Blood glucose control system

Abstract

The glucose control system can autonomously modify a therapy provided to a subject based on a comparison of the effects of different values ​​for the control parameter. The system can deliver a therapy to a subject during a first therapy period using a first value of the control parameter and determine a corresponding first effect for the first therapy by analyzing glycemic control of blood glucose in the subject. The system can autonomously generate a second value of the control parameter and use the second value to determine a second effect corresponding to a second therapy provided during a second period. By comparing the effects of the two therapy periods, a value of the control parameter that provides improved blood glucose management can be determined.

Description

Technical Field

[0001] Description of Research and Development Funded by the Federal Government This invention was made with government support under Contract No. DK120234 awarded by the National Institutes of Health. The United States government has certain rights in this invention. Incorporation by reference to any prior application This application claims the benefit of U.S. Provisional Patent Application No. 62 / 987,842, filed Mar. 10, 2020; U.S. Provisional Patent Application No. 63 / 037,472, filed Jun. 10, 2020; U.S. Provisional Patent Application No. 62 / 874,928, filed Jul. 16, 2019; U.S. Provisional Patent Application No. 62 / 874,934, filed Jul. 16, 2019; U.S. Provisional Patent Application No. 62 / 874,950, filed Jul. 16, 2019; U.S. Provisional Patent Application No. 62 / 874,954, filed Jul. 16, 2019; U.S. Provisional Patent Application No. 62 / 874,959, filed Jul. 16, 2019; U.S. Provisional Patent Application No. 62 / 874,964, filed Jul. 16, 2019; U.S. Provisional Patent Application No. 62 / 874,968, filed Jul. 16, 2019; U.S. Provisional Patent Application No. 62 / 874,972, filed Jul. 16, 2019; U.S. Provisional Patent Application No. 62 / 874,975, filed Jul. 16, 2019; U.S. Provisional Patent Application No. 62 / 874,977, filed Jul. 16, 2019; U.S. Provisional Patent Application No. 62 / 910,970, filed Oct. 4, 2019; U.S. Provisional Patent Application No. 62 / 911,017, filed Oct. 4, 2019; and U.S. Provisional Patent Application No. 62 / 911,143, filed Oct. 4, 2019. Further, this application claims the benefit of priority of International Patent Application No. PCT / US2020 / 042198, filed Jul. 15, 2020 and International Patent Application No. PCT / US2020 / 042195, filed Jul. 15, 2020. The entire contents of each application referenced in this paragraph are hereby incorporated by reference herein and made a part hereof. Any and all applications in which foreign or domestic priority claims are identified in the application data sheet filed with this application are hereby incorporated by reference herein under 37 CFR 1.57.

[0002] The present disclosure relates to portable medical devices, such as a blood glucose control system that provides therapy to a subject.

Background Art

[0003] Sustained delivery pump-driven drug injection devices generally include a delivery cannula that is subcutaneously attached through the patient's skin at the injection site. The pump draws the drug from a reservoir and delivers the drug to the patient through the cannula. The injection device typically includes a channel that transmits the drug from an inlet port to the delivery cannula, thereby providing delivery to the subcutaneous tissue layer where the delivery cannula terminates. Some injection devices are configured to deliver a single drug to the patient, while other injection devices are configured to deliver multiple drugs to the patient. SUMMARY OF THE INVENTION

[0004] The systems, methods, and devices of the present disclosure each have a plurality of innovative aspects, and no single one of those aspects alone bears all of the desirable attributes disclosed herein. Details of one or more implementations of the subject matter described in this specification are set forth in the accompanying drawings and the description below.

[0005] The specific embodiments disclosed herein relate to a computer-implemented method for generating metrics for total glycemic therapy over a period of time in a subject using a drug pump configured to deliver at least insulin therapy. The method can be executed by a hardware processor configured to generate a dosage control signal for a drug pump configured to deliver at least insulin therapy. The method can include receiving a glucose value of the subject and determining that a trigger event has occurred to increase the blood glucose value of the subject, at least partially based on the glucose value. The trigger event can include determining that there is an imminent risk of hypoglycemia in the subject or that there is an episode of hypoglycemia in the subject. The method determines the amount of an antagonist regulator and low It may further include responding to an imminent risk of hyperglycemia or an episode of hypoglycemia. Further, the method may include determining a dosage of glucotherapy based at least in part on the amount of the counterregulatory agent. Further, the method may include tracking the determined dosage of glucotherapy over a period including a plurality of hypoglycemia risk events or hypoglycemia episodes to generate an indicator of total glucotherapy over the period. The method may include outputting an indicator of total glucotherapy.

[0006] Additional embodiments of the present disclosure relate to an automated blood glucose control system configured to generate an indicator of total glucotherapy over a period in a subject. The automated blood glucose control system may include a drug delivery interface configured to operably connect to a drug pump configured to inject a drug into the subject. The drug may include at least insulin. Further, the automated blood glucose control system includes a memory configured to store certain computer-executable instructions and a hardware processor in communication with the memory, the hardware processor executing the certain computer-executable instructions to at least receive a glucose value of the subject and determine that a trigger event has occurred to increase the blood glucose value of the subject based at least in part on the glucose value, the trigger event including the presence of an imminent risk of hypoglycemia in the subject or the presence of an episode of hypoglycemia in the subject, determining an amount of a counterregulatory agent to respond to the imminent risk of hypoglycemia or the episode of hypoglycemia, determining a dosage of glucotherapy based at least in part on the amount of the counterregulatory agent, tracking the determined dosage of glucotherapy over a period including a plurality of hypoglycemia risk events or hypoglycemia episodes to generate an indicator of total glucotherapy over the period, and outputting an indicator of total glucotherapy.

[0007] Certain embodiments of the present disclosure relate to an automated blood glucose control system configured to generate a backup therapy protocol that includes an insulin therapy instruction derived from an autonomously determined insulin dosage. The automated blood glucose control system may include a drug delivery interface configured to operably connect to a drug pump for injecting a drug into a subject. Further, the automated blood glucose control system includes a memory configured to store certain computer-executable instructions and a hardware processor in communication with the memory, the hardware processor executing the certain computer-executable instructions to, at least, receive a glucose value signal from a sensor operably configured to determine a glucose value in the subject, generate a dosage control signal using a control algorithm configured to autonomously determine a dosage of insulin to be injected into the subject for the purpose of controlling the subject's blood glucose based at least in part on the glucose value signal, track an insulin therapy administered to the subject over a tracking period including at least one day, wherein tracking the insulin therapy includes storing an indicator of the autonomously determined insulin dosage delivered to the subject as basal insulin, an insulin correction bolus, or an insulin meal bolus, generate at least one of a backup injection therapy protocol or a backup pump therapy protocol that includes an insulin therapy instruction based at least in part on the insulin therapy administered to the subject over the tracking period, and output at least one of the backup injection therapy protocol or the backup pump therapy protocol on a display when the automated blood glucose control system is not providing therapy to the subject to enable the therapy to be maintained at a rate determined by the automated blood glucose control system. The automated blood glucose control system may include a hardware processor configured to perform the foregoing.

[0008] Additional embodiments of the present disclosure relate to a computer-implemented method for generating a backup therapy protocol that includes an insulin therapy instruction derived from an autonomously determined insulin dosage determined by an automated blood glucose control system. The method can be executed by a hardware processor of the automated blood glucose control system. The method includes receiving a glucose value signal from a sensor operably configured to determine a glucose value in a subject, and for the purpose of controlling the subject's blood glucose based at least in part on the glucose value signal, generating a dosage control signal using a control algorithm configured to autonomously determine a dosage of insulin to be injected into the subject. Further, the method can include tracking an insulin therapy administered to the subject over a tracking period including at least one day by the automated blood glucose control system. Tracking the insulin therapy can include storing an indication of the autonomously determined dosage of insulin delivered to the subject. Further, the method can include generating at least one of a backup injection therapy protocol or a backup pump therapy protocol that includes an insulin therapy instruction based at least in part on the insulin therapy administered to the subject over the tracking period. Further, the method can include outputting at least one of the backup injection therapy protocol or the backup pump therapy protocol on a display when the automated blood glucose control system is not providing therapy to the subject, to enable the therapy to be maintained at a rate determined by the automated blood glucose control system.

[0009] Some embodiments of the present disclosure relate to an automatic blood glucose control system configured to generate a report of therapy protocol modifications made by a user of the automatic blood glucose control system. The automatic blood glucose control system may include a drug delivery interface configured to operably connect to a drug pump for injecting a drug into a subject. Further, the automatic blood glucose control system may include a memory configured to store certain computer-executable instructions, stored control parameter values, and a therapy log. Further, the automatic blood glucose control system is a hardware processor that communicates with the memory and is configured to execute certain computer-executable instructions to at least receive a glucose value signal from a sensor operably configured to determine a glucose value in the subject, and based at least in part on the glucose value signal and a control parameter that is modifiable by a user interaction with a control parameter selection interface element, generate a dosage control signal using a control algorithm configured to autonomously determine a dosage of insulin to be injected into the subject for the purpose of controlling the subject's blood glucose, track user modifications to the control parameters over a tracking period that includes at least one day, where tracking the user modifications includes storing in the therapy log whether each user modification includes an increase or decrease in the control parameter from the stored control parameter value and the time at which each user modification occurred, and generate a report of the user modifications to the control parameters, where the report includes measurements of the frequency of increases and decreases from the stored control parameter values. And a hardware processor configured to perform the above may be included.

[0010] Certain embodiments of the present disclosure relate to a computer-implemented method for modifying a therapy provided to a subject using a blood glucose control system. The method can be executed by a hardware processor configured to generate a dosage control signal for the blood glucose control system. Further, the method can include receiving a glucose value signal from a glucose value sensor operably connected to the subject. Further, the method can include causing the blood glucose control system to deliver a first therapy to the subject during a first therapy period, wherein the first therapy is delivered at least in part based on a first value of control parameters used by a control algorithm to generate the dosage control signal. The control parameters can be used by the control algorithm to account for insulin accumulation in the subject, thereby controlling the insulin administration response of the control algorithm to blood glucose excursions in the subject indicated by the glucose value signal. Further, the method can include determining a first effect corresponding at least in part to the first therapy. Determining the first effect can include analyzing the blood glucose control of the subject indicated by the glucose value signal. Further, the method can include autonomously generating a second value of the control parameters. The autonomously generated second value can be determined as a function based on the first value and the first effect. Further, the method can include modifying the control parameters from the first value to the second value and causing the blood glucose control system to deliver a second therapy to the subject during a second therapy period. The second therapy can be delivered at least in part based on the second value of the control parameters. Further, by changing the control parameters, the therapy provided to the subject can be modified.

[0011] Additional embodiments of the present disclosure relate to a computer-implemented method for modifying a therapy provided to a subject using a blood glucose control system. The method can be executed by a hardware processor configured to generate a dosage control signal for the blood glucose control system. The method can include causing the blood glucose control system to deliver a first therapy to the subject during a first therapy period. The first therapy can be delivered based at least in part on a first value of a control parameter used by a control algorithm to generate the dosage control signal. The method can further include determining a first effect that at least partially corresponds to the first therapy. Determining the first effect can include receiving a glucose value signal from a glucose value sensor operably connected to the subject. Further, the method can include autonomously generating a second value of the control parameter based at least in part on a baseline value of the control parameter and an output of a function defined based on the subject's blood glucose control. The glucose value signal can include an indicator of the subject's blood glucose control during the first therapy period. Further, the method can include modifying the control parameter from the first value to the second value and causing the blood glucose control system to deliver a second therapy to the subject during a second therapy period. The second therapy can be delivered based at least in part on the second value of the control parameter. Changing the control parameter can include modifying the therapy provided to the subject.

[0012] Some embodiments of the present disclosure relate to a computer-implemented method of modifying a therapy provided to a subject using a blood glucose control system. The method can be implemented by a hardware processor configured to generate a dosing control signal for the blood glucose control system. The method can include causing the blood glucose control system to deliver a first therapy to the subject during a first therapy period. The first therapy can be delivered based at least in part on a first value of a control parameter used by a control algorithm to generate the dosing control signal. The method can further include determining a first effect that at least partially corresponds to the first therapy. Determining the first effect can include receiving a glucose value signal from a glucose value sensor operably connected to the subject. Further, the method can include autonomously generating a second value of the control parameter. The autonomously generated second value can be determined as a function based at least in part on a baseline value. Further, the method can include modifying the control parameter from the first value to the second value. The method can further include causing the blood glucose control system to deliver a second therapy to the subject during a second therapy period. The second therapy can be delivered based at least in part on the second value of the control parameter. Further, changing the control parameter can include modifying the therapy provided to the subject. The method can include determining a second effect that at least partially corresponds to the second therapy and autonomously comparing the first effect and the second effect without human action. Further, the method can include selecting, based at least in part on a comparison of the first effect and the second effect, one of the first value of the control parameter or the second value of the control parameter as an active control parameter value. Further, the method can include configuring the blood glucose control system to provide a therapy to the subject during a third therapy period based at least in part on the active control parameter value. Selection of the active control parameter value can modify the therapy provided to the subject.

[0013] Furthermore, any of the foregoing embodiments can be combined. For example, a single automatic blood glucose control system can be configured to implement one or more of the foregoing embodiments.

[0014] Throughout the drawings, reference numbers are reused to indicate corresponding between the elements being referenced. The drawings are provided to illustrate particular aspects of the subject matter described herein and are not intended to limit its scope.

Brief Description of the Drawings

[0015]

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Mode for Carrying Out the Invention

[0016] Some embodiments described herein relate to a drug infusion system for one or more drugs and components of such a system (e.g., an infusion pump, a drug cartridge, a cartridge connector, a lumen assembly, an infusion connector, an infusion set, etc.). Some embodiments relate to methods of manufacturing an infusion system and its components. Some embodiments relate to methods of using any of the foregoing systems or components to inject one or more drugs (e.g., pharmaceuticals, hormones, etc.) into a patient. By way of example, the infusion system may include an infusion pump, which may include one or more drug cartridges or may have an integrated reservoir for the drug. The infusion system may include a drug cartridge and a cartridge connector but not include a pump. The infusion system may include a cartridge connector and an infusion pump but not include a drug cartridge. The infusion system may include an infusion connector, a lumen assembly, a cartridge connector, and an infusion pump but not include a drug cartridge or an infusion set. A blood glucose control system may operate in conjunction with the infusion system to inject one or more drugs into a subject, which includes at least one blood glucose control agent. Any feature, structure, component, material, step, or method described and / or illustrated in any embodiment herein may be used in conjunction with or instead of any feature, structure, component, material, step, or method described and / or illustrated in any other embodiment herein. Additionally, any feature, structure, component, material, step, or method described and / or illustrated in one embodiment may not be present in another embodiment.

