IP Library Granted Patent US 12,573,490
Granted Patent B2
US 12,573,490 · App. 17/996,039 · Granted Mar 10, 2026

Medication delivery simulation system

Inventor: Kevin S. Lee (Milpitas, CA)
Assignee: Bigfoot Biomedical, Inc.
G16H20/17A61M5/14244A61M2005/14292
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Quick Facts
Patent No.
US 12,573,490
App. No.
17/996,039
Granted
Mar 10, 2026
Kind
B2
Abstract

This document generally describes systems and methods for simulating a medication delivery system. Some embodiments can include a medication delivery simulation system that simulates an operation of a medication delivery system, such as delivery of a medication and detection of a response to the delivery. The simulation system can be used to simulate at least part of the operation of a medication delivery system and can check operations of one or more components in the medication delivery system, such as a pump, a sensor, a user device (e.g., a mobile device), and a server computing device.

Claims (48)

1 . A method for simulating a glucose monitoring system, wherein the glucose monitoring system includes a medication delivery device configured to dispense medication, the method comprising:

obtaining, at a simulation system, first data representative of a first glucose-impacting event;

generating, at the simulation system, second data based on the first data, the second data representative of a simulated physiological response to the first glucose-impacting event;

calculating, at the simulation system, third data based on the second data, the third data representative of a simulated glucose value according to the simulated physiological response;

transmitting, using the simulation system, the third data to the medication delivery device;

receiving, at the simulation system, fourth data from the medication delivery device, wherein the medication delivery device generates the fourth data representative of a second glucose-impacting event, and wherein the medication delivery device generates the fourth data based on the third data transmitted from the simulation system;

generating, at the simulation system, fifth data based on the fourth data, the fifth data representative of an expected glucose value based on the second glucose-impacting event;

determining, at the simulation system, whether the expected glucose value meets a threshold; and

generating, at the simulation system, a notification when the expected glucose value does not meet the threshold.

2 . The method of claim 1 , wherein the simulation system:

obtains the first data representative of the first glucose-impacting event at a first time, and

receives the fourth data representative of the second glucose-impacting event at a second time later than the first time.

3 . The method of claim 1 , wherein obtaining first data representative of a first glucose-impacting event includes:

receiving, at the simulation system and from a server, the first data representative of the first glucose-impacting event.

4 . The method of claim 1 , wherein obtaining first data representative of a first glucose-impacting event includes:

retrieving, at the simulation system, the first data representative of the first glucose-impacting event, wherein the first data is stored in the simulation system.

5 . The method of claim 1 , wherein the first glucose-impacting event includes at least one of carb ingestion, exogenous insulin delivery, exercise, adjusted physiological parameter, system disconnection, or sensor fault.

6 . The method of claim 1 , wherein the second glucose-impacting event includes a dosage of the medication being calculated based on the simulated glucose value.

7 . The method of claim 1 , wherein the glucose monitoring system further comprises:

a user computing device configured to communicate with the medication delivery device; and

a server configured to communicate with the user computing device.

8 . The method of claim 1 , wherein the medication delivery device includes a portable infusion pump.

9 . The method of claim 1 , wherein the medication delivery device comprises a medication injection pen.

10 . The method of claim 1 , wherein the simulation system comprises an adaptive learning algorithm configured to generate the second data.

11 . The method of claim 1 , wherein the notification is generated in real time.

12 . A simulation system for simulating a glucose monitoring system, wherein the glucose monitoring system includes a medication delivery device configured to dispense medication, the simulation system comprising:

an input device configured to obtain first data representative of a first glucose-impacting event;

a processor in communication with the input device, wherein the processor is configured to generate second data based on the first data, the second data representative of a simulated physiological response to the first glucose-impacting event; and

a simulated glucose sensor in communication with the processor, wherein the simulated glucose sensor is configured to:

generate third data based on the second data, the third data representative of a simulated glucose value according to the simulated physiological response; and

transmit the third data to the medication delivery device,

wherein the processor is further configured to:

receive, from the medication delivery device, fourth data representative of a second glucose-impacting event, wherein the fourth data is generated by the medication delivery device based on the third data transmitted from the simulated glucose sensor.

13 . The system of claim 12 , wherein the processor is further configured to:

generate fifth data based on the fourth data, the fifth data representative of an expected glucose value based on the second glucose-impacting event;

determine whether the expected glucose value meets a threshold; and

generate a notification when the expected glucose value does not meet the threshold.

14 . The system of claim 12 , wherein the input device is configured to receive a user input of the first data representative of the first glucose-impacting event.

15 . The system of claim 12 , wherein the input device is configured to receive the first data representative of the first glucose-impacting event from a server.

16 . The system of claim 12 , further comprising a storage device accessible by the processor, wherein the storage device is configured to store a script and the first data representative of a plurality of glucose-impacting events including the first glucose-impacting event, and

wherein the processor is further configured to;

run the script to simulate the plurality of glucose-impacting events over a period of time, and

generate the second data based on the plurality of glucose-impacting events.

17 . The system of claim 12 , wherein the first glucose-impacting event includes at least one of carb ingestion, exogenous insulin delivery, exercise, adjusted physiological parameter, system disconnection, or sensor fault.

18 . The system of claim 12 , wherein the second glucose-impacting event includes a dosage of the medication being calculated based on the simulated glucose value.

19 . The system of claim 12 , wherein the first glucose-impacting event relates to a category of patients, wherein the category of patients comprises an age, a type of lifestyle, or a type of diabetes.

20 . The system of claim 12 , wherein the medication delivery device comprises a medication injection pen.

21 . The system of claim 12 , wherein the simulation system comprises an adaptive learning algorithm configured to generate the second data.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 18, 2023
From: LEE, KEVIN S.
To: BIGFOOT BIOMEDICAL, INC.
Reel/Frame 063352/0181 →