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US-12623019-B2 - System, method, and computer readable medium for dynamic insulin sensitivity in diabetic pump users

US12623019B2US 12623019 B2US12623019 B2US 12623019B2US-12623019-B2

Abstract

A technique for treating diabetes that recognizes patient insulin sensitivity is a time-varying physiological parameter. The described techniques for treating diabetes include measuring interstitial fluid glucose concentration, reading insulin delivery data, determining patient insulin sensitivity based on the interstitial fluid glucose concentration and insulin delivery data, and a time-varying physiological parameter, and dispensing an insulin dose from an insulin delivery device based on the determined patient insulin sensitivity.

Inventors

  • Marc D. Breton
  • Boyi Jiang
  • Chiara Fabris

Assignees

  • UNIVERSITY OF VIRGINIA PATENT FOUNDATION

Dates

Publication Date
20260512
Application Date
20190926

Claims (18)

  1. 1 . A controller for an insulin dispensing device, the controller comprising: a communications module configured to receive interstitial fluid glucose concentration from a glucose monitor, and receive insulin delivery data; a patient insulin sensitivity determination module configured to determine patient insulin sensitivity based on the interstitial fluid glucose concentration, the insulin delivery data, an estimated glucose rate of appearance, and an estimated insulin concentration, wherein: the patient insulin sensitivity determination module is configured to use the interstitial fluid glucose concentration as an approximation of patient blood glucose; and the patient insulin sensitivity determination module is configured to determine the estimated glucose rate of appearance using a meal compartment including a first meal absorption model compartment and a second meal absorption modelcompartment, the first meal absorption compartment being faster than the second meal absorption compartment, wherein the estimated glucose rate of appearance is determined from the meal compartment based on a summation of the first meal absorption compartment and the second meal absorption compartment; and an insulin dosage calculation module configured to modify an insulin dose by adjusting one or more of a rapid-acting insulin dosage amount, a short-acting insulin dosage amount, an intermediate-acting insulin dosage amount, a long-acting insulin dosage amount, or a pre-mixed insulin dosage amount based on the determined patient insulin sensitivity that is specific to a patient; and wherein the communication module causes the insulin dispensing device to dispense the modified insulin dose to the patient.
  2. 2 . The controller of claim 1 , comprising: an estimation module configured to calculate the estimated glucose rate of appearance and the estimated insulin concentration, wherein the estimated insulin concentration is determined from an insulin compartment.
  3. 3 . The controller of claim 1 , wherein at least one of the estimated glucose rate of appearance or the estimated insulin concentration is estimated based on an adaptation of a Kalman filtering process.
  4. 4 . The controller of claim 1 , wherein the patient insulin sensitivity determination module is configured to receive a weighted value of the measured interstitial fluid glucose concentration.
  5. 5 . The controller of claim 1 , wherein the patient insulin sensitivity determination module is configured to compensate for calibration and measurement noise.
  6. 6 . The controller of claim 1 , comprising: a patient physical activity module configured to collect patient physical activity information, wherein a patient insulin sensitivity determined by the patient insulin sensitivity determination module will be based in part on patient physical activity information collected by the patient physical activity module.
  7. 7 . The controller of claim 1 , comprising: a patient physical activity module configured to collect patient circadian rhythm information; wherein the patient insulin sensitivity determined by the patient insulin sensitivity determination module will based in part on the patient circadian rhythm information.
  8. 8 . The controller of claim 1 , wherein the patient insulin sensitivity is based in part on a specified patient dietary habit.
  9. 9 . The controller of claim, 1 in combination with a single housing enclosing at least the glucose monitor, the patient insulin sensitivity determination module, and the insulin dosage calculation module.
  10. 10 . The controller of claim 1 , in combination with the display device, wherein the display device is configured to display information related to the calculated insulin dose.
  11. 11 . A device for administering insulin, the device comprising: a controller including at least one operating module, the controller configured to: receive interstitial fluid glucose concentration measurements from a glucose monitor; receive insulin delivery data; determine patient insulin sensitivity based on the received interstitial fluid glucose concentration measurements, the received insulin delivery data, an estimated glucose rate of appearance, and an estimated insulin concentration, wherein: the interstitial fluid glucose concentration is used as an approximation of patient blood glucose; and the estimated glucose rate of appearance is determined from a meal compartment including a first meal absorption compartment and a second meal absorption compartment, the first meal absorption compartment being faster than the second meal absorption compartment, wherein the estimated glucose rate of appearance is determined from the meal compartment based on a summation of the first meal absorption compartment and the second meal absorption compartment; modify an insulin dose by adjusting one or more of a rapid-acting insulin dosage amount, a short-acting insulin dosage amount, an intermediate-acting insulin dosage amount, a long-acting insulin dosage amount, or a pre-mixed insulin dosage amount based on the determined patient insulin sensitivity that is specific to a patient; and dispense the modified insulin dose to the patient.
  12. 12 . The device of claim 11 , wherein the device is configured to determine the estimated insulin concentration from an insulin compartment.
  13. 13 . The device of claim 11 , wherein at least one of the estimated glucose rate of appearance or the estimated insulin concentration is estimated based on an adaptation of a Kalman filtering process.
  14. 14 . The device of claim 11 , wherein the determined patient insulin sensitivity is based on a weighted value of the measured interstitial fluid glucose concentration.
  15. 15 . The device of claim 11 , wherein the device is configured to compensate the determined patient insulin sensitivity for calibration and measurement noise.
  16. 16 . The device of claim 11 , wherein the device is configured to receive patient physical activity information, and wherein the determined patient insulin sensitivity is based on the received patient physical activity information.
  17. 17 . The device of claim 11 , wherein the device is configured to receive patient circadian rhythm information, and wherein the determined patient insulin sensitivity is based on the received patient circadian rhythm information.
  18. 18 . The device of claim 11 , wherein the determined patient insulin sensitivity is based on a specified patient dietary habit.