[0017] Overview of the Blood Glucose Control System A blood glucose control system is used to control the blood glucose level of a subject. The blood glucose control system may include a controller configured to generate a dosage control signal for one or more glucose control agents that can be injected into the subject. Glucose control agents include regulators that tend to lower blood glucose levels, such as insulin and insulin analogs, and counter-regulatory agents that tend to increase blood glucose levels, such as glucagon or dextrose. A blood glucose control system configured to be used with two or more glucose control agents can generate a dosage control signal for each of the agents. In some embodiments, the blood glucose control system can generate a dosage control signal for an agent even when the agent is not available for dosing via a drug pump connected to the subject.

[0018] The glucose control agent can be delivered to the subject via subcutaneous injection, intravenous injection, or another suitable delivery method. In the case of blood glucose control therapy with a portable drug pump, subcutaneous injection is the most common. The portable drug pump 100 is a type of portable medical device and may also be referred to herein as a portable device, a portable drug device, a mobile portable device, or an AMD. Portable medical devices include portable drug pumps and other devices configured to be carried by a subject and deliver therapy to the subject.

[0019] In some examples, the portable medical device (AMD) is an electrical stimulation device, and delivering therapy includes providing electrical stimulation to the subject. An example of an electrical stimulation device is a cardiac pacemaker. The cardiac pacemaker generates electrical stimulation of the myocardium to control the rhythm of the heart. Another example of an electrical stimulation device is a deep brain stimulation device for treating Parkinson's disease or movement disorders.

[0020] Figures 1A to 1C show examples of a blood glucose control system that provides blood glucose control via a portable drug pump connected to a subject. In Figure 1A, the drug pump 100 is connected to an injection site 102 using an infusion set 104. The drug pump is integrated with a pump control unit 106a, whereby the user can display pump data and change treatment settings via user interaction with the pump control unit 106a. The glucose value sensor 110 generates a glucose value signal received by the blood glucose control system.

[0021] In Figure 1B, the drug pump 100 communicates with an external electronic device 108 (e.g., a smartphone, etc.) via a wireless data connection. At least a part of the pump control units 106a and 106b can be operated via user interaction with user interface elements of the external electronic device 108. The glucose value sensor 110 can also communicate with the drug pump 100 via a wireless data connection.

[0022] In Figure 1C, the drug pump 100 includes an integrated cannula that is inserted into the injection site 102 without a separate infusion set. At least a part of the pump control unit 106b can be operated via user interaction with user interface elements of the external electronic device 108. In some cases, the pump control unit is connected to the drug pump 100 via a direct or indirect electronic data connection, and can be operated via user interaction with user interface elements generated by a remote computing environment (not shown), such as a cloud computing service.

[0023] A glucose control system typically includes a user interface, which is configured to provide one or more of treatment control elements that can change treatment settings through treatment information, glucose value information, and / or user interaction with interface control. The user interface can be implemented via an electronic device including a display and one or more buttons, switches, dials, capacitive touch interfaces, or touch screen interfaces. In some embodiments, at least a portion of the user interface is integrated with a portable drug pump that can be connected to the subject's body via an infusion set, and the infusion set is configured to facilitate subcutaneous injection of one or more glucose control agents. In certain embodiments, at least a portion of the user interface is implemented via an electronic device separate from a portable drug pump such as a smartphone.

[0024] Figures 2A - 2D show block diagrams illustrating exemplary configurations of a glucose control system 200. As shown in Figure 2A, the glucose control system 200a can include a controller 202a having an electronic processor 204a and a memory 210a storing instructions 208a executable by the processor 204a. The controller 202a and the pump 212 can be integrated into a portable medical device (AMD) 100. The AMD 100 can include a transceiver 214a for wireless digital data communication with an external electronic device. When the instructions 208a stored in the memory 210a are executed by the electronic processor 204a, the controller 202a can implement at least a portion of a control algorithm that generates a dosage control signal for one or more glucose control agents based on the subject's time-varying glucose value and one or more control parameters. The dosage control signal, when delivered to the pump 212, results in a dosing operation to control the subject's blood glucose.

[0025] As shown in FIG. 2B, the glucose control system 200b can operate at least in part via execution of instructions 208b by an electronic processor 204b of an electronic device 108 separate from the portable medical device 100. The electronic device 108 can include a transceiver 214b that can establish a wireless digital data connection to the AMD 100, and the controller 202b can implement at least a portion of a control algorithm via execution of instructions 208b stored in a memory 210b. When the instructions 208b stored in the memory 210b are executed by the electronic processor 204b, the controller 202b can implement at least a portion of a control algorithm that generates a dosage control signal for one or more glucose control agents based on a time-varying glucose value of a subject and one or more control parameters. When the dosage control signal is delivered to the pump 212, it results in a dosing operation that controls the blood glucose of the subject. In some embodiments, the dosage control signal is transmitted from the device transceiver 214b to the AMD transceiver 214a via a short-range wireless data connection 216. The AMD 100 receives the dosage control signals and passes them to the pump 212 for dosing operations.

[0026] As shown in FIG. 2C, the glucose control system 200c can operate at least in part via execution of instructions 208c on an electronic processor 204c integrated with a remote computer 206, such as a cloud service. When the instructions 208c stored in the memory 210c are executed by the electronic processor 204c, the controller 202c can implement at least a portion of a control algorithm that generates a dosage control signal for one or more glucose control agents based on a time-varying glucose value of a subject and one or more control parameters. When the dosage control signal is delivered to the pump 212, it results in a dosing operation that controls the blood glucose of the subject. In some embodiments, the dosage control signal is transmitted from the remote computer WAN connection interface 220c to the AMD WAN connection interface 220a via an end-to-end wireless data connection 218. The AMD 100 receives the dosage control signals and passes them to the pump 212 for dosing operations.

[0027] As shown in FIG. 2D, the glucose control system 200d may include two or more controllers 202a, 202b, 202c, which cooperate to generate a dosage control signal for the dosing operation by the pump 212. The remote computer 206 can transmit or receive data or instructions that have passed through the WAN connection interface 220c via the WAN wireless data connection 218 to the WAN connection interface 220b of the electronic device 108. The electronic device 108 can transmit or receive data or instructions that have passed through the transceiver 214b via the short-range wireless data connection 216 to the transceiver 214a of the AMD 100. In some embodiments, the electronic device can be omitted, and the controllers 202a, 202c of the AMD 100 and the remote computer 206 cooperate to generate the dosage control signal passed to the pump 212. In such embodiments, the AMD 100 may have its own WAN connection interface 220a and support a direct end-to-end wireless data connection to the remote computer 206.

[0028] As shown in FIG. 3, in some embodiments, the glucose control system 200 includes circuitry implementing an electronic communication interface (ECI) 302 configured to transmit and receive electronic data from one or more electronic devices. The ECI includes a sensor interface 304 configured to receive glucose value signals from a sensor 110, such as a continuous glucose monitor (CGM). Some CGMs generate glucose value signals at fixed measurement intervals, such as every five minutes. The sensor 110 may be operably connected to the subject to generate a glucose value signal corresponding to an estimated or measured blood glucose value of the subject. The glucose value signal may be used by the controller 202 to generate a dosage control signal. The dosage control signal may be provided to the pump 212 via the pump interface 306. In some embodiments, the sensor interface 304 connects to the sensor 110 via a short-range wireless connection 308. In some embodiments, the pump interface 306 connects to the pump 212 via a short-range wireless connection 310. In other embodiments, the pump interface 306 connects to the pump 212 via a local data bus, such as when the controller 202, the ECI 306, and the pump 212 are integrated into the AMD 100.

[0029] The controller can be configured to generate a dosage control signal using a control algorithm that generates at least one of a basal dosage, a correction dosage, and / or a meal dosage. Examples of control algorithms that can be used to generate these dosages are disclosed in U.S. Patent Application Publication Nos. 2008 / 0208113, 2013 / 0245547, 2016 / 0331898, and 2018 / 0220942 (referred to herein as the "controller disclosure"), the entire contents of which are incorporated herein by reference and form a part of this specification. The correction dosage can include an adjuster or an antagonist adjuster and can be generated using a model predictive control (MPC) algorithm such as those disclosed in the controller disclosure. The basal dosage can include an adjuster and can be generated using a basal control algorithm such as those disclosed in the controller disclosure. The meal dosage can include an adjuster and can be generated using a meal control algorithm such as those disclosed in the controller disclosure. Additional aspects and improvements of at least some of these controllers are disclosed herein. The dosage control signal can be transmitted to the infusion motor 306 via the ECI 302 or, if the controller 202a is integrated into the same housing as the infusion motor 306, can be transmitted to the infusion motor 306 via a conductor.

[0030] As shown in FIG. 4A, the controller 400 can be configured to operate in an "online mode" during a period in which the controller receives a glucose value signal 402 from the sensor 110. In the online mode, the control algorithm generates a dosage control signal 404, thereby implementing a periodic correction dosage based on the value of the glucose value signal 402 and the control parameters of the control algorithm. The pump 212 is configured to deliver at least the correction dosage and the basal dosage without substantial user intervention while the controller 400 maintains the online mode.

[0031] ​As shown in FIG. 4B, the controller 400 can be configured to operate in an “offline mode” during a period in which the controller does not receive the glucose value signal 402 from the sensor 110, at least during a period in which the glucose value signal 402 is expected but not received. In the offline mode, the control algorithm generates a dosage control signal 404, whereby a corrected dosage based on the control parameters of the control algorithm is implemented in response to a separate glucose measurement 406 (e.g., a measurement obtained from the subject using a glucose test strip, etc.). The pump 212 is configured to deliver a basal dosage to the subject without substantial user intervention and can deliver a corrected dosage to the subject in response to the separate glucose measurement 406 while the controller 400 maintains the offline mode.

[0032] Exemplary implementation of a glucose control system FIG. 5 shows an automatic glucose control system 510 for regulating the blood glucose level of an animal subject 512, which can be a human (the subject). The automatic glucose control system 510 is an example of a drug infusion system and can include any of the embodiments described above with respect to the drug infusion system.

[0033] Subject 512 can receive a dosage of insulin from an infusion pump (s) coupled to the subcutaneous space of subject 512 by one or more delivery devices 514, such as a catheter (s). As will be described below, delivery device 514 can also deliver a hyperglycemic agent, such as an anti-regulatory agent or glucagon or dextrose, to control blood glucose levels under certain circumstances. To deliver both insulin and an anti-regulatory agent (e.g., glucagon), delivery device 514 can be a mechanically actuated infusion mechanism having dual cartridges for insulin and anti-regulatory agent, respectively. Although reference is made herein particularly to glucagon, it is to be understood that this is for convenience only and that other anti-regulatory agents (e.g., dextrose) can be used. Similarly, the term "insulin" as used herein is to be understood to encompass all forms of insulin-like substances, including natural human or animal insulin, as well as synthetic insulin in any of its various forms (generally referred to as "insulin analogs").

[0034] In the case of online operation or autonomous operation, the glucose sensor 516 is operably coupled to the subject 512 to continuously sample the glucose value of the subject 512. In some cases, the glucose sensor 516 may be referred to as a continuous glucose monitoring (CGM) sensor, which may measure or sense the blood glucose value of the subject 512 continuously or periodically for at least a certain period of time. Sensing can generally be achieved in various ways including some form of physical coupling 521 between the subject 512 and the glucose sensor 516. The controller 518 can control the operation of the delivery device(s) 514 as a function of the glucose value signal 519 from the glucose sensor 516 and in accordance with program input parameters (PARAMS) 520 that may be provided by a user such as the subject 512, a parent or guardian of the subject 512, or a healthcare provider (e.g., a clinician or physician). One input parameter for autonomous operation may include the weight of the subject 512. In some cases, the glucose control system 510 can provide effective automatic control without receiving explicit information regarding either the meal or other "feed-forward" information ingested by the subject 512, which is partially achieved by an adaptive aspect to the operation of the controller 518. In other cases, the glucose control system 510 can use received information regarding the meal the subject has ingested or is scheduled to ingest, or other "feed-forward" information, to modify the control of blood glucose and / or the delivery of insulin or an antiregulatory agent.

[0035] The controller 518 is an electrical device having a control circuit that provides the operating functions described herein. In one embodiment, the controller 518 may be implemented as a computerized device (e.g., a hardware processor) having a computer instruction processing circuit that executes one or more computer programs, each including a respective set of computer instructions. In some cases, the processing circuit generally includes one or more processors 530 coupled to or communicating with a memory 540 and an input / output circuit 532, where the memory 540 stores computer program instructions and data, and the input / output circuit 532 can provide an interface(s) to external devices such as the glucose sensor 516 and the delivery device(s) 514. In some cases, the input / output circuit 532 may provide a user interface or may operate with one or more processors (e.g., the controller 518 or a separate processor 530 included in a separate computer system such as the glucose control system 510 or a smartphone, laptop computer, desktop computer, smartwatch, etc.) to provide the user interface to a user (e.g., the subject 512, a parent or guardian, or a clinician). In some cases, the input / output circuit 532 may include a touch screen and / or a touch screen controller 538 configured to control a touch screen (not shown).

[0036] In some cases, the controller 518 can perform all the functions of the glucose value control system 510. In such cases, the processor 530 is optional or can be omitted. In other cases, the controller 518 can perform at least the automatic blood glucose control of the subject 512, and one or more separate processors 530 can track the occurrence of hyperglycemic events, hypoglycemic events or risk events, output data to the user, control or initiate communication with another computing system, adjust access to the glucose value control system 510, or perform one or more additional operations of the blood glucose control system 510 (or the drug pump), such as other operations not related to the operation of the drug pump or delivery device 514.

[0037] The input / output circuit 532 can control communication with one or more other computing systems and / or the user. In some cases, the input / output circuit 532 can include one or more separate interface circuits or controllers to facilitate user interaction and / or communication. For example, the input / output circuit 532 may include a user interface circuit 534, a network interface circuit 536, and / or a touch screen controller 538.

[0038] The user interface circuit 534 may include any circuit or processor that can output the user interface to the user and / or receive user input from the user via the user interface. The user interface circuit 534 can receive one or more signals from the processor 530 corresponding to the user interface. The user interface circuit 534 can control a display to present the user interface to the user based on the one or more signals received from the processor 530. Further, the user interface circuit 534 may include any circuit that can receive a signal corresponding to the user's interaction with the user interface and that can provide the signal to the processor 530 and / or the controller 518 for further processing. In some cases, the user interface circuit may be replaced by a touch screen controller 538 that can control a touch screen interface. In other cases, the touch screen controller 538 may be added to the user interface circuit 534.

[0039] The network interface circuit 536 may include any circuit that enables communication with a wired network or a wireless network. The network interface circuit 536 may include one or more network interface cards and / or wireless radios (e.g., Bluetooth radio, Bluetooth Low Energy (BLE) radio, 4G LTE radio, 5G radio, ND-LTE radio, etc.).

[0040] The memory 540 may include non-volatile memory and / or volatile memory. The non-volatile memory may include flash memory or solid-state memory.

[0041] The control system 510 can also operate in an offline mode that is used to provide delivery of insulin (and potentially glucagon) independent of or without receiving the glucose values reported by the sensor 516. For example, if the sensor 516 needs to be replaced, is not properly connected to the subject 512, or is defective, the glucose control system 510 may operate offline without input from the sensor 516. Thus, the overall operation can be divided between an online period that each includes a series of sampling intervals when the glucose signal (value) 519 is available, and an offline period that each includes a series of sampling intervals when the glucose signal (value) 519 is completely or intermittently unavailable. The terms "online" and "offline" are used in the following description for these periods. Also, offline operation can be user-selected for any reason even if the glucose value signal 519 is available for use.

