 2-4, 7-9, 11-13, 16, 17, and 19 are as originally filed;
Claims 5 and 14 are previously presented; and
Claims 6 and 15 are cancelled.
Response to Arguments
4.	Applicant’s arguments, see Remarks, pp. 9-11, filed 25 September 2024, with respect to the rejection of claims 1-20 under 35 U.S.C. 103 as being unpatentable over Thukral et al., U.S. Patent Application Publication No. 2009/0006129 A1 (“Thukral”), in view of Singley, U.S. Patent Application Publication No. 2005/0187749 A1 (“Singley”), have been fully considered, and are persuasive.  The rejection of claims 1-20 has been withdrawn.
Reasons for Allowance
5.	Claims 1-5, 7-14, and 16-20 are allowed.
6.	The following is an examiner’s statement of reasons for allowance:
As to Claims 1-5 and 7-9, neither Thukral, Singley nor the prior art of record teaches the system of base claim 1, including the following, in combination with all other limitations of the base claim:
…
one or more processor-readable storage media storing instructions which, when executed by the one or more processors, cause performance of:
…
obtaining a patient-specific conversion factor that indicates an effect of protein on glucose levels of a patient, wherein the patient-specific conversion factor is determined based on predictions of glucose level rise for the patient using historical meal data and historical glucose levels of the patient;
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 the patient-specific conversion factor;
…
As to Claims 10-14, 16, and 17, neither Thukral, Singley nor the prior art of record teaches the processor-implemented method of base claim 10, including the following, in combination with all other limitations of the base claim:
…
obtaining a patient-specific conversion factor that indicates an effect of protein on glucose levels of a patient, wherein the patient-specific conversion factor is determined based on predictions of glucose level rise for the patient using historical meal data and historical glucose levels of the patient;
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 the patient-specific conversion factor;
…
As to Claims 18-20, neither Thukral, Singley nor the prior art of record teaches the one or more non-transitory processor-readable storage media of base claim 18, including the following, in combination with all other limitations of the base claim:
…
obtaining a patient-specific conversion factor that indicates an effect of protein on glucose levels of a patient, wherein the patient-specific conversion factor is determined based on predictions of glucose level rise for the patient using historical meal data and historical glucose levels of the patient;
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 the patient-specific conversion factor;
…
7.	Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee.  Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Conclusion
8.

CITED REFERENCE SUMMARIES: Ref US20090006129A1: Claims:
A computerized method for providing medical diagnosis, therapy and prognosis of a patient with a chronic disease on a computer, the method comprising: specifying on the computer one or more protocols that address specific diagnosis and therapy needs of the patient; specifying on the computer a patient model; performing analysis on the computer to determine parameters of the patient model; performing model verification of the parameters on the computer to further ensure that the patient model has captured appropriate dynamics that address the specific diagnosis and therapy needs of the patient; applying data collected per the one or more protocols to perform analysis on the computer using the patient model to provide at least one recommended patient-specific therapy; and providing on the computer the recommended patient-specific therapy for approval.
specifying on the computer one or more protocols that address specific diagnosis and therapy needs of the patient;
specifying on the computer a patient model;
performing analysis on the computer to determine parameters of the patient model;
performing model verification of the parameters on the computer to further ensure that the patient model has captured appropriate dynamics that address the specific diagnosis and therapy needs of the patient;
applying data collected per the one or more protocols to perform analysis on the computer using the patient model to provide at least one recommended patient-specific therapy; and
providing on the computer the recommended patient-specific therapy for approval.
The computerized method according to claim 1 further comprises tuning the recommended patient-specific therapy.
The computerized method according to claim 1 further comprises defining and implementing test scenarios on the computer that help in testing the recommended patient-specific therapy and quantifying the quality of therapy potentially achievable using the recommended patient-specific therapy.
The computerized method according to claim 1 further comprises defining and implementing test scenarios on the computer that help in performing the model verification of the parameters.
The computerized method according to claim 1 further comprises providing a plurality of recommended patient-specific therapies, and testing the recommended patient-specific therapies against several critical test scenarios and evaluating expected therapy outcomes to provide a prognosis based on a selected one of the recommended patient-specific therapies.
