Office Action 5: Notice of Allowance (2025-02-28)

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;
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 \[\[a\]\] the 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: (Previously Presented) 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: (Canceled).
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;
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 \[\[a\]\] the 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: (Previously Presented) 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: (Canceled)

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;
obtaining apatient-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 \[\[a\]\] the 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-.

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.

APPLICANT REBUTTAL: REMARKS
Claims 1, 10, 18, and 20 are amended. Claims 6 and 15 are canceled. Claims 1-5, 7-14, and 16-20 remain pending. Applicant respectfully requests reconsideration in view of the remarks presented below.
Interview Summary
Applicant thanks the Examiner for the telephonic interview conducted July 18, 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.
No agreement regarding allowability was reached.
Claim Re
j
ections Under 35 U.S.C.
The Office Action rejected claims 1-20 under 35 U.S.C. § 103 as being unpatentable over Thukral (U.S. Publication No. 2009/0006129, hereinafter THUKRAL) in view of Singley (U.S. Publication No. 20050187749 Al, hereinafter SINGLEY). In rejecting the independent claims, the Office asserted that paragraphs [0212] and [0213] of Thukral disclose "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 value by a patient-specific conversion factor." In particular, in the rejection of claim 1, the Office asserted that "the rate of gut glucose absorption" as described in paragraph [0213] of Thukral corresponds to the "patient-specific conversion factor" recited in the independent claims.
Paragraph [0212] of Thukral states "[p]roteins and fat are converted to an equivalent
carbohydrate amount." Thukral goes on to state "[i]t is acknowledged that one of the factors that affect the rate of gut glucose absorption (i.e., the speed of the meal) is meal composition," and "implicit to the meal amount selection, the speed of the meal is accounted." (Thukral, paragraph [0213].
Applicant respectfully submits that even assuming arguendo that the rate of gut glucose absorption described in paragraph [0213] of Thukral corresponds to the patient-specific conversion factor recited in Applicant's claims (which Applicant does not concede), nowhere does Thukral disclose or suggest
how
protein and fat are converted to an equivalent carbohydrate
value, and makes no mention of how the rate of gut glucose absorption (which the Office asserted corresponds to the patient-specific conversion factor recited in Applicant's claims) is used to convert protein to an equivalent carbohydrate value. Instead, Thukral merely states in paragraph [0212] that "protein and fat are converted to an equivalent carbohydrate value" and Thukral provides no additional detail.
Accordingly, Applicant respectfully submits that Thukral does not disclose or suggest "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 recited in Applicant's claims 1, 10, and 18.
However, and without conceding in the basis of the rejection, and solely to expedite
prosecution of the application, Applicant has amended independent claims 1, 10, and 18 to recite, inter alia:
obtaining an estimated protein value for a meal and an estimated carbohydrate value for the meal;
obtaining a
p
atient-s
p
ecific conversion factor that indicates an effect of
p
rotein on
gl
ucose levels of a
p
atient
,
wherein the
p
atient-s
p
ecific conversion factor is determined
based on predictions of
gl
ucose level rise for the patient using
historical meal data and historical glucose levels of the
p
atient;
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;
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 1 as amended; emphasis added).
The amendments made herein to independent claims 1, 10, and 18 are similar to what was previously recited in dependent claims 6 and 15 prior to the current amendments.
In rejecting dependent claims 6 and 16, which recites "the conversion factor is
determined based on historical meal data for the patient and further based on historical glucose level data for the patient," the Office cited paragraphs [0143], [0144], [0147], [0153], and [0212]-[0213] of Thukral. (Office Action, page 6).
Applicant respectfully submits that even assuming arguendo that the rate of gut glucose absorption described in paragraph [0213] of Thukral corresponds to the "patient-specific conversion factor" recited in Applicant's independent claims (which Applicant does not concede), nowhere does Thukral disclose or suggest
"the
p
atient-s
p
ecific conversion factor is determined based on
p
redictions of glucose level rise for the
p
atient using historical meal data and historical glucose levels of the patient,"
as recited in the amendments made to claims 1, 10, and 18. Rather, in Thukral, the rate of gut glucose absorption is based on
meal size.
Finally, Applicant respectfully submits that paragraphs [0143], [0144], [0147], and [0153] of Thukral are entirely unrelated to conversion of a protein value to an equivalent carbohydrate value.
Response to Advisor
y
Action
In the Advisory Action dated August 30, 2024 regarding the amendments to the
independent claims made herein, the Office asserted that Singley describes "converting protein values to equivalent carbohydrates/glucose using specific mathematical functions," citing paragraph [0025] of Singley. However, Singley states "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." Singley uses the example of "it is known that 1 ounce of a "protein food" (e.g., meat, poultry, etc.) equals 4.2 grams of carbs from proteins," and accordingly, "3 ounces of chicken ... has 12.6 grams carbs from that protein." In other words, in Singley, grams of carbs from proteins is based on a
food ty
p
e s
p
ecific factor
,
n
ot
a
p
atient-s
p
ecific
conversion factor. Nothing in Thukral or Singley describes "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
p
atient-s
p
ecific conversion factor."
Secondly, in the Advisory Action, regarding the amendments made herein to the
independent claims, the Office asserted that Thukral describes "determining a patient-specific glucose factor based on historical glucose rise using historical meal data and historical glucose
levels of a patient," citing paragraphs [0120] and [0192]. Applicant respectfully submits that the cited portions of Thukral
have nothing to do with
"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," as recited in the amended independent claims. Rather, paragraph [0120] of Thukral merely describes a fact pattern for a specific patient. Paragraph [0192] has nothing to do with paragraph [0120] of Thukral, and generally describes updating "a glucose push vector" and is related to "the expected glucose rise per gram of
carbohydrate."
The expected glucose rise per gram of carbohydrate described in paragraph [0192] of Thukral is different from "a patient-specific conversion factor that indicates an effect of
nr
otein
on glucose levels of a patient," let alone where such 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," as recited in the amended independent claims.
For at least these reasons, Applicant respectfully requests reconsideration and withdrawal of the rejections of the claims under 35 U.S.C. § 103.
Conclusion