[0042] The user control input (USER CNTL523) can be provided via certain types of local or remote user interfaces. In some embodiments, the user interface may be similar to that of a conventional insulin pump or similar device, for example, by including control buttons for instructing the delivery of a bolus and perhaps a small display. In other embodiments, the system may have a wired or wireless interface to a remote device that can incorporate a more feature-rich user interface, such as a smartphone, smartwatch, laptop computer, desktop computer, cloud computing service, or other wearable or computing device. In some cases, the wireless interface may provide access to a local area network, such as an individual's home network, a company's network, etc. Alternatively, or in addition, the wireless interface can provide a direct connection between local devices that are available to the user (e.g., via Bluetooth or other short-range wireless communication technologies). In some cases, the wireless interface may provide access to a wide area network such as the Internet, but is not limited thereto. For example, the wireless interface may include a cellular interface that permits access to a network via a 4G or 5G cellular connection. In some cases, the cellular interface may be a low-power interface such as narrowband LTE or other Internet of Things (IoT) interfaces.

[0043] In the offline mode, the glucose sensor 516 may not be present, may not be functioning, or may not be attached to the subject 512. Thus, in the offline mode, the blood glucose signal 519 may not be available for use in controlling the automated operation. In some cases, the user may provide one or more blood glucose measurements to the control system 510 to facilitate the automated operation of the control system 510. These measurements may be provided over a specific period of time. Alternatively, or in addition, the glucose control system 510 may use the treatment history and / or the history of past blood glucose control measurements to facilitate the automated operation of the control system 510 for at least a specific period of time.

[0044] The description herein refers to a "user" as a source of user control input 523 The "user" as used herein can be the subject 512, a parent or caregiver of the subject 512, a healthcare provider (e.g., a clinician, a physician, or another person who can provide medical treatment to the subject), or any other user who may be permitted to assist in the management of the therapy of the subject 512. In certain implementations, the glucose value control system 510 is a personal device worn by the subject 512 for continuous glucose control. In some such implementations, the user and the subject 512 can be the same person. In other implementations, there may be another person who is involved in the care of the subject 512 and provides control input, and in such implementations, that other person has the role of the user.

[0045] Exemplary Controller of a Blood Glucose Control System FIG. 6 shows an exemplary structure of the controller 518 according to a particular embodiment. The controller 518 shown in FIG. 6 may represent a physical structure with different controllers or processors, or a logical structure implemented by one or more physical processors. In other words, a single processor may be used to implement each of the controllers shown in FIG. 6, each controller may be implemented by its own processor, or a particular processor may implement a plurality, but not necessarily all, of the controllers shown in FIG. 6 as part of the controller 518. Further, although the controllers in FIG. 6 are shown as part of the controller 518, in some implementations, one or more controllers may be separated from the controller 518.

[0046] The controller 518 may include four distinct controllers, namely, a glucagon (or antagonist regulator) controller 622, a basal insulin controller 624, a correction insulin controller 626, and a priming insulin controller 628. The basal insulin controller 624 includes a nominal rate controller 630 and an adjustment controller 632. As shown, the glucagon controller 622 generates a glucagon dosage control signal 634 provided to the glucagon delivery device 514-1. The respective outputs 636-640 from the controllers 624-628 can be combined to form an overall insulin dosage control signal 642 provided to the insulin delivery device(s) 514-2. As shown, the output signal 636 from the basal insulin controller 624 can be formed by the combination of the respective outputs of the nominal rate controller 630 and the adjustment controller 632. The insulin delivery device(s) 514-2 may include devices adjusted to deliver different types and / or amounts of insulin, and the exact configuration may be recognized by and / or under the control of the controllers 624-628. For ease of explanation, the collection of one or more insulin delivery devices 514-2 is hereinafter referred to in the singular as the insulin delivery device 514-2.

[0047] FIG. 6 also shows the input / output signals of various controllers, including glucose value signal 519, parameter 520, and user input 523, as well as set of inter-controller signals 644. The inter-controller signals 644 enable communication of information from one controller where the information is developed or generated to another controller where the information can be used for the control function of that controller.

[0048] Controllers 622-628 can operate in either an online mode / automode or an offline mode. In the auto mode, correction controller 626 adjusts the glucose value using a control scheme as described in U.S. Patent No. 7,806,854, the content of which is hereby incorporated by reference in its entirety. Basic controller 624 and priming insulin controller 628 can perform adaptive automatic control as described in International Publication No. WO2012 / 058694A2, the content of which is hereby incorporated by reference in its entirety. Controllers 622-628 generally include control parameters that are mathematically combined with the reported glucose value to generate an output value, which is converted (either directly or via additional adjustment) into dosage control signals 634, 642. For example, the control scheme described in U.S. Patent No. 7,806,854 includes a generalized predictive control (GPC) method incorporating various control parameters. The control algorithms are generally adaptive. This means that the control parameters are dynamically adjusted during operation to reflect the operating situation and "learning" mode that change, and the algorithm adjusts its operation more specifically to suit individual users by monitoring its own operation, enhancing the effectiveness of the algorithm and reducing or avoiding the need for additional explicit input information regarding the user. Note that input parameter 520 can form part of the control parameters used by the control algorithm. Other control parameters are internal parameters depending on the details of the algorithm, and selected ones of those internal control parameters are dynamically adjusted to achieve adaptation of the control algorithm. The control method or algorithm used generally involves control parameters that are mathematically combined with the reported glucose value to generate an output value, which is converted (either directly or via additional adjustment) into dosage control signals 634, 642. For example, the control scheme described in U.S. Patent No. 7,806,854 includes a generalized predictive control (GPC) method incorporating various control parameters. The control algorithms are generally adaptive. This means that the control parameters are dynamically adjusted during operation to reflect the operating situation and "learning" mode that change, and the algorithm adjusts its operation more specifically to suit individual users by monitoring its own operation, enhancing the effectiveness of the algorithm and reducing or avoiding the need for additional explicit input information regarding the user. Note that input parameter 520 can form part of the control parameters used by the control algorithm. Other control parameters are internal parameters depending on the details of the algorithm, and selected ones of those internal control parameters are dynamically adjusted to achieve adaptation of the control algorithm.

[0049] One feature of the operation is that the controller can learn from the period of recent past online operation and use that learning during offline operation. U.S. Patent No. 10,543,313, the entire content of which is incorporated herein by reference, describes two ways that can be used independently or together during offline operation. In the first method, when a separate glucose measurement is received, the correct size of the insulin correction bolus is automatically calculated, and then the correction bolus is administered by the system in response to user control input. In the second method, the correct size of the insulin meal bolus is automatically calculated and it is administered in response to user control input. Both methods utilize information obtained during a past period of online operation to automatically calculate the correct value, eliminating the need for the user to perform the calculation or provide a correction factor.

[0050] Tracking the Equivalence of Carbohydrate Therapies Hyperglycemia is a condition that occurs when the level of sugar or glucose in the blood exceeds a specific level (e.g., 180 mg / dL). This condition can occur in diabetic patients. To help reduce the occurrence of hyperglycemia, a subject can use an automatic blood glucose control system that can automatically provide insulin to the subject using a drug pump. The administered insulin can help control the subject's blood glucose level by consuming glucose in the subject.

[0051] Hypoglycemia is a condition that occurs when the level of sugar or glucose in the blood drops below a certain level (e.g., 70 mg / dL). This condition can have adverse effects including loss of consciousness, seizures, and death. The blood sugar levels that result in hyperglycemia and hypoglycemia can vary from patient to patient. To reduce the risk of hypoglycemia, a subject can consume carbohydrates to raise blood sugar levels. Since hypoglycemic events are associated with severe outcomes, subjects typically consume carbohydrates that are quickly metabolized. These carbohydrates are often unhealthy but are preferable to the occurrence of hypoglycemic events. For example, the carbohydrates may include candy bars that contain a large amount of refined sugar.

[0052] A biphasic glucose control system can reduce the risk of hypoglycemia by including, in addition to insulin, an antagonist regulator (e.g., glucagon) that can be administered to a subject when blood sugar levels become too low (e.g., less than 50 mg / dL). For subjects who do not have a biphasic glucose control system, it can be useful to understand carbohydrate therapy or a reduction in carbohydrate consumption to address hypoglycemic events or potential hypoglycemic events that can be achieved by switching to a biphasic glucose control system. Furthermore, understanding the reduction in carbohydrate therapy obtained by having a biphasic glucose control system can be useful for subjects who have a biphasic glucose control system. For example, understanding the amount of carbohydrate therapy consumed or avoided can become important in monitoring a subject's nutritional intake. Monitoring the nutrients being consumed is important for everyone, but it is particularly important for diabetics. This is because diabetics need to maintain a healthy diet and balance their blood sugar levels within a specific range to avoid both hyperglycemia and hypoglycemia.

[0053] The present disclosure relates to a system capable of performing a computer-implemented method for generating an indicator of total glycemic therapy over a period of time in a subject using a drug pump configured to deliver at least insulin therapy. The system can be an automatic blood glucose control system (e.g., glucose value control system 510) including a hardware processor (e.g., controller 518) for determining a dosage control signal to provide to the drug pump (e.g., delivery device 514). In some cases, the drug pump can be configured to deliver both insulin therapy and an antagonist regulator (e.g., glucagon) therapy. Alternatively, the system may be separate from the blood glucose control system but may receive blood glucose information from the blood glucose control system. For example, the system may be a personal computing system or a cloud computing system capable of receiving blood glucose information from the blood glucose control system.

[0054] The system can receive or determine the glucose value of a subject (e.g., subject 512). The glucose value of the subject can be determined based on a signal (e.g., glucose value signal) received from a continuous glucose monitoring (CGM) sensor (e.g., glucose sensor 516) corresponding to the glucose value of the subject. In some cases, the glucose value can be determined from a discrete glucose measurement, e.g., a measurement obtained using a glucose measurement kit and / or glucose paper.

[0055] The system can determine whether a trigger event has occurred to increase the subject's blood glucose level, using at least the subject's glucose value. Examples of trigger events include the occurrence of a hypoglycemic event within a specific period or a blood glucose value indicating the risk of occurrence of a hypoglycemic event exceeding a risk threshold. The risk of a hypoglycemic event can be determined when the subject's glucose value falls below a glucose threshold. This glucose threshold may vary for each subject and, in some cases, can be specified by the subject or a caregiver (e.g., a healthcare provider, parent, or guardian). Thus, in some cases, different trigger events can be defined based on the subject's risk tolerance for the occurrence of hypoglycemia or possible different preferences for the amount of blood glucose present in the subject. Depending on the subject, for example, due to differences in activity level or metabolism among different subjects, they may prefer or attempt to maintain blood glucose at different levels. Determining the risk of occurrence of a hypoglycemic event may include receiving an indicator of the risk of hypoglycemia or a prediction of a future glucose value from a glucose sensor. For example, determining an imminent risk of hypoglycemia may include a determination that the subject's blood glucose level is expected to be less than 60 mg / dl within the next 5 to 15 minutes.

[0056] In response to a trigger event, the system can determine the amount of counterregulatory agent to administer, or the amount of counterregulatory agent to be administered if the blood glucose control system includes the ability to administer the counterregulatory agent. In some cases, the counterregulatory agent is administered, for example, by an automated blood glucose control system. In other cases, the counterregulatory agent is not administered. For example, the automated blood glucose control system may not be able to deliver the counterregulatory agent. As another example, the automated blood glucose control system may be able to deliver the counterregulatory agent but may not have an available dosage of the counterregulatory agent.

[0057] The system can determine the corresponding amount of carbohydrate using an indicator of the antagonist modulator to be administered or that will be administered. The corresponding amount of carbohydrate can represent the amount of carbohydrate consumed to prevent a hypoglycemic event, consumed to reduce the risk of a hypoglycemic event, or consumed in response to the occurrence of a hypoglycemic event. Alternatively, or in addition, the corresponding amount of carbohydrate can represent the amount of carbohydrate that would have been consumed if the antagonist modulator had not been available. will.

[0058] The corresponding amount of carbohydrate can be obtained from a mapping between the amount of antagonist modulator and the amount of carbohydrate. In some cases, the mapping can be based on an equivalence measured between the carbohydrate and the antagonist modulator. Alternatively, or in addition, the mapping can be a mapping between the determined amount of antagonist modulator and the amount of carbohydrate indicative of what the subject would typically consume if a hypoglycemic event were determined to be likely to occur.

[0059] This mapping can be implemented by a lookup table that maps different amounts of antagonist modulator to different corresponding amounts of carbohydrate. In some cases, depending on the type of carbohydrate consumed (e.g., simple and complex carbohydrates, or the type of candy bar consumed), a single amount of antagonist modulator can be mapped to different amounts of carbohydrate. Alternatively, the mapping can be based on a mathematical formula that converts the amount of antagonist modulator to the amount of carbohydrate based on the correspondence between the amount of antagonist modulator and the amount of carbohydrate. The relationship between the antagonist modulator and the carbohydrate can be determined based on clinical trials comparing the carbohydrate and the antagonist modulator (e.g., glucagon, dextrose, etc.). Further, the mapping can be based at least in part on the subject's preferred carbohydrate source and / or the subject's characteristics (e.g., weight).

[0060] In some cases, the system can track the number of hypoglycemic events or the number of occurrences of triggers indicating an imminent risk of hypoglycemic events within a specific period. This period can be several days, weeks, months, years, or any other period for which it is desirable to determine the relationship between the carbohydrates consumed or avoided, based on the unavailability or availability of counterregulatory agents. In some cases, the tracking of carbohydrate therapy can be based on the number of hypoglycemic events or hypoglycemic risk events, instead of or in addition to this period.

[0061] For each occurrence of a hypoglycemic event or a trigger indicating an imminent risk of a hypoglycemic event, the system can determine an estimated value of carbohydrate therapy that has been saved or would have been saved by having access to a counterregulatory agent. The system can generate a report indicating the total amount of carbohydrates saved during the period, or saved by having access to a counterregulatory agent. This report can include the total or sum of carbohydrate therapy required or saved during the period. This period can be several days, weeks, months, years, or after a specific time (e.g., since the subject started using the system). Further, the report can indicate the types of carbohydrates typically consumed by the subject in response to a hypoglycemic event or risk of an imminent hypoglycemic event. This report can be presented to the subject, a healthcare provider, and / or the subject's parent or guardian. The healthcare provider can use this report to assist in the care of the subject. For example, the healthcare provider can use the report to create a nutrition plan for the subject, taking into account the carbohydrates consumed to maintain blood glucose levels within a desired or set range.

[0062] The report can include the range of carbohydrate therapies that are likely to be avoided or consumed to address the risk of hypoglycemic events. Further, the report can include the amount of calories saved or not consumed, the amount of sugar avoided, the amount of food not consumed, the possible weight gain avoided, etc., based on the consumption of counterregulatory agents instead of carbohydrate therapy.