The computerized method according to claim 1 further comprises performing mathematical analysis to evaluate stability, sensitivity, robustness, and provided an indication of confidence for the recommended patient-specific therapy.
The computerized method according to claim 1 further comprises confirming that the dynamics of the patient model by simulating special test cases to evaluate dynamic response against at least one of literature data and clinical data.
The computerized method according to claim 1 further comprises providing mathematical analysis tools, visualization tools, and data presentation tools to help perform the analysis on the computer.
The computerized method according to claim 1 further comprises providing a simulated environment to defining and implementing test scenarios on the computer that help in performing the model verification of the parameters.
The computerized method according to claim 1 further comprises implementing the recommended patient-specific therapy on a portable unit.
The computerized method according to claim 1 further comprises collecting the data per the one or more protocols from a patient data collection device.
The computerized method according to claim 1 further comprises using an algorithm on the computer to govern the collection of the data, the performing of analysis on the data, the applying of the data to the patient model, and the providing of the recommended patient-specific therapy.
The computerized method according to claim 1 wherein the data collected includes at least one of event activities and physiological measurements which update the analysis for provided the recommended patient-specific therapy.
The computerized method according to claim 1 further comprises approving the recommended patient-specific therapy as a prescription, and using an algorithm on the computer to govern scheduling, controlling, and monitoring of the prescription.
The computerized method according to claim 1 further comprises approving the recommended patient-specific therapy as a prescription, and using an algorithm on the computer to control implementation of the prescription open loop with a portable device providing administration of the prescription directly to the patient.
The computerized method according to claim 1 further comprises approving the recommended patient-specific therapy as a prescription, and using an algorithm on the computer to control implementation of the prescription closed loop with a portable device providing administration of the prescription directly to the patient.
The computerized method according to claim 15 further comprises the algorithm commanding the portable unit to dispense medication and perform a measurement task according to the prescription.
The computerized method according to claim 16 further comprises the algorithm commanding the portable unit to dispense medication and perform a measurement task each with a given input characteristics, and using the input characteristics to update the algorithm.
The computerized method of claim 1 further comprises the claim 1 being provided in a client-server computer system environment.
A computerized method to evaluate pharmacokinetic effects and therapy efficacy in a specific patient on a computer, the method comprising: providing patient data to the computer, the patient data include metabolic, physiological, and lifestyle information on the patient; performing a validity check on the patient data on the computer to provided validated data; analysis the validated data on the computer using one or more patient models to quantify disease progression, to determine therapy tailored to the patient by considering the metabolic, physiological, and lifestyle information, and to determine therapy prognosis; and providing the tailored therapy and therapy prognosis.
providing patient data to the computer, the patient data include metabolic, physiological, and lifestyle information on the patient;
performing a validity check on the patient data on the computer to provided validated data;
analysis the validated data on the computer using one or more patient models to quantify disease progression, to determine therapy tailored to the patient by considering the metabolic, physiological, and lifestyle information, and to determine therapy prognosis; and
providing the tailored therapy and therapy prognosis.
The method of claim 20 wherein the one or more patient models includes physiological models, metabolic models, and mathematics for determining a drug dose based on the pharmacokinetics and pharmacodynamics of the drug.
The method of claim 20 wherein the therapy prognosis includes whether a particular action will have an effect that is either adverse or desired.
A computerized system for providing medical diagnosis, therapy and prognosis of a patient with a chronic disease, the system comprising: a data collection of collection protocols and patient models; a first software module for testing integrity and accuracy of data collected per one of the collection protocols; a second software module for analyzing the collected data with at least one of the patient models to characterize specific metabolic needs of the patient; and a third software module which uses the characterized specific metabolic needs of the patient in diagnosing the patient to determine a patient-specific therapy and to offer prognosis of the patient-specific therapy.
a data collection of collection protocols and patient models;
a first software module for testing integrity and accuracy of data collected per one of the collection protocols;
a second software module for analyzing the collected data with at least one of the patient models to characterize specific metabolic needs of the patient; and
a third software module which uses the characterized specific metabolic needs of the patient in diagnosing the patient to determine a patient-specific therapy and to offer prognosis of the patient-specific therapy.