Description

RELATED APPLICATIONS This application is a continuation of U.S. patent application Ser. No. 15/255,828 filed Sep. 2, 2016, which claims the benefit under 35 U.S.C. § 119 of U.S. Provisional Patent Application No. 62/213,198 filed on Sep. 2, 2015, the entire contents of which are hereby incorporated by reference in their entireties. FIELD The present disclosure provides system, method, and computer readable medium for dispensing insulin to a patient that recognizes patient insulin sensitivity varies over time. BACKGROUND Insulin is a hormone needed by the body to absorb glucose from the blood into fat, liver, and skeletal muscle cells, among others. Patients with diabetes either do not produce insulin (type 1 diabetes) or produce insulin but are resistant to insulin's effects (type 2 diabetes) and so their bodies cannot break down the sugars and starches from food into glucose for use as energy by the body. Patients with type 1 and type 2 diabetes can treat their condition in multiple ways including dietary changes, exercise, non-insulin based medications, or insulin. The non-insulin medication may come in the form of an oral agent, for example, and the insulin may be delivered in multiple ways including syringes, pre-filled insulin pens, or an insulin pump. Some patients may be prescribed treatment regimes that employ several treatments for their complementary effects. For example, a patient may receive a non-insulin based medication in addition to insulin when the non-insulin based medication is designed to improve the patient's responsiveness to insulin. Examples of non-insulin medications include forms of biguanides, sulfonylureas, megalitindes, d-phenylalanine derivatives, thiazolidinediones, pioglitazones, DDP-4 inhibitors, alpha-glucosidase inhibitors, and bile acid sequestrants. Another patient may instead receive a different combination of rapid-acting, short-acting, intermediate-acting, long-acting, and pre-mixed insulin, depending on the patient's symptoms, and based on the patient's insulin sensitivity. Examples of possible delivery methods of these different types of insulin include syringes, insulin pens, insulin pumps, jet injectors, inhaled insulin, and the like. Based on the understanding of a patient's physiology, different combinations of these different treatments are prescribed by medical professionals to manage a patient's diabetes. Insulin sensitivity (SI) is an index that describes the effectiveness of a patient's insulin reaction to glucose. In the late 1970s, a hyperinsulinemic-euglycemic clamp technique was proposed for measuring the whole-body SI in the hospital setting. Two alternatives to the hyperinsulinemic-euglycemic clamp technique were intravenous glucose tolerance tests (VGTT) and oral glucose tolerance tests (OGTT). In VGTT and OGTT, a predetermined amount of glucose is intravenously or orally dosed and the results measured. An oral minimal model is a useful tool for insulin sensitivity estimation based on OGTT data. Although these traditional techniques are effective and robust, the patient must be in an inpatient clinical setting either with intravenous lines attached or the patient must endure multiple venipunctures. These procedures are invasive to the patient, disrupt the patients' daily insulin treatment in the home or other setting, and only provide a one data point as to the patient's condition. Accordingly, the above described treatment regimes for diabetic patients did not consider the possibility that a patient's insulin sensitivity could vary over time. Recently, improvements in medical technology have allowed for more comprehensive glucose monitoring of the patient through the use of wearable glucose monitors, for example. In addition, insulin pumps have been miniaturized so that patients can easily adjust the insulin dose as needed, and insulin pens have begun including wireless technologies to report various types of information. The advent of these glucose monitors and insulin delivery systems have improved patients' ability to understand their condition and to conveniently manage their own treatment, within the boundaries set by their medical professionals. Although others, including those mentioned below in the Background References section, have proposed estimating a patient's insulin sensitivity using pump data and continuous glucose monitoring data, those who have previously estimated insulin sensitivity assumed that insulin sensitivity was a time invariant physiological parameter at least during the testing process. Studies have, however, shown that insulin sensitivity does vary significant in response to a variety of factors including circadian rhythm, physical activity, dietary habits, and illness or stress. Dynamic insulin sensitivity indexes were therefore devised to address this improved understanding, and it has been demonstrated that stochastic modeling can provide first order estimates of insulin sensitivity. The application of the improved u