[0063] Equivalence Tracking Process for Carbohydrate Therapy FIG. 7 presents a flowchart of an exemplary carbohydrate therapy equivalence tracking process 700 according to a particular embodiment. Process 700 can track a subject's glucose value over time and identify the occurrence of a hypoglycemic event, or when the risk of a hypoglycemic event meets or exceeds a threshold (e.g., when the risk of a hypoglycemic event matches or exceeds a particular probability), by any system that can be implemented. For example, process 700 may be implemented by one or more elements of glucose value control system 510. In some cases, at least certain operations of process 700 may be implemented by a separate computing system that receives an indicator of the subject 512's blood glucose value and / or an indicator of a hypoglycemic event (or an indicator identified as a hypoglycemic risk event exceeding a threshold) from glucose value control system 510. Although one or more different systems can perform one or more operations of process 700, for simplicity of discussion and without limiting the present disclosure, process 700 is described with respect to a particular system.

[0064] Process 700 begins at block 702 where glucose value control system 510 receives the glucose value of subject 512. Receiving the glucose value can include receiving a glucose value signal corresponding to the subject's glucose value. The glucose value signal can be received from a glucose sensor 516 (e.g., a CGM sensor). Alternatively, or in addition, the glucose value can be received from a user who provides the glucose value to glucose value control system 510 via a user interface such as a user interface generated by processor 530 that can be output on the touch screen by touch screen controller 538. The glucose value received from the user can be a glucose value measured using an alternative sensor or measurement mechanism (e.g., a diabetes measurement strip) that can be used in place of glucose sensor 516.

[0065] In block 704, the glucose value control system 510 determines that a trigger event has occurred to increase the blood glucose value of the subject 512, based at least in part on the glucose value. The trigger event may include a determination that a hypoglycemic event or episode of hypoglycemia exists or is occurring within the subject 512. Alternatively, or in addition, the trigger event may include a determination that there is an imminent risk of hypoglycemia in the subject 512, or a determination that there is an imminent risk of a hypoglycemic event occurring within a specific time period in the subject 512. The determination of a hypoglycemic event or the risk of a hypoglycemic event occurring may be determined by comparing the glucose value of the subject to a glucose threshold. Alternatively, or in addition, the determination of a hypoglycemic event or the risk of a hypoglycemic event occurring may be determined by comparing the trend and / or rate of change (e.g., rate of decrease) of the glucose value to a threshold. In some cases, a combination of a specific blood glucose value and the trend of the blood glucose value can be used to determine the risk of hypoglycemia. For example, if the glucose value is low (e.g., below a specific threshold such as 60 mg / dL), but the determined trend of the glucose value is upward, the risk of hypoglycemia may be lower than if the glucose value is above the threshold but the determined trend of the glucose value is downward towards the threshold. In some cases, the threshold(s) used to determine whether a hypoglycemic event is occurring or to determine that there is a risk of exceeding the threshold for the occurrence of hypoglycemia may vary based on the physiological characteristics of the subject 512. This physiological characteristic may be based on physiological characteristics that are associated or shared among groups of patients (e.g., gender, age, weight), or may be specific to a particular subject 512. For example, the threshold related to the risk of hypoglycemia may be determined based on the determined glucose value of the subject 512 during past occurrences of hypoglycemia determined by the glucose value control system 510, or based on clinical data specific to the subject 512.

[0066] In response to a trigger event at block 704, the glucose value control system 510 determines the amount of the antagonist regulator at block 706. The glucose value control system 510 can determine the amount of the antagonist regulator based at least in part on the blood glucose value of the subject 512, the amount or rate of the risk of hypoglycemia occurring (e.g., if the risk or probability of hypoglycemia is 99%, a higher dose of the antagonist regulator can be triggered than when the risk or probability of hypoglycemia is 75%), the physiological characteristics of the subject 512, the trend of the blood glucose value of the subject 512, or the type of the antagonist regulator.

[0067] In some cases, the glucose value control system 510 can deliver the determined amount of the antagonist regulator to the subject 512 using the delivery device 514-1. The antagonist regulator can be delivered to the subject 512 in response to an imminent risk of hypoglycemia or a hypoglycemic episode and / or in response to a glucose value that meets or falls below a threshold glucose value. The determination of whether to deliver the threshold glucose value or the antagonist regulator can be based on the physiological characteristics of the subject 512 and / or the risk tolerance of the subject 512 to hypoglycemic events. It should be understood that herein, the risk tolerance generally does not refer to the subjective risk tendency of the user. Instead, the risk tolerance is usually an objective determination value of how likely the subject 512 is to have a hypoglycemic event or how likely hypoglycemic symptoms will occur when the blood glucose value of the subject 512 is at a specific level. This risk tolerance can be determined based on the history of hypoglycemia or its absence in the subject 512 at a specific blood glucose value and / or based on the clinical data obtained for the subject 512.

[0068] In other cases, the glucose value control system 510 may not need to deliver the antagonist regulator to the subject 512, for example, because the glucose control system 510 may not be able to deliver the antagonist regulator, or because the cartridge holding the antagonist regulator is empty or only has less than a threshold amount of the antagonist regulator remaining.

[0069] In block 708, glucose value control system 510 determines the dosage of carbohydrate therapy based at least in part on the antagonist regulator. Carbohydrate therapy may refer to carbohydrates consumed to prevent or respond to the occurrence of hypoglycemia. Carbohydrates can include any type of carbohydrate that subject 512 can consume to prevent or respond to the occurrence of hypoglycemia, and can typically include fast-acting carbohydrates including carbohydrate foods that are easily converted to sugar in the human body. For example, the carbohydrates may be candy bars, sodas, fruit juices, or other foods that may contain a lot of sugar or refined sugar.

[0070] Determining the dosage of carbohydrate therapy may include accessing a mapping between the antagonist regulator and the carbohydrates. This mapping can be stored in memory 540 and accessed therefrom, and / or accessed from another computing device. Glucose value control system 510 can determine the dosage of carbohydrate therapy based at least in part on the mapping and the amount of the antagonist regulator. In some cases, the mapping may vary based on the type of antagonist regulator and / or the type of carbohydrate. The type of antagonist regulator can be specified by the user or automatically determined based on a drug cartridge installed or inserted into glucose value control system 510. Further, the type of carbohydrate can be specified by the user and can include identification information of the type of carbohydrate that is typically consumed by subject 512 when responding to the occurrence or risk of occurrence of hypoglycemia. For example, the user may specify via the user interface whether the subject typically consumes candy bars or fruit juices, or the size of the carbohydrates that are typically consumed when responding to the occurrence or risk of occurrence of hypoglycemia.

[0071] In some cases, the mapping between the antagonist regulator and the carbohydrates can be generated based on a clinical comparison between the antagonist regulator and the carbohydrates. Alternatively, or in addition, the mapping can be based at least in part on the physiological characteristics of subject 512.

[0072] The mapping can be stored in a lookup table or other data structure that can remember the relationships between various carbohydrates and the counterregulatory agents. The mapping can be a mapping between different amounts and / or types of carbohydrates and different amounts and / or types of counterregulatory agents. Alternatively, or in addition, the mapping can be a mathematical formula that associates a carbohydrate with a counterregulatory agent or vice versa. For example, the glucose value control system 510 may use the determined amount of the counterregulatory agent as an index into a lookup table to determine the corresponding amount of the carbohydrate. Alternatively, the glucose control system 510 may apply the determined amount of the counterregulatory agent to a mathematical formula to calculate the corresponding amount of the carbohydrate. This mathematical formula can be generated based on the type of the counterregulatory agent and / or carbohydrate, the physiological characteristics of the user, and / or clinical data.

[0073] In some cases, the mapping can vary based on the glucose value control system 510. For example, if the glucose value control system 510 (or its drug pump) is a bihormonal pump configured to deliver insulin and counterregulatory agent therapy to a subject, the glucose value control system 510 may include a first mapping, and if the glucose value control system 510 is not configured to deliver counterregulatory agent therapy to the subject 512, it may include a second mapping. In some cases, the glucose value control system 510 can store both mappings in the memory 540. For example, the glucose value control system 510 may use the first mapping when the counterregulatory agent is available and the second mapping when the counterregulatory agent is not available. The mapping can vary for a plurality of reasons. This includes that the bihormonal glucose value control system 510 can more accurately control the occurrence of hypoglycemic events due to the availability of the counterregulatory agent that can change the frequency and type of carbohydrates that the subject can consume.

[0074] In block 710, the glucose value control system 510 outputs an indicator of the dosage of carbohydrate therapy. Outputting an indicator of the dosage of carbohydrate therapy may include outputting an indicator of the dosage of carbohydrate therapy on a display for presentation to a user. Further, the indicator of the dosage of carbohydrate therapy may be sent to another computing system to display or aggregate other therapy data related to subject 512, such as therapy data used by a clinician to assist in managing the care of subject 512. In some cases, the indicator of the dosage of carbohydrate therapy may be included in a report corresponding to the care of subject 512.

[0075] In certain embodiments, the operations of process 700 are performed or repeated over a period of time. For example, the operations associated with blocks 702-708 may be repeated one or more times over a period of time. In such cases, the determined dosage of carbohydrate therapy may be aggregated over a period of time and the total carbohydrate therapy for the period is determined. Further, block 710 may include outputting an indicator of the dosage of carbohydrate therapy for each individual time at which the dosage of carbohydrate therapy is determined and / or outputting the determined total dosage of carbohydrate therapy for a period of time. This period of time may be any period. For example, this period of time may be one day, one week, one month, one year, since subject 512 started using the glucose value control system 510, since the user obtained access to the counter-regulatory agent, or since the user lost access, or any other period. In some cases, the period of time is defined by the occurrence of a hypoglycemic event or the occurrence of a risk of hypoglycemia meeting a threshold. For example, the period of time may be the time associated with the occurrence of 5, 10, 15, 100, or other number of hypoglycemic events or risks of hypoglycemia meeting a threshold.

[0076] Indicators of total carbohydrate therapy can, for example, correspond to a decrease in carbohydrates consumed by subject 512 due to, for example, the availability of an antagonist regulator to the glucose value control system 510 and thus to subject 514. Thus, indicators of total carbohydrate therapy can correspond to a decrease in carbohydrates achievable by the availability of an antagonist regulator to subject 512. Further, indicators of total carbohydrate therapy can correspond to the amount of antagonist regulator provided or available for provision to the subject as a substitute for carbohydrates.

[0077] The specific carbohydrates consumed by each subject, or the amount of carbohydrates consumed during each hypoglycemic event, can vary. For example, subject 512 may consume a particular candy bar if the measured blood glucose value of subject 512 is too low, or if the subject feels that the blood glucose value is likely to be low (e.g., begins to feel some hypoglycemic effects). The subject may consume all of the candy bar or a portion of it. A portion of the candy bar may be lost from the subject (e.g., fall to the ground). In other cases, the subject may have different available candy bars or other refined sugar sources during different hypoglycemic events. Thus, even if there may be an objective mapping between carbohydrates and antagonist regulators, the amount of carbohydrates consumed or avoided due to the availability of an antagonist regulator can vary for each hypoglycemic event. Thus, indicators of total carbohydrate therapy that are avoided or can be avoided when an antagonist regulator is available can indicate the range of carbohydrates that can potentially be replaced by the availability of an antagonist regulator. Indicators of total carbohydrate therapy that are avoided or can be avoided when an antagonist regulator is available can indicate the range of carbohydrates that can potentially be replaced by the availability of an antagonist regulator.

[0078] In some cases, the metrics for carbohydrate therapy or total carbohydrate therapy may include one or more of a calorie metric, a carbohydrate metric, a sugar measurement metric, a food quantity metric, or a metric of the subject's weight resulting from carbohydrate therapy. The metrics may be associated with what is consumed due to the lack of counterregulatory agents or what is avoided based on the availability of counterregulatory agents. For example, the calorie metric may be the amount of calories not consumed due to the presence of counterregulatory agents. Advantageously, by making treatment information related to carbohydrate therapy or avoided carbohydrate therapy available, patient care can be supported. For example, the subject can reduce the consumption of refined sugars that can have a significant impact on health. Further, the healthcare provider can better assist the subject in controlling their weight based on carbohydrate information.

[0079] The metrics for carbohydrate therapy can be presented to the user in any presentable form. For example, the metrics for carbohydrate therapy may be presented as a table, chart, graph, histogram, or other data presentation tool for showing the reduction of carbohydrates over time that can be achieved by the presence of counterregulatory agents or can be achieved by the use of counterregulatory agents for a particular subject 512. It should be understood that the metrics for carbohydrate therapy data can vary from user to user due to factors such as differences in the physiological characteristics of the users, differences in diabetes for each user, and differences in the lifestyle of each user. Advantageously, by using the glucose value control system 510 to track the carbohydrate therapy of the subject 512 or to determine the carbohydrate therapy that is avoided or avoidable in relation to counterregulatory agents, the management of the blood glucose level of the subject 512 can be personalized.

[0080] Embodiments of additional carbohydrate therapy equivalence tracking Diabetic patients often consume oral carbohydrates for the purpose of treating or preventing hypoglycemia. Such extra carbohydrates can lead to unhealthy outcomes, one of which is weight gain. By having a bihormonal glucose control system that infuses an anti-regulatory agent (e.g., glucagon) to reduce the frequency, degree, and duration of hypoglycemia, the amount of oral carbohydrates "medically" required to treat or prevent hypoglycemia can be significantly reduced.

[0081] Certain embodiments of the present disclosure relate to a method of converting the amount of online anti-regulatory dosing (e.g., glucagon) calculated by an autonomous glucose control system into an amount of carbohydrate that is presumed not to be needed by the user for anti-regulatory dosing, or an amount of carbohydrate that is not needed by the user when the user has access to an anti-regulatory agent. In a bihormonal autonomous glucose control system that infuses both insulin and an anti-regulatory agent / hormone, the method can include a mapping between the online anti-regulatory dosing delivered to treat or prevent low glucose values and the oral carbohydrates otherwise estimated to be required to achieve an equivalent safe control situation (if the anti-regulatory dosing had not been delivered). In an insulin-only autonomous glucose control system where the dosing of the anti-regulatory agent / hormone is not delivered but is still calculated online, the method can include a mapping between the calculated online anti-regulatory dosing and an estimated amount of oral carbohydrates that the subject is likely to be spared from the need to consume to treat or prevent low glucose values if the anti-regulatory agent were available and its dosing were actually delivered.

[0082] Without loss of generality, embodiments disclosed herein include an autonomous glucose control system where the antagonist regulator is specifically glucagon. However, other agents and / or antagonist regulators can be utilized. The method relates the calculated online glucagon dosing to oral carbohydrates consumed for the treatment or prevention of low glucose values observed in actual use (e.g., during clinical studies) in an insulin-only configuration (the "treatment carbohydrates"), and may include relating the relationship between the antagonist regulator and the carbohydrates to a similar relationship between the delivered online glucagon dose (or other antagonist regulator) and oral carbohydrates similarly consumed in a bihormonal (insulin-glucagon) configuration.