CITED REFERENCE SUMMARIES: Ref US20090006129: Claims:
1. 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.
2. The computerized method according to claim 1 further comprises tuning the recommended patient-specific therapy.
3. 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.
4. 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.
5. 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.
6. 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.
7. 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.
8. 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.
9. 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.
10. The computerized method according to claim 1 further comprises implementing the recommended patient-specific therapy on a portable unit.
11. The computerized method according to claim 1 further comprises collecting the data per the one or more protocols from a patient data collection device.
12. 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.
13. 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.
14. 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.
15. 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.
16. 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.
17. 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.
18. 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.
19. The computerized method of claim 1 further comprises the claim 1 being provided in a client-server computer system environment.
20. 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.
21. 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.
22. The method of claim 20 wherein the therapy prognosis includes whether a particular action will have an effect that is either adverse or desired.
23. 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.
24. 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.
25. 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.
26. 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.
27. 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.
28. The computerized system according to claim 23 further comprises a portable unit which implements the patient-specific therapy.
29. 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.
30. 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.
31. The computerized system according to claim 23 further comprises an algorithm which governs scheduling, controlling, and monitoring of the patient-specific therapy.
32. 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.
33. 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.
34. 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.
35. 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 US20050187749: Claims:
1. 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.
2. The method of claim 1, wherein said step of calculating the total grams of carbohydrates includes: 
calculation of carbohydrates from non-protein sources.
3. The method of claim 2, wherein said step of calculating the total grams of carbohydrates further includes: 
calculation of carbohydrates from protein sources.
4. 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.
5. 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.
6. The method of claim 5, wherein said insulin dose calculation is performed using an algorithm stored on said first processing device.
7. The method of claim 6, wherein said algorithm is stored on said first processing device during said synchronization process.
8. 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.
9. 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.
10. The system of claim 9, wherein said means for calculating the total grams of carbohydrates includes: 
means for calculating carbohydrates from non-protein sources.
11. The system of claim 10, wherein said means for calculating the total grams of carbohydrates further includes: 
means for calculating carbohydrates from protein sources.
12. 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.
13. 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.
14. The system of claim 13, wherein said insulin dose calculation is performed using an algorithm stored on said first processing device.
15. The system of claim 14, wherein said algorithm is stored on said first processing device during said synchronization process.
16. 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.
17. 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.
18. The computer program product of claim 17, wherein said computer-readable program code that calculates the total grams of carbohydrates includes: 
computer-readable program code that calculates carbohydrates from non-protein sources.
19. The computer program product of claim 18, wherein said computer-readable program code that calculates the total grams of carbohydrates further includes: 
computer-readable program code that calculates carbohydrates from protein sources.
20. The computer program product of claim 19, 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.
21. The computer program product of claim 20, 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.
22. The computer program product of claim 21, wherein said insulin dose calculation is performed using an algorithm stored on said first processing device.
23. The computer program product of claim 22, wherein said algorithm is stored on said first processing device during said synchronization process.
24. The computer program product of claim 17, 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.
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 accordi
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