The computerized system according to claim 23 further comprises a fourth software module which provides tools to define a prescription that is consistent with the characterized specific metabolic needs of the patient, and to assess critical scenarios which ensure stability and robustness of the patient-specific therapy.
The computerized system according to claim 23 further comprises a test stand program providing a simulation environment for defining and implementing test scenarios that help in testing recommended patient-specific therapy and quantifying quality of therapy potentially achievable using the recommended patient-specific therapy.
The computerized system according to claim 23 further comprises a test stand program providing a simulation environment for defining and implementing test scenarios that help in performing model verification of parameters.
The computerized system according to claim 23 further comprises a test stand program providing a simulation environment for simulating special test cases to evaluate dynamic response of the patient models against at least one of literature data and clinical data.
The computerized system according to claim 23 further comprises a portable unit which implements the patient-specific therapy.
The computerized system according to claim 23 further comprises a patient data collection device which collects the data per one or more of the collection protocols.
The computerized system according to claim 23 wherein the data collected includes at least one of event activities and physiological measurements which an algorithm uses to update the analysis for provided the patient-specific therapy.
The computerized system according to claim 23 further comprises an algorithm which governs scheduling, controlling, and monitoring of the patient-specific therapy.
The computerized system according to claim 23 further comprises an algorithm which controls implementation of the patient-specific therapy open loop with a portable device providing administration of patient-specific therapy directly to the patient.
The computerized system according to claim 23 further comprises an algorithm which controls implementation of the prescription closed loop with a portable device providing administration of the patient-specific therapy directly to the patient.
The computerized method according to claim 23 further comprises a portable unit for dispensing medication and performing a measurement when commanded by an algorithm following the patient-specific therapy.
The computerized method according to claim 23 further comprises a portable unit for performing actions which include dispensing medication and performing a measurement when commanded by an algorithm following the patient-specific therapy, each actions when performed provides a given input characteristics to update an algorithm in the system used to control and monitor application of the patient-specific therapy.
Ref US20050187749A1: Claims:
A computer-based method for calculation of insulin levels based upon about-to-be-consumed food, comprising the steps of: identifying the about-to-be-consumed food in a first processing device; weighing said about-to-be-consumed food and inputting said weight into said first processing device; obtaining nutritional information regarding said about-to-be-consumed food from said first processing device; using said first processing device, calculating the total grams of carbohydrates in said about-to-be-consumed food; obtaining personal information regarding a consumer of said about-to-be-consumed food from said first processing device; calculating an insulin dose for said consumer based on said total grams of carbohydrates and said personal information; and displaying said calculated insulin dose via said first processing device.
identifying the about-to-be-consumed food in a first processing device;
weighing said about-to-be-consumed food and inputting said weight into said first processing device;
obtaining nutritional information regarding said about-to-be-consumed food from said first processing device;
using said first processing device, calculating the total grams of carbohydrates in said about-to-be-consumed food;
obtaining personal information regarding a consumer of said about-to-be-consumed food from said first processing device;
calculating an insulin dose for said consumer based on said total grams of carbohydrates and said personal information; and
displaying said calculated insulin dose via said first processing device.
The method of claim 1 , wherein said step of calculating the total grams of carbohydrates includes: calculation of carbohydrates from non-protein sources.
calculation of carbohydrates from non-protein sources.
The method of claim 2 , wherein said step of calculating the total grams of carbohydrates further includes: calculation of carbohydrates from protein sources.
calculation of carbohydrates from protein sources.
The method of claim 3 , further comprising a scale, coupleable to said first processing device, for weighing said about-to-be-consumed food and inputting the weight of said about-to-be-consumed food to said first processing device.
The method of claim 4 , wherein said first processing device is a portable processing device, coupleable to a second processing device, wherein said nutritional information and personal information is stored on said second processing device and transferred to said first processing device by a synchronization process.
The method of claim 5 , wherein said insulin dose calculation is performed using an algorithm stored on said first processing device.