[0083] Using data collected from actual use (e.g., clinical studies), the treatment carbohydrates C consumed in an insulin-only configuration io and the relationship between the online calculated (not delivered) glucagon dosing Gc is relationship C io =R io (x)*Gc, where R io (x) can be a relevance factor and can be a function of a plurality of dependencies included in vector x. Such dependencies can include the specific insulin and / or glucagon being used (e.g., their clinical characteristics), and / or the pharmacokinetic settings assumed by the control system with respect to insulin and / or glucagon. This dependency can also include the user's physique and the glucose target used by the glucose control system. In some embodiments, (e.g., due to limited effect, limited variation in the relevant dependencies, or no variation at all) for a system showing limited variation in the relationship between C io and G c , Rio(x) can be a constant or Rio(x)≡Rio.

[0084] Similar to the insulin-only configuration, from actual data, the treatment carbohydrates C consumed in a bihormonal (insulin-glucagon) configuration bhand the glucagon dosage G delivered online d The relationship with is C bh =R bh (x)*G d can be described by the relationship. In the formula, R bh (x) can be described in the same way as the above R io (x). In some cases, C io , G c , C bh , and G d The amounts of and G may refer to the daily amount averaged over a certain period of use (e.g., one week). In some cases, C io , G c , C bh , and G d The amounts of and G refer to the average daily amount per user's body build, and in this case, the dependence on body build can be excluded from x.

[0085] Although G c is calculated, if glucagon is not actually delivered in an insulin-only system, G c has no effect on glucose as long as it treats or prevents low glucose values, which, in turn, generally causes a further calculated glucagon dosage to be triggered (e.g., proceeding in the direction of increasing the magnitude of G d for a given situation). In contrast, since G d is delivered in a bihormonal system, it is expected to have the effect of preventing or reducing the frequency, degree, or duration of low glucose values, thereby limiting the overall magnitude of the glucagon dosage (e.g., limiting G d for a given situation). Therefore, for a given set of dependencies, generally, G c >G d is expected to occur between the two system configurations. Similarly, G c has no effect on counteracting low glucose values, while G d has such an effect. Therefore, when comparing the two system configurations, the therapeutic carbohydrate is C io >C bh is expected.

[0086] For a given actual usage example of an insulin-only system using Gc, the calculated online glucagon dosage when actually delivered as G d and the corresponding C for the same actual usage scenario when delivered as such can be ideally associated. Instead, if a dual-hormone system (using the same insulin controller) in which glucagon would have been delivered is used, it can be predicted that the user would have required (e.g., would have been able to save) only less therapeutic carbohydrates of "C io -C io -C bh ". Conversely, for a given actual usage example of a dual-hormone system having G d when the online glucagon dosage to be delivered is not delivered and is only calculated as G and the corresponding C for the same actual usage scenario can be ideally associated. Instead, if an insulin-only system (using the same insulin controller) in which glucagon is not delivered is used, it can be predicted that the user would have actually avoided the need to ingest the additional therapeutic carbohydrates of "C c -C bh ". In reality, it should be understood that the above calculations are estimates in an ideal situation because it is impossible to rerun past actual scenarios to obtain such an ideal relationship. io -C bh ". In reality, it should be understood that the above calculations are estimates in an ideal situation because it is impossible to rerun past actual scenarios to obtain such an ideal relationship.

[0087] In an actual implementation, while assuming that a dual-hormone system in which glucagon is assumed to be delivered is available, the actual usage examples in which an insulin-only system was used can be resimulated. Since the control system can take into account the delivered dosage when issuing subsequent nearby glucagon dosages, the simulated glucagon dosage is the original G of the insulin-only system ccan show a decrease. However, if the glucose profile remains unchanged in the simulation, the simulation may not reflect the glucose excursions that occur in response to the assumed delivered glucagon dose. The simulation may not reflect the complete decrease in glucagon dose up to G d and may overstate the magnitude of the decrease in glucagon dose observed in the simulation, the pseudo-delivered glucagon

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[0088] Certain embodiments include a system that includes a controller for automatically controlling the blood glucose level of a subject. The controller can be operative to generate an insulin dosage control signal based on the time-varying glucose value of the subject, represented by a glucose value signal over time. The glucose value signal can be generated by a glucose sensor operative to continuously sense the glucose value of the subject. The insulin dosage control signal can control the delivery of the dosage of insulin by a delivery device. Further, the controller can operate at a certain frequency to generate an insulin dosage control signal for adjusting the glucose value of the subject. During online operation, the controller can use a control algorithm that generates a glucagon dosage signal, which can be mapped to a relevant amount of oral carbohydrates.

[0089] Oral carbohydrates may be relevant to the prevention or treatment of low glucose values. Further, the mapping between the glucagon dosing signal and oral carbohydrates can be derived from the analysis of clinical data. The glucagon dosing signal can be calculated but is not delivered in an insulin-only system configuration. In contrast, the glucagon dosing signal can be calculated and glucagon can be delivered in an insulin-glucagon system configuration. The glucagon dosing calculated in an insulin-only system configuration can be mapped to the amount of oral carbohydrates presumed to be saved when glucagon dosing is delivered if an insulin-glucagon system configuration were used instead. The glucagon dosing delivered in an insulin-glucagon system configuration can be mapped to the amount of oral carbohydrates presumed to be saved if an insulin-only system configuration were used instead. The mapping can depend on the clinical characteristics of the insulin and glucagon being used, as well as the settings of the control system related to the actions and effects of insulin and glucagon. Further, the mapping can depend on the physique of the subject.

[0090] Generation of Backup Therapy Protocol Portable drug delivery devices, such as blood glucose control systems (e.g., insulin pumps or pumps for combinations of insulin and counterregulatory agents (e.g., glucagon)), can provide personalized therapy to a subject. In other words, portable drug delivery devices can provide drugs that are specific to the physiological state, symptoms, activities, etc. of the subject. Further, some portable drug delivery devices monitor the subject's symptoms to determine when to provide therapy, what type of therapy (e.g., insulin or counterregulatory agent therapy) to provide, and / or how much therapy to provide. The therapy provided by a portable drug delivery device may be a continuous therapy and, in some cases, a life-saving therapy. Therefore, it is important that the portable drug delivery device functions without interruption.

[0091] However, despite best efforts, therapy with a portable drug device may be interrupted. For example, the portable drug device may be damaged, the subject may run out of or be unable to access necessary disposable items (e.g., replacement insulin cartridges, site kits for changing parts of the portable drug device, replacement batteries, etc.), or the subject may forget to charge the battery of the portable drug device or there may be no available power source to charge the portable drug device. Thus, there may be cases where the portable drug device is unavailable or in need of replacement. When the portable drug device is unavailable or in need of replacement, it may be desirable to obtain an indication of the treatment settings from the portable drug device. For example, if a user (e.g., the subject, a healthcare provider, a parent, or a caregiver) is providing an alternative therapy (e.g., injection therapy) during the implementation of the portable drug device, it may be necessary to know the amount of therapy to be provided under certain circumstances or at a certain time.

[0092] In some cases, a healthcare provider may be able to access treatment information that may have been determined in the past, e.g., by a clinical trial. This treatment information may include any type of information that can be used to determine the therapy to be provided to the subject under certain times or conditions. For example, the treatment information may indicate a set insulin range for the subject, the amount of insulin to be provided to the user to adjust glucose values, the amount of time it takes for insulin to reach maximum concentration in the subject, or any other information that may affect the timing or amount of drug dosing.

[0093]

[0094] ​However, there may be cases where the treatment information available to the healthcare provider is insufficient. For example, the subject may not be able to contact the healthcare provider to obtain treatment information at the time when the information is needed. Further, in some cases, for example, since the therapy may be improved over time by a portable drug device, the information may be outdated. If the improvement has been recently made, the healthcare provider's old values may be sufficient until the replacement portable drug device can repeat the improvement process of the original portable drug device. However, in other cases, for example, since there may have been significant improvements since the last clinical trial was conducted, or there may have been physiological changes (e.g., weight gain or loss, or metabolic changes) in the subject, the old treatment information may be insufficient. Using old treatment information may result in reduced effectiveness, discomfort to the subject, or harm.

[0095] Certain embodiments of the systems disclosed herein can generate backup therapy data. Using the backup therapy data, a subject (or user) can perform an injection therapy or configure a replacement portable drug device even if the subject's current device malfunctions. By using the backup therapy data, the subject can maintain a level of care that matches or more closely matches what was provided by the portable drug device than the clinical data that may be available but outdated.

[0096] The system may include an automatic blood glucose control system (e.g., glucose value control system 510), and the automatic blood glucose control system is configured to generate a backup therapy protocol that includes an instruction for insulin therapy derived from an autonomously determined insulin dosage. During normal operation, the system can receive a glucose value signal from a sensor operably configured to determine the subject's glucose value. The sensor can include any type of sensor that can determine a glucose value. For example, the sensor may be a continuous glucose monitoring (CGM) sensor.

[0097] Using the determined glucose value, the system can autonomously determine and / or generate a dosage control signal using a control algorithm. The determination and / or generation of the dosage control system can be performed without user operation or interaction with a blood glucose control signal. In some cases, the lack of user operation or interaction with the blood glucose control system refers to conscious behavior, and sensor measurements of the subject's physiological characteristics can be excluded. The control algorithm can autonomously determine the dosage of insulin to be injected into the subject for the purpose of controlling the subject's blood glucose based at least in part on the glucose value signal. The control algorithm can include any type of control algorithm.

[0098] For example, the control algorithm may be a biexponential pharmacokinetic (PK) model that models the accumulation of insulin dosage in the subject's plasma. The automated blood glucose system can control the delivery or administration of insulin or an antagonist regulator based on the biexponential PK model and one or more blood glucose measurements of the subject. The biexponential PK model can model the absorption of subcutaneously administered insulin into the blood and / or the rate of decrease of glucose in the blood. The biexponential PK model over time can be represented by the following mathematical formula.

Equation

[0099] As an alternative example, the control algorithm may include a linear algorithm that models the decrease or accumulation of glucose in a subject based on a linear rate of decrease. For example, the control algorithm may determine that a specific dose D of insulin is to be administered to the subject. Next, the control algorithm may estimate that insulin is absorbed into the plasma at a rate of 0.25*D per hour over 4 hours. Similarly, the control algorithm may estimate that insulin decreases at a rate of 0.33*D per hour over 3 hours when the insulin reaches its maximum concentration in the plasma.

[0100] Regardless of the control algorithm used, an automated blood glucose control system can administer insulin, and in some cases, an anti-regulatory agent, one or more times over a specified period. There can be multiple reasons and / or triggers that cause the automated blood glucose control system to supply insulin. For example, the automated blood glucose control system may periodically provide a basal dose of insulin in an attempt to maintain a stable blood glucose level in the subject's plasma. As another example, the automated blood glucose control system may supply a meal-time bolus of insulin in consideration of the expected amount of glucose consumed as part of a meal. The meal-time bolus can be an amount specified by the user or the amount of insulin administered in response to an indicator of the meal size by the subject. This indicator of the meal size can be subjective. In some cases, the size of the insulin bolus for a specified meal size can be a fixed or constant value. In some other cases, the size of the insulin bolus for a specified meal size can vary over time as the automated blood glucose control system learns or improves the amount of insulin to administer to the subject to keep the subject's blood glucose within a target set point. The automated blood glucose control system can learn or improve the optimal insulin to administer based on a comparison of the predicted blood glucose measurement value to the actual blood glucose measurement value when the subject (or another user) makes a subjective determination of the meal amount. In addition to the basal and meal-time boluses of insulin, the automated blood glucose control system can also supply a corrective dose of insulin to the subject based on a glucose value signal. The corrective dose of insulin can be supplied in response to a model predictive controller (MPC) that determines or estimates that the user's insulin level is expected to fall below a threshold over a future period based on the measured value of the blood glucose. The MPC can execute a control algorithm that can adjust the glucose concentration to a reference set point while simultaneously minimizing both the aggressiveness of the control signal and local insulin accumulation. The mathematical formulation that describes the subcutaneous accumulation of the administered insulin can be derived based on nominal time values related to the pharmacokinetics of insulin in the subject.The mathematical formulation can relate to insulin absorption rate, peak insulin absorption time, and / or overall action time of insulin (or other agents). An example of an MPC controller that can be used with embodiments of the present disclosure is described in U.S. Patent No. 7,806,854, issued October 5, 2010, the disclosure of which is hereby incorporated by reference in its entirety for all purposes.

[0101] An automatic blood glucose control system can track insulin therapy administered to a subject over a tracking period. The tracking period is not limited in length and can generally be any period, but typically, the tracking period is at least a minimum period sufficient for the automatic blood glucose control system to learn or improve the amount of agent (e.g., insulin) administered to the subject under certain conditions (e.g., when a specific blood glucose value is detected, or when a specific meal amount is specified). For example, the automatic blood glucose control system may first administer 6 units of insulin for lunch and 10 units of insulin for dinner. These initial values can be set by a healthcare provider and / or the subject, for example, based on the subject's clinical data. However, over time (e.g., 3 - 5 days), the automatic blood glucose control system may determine that by providing 7 units of insulin for lunch and 8 units of insulin for dinner, the subject's blood glucose value is maintained closer to the median of the set value range than the initial configuration. Although not limited as such, generally, each unit of insulin is 1 / 100 milliliter of insulin.

[0102] As shown, the tracking period can be a time of any length. For example, the tracking period can be 1 day, 3 days, 5 days, 7 days, or any period in between, or more. Usually, the tracking period is at least long enough to provide sufficient time to learn or improve the initial settings of the automated blood glucose control system for the subject. In some cases, the tracking period can be 1 day or 2 days. In other cases, the tracking period can be from a specific period to the current period. For example, the tracking period can be from the start of the therapy to the current time. In other cases, the tracking period can be a moving window or a shifting window. For example, the tracking period can be at least 1 week, 2 weeks, 1 month, or 1 year. Further, in the case of a non-blood glucose system, the tracking period can vary based on the amount of time sufficient to determine or improve the drug control value for the subject. In some cases, the tracking period can be a window of a specific length. This window can be a moving window. For example, the window can be the past 7 days. Over time, the window moves and continues to include the past 7 days.

[0103] Tracking insulin therapy can include storing the autonomously determined insulin dosages delivered to the subject. These autonomously determined insulin dosages can include one or more of a basal insulin dosage, a meal-time insulin bolus, or a correction insulin dosage. Further, tracking insulin therapy can sometimes include tracking the type of insulin used. Examples of insulin types include any type of insulin such as rapid-acting insulin (e.g., lispro, aspro, or glulisine), rapid- or short-acting insulin (e.g., Humulin R, Novolin R, or Velosulin R), intermediate-acting insulin (e.g., Humulin N, Novolin N, ReliOn), long-acting insulin (e.g., detemir (Levemir), glargine (Basaglar, Lantus)), or ultra-long-acting insulin (e.g., degludec (Tresiba), glargine u-300 (Toujeo)). Further, tracking insulin therapy can include tracking antagonist regulator (e.g., glucagon) therapy.

[0104] In some cases, tracking insulin therapy may include calculating the average therapy provided over a certain period (e.g., the entire tracking window). For example, tracking insulin therapy may include determining a moving average of the nominal basal dose over the past 7 days during each dosing interval. Assuming the basal therapy is provided every 5 minutes, the moving average can be calculated based on the past 288 doses (e.g., for 1 day) or 2016 doses (e.g., for 7 days). This calculation can be used to obtain the backup therapy's basal rate profile. In some cases, the period is divided into different time segments, and the time segments can be associated with different treatment rates. For example, there may be four basal therapy periods (e.g., 10 p.m. to 4 a.m., 4 a.m. to 10 a.m., 10 a.m. to 4 p.m., and 4 p.m. to 10 p.m.). Thus, for each of the basal therapy periods over a day or other certain period (e.g., 7 days) a separate moving average can be calculated. The calculated average can be used to calculate a backup basal rate that can be used to program an automatic glucose control system. Further, the basal rate profile may include aggregating the doses over a day to determine the dose of long-acting insulin that can be used for injection therapy.

[0105] Similar to the basal therapy, a moving average of the correction doses can be calculated, and the correction bolus of insulin to be supplied can be determined via pump therapy or injection therapy. Alternatively, or in addition, the moving average of the correction doses combined with the measured blood glucose values of the subject over time can be used to determine the rate of change of blood glucose from the units of insulin provided during correction therapy.

[0106] The meal bolus can also be calculated using a moving average. Further, separate moving averages can be calculated for the dosage of each meal (e.g., breakfast, lunch, and dinner) over a certain period (e.g., the 7 days prior to the meal time). In some cases, each of the moving averages can be calculated using a different window function. For example, the moving average may be calculated using a Hann window or a Hamming window. In some cases, different levels of dosing may be determined for different meal sizes, and different dosages may be determined for different meals. In some cases, for example, due to the difference in the subject's blood glucose levels at waking and normal lunchtime, or due to the difference in the types of food consumed at breakfast and lunch, even if the sizes are similar, the dosages may be different for different meals (e.g., breakfast vs. lunch). Further, in some cases, different meal boluses may occur due to differences in metabolism among different subjects.

[0107] Insulin therapy can be stored in a therapy log or other types of data structures. Further, insulin therapy can be stored within the memory of an automated blood glucose system, on a companion device, on a subject's or user's computing device (e.g., a laptop or desktop), within a cloud computing environment, or within any other storage system capable of receiving insulin therapy information from an automated blood glucose control system.

[0108] A backup insulin therapy protocol can be generated using a therapy log or tracked insulin data, an automated blood glucose system, or a computing system that can access the therapy log or tracked insulin data. The backup insulin therapy protocol can include a backup injection therapy protocol or a backup pump therapy protocol. The backup injection therapy protocol includes one or more amounts of insulin (or other agents) administered using injection therapy (e.g., a shot provided manually) one or more times, which can help maintain the subject's condition within a normal or desired physiological range or state. The backup pump therapy protocol can include data and / or instructions for a replacement drug pump of the same or a different type for supplying therapy to the subject. The replacement drug pump can be a permanent replacement or a temporary replacement.

[0109] The backup pump therapy protocol can be the same as the backup injection therapy protocol and / or can include the same type of information as the backup injection therapy protocol. Alternatively, or in addition, the backup pump therapy protocol can include values different from the backup injection therapy protocol. For example, the backup pump therapy protocol can include metrics for basal therapy provided periodically in relatively short increments (e.g., every 5 minutes, every 30 minutes, hourly, etc.). Since an insulin pump can automatically administer insulin, it is possible to provide a steady or periodic drip of insulin. However, it is not practical for a subject using injection therapy to manually administer insulin in similar short increments. Instead, the user can administer therapy on a less regular basis (e.g., once every approximately 4 - 5 hours or 6 - 8 hours). Thus, the backup therapy protocols for pumps and injections can be different. Further, the types of insulin used or specified in the backup protocol can be different.

[0110] In some cases, the backup pump therapy protocol can be used to manually improve the pump settings of the replacement blood glucose control system used by the subject. In other cases, the alternative blood glucose control system can automatically configure itself based on the backup therapy protocol. For example, the user may cause the backup therapy protocol to be provided to the alternative blood glucose control system, which may be self-calibrated using the information.

[0111] Regardless of whether a backup protocol is generated or required, collecting and analyzing therapy data for the therapy provided by an automated blood glucose control system can be useful for assisting in the management of the subject's condition. For example, the therapy data may be useful for determining whether the subject is satisfied with the therapy provided by the automated blood glucose control system, or whether the blood glucose control system is configured to best fit the subject's lifestyle or preferences (subjective or otherwise) for therapy. One way to determine whether the blood glucose control system is providing the desired therapy or therapy at the desired rate is to determine the frequency and / or magnitude of the corrections made by the subject or other users who may assist in managing the subject's therapy, to the therapy provided by the automated blood glucose control system.

[0112] The automatic blood glucose control system disclosed in this specification can track user modifications to control parameters over a tracking period. The tracking period can include any of the above periods for tracking therapy to generate a backup protocol. Further, the control parameters can include any type of control parameter that can affect the administration of therapy. For example, the control parameters can be related to, among other control parameters, the amount of therapy, the timing of the therapy delivered, the rate at which the therapy is delivered, or the trigger for when to deliver the therapy. Further, the control parameters can directly affect the delivery of therapy (e.g., specify the time to deliver a drug or the amount of drug to deliver) or can indirectly affect the therapy (e.g., used to modify a control algorithm for administering therapy by adjusting a setpoint range to maintain blood glucose or insulin accumulation rate in a subject).

[0113] User modifications can include any change to a control parameter or setting of the automatic blood glucose control system. For example, the automatic blood glucose control system may track the number or rate at which each instance and / or user decreases or increases a control parameter (e.g., the amount of insulin administered). Further, tracking changes to control parameters can include the frequency with which a user interrupts therapy or temporarily adjusts the target blood glucose range, or tracking other control parameters. Further, tracking changes to control parameters can include tracking when the user makes a change to a control parameter. For example, a user may typically modify control parameters at night but leave daytime parameters unchanged, or vice versa. In some cases, the automatic blood glucose control system can track the subject's weight over time. The weight can be provided by the user and can affect blood glucose control (e.g., the amount of insulin administered may be related to the subject's weight).

[0114] An automatic blood glucose control system can generate a report that tracks user modifications to control parameters. This report may include a measure of the frequency of increases and decreases from the stored control parameter values. Further, the report may include an indicator of the percentage of times the user has modified a control parameter higher or lower than the stored control parameter values of the automatic blood glucose control system over a tracking period. In some cases, the report indicates the number of times insulin infusion has been interrupted during the tracking period, or the rate (e.g., aggressiveness) at which insulin is delivered to the subject.

[0115] Using this report, a clinician or other healthcare provider can determine whether modifications need to be made to the control parameters to more appropriately manage the subject's therapy. For example, if it is determined that the subject is raising the blood glucose target level 4 - 5 times a week in the evening or at night, the clinician may decide that the evening target setting should be adjusted to reduce the number of times the user manually adjusts the therapy provided by the automatic blood glucose control system or the control parameter settings for the therapy. In some cases, the subject may adjust the therapy based on subjective reasons. In some such cases, the treatment report may enable the clinician or healthcare provider to train the subject in controlling the subject's illness. In other cases, the clinician may determine that the subject has a different tolerance to blood glucose than the initially determined or average subject and accordingly adjust one or more control parameters of the automatic blood glucose control system.

[0116] In some implementations, the automatic blood glucose control system can automatically adjust one or more control parameters over time based on the report. For example, if the automatic blood glucose control system determines that the subject has adjusted the daytime target glucose range lower 20 out of 30 days in a month, the automatic blood glucose control system may modify the control parameter to lower the set value range. In some cases, the automatic blood glucose control system can notify a user such as the subject, a parent or guardian, or a healthcare provider of the change.

[0117] Exemplary Backup Therapy Protocol Generation Process FIG. 8 presents a flowchart of an exemplary backup therapy protocol generation process 800 according to a particular embodiment. Process 800 can be executed by any system that can track a drug therapy (e.g., insulin therapy) provided to a subject over time and generate a backup therapy protocol that can be used when the glucose value control system 510 becomes unavailable. For example, process 800 may be executed by one or more elements of the glucose value control system 510. In some cases, at least certain operations of process 800 may be executed by a separate computing system that receives an indicator of the drug therapy provided from the glucose value control system 510 to the subject 512. Although one or more different systems can execute one or more operations of process 800, for simplicity of discussion and without limiting the present disclosure, process 800 will be described with respect to a particular system.

[0118] Process 800 begins at block 802 where the glucose value control system 510 receives a glucose value of the subject 512. Receiving a glucose value can include receiving and / or determining a glucose value signal corresponding to the subject's glucose value. The glucose value signal can be received from a glucose sensor 516 (e.g., a CGM sensor). Alternatively, or in addition, the glucose value can be received from a user who provides the glucose value to the glucose value control system 510 via a user interface such as a user interface generated by the processor 530 that can be output on the touch screen by the touch screen controller 538. The glucose value received from the user can be a glucose value measured using an alternative sensor or measurement mechanism (e.g., a diabetes measurement strip) that can be used in place of the glucose sensor 516.

[0119] In block 804, the glucose value control system 510 generates an insulin dosage control signal based at least in part on the glucose value signal. In some cases, the insulin dosage control signal can be a drug control signal configured to control a drug pump for administering a drug (e.g., insulin, an antagonist regulator, or other drug) to subject 512. The dosage control signal is generated using a control algorithm configured to autonomously determine the dosage of insulin to be administered or infused into the subject for the purpose of controlling the subject's blood glucose based at least in part on the glucose value or glucose value signal determined in block 802. It can be obtained.

[0120] In block 806, the glucose value control system 510 tracks the insulin therapy administered to subject 512 over a tracking period. The tracking period is typically at least one day and can be longer. For example, the tracking period can be one day, two days, one week, one month, several months, one year, any length between the foregoing examples, or more. In some cases, the tracking period can be continuous from the time tracking is initiated. For example, the tracking period can encompass the entire useful life of the glucose value control system 510 by subject 512. If the tracking period is set during a defined period (which can be modified for different iterations of process 800), process 800 can be periodically repeated in response to a request or a trigger event, using a new tracking period of equal or different length. The trigger event can include any event that can potentially render a previously generated backup therapy protocol obsolete. For example, the trigger event can include a change in the type of drug (e.g., a different insulin or antagonist regulator formulation), a change in the physiological characteristics of subject 512 (e.g., weight or a change in sensitivity to different glucose values or drugs), or a change in the average activity level of subject 512.

[0121] The tracking period is typically at least one day and enables the glucose value control system 510 to determine a backup protocol based on data from the entire cycle of use of the glucose value control system 510 (e.g., waking and sleeping hours), although in some cases the tracking period may be less than one day, at least initially. For example, an initial backup therapy protocol may be generated after half a day of activity. This initial backup therapy protocol may be updated as more data becomes available through the full-day (and in some cases the next day) use of the glucose value control system 510.

[0122] In some cases, the tracking period may be defined by or based on a specific number of insulin administration events. For example, the tracking period may be defined by at least 10 instances of generating an insulin dose based on a glucose value signal. As another example, the tracking period may be defined by a minimum number of meal events, correction dose events, and / or basal dose events. For example, the tracking period may require 3 meals, or 3 meals of each meal type, 2 correction doses, and / or 100 basal doses. It should be understood that the foregoing number of administrations is merely an example and the tracking period may include more or fewer administrations. Further, the tracking period can be defined or specified as a combination of time and the occurrence of a specific number of insulin administrations.

[0123] In some cases, the tracking period may vary. For example, if the glucose value control system 510 determines that the insulin dose therapy is inconsistent or unstable over the tracking period (e.g., due to inconsistent exercise or eating habits), the tracking period may be extended.

[0124] Tracking insulin therapy can include storing an insulin dosage control signal generated at least in part based on the glucose value signal at block 804. Alternatively, or in addition, tracking insulin therapy can include storing an indication of the amount of insulin (or other agent) corresponding to the dosage control signal for insulin (or other agent). The insulin dosage control signal and / or the indication of insulin amount can correspond to the amount of insulin delivered to subject 512 as a basal insulin dosage, a correction bolus of insulin, and / or a meal bolus of insulin.

[0125] Storing the insulin dosage control signal and / or the indication of insulin amount can include storing the insulin dosage control signal and / or the indication of insulin amount in a therapy log or any other type of It may include storing in the memory 540 of the glucose value control system 510 in the data structure. Alternatively, or in addition, the glucose value control system 510 can store the insulin dosage control signal and / or an indicator of the amount of insulin in a remote data store. This remote data store can be a local computing system (e.g., the subject 512 or the user's laptop, desktop, smartphone, or other computing device) with which the glucose value control system 510 can communicate. The glucose control system 510 can provide the insulin dosage control signal data or an indicator of the amount of insulin to the local computing system via Bluetooth® or other short-range wireless communication services, or via a local network. Alternatively, or in addition, the remote data store can be a remote computing system with which the glucose value control system 510 can communicate via a wide area network such as a wireless area network, a cellular network using IoT-based communication technologies, cellular communication technologies, or any other communication network. In some cases, the wide area network can include the Internet. The glucose value control system 510 can include a wireless radio that enables it to communicate with the local or remote computing system. Further, the remote computing system can be a computing system of a data center or a cloud computing environment.

[0126] Whether it is a local computing system or a remote computing system, the glucose value control system 510 can establish a communication channel with the computing system. This communication channel can be an encrypted channel. Further, the communication channel can be a direct end-to-end connection between the glucose value control system 510 and the computing system. Once the communication channel is established, the glucose value control system 510 can transmit the insulin dosage control signal data or an indicator of the amount of insulin to the computing system.

[0127] Generally, the operations associated with blocks 802-806 can be repeated multiple times throughout the tracking period. For example, in some cases, an insulin dosage control system associated with basal insulin may be generated up to 288 times per day. Thus, tracking insulin therapy can include storing corresponding indicators of insulin control signals and / or amounts of insulin for a plurality of autonomously determined insulin dosages injected into subject 512 over the entire tracking period.

[0128] Generally, counterregulatory therapy includes administering a counterregulatory agent (e.g., glucagon) when there is a risk or occurrence of hypoglycemia. Typically, counterregulatory agents are not supplied periodically or daily. However, it can be useful to understand the amount and frequency with which a counterregulatory agent is administered to subject 512. For example, it can help a healthcare provider or user guide or adjust the care of subject 512. Further, tracking the use of counterregulatory agents can help determine the minimum amount of counterregulatory agent to which subject 512 should have access, either in a bihormonal pump or injection therapy. In some cases, block 806 can include tracking counterregulatory agents administered during the tracking period. Tracking counterregulatory therapy can include storing an indicator of an autonomously determined dosage of a counterregulatory agent delivered to subject 512 in response to the glucose value signal obtained at block 802.