The method of claim 6 , wherein said algorithm is stored on said first processing device during said synchronization process.
The method of claim 1 , wherein said first processing device is coupleable to an insulin pump, and wherein when said first processing device is coupled to said insulin pump, said calculated insulin dose is automatically input to said insulin pump to set said insulin pump to deliver said calculated insulin dose to a patient using said insulin pump.
A computer-based system for calculation of insulin levels based upon about-to-be-consumed food, comprising: means for identifying the about-to-be-consumed food in a first processing device; means for weighing said about-to-be-consumed food and inputting said weight into said first processing device; means for obtaining nutritional information regarding said about-to-be-consumed food from said first processing device; means for calculating, using said first processing device, the total grams of carbohydrates in said about-to-be-consumed food; means for obtaining personal information regarding a consumer of said about-to-be-consumed food from said first processing device; means for calculating an insulin dose for said consumer based on said total grams of carbohydrates and said personal information; and means for displaying said calculated insulin dose via said first processing device.
means for identifying the about-to-be-consumed food in a first processing device;
means for weighing said about-to-be-consumed food and inputting said weight into said first processing device;
means for obtaining nutritional information regarding said about-to-be-consumed food from said first processing device;
means for calculating, using said first processing device, the total grams of carbohydrates in said about-to-be-consumed food;
means for obtaining personal information regarding a consumer of said about-to-be-consumed food from said first processing device;
means for calculating an insulin dose for said consumer based on said total grams of carbohydrates and said personal information; and
means for displaying said calculated insulin dose via said first processing device.
The system of claim 9 , wherein said means for calculating the total grams of carbohydrates includes: means for calculating carbohydrates from non-protein sources.
means for calculating carbohydrates from non-protein sources.
The system of claim 10 , wherein said means for calculating the total grams of carbohydrates further includes: means for calculating carbohydrates from protein sources.
means for calculating carbohydrates from protein sources.
The system of claim 11 , further comprising a scale, coupleable to said first processing device, for weighing said about-to-be-consumed food and inputting the weight of said about-to-be-consumed food to said first processing device.
The system of claim 12 , wherein said first processing device is a portable processing device, coupleable to a second processing device, wherein said nutritional information and personal information is stored on said second processing device and transferred to said first processing device by a synchronization process.
The system of claim 13 , wherein said insulin dose calculation is performed using an algorithm stored on said first processing device.
The system of claim 14 , wherein said algorithm is stored on said first processing device during said synchronization process.
The system of claim 9 , wherein said first processing device is coupleable to an insulin pump, and wherein when said first processing device is coupled to said insulin pump, said calculated insulin dose is automatically input to said insulin pump to set said insulin pump to deliver said calculated insulin dose to a patient using said insulin pump.
A computer-based computer program product for calculation of insulin levels based upon about-to-be-consumed food, the computer program product comprising a computer-readable storage medium having computer-readable program code embodied in the medium, the computer-readable program code comprising: computer-readable program code that identifies the about-to-be-consumed food in a first processing device; computer-readable program code that determines the weight of said about-to-be-consumed food and inputs said weight into said first processing device; computer-readable program code that obtains nutritional information regarding said about-to-be-consumed food from said first processing device; computer-readable program code that, using said first processing device, calculates the total grams of carbohydrates in said about-to-be-consumed food; computer-readable program code that obtains personal information regarding a consumer of said about-to-be-consumed food from said first processing device; computer-readable program code that calculates an insulin dose for said consumer based on said total grams of carbohydrates and said personal information; and computer-readable program code that enables display of said calculated insulin dose via said first processing device.
computer-readable program code that identifies the about-to-be-consumed food in a first processing device;
computer-readable program code that determines the weight of said about-to-be-consumed food and inputs said weight into said first processing device;
computer-readable program code that obtains nutritional information regarding said about-to-be-consumed food from said first processing device;
computer-readable program code that, using said first processing device, calculates the total grams of carbohydrates in said about-to-be-consumed food;
computer-readable program code that obtains personal information regarding a consumer of said about-to-be-consumed food from said first processing device;
computer-readable program code that calculates an ins
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