[0129] At block 808, glucose value control system 510 generates a backup therapy protocol based at least in part on the tracked insulin therapy. The backup therapy protocol can be determined based on the average amount or rate of insulin administered to the user over various portions of the tracking period (e.g., breakfast, lunch, and dinner, or wake and sleep times, etc.) during the tracking period, or in response to a particular event (e.g., at mealtime, when the blood glucose value exceeds a threshold level, etc.). The backup therapy protocol is a backup injection It may include an injection protocol and / or a backup pump therapy protocol. The backup injection protocol may provide the user (e.g., subject 512, parent or guardian, or other caregiver of subject 512) with an amount of insulin that can be administered to subject 512 via injection. Further, the backup injection therapy may indicate the time at which insulin can be administered. For example, the backup injection therapy may indicate the amount of insulin to be administered at a specific meal time. Further, the backup injection therapy may indicate the effect that a unit of insulin can have on subject 512 so that the user can calculate how much insulin should be administered to subject 512 when the blood glucose reading indicates that the glucose value of subject 512 is too high (e.g., above the desired set value range).

[0130] Similar to the backup injection therapy protocol, the backup pump therapy protocol may provide the user (e.g., subject 512, parent or guardian, or other caregiver of subject 512) with an amount of insulin that can be administered to subject 512 via a drug pump. Using the backup pump therapy protocol, the user can configure the drug pump to administer a specified amount of insulin. The backup pump therapy protocol can be used to configure the drug pump when access to the CGM sensor is not available (e.g., when subject 512 does not own a CGM sensor or when there is a malfunction in the drug pump or CGM sensor). Further, the backup pump therapy protocol may be useful for providing an initial configuration to an alternative glucose value control system.

[0131] In some cases, the backup injection therapy protocol and the backup pump therapy protocol may be the same. However, in many cases, at least the recommended basal therapy settings may be different. It is generally not practical for insulin to be administered to subject 512 more than several times a day via injection therapy. Thus, the backup injection therapy protocol can identify long-acting insulin units or dosages that can be administered limitedly (e.g., once or twice a day). However, a drug pump can administer insulin more easily than at limited intervals (e.g., hourly, every 30 minutes, every 5 minutes, etc.). Thus, the backup pump therapy protocol can identify the basal rate of insulin that can be administered once per unit time (e.g., once per hour or once per 15 minutes or once per 5 minutes), or continuously at a specific rate (e.g., 0.5 or 0.6 units) per unit time (e.g., per hour). Further, the backup pump therapy protocol can identify different rates for various parts of the day (e.g., for the subject, a rate once every half day, a rate once every quarter day, or a rate during normal waking hours and a rate during normal sleeping hours, etc.).

[0132] In some cases, an initial backup therapy protocol can be generated at block 808. The initial backup therapy protocol can be updated over time as additional insulin therapy data is acquired.

[0133] Generating a backup therapy protocol can include determining the number of long-acting insulin units based at least in part on the average total basal insulin provided to subject 512 per day over a tracking period. The average total basal insulin provided per day can be included in the backup injection therapy protocol as a single dose of long-acting insulin configured to help maintain the basal insulin level of subject 512 throughout the day. In some cases, the average total basal insulin provided per day can be included in the backup injection therapy protocol as multiple doses of insulin (e.g., two or three doses per day).

[0134] Alternatively, or in addition, the basal insulin can be the rate of a dose supplied to a pump to provide a rate of basal insulin throughout the day, in a backup pump therapy pro It may be included in a backup therapy protocol such as Tokor. Further, in some cases, each day of the tracking period may be divided into a plurality of sub-periods. For example, each day of the tracking period may be divided into two, three, four, or more periods, or periods of equal or different lengths. In some such cases, generating a backup therapy protocol may include determining a per-hour base rate for each of the plurality of sub-periods. This per-hour base rate may be determined by averaging the corresponding sub-periods for each day of the tracking period. For example, if each day of the tracking period is divided into two sub-periods (e.g., from noon to midnight and from midnight to noon), the base rate supplied during the first sub-period of the entire tracking period is averaged, and the base rate supplied during the second sub-period of the entire tracking period is averaged to determine two base rates for inclusion in the backup therapy protocol. The base rate may be determined based on a time rate or other period. Alternatively, the base rate may be determined based on the amount of time in which a particular amount (e.g., 1 unit) of insulin is recommended to be administered to subject 512 as part of the backup therapy protocol. For example, if glucose value control system 510 determines that subject 512 is receiving 1 unit of insulin every 1.125 hours, the backup therapy protocol may indicate that the base rate is 1 unit every 1.125 hours. Alternatively, or in addition, the backup therapy protocol may indicate a base rate of 0.89 units per hour.

[0135] Furthermore, generating a backup therapy protocol may include determining an average correction bolus provided to a subject per day over a tracking period. The average correction bolus can be determined by adding the total amount of correction doses administered to each data and dividing by the number of days in the tracking period. The average correction bolus may be included in the backup therapy protocol as guidance to the user. However, generally, the correction bolus is supplied in response to a determination that the subject's blood glucose level has spiked or exceeded a threshold, and is not necessarily supplied as the daily insulin dose. Thus, the average correction bolus may be included as part of the backup therapy protocol to facilitate the user's understanding of the amount of insulin that may be needed on an average day, which may be useful for the user (e.g., the subject) to determine how much insulin is accessible for use, for example, in injection therapy. In some cases, one or more days or periods of the tracking period may be omitted when determining the average correction bolus. This is because, for example, one or more days or periods may be determined to be outliers. The outliers may be omitted to more accurately understand the average insulin requirement or consumption.

[0136] In some implementations, the glucose value control system 510 can determine the average change in blood glucose at least partially attributable to the units of insulin provided to the subject as a correction bolus during a tracking period. In some cases, the glucose value control system 510 can correlate each correction bolus applied during the tracking period with the change in the blood glucose value of the subject 512.

[0137] To generate a backup therapy protocol, for each meal time out of multiple meal times per day, it may include determining the average meal-time bolus of insulin provided to the subject over a tracking period. In some cases, the average meal-time bolus for a specific meal (such as breakfast, lunch, dinner, etc.) is determined, and other meal intake periods (such as snacks or tea time) may be omitted or ignored. Further, the average meal-time bolus may be associated with a specific meal size specified by the user. For example, the glucose value control system 510 may determine the average meal-time bolus for small and large meals, or for small, medium, and large meals. The average meal-time bolus is determined for each meal time and the specified meal size by averaging the amount of insulin that the glucose value control system 510 determines should be administered to the subject 512.

[0138] In some cases, the backup therapy protocol may include data related to the administration of counterregulatory agents. For example, the backup therapy protocol may include the total counterregulatory agent provided to the subject over a tracking period and / or an index of the daily counterregulatory agent.

[0139] In block 810, the glucose value control system 510 outputs a backup therapy protocol. Outputting the backup therapy protocol may include displaying the backup therapy protocol on a display that enables the user to implement the backup therapy protocol. Alternatively, or in addition, outputting the backup therapy protocol may include sending the backup therapy protocol to the user's computing device for display and / or storage. In some cases, the backup therapy protocol may be stored in the glucose value control system 510 and accessed in response to a user interaction with the user interface of the glucose value control system 510.

[0140] In some cases, process 800 can be combined, at least in part, with process 900 described below. Thus, in some cases, the backup therapy protocol may further include a record of user modifications to one or more control parameters used by the control algorithm of glucose value control system 510 to autonomously determine the dosage of insulin injected or administered to a subject. This record of user modifications may include identification information of instances of user modifications to the control parameters, and / or the rate of the number of times the user has modified the control parameters during each day and / or over the entire tracking period.

[0141] Figure 9 presents a flowchart of an exemplary control parameter modification tracking process 900 according to a particular embodiment. Process 900 can be executed by any system that can track the occurrence of a user modifying the control parameters used by glucose value control system 510 to assist in the control of drug delivery to subject 512, more specifically, the user interaction with glucose value control system 510. For example, process 900 may be executed by one or more elements of glucose value control system 510. In some cases, at least certain operations of process 900 are performed by a separate computing system that receives an indication of a change to the control parameter settings of glucose value control system 510 from glucose value control system 510 and / or from the user interaction with the user interface in a separate computing system before transmitting the modification to glucose value control system 510. Although one or more different systems can execute one or more operations of process 900, for simplicity of discussion and without limiting the present disclosure, process 900 is described with respect to a particular system.

[0142] Process 900 begins at block 902 where glucose value control system 510 receives the glucose value of subject 512. Block 902 may include one or more of the embodiments described above with respect to block 802.

[0143] In block 904, the glucose value control system 510 generates an insulin dosage control signal based at least in part on the glucose value signal and control parameters. The insulin dosage control signal can be generated based on a control algorithm that enables the glucose value control system 510 to autonomously determine the dosage of insulin to be injected or administered to the subject to control the subject's blood glucose value. The control algorithm can determine the dosage of insulin based at least in part on the control parameters. The control parameters can affect the operation or output of the control algorithm or the operation of the glucose value control system 510 and can include any parameter that can be modified by a user (e.g., the subject 512 or a user who is at least partially involved in the care of the subject 512 (e.g., a parent or caregiver)). In some cases, the control parameter can be or correspond to a target setpoint for the glucose value of the subject 512. In other cases, the control parameter can correspond to whether the glucose value control system 510 generates an insulin dosage control signal for at least a certain period of time. For example, the control parameter may be related to whether at least a part of the operation of the glucose value control system 510 is interrupted or active. Block 904 can include one or more of the embodiments described above with respect to block 804.

[0144] In block 906, the glucose value control system 510 tracks one or more user modifications to the control parameters over a tracking period. The tracking period can be one day, less than one day, or longer than one day (e.g., two days, three days, one week, one month, etc.). Further, the tracking period can include one or more periods as described above with respect to process 800. The user can be the subject 512 or any other user who is permitted to modify the control parameters of the glucose value control system 510 (e.g., a parent or caregiver, or a healthcare provider).

[0145] The user can modify the control parameters using a user interface that can be generated and / or output by the glucose value control system 510. Alternatively, or in addition, the user interface can be generated and / or output by a computing system that can communicate with and / or modify the control parameters in the glucose value control system 510. For example, the computing system can be a smartphone, smartwatch, laptop, or desktop computer, or any other type of computing device that can be used to configure the glucose value control system 510. The user interface can be output to a touch screen that can have an interface for the user to modify the control parameters. The user can interact with a control parameter selection element or other user interface elements to select and / or modify the control parameters. In some cases, the user can provide any value supported by the glucose value control system 510 to the control parameters. In other cases, the user may be limited to selecting a specific value of the control parameter, which may be less than the supported capabilities of the glucose value control system 510 or less than what other users are permitted to select. For example, a clinician may be given a wider range of modification than a parent to modify the control parameters.

[0146] Tracking one or more user modifications may include storing the one or more user modifications in a therapy log, database, or other data structure. Further, tracking one or more user modifications may include tracking or storing whether each of the user modifications includes an increase or decrease in a control parameter. Determining whether the control parameter has increased or decreased may be determined based on whether the value of the control parameter has increased or decreased relative to a reference value. The reference value may include the current value of the control parameter, a default value, a clinical value supplied to the glucose value control system 510, and / or a value determined by the glucose value control system 510. Further, tracking one or more user modifications may include storing the time when the control parameter is modified and / or one or more conditions. For example, the glucose value control system 510 may store the time, the activity level of the subject 512 determined from one or more physiological sensors and / or specified by the user, the consumed meal or the unconsumed meal, etc. Further, tracking insulin therapy may include storing an indicator of the autonomously determined insulin dosage delivered or administered to the subject 512.

[0147] In some cases, the tracking period can be divided into a plurality of sub-periods. The sub-periods may correspond to various portions of a day within the tracking period. For example, each day within the tracking period may be divided into two equal halves corresponding approximately to day and night, or may be divided into three or four different periods corresponding to a specific number of hours of that day. The sub-periods may or may not be of equal length. Tracking one or more user modifications may include tracking the occurrence of modifications to the control parameter within the sub-periods of the tracking period. Further, the occurrence of modifications within a sub-period of a day within the tracking period can be combined with the occurrence of modifications within the corresponding sub-period of another day within the tracking period. In other words, each occurrence of a modification of the control parameter in a sub-period defined from 9:00 to 21:00 can be aggregated over the entire number of days of the tracking period.

[0148] In some cases, different reference values may be determined for the control parameters for each sub-period. In some such cases, tracking one or more user modifications may include tracking modifications to the control parameter values with respect to the reference values of the sub-periods.

[0149] In block 908, the glucose value control system 510 generates a report of user modifications to the control parameters. Alternatively, or in addition, the report may be generated by another computing system, such as a cloud computing system or a healthcare provider's computing system, based on data received from the glucose value control system 510 (e.g., the occurrence of user modifications to the control parameter values).

[0150] The report may include a measure of the frequency of increases and decreases from the stored control parameter values. Further, the report may indicate the number of times the operation of one or more features of the glucose value control system 510 has been interrupted or aborted, or the percentage of the tracking period during which the operation of one or more features of the glucose value control system 510 has been interrupted or aborted. Further, the report may indicate, overall and / or on average, the magnitude of the modification to each control parameter for each occurrence. In some cases, the report may indicate the percentage of user modifications that are higher or lower than the reference value during the tracking period. Further, if the tracking period, or each day within the tracking period, is divided into sub-periods, the report may include a measure of the frequency of increases and decreases from the reference values of the control parameters for each sub-period within the tracking period. In some cases, the report may include identification information of user activities that occurred when the user modified the value of the control parameter or within a threshold time period. For example, the report may identify whether the user was exercising (e.g., swimming, running, dancing, etc.) when the user modified the control parameter value.

[0151] In some embodiments, block 908 may include storing the generated report in the glucose value control system 510 (e.g., within memory 540) and / or the storage of another computing device. In some cases, the computing device may be the computing device of the subject 512 (or a parent or guardian). Additionally, the computing device may be the computing device of a healthcare provider. In some cases, the computing device may be the computing device of a cloud computing service.

[0152] The report can be obtained from the glucose value control system 510 by a wired connection (e.g., a USB cable). Alternatively, or in addition, the report may be obtained via a wireless connection to the glucose value control system 510. For example, the glucose value control system 510 may establish an encrypted connection to the computing system of a healthcare provider, and the computing system may receive the report from the glucose value control system 510. Alternatively, or in addition, the glucose value control system 510 may establish an encrypted communication channel with a cloud computing provider from which the glucose value control system 510 can receive reports. This report can be accessed by authorized users.

[0153] ​Advantageously, in certain embodiments, a healthcare provider can use the report to help manage the care of subject 512. For example, if the healthcare provider determines that the user has modified a control parameter more than a threshold number of times or during a particular period, the healthcare provider can use this information to modify the care provided to subject 512 and / or educate subject 512 about optimal care. For example, it may be necessary to modify the rate of therapy, or the amount of insulin may be too low for the subject to be comfortable. For example, in some cases, subject 512 may have a tolerance for blood glucose levels that is different from that of an average user, and the user may be allowed to modify the setpoint range. Understanding this information can help the healthcare provider manage the care of subject 512 (e.g., adjust the initial setpoint range or modify the type of insulin prescribed).

[0154] Furthermore, as shown above, process 900 can be combined with process 800. In other words, a report can be generated that includes both a backup therapy protocol and a record of the number of times the user can modify one or more control parameters of glucose value control system 510. In other cases, processes 800 and 900 can be triggered and / or executed independently.

[0155] Exemplary Backup Therapy Report Figures 10-12 show one non-limiting example of a backup therapy report or series of reports that can be generated using one or more embodiments disclosed herein. In other words, the reports of Figures 10-12 may be part of a single report generated by the glucose value control system 510, or may be separate reports generated simultaneously or based on different data and / or over different tracking periods. The reports can be generated by the automatic blood glucose control system 510 or by another computing system that can receive therapy data from the automatic blood glucose control system. Further, Figures 10-12 represent one non-limiting example of a report or series of reports that can be generated. Other reports containing more or less data are possible. For example, the backup injection therapy protocol and backup pump therapy protocol illustrated in Figure 10 may be separated into two separate reports that can be generated and / or accessed separately.

[0156] Figure 10 shows an exemplary backup therapy protocol report 1000 according to a particular embodiment. The amount of insulin recommended under various relationships and / or conditions can be displayed in units. In some cases, the report 1000 can identify the amount of insulin contained in one unit and / or the type of insulin. Further, in some cases, the report 1000 can be an interactive report that allows the user to modify the type of insulin or the size of the insulin unit. In some such cases, the table 1002 can update the recommended number of insulin units to administer under specific times or conditions based on the type of insulin and / or the size of the selected insulin unit.

[0157] Report 1000 can identify the length of the tracking period 1006 used to determine the backup therapy protocol. Further, report 1000 can identify the time or date range 1008 during which the tracking period 1006 occurred. Advantageously, knowing the tracking period 1006 can help determine the reliability of the recommendations included in the backup therapy protocol. The longer the tracking period, the more likely the recommendations are to be accurate. For example, since the tracking period may include more days that are outliers from the subject's typical state or activity level, the shorter the tracking period, the more likely the accuracy of the recommendations is to be low. For example, a one-day tracking period that occurs on a day when the subject consumes more than normal meals or exercises significantly more than normal may result in backup therapy recommendations that do not match the subject's typical lifestyle. Further, knowing when the tracking period occurred can help determine how up-to-date the recommendations are and whether they are a reliable indicator of the amount of insulin the subject should receive. For example, if the date range 1008 of the tracking period 1006 is from a year ago and the subject has significantly gained or lost weight over the year, the backup therapy protocol may no longer be a reliable indicator of the recommended injection therapy. In such a case, the user can adjust this recommendation and / or trigger a new occurrence of process 800. For example, a one-day tracking period that occurs on a day when the subject consumes more than normal meals or exercises significantly more than normal may result in backup therapy recommendations that do not match the subject's typical lifestyle. Further, knowing when the tracking period occurred can help determine how up-to-date the recommendations are and whether they are a reliable indicator of the amount of insulin the subject should receive. For example, if the date range 1008 of the tracking period 1006 is from a year ago and the subject has significantly gained or lost weight over the year, the backup therapy protocol may no longer be a reliable indicator of the recommended injection therapy. In such a case, the user can adjust this recommendation and / or trigger a new occurrence of process 800.

[0158] Table 1002 shows an exemplary backup injection therapy protocol, which can indicate various insulin dosages that can be administered to subject 512 at various times or under various conditions using injection therapy. Table 1002 identifies the amount of insulin that subject 512 can inject when consuming a normal-sized meal for breakfast, lunch, or dinner. A normal-sized meal can refer to the size of a meal that a particular subject 512 normally consumes or is recommended by a healthcare provider to consume. The units of insulin specified can refer to the amount of insulin that the automated blood glucose control system 510 on average provides to subject 512 when the user consumes the identified normal-sized meal. In some cases, Table 1002 can further include recommended insulin dosages for meals of different sizes. For example, each breakfast can indicate three different values (e.g., 5 units, 6 units, and 8 units) corresponding to a lighter-than-normal breakfast or a small breakfast, a normal-sized breakfast, and a heavier-than-normal breakfast or a large breakfast.

[0159] It should be understood that the amount of insulin delivered can vary over time and / or based on the patient's condition at a particular time. Thus, as shown at the top of report 1000, the recommendations for the backup therapy protocol are proposed for temporary use for a specific time (e.g., up to 72 hours in the illustrated example). The amount of time for which the recommendations are valid can vary based on subject 512, the amount of historical data collected (e.g., the size of the tracking period), the daily variability of the subject's blood glucose levels, or any number of other factors that can affect the amount of time that the backup therapy protocol can be safely followed.

[0160] As shown in Table 1002, the backup injection therapy protocol can further identify the amount of long-acting insulin that is recommended for subject 512 to administer daily (or at a particular time of day). This long-acting insulin can be used in place of the basal insulin that the glucose value control system 510 can periodically provide.

[0161] Furthermore, Table 1002 identifies the decrease in glucose value caused by 1 unit of insulin. For example, as shown in Table 1002, the automatic blood glucose control system 510 determines that 1 unit of insulin (e.g., 1 / 100 milliliter of insulin) may lower the blood glucose value of the subject 512 by 9 mg / dL. Therefore, a user implementing injection therapy measures the blood glucose value of the subject 512, determines the difference between the measured blood glucose value and the desired set value or threshold glucose value, and divides that difference by 9 to determine the number of insulin units to be injected in response to a determination that a corrective dose is warranted (e.g., the blood glucose is outside the desired set value range).

[0162] Table 1004 of Report 1000 provides an example of a backup pump therapy protocol. As shown, the backup pump therapy protocol may have the same treatment information as the backup injection therapy protocol for meal times and correction factors. However, since the pump can provide periodic basal therapy, the long-acting insulin units of injection therapy can be replaced with a basal rate that indicates the rate at which the backup or replacement pump administers insulin to the subject. As shown, the basal rate can vary over time. In the example shown, the basal rate is provided over four different periods that make up 24 hours of a day However, the basal rate may be divided into fewer (e.g., two 12-hour blocks) or more (e.g., every 4 hours) numbers of periods, and each period may potentially have a different basal rate as determined based on historical therapy data provided by the automatic blood glucose control system.

[0163] In some cases, report 1000 may include additional data that can be tracked over a tracking period. This additional data may include any data that can facilitate the care of subject 512 and / or the maintenance of the automatic glucose value control system 510. For example, non-limiting examples of some of the additional data that can be tracked using process 800 or 900 and included in the report are shown in chart 1010 of report 1000. For example, as shown in chart 1010, the report may include the average blood glucose value of subject 512 over the tracking period and / or the corresponding estimated A1C percentage. Further, report 1000 may indicate the amount or percentage of time that the subject's blood glucose value is within the desired set value range and / or exceeds the desired set value range. Similarly, report 1000 may indicate the amount or percentage of time that the subject's blood glucose value is below the threshold blood glucose value.

[0164] Further, report 1000 may indicate the average number of meal notifications per day. As shown in chart 1010, subject 512 for whom an exemplary report 1000 was generated averaged 4.2 meal notifications, indicating that on average, the subject consumed more than 3 meals per day. In some cases, the report may further indicate the types of meals reported (e.g., 2 breakfasts, 1 lunch, and 1 dinner). The second breakfast may be a small breakfast for the subject and a large snack of approximately equal size. Thus, the subject may make an additional breakfast meal notification. In some cases, the automatic glucose value control system 510 may support separate snacks or other meal notification options.

[0165] Report 1000 may further include the total amount of insulin administered to the subject per day and / or the total amount of counterregulatory agent (e.g., glucagon) administered to the subject per day. Additionally, report 1000 may indicate the amount of the percentage of time that the automatic glucose value control system 510 can be connected or communicate with the CGM sensor during the tracking period, which may correspond to the amount of time that the automatic glucose value control system 510 functions in the online mode during the tracking period.

[0166] Figure 11 shows an exemplary control parameter modification report 1100 according to a particular embodiment. As described above, report 1100 may be a separate report generated, for example, using process 900. Alternatively, report 1100 may be included as a second report within report 1000.

[0167] Report 1100 may generally provide an indication of the number or rate at which a user has modified one or more control parameters of the automatic glucose value control system 510 during a tracking period. Further, similar to report 1000, report 1100 may identify the time or date range 1008 during which tracking period 1006 occurred. In some cases, the user may interact with report 1100 to determine the rate of the number of times the user has modified one or more control parameters during a subset of the tracking period. Similarly, the user may filter or narrow the date range to display other data described herein for a subset of the tracking period (e.g., a selected data range).

[0168] Report 1100 may include a graph 1102 showing the target blood glucose values of the subject with respect to the desired target setting value range over a day during the tracking period. This day may be the average of the values obtained for each day during the tracking period or may indicate a specific selected day.

[0169] Further, report 1100 may include a table 1104 showing the rate of the number of times the user has modified the blood glucose target during a specific period. Table 1102 of non-limiting example report 1100 shows two periods, namely daytime and nighttime. However, it should be understood that table 1104 may show fewer or more periods. Further, the periods may indicate periods of specific times (e.g., 9:00 - 21:00 and 21:00 - 9:00).

[0170] As shown, Table 1104 may indicate the percentage of times the user increased or decreased the glucose target value. Further, the report may show the percentage of times the user did not modify the glucose target value or kept it as usual. This target value shown in Table 1104 may refer to a single target value (e.g., 110 mg / dL, 125 mg / dL, 130 mg / dL, etc.) or a target value range (e.g., 70 - 180 mg / dL).

[0171] Further, Report 1100 may show the number of times the user set a temporary glucose target (Temporary Target Count 1106) or the selected data range during the tracking period. The report may also show the number of times the user interrupted therapy (e.g., Count 1108 of interrupted insulin therapy) and / or the selected date range during the tracking period.

[0172] The blood glucose of the subject may be affected by the subject's weight. Accordingly, the subject can provide an update of the weight to the automatic blood glucose control system. In some such cases, the report may show the weight change and the time when the weight parameter was modified (e.g., Weight Data 1110). In some cases, Report 1100 may be filtered to display the data before and after the weight change separately. The weight data can help a healthcare provider determine, for example, whether the change in weight may at least partially underlie the user's modification to the target blood glucose value. Generally, the automatic glucose value control system 510 (e.g., using blood glucose measurements) automatically considers the possible impact of weight changes on blood glucose control. However, the subject 512 may have different feelings about this. The ability to collect modification data regarding the user's modification of the automatic glucose value control system 510 and correlate the data with weight changes can assist the healthcare provider in better treating the subject 512, for example, by adjusting the settings of the automatic glucose value control system 510, changing the insulin prescription, educating the subject 512, or any other action that can improve the care of the subject 512.

[0173] In some cases, in the report, changes to blood glucose target settings below the threshold may be omitted. In other words, small changes that may be statistical noise can be ignored. Further, in some cases, the report may indicate when control parameters (e.g., for specific meals such as bedtime, dinner, etc.) are modified. In some cases, the report may also show the period of change to the glucose target value or other control parameters.

[0174] FIG. 12 shows an exemplary meal selection report 1200 that may be included as part of an implementation of a portion of the control parameter modification report 1100 of FIG. 11, according to a particular embodiment. Report 1200 may include a table 1202 that identifies the average number of times per day that a user (e.g., subject 512) indicates each meal type. Typically, a user indicates a meal 0 or 1 time per day. However, in some cases, a user may indicate a particular meal time more than once, for example, considering a large number of snacks where the particular meal and size may be similar. Small snacks are often processed by the control algorithm of the automatic glucose value control system 510 (e.g., by the correction insulin controller 626) without a meal indication.

[0175] Further, table 1202 may identify the number of times during a tracking period that a meal of a particular size is indicated by the user, or a selected period within the tracking period. For example, table 102 may show the number of times a normal-sized meal is indicated, the number of times a meal smaller than normal size is indicated, or the number of times a meal larger than normal size is indicated. The number of times, or a selected period within the tracking period. For example, table 102 may show the number of times a normal-sized meal is indicated, the number of times a meal smaller than normal size is indicated, or the number of times a meal larger than normal size is indicated.

[0176] Improvements in Automatic Blood Glucose Control An automatic blood glucose control system (e.g., glucose value control system 510) automatically provides insulin and / or an antagonist regulator (e.g., glucagon) to a subject 512, which can help control the blood glucose value of the subject 512. Generally, a control algorithm can be implemented by the automatic blood glucose control system 510 to determine the timing of delivering insulin and the amount of insulin to provide to the subject. Further, the control algorithm can control both the continuous or periodic delivery of insulin (e.g., basal dose) and the correction bolus that can be provided to adjust the subject's blood glucose value within a desired range. The control algorithm can use the read value of the blood glucose level obtained from a sensor such as a continuous glucose monitoring (CGM) sensor that acquires automatic blood glucose measurement values from the subject. Further, in some cases, the control algorithm can deliver an insulin bolus in response to the meal consumed by the subject 512 or an indicator of the meal being consumed.

[0177] Insulin can be administered subcutaneously into the blood of the subject 512. There is often a delay between when insulin is provided and when the amount of insulin in the subject's plasma reaches its maximum concentration. This time can vary based on the type of insulin and / or the physiological state of a particular subject. For example, in the case of rapid-acting insulin, it may take about 65 minutes for the insulin bolus to reach its maximum concentration in the plasma of one subject, but it may take 60, 64, or 70 minutes in another subject. In the case of other types of insulin, it may take 3 - 5 hours to reach the maximum concentration in the subject's plasma. Thus, the blood glucose control system can implement a prediction algorithm that implements a bi-exponential pharmacokinetic (PK) model to model the accumulation of the insulin dosage in the subject's plasma over time. The blood glucose control system can modify its prediction based on the type of insulin, one or more blood glucose measurement values, and / or the physiological characteristics of the subject. These physiological characteristics can include characteristics shared among most of the population (e.g., weight, gender, age, etc.), as well as characteristics that may be unique or specific to the subject or shared among a small number of people (e.g., characteristics related to genetics).

[0178] Due to differences in physiological states among different subjects, there may be differences in the optimal blood glucose range for each subject or for some of the multiple subjects. Furthermore, differences in physiological states may also affect the absorption of insulin into the plasma. In other words, different physiological states of different subjects may result in insulin absorption that requires different times for different subjects. Therefore, the maximum concentration of glucose in the plasma can be 65 minutes after a bolus administration of rapid-acting insulin in one subject, but can be 60 minutes or 70 minutes in another subject.

[0179] As described above, a blood glucose system such as an automated blood glucose system can control the delivery or administration of insulin or an antiregulatory agent based on a biexponential PK model and one or more blood glucose measurements of a subject. The biexponential PK model can model the absorption of subcutaneously administered insulin into the blood and / or the rate of decrease of glucose in the blood. The biexponential PK model over time can be represented by the following equation.

Equation

Equation

[0180] Often, a blood glucose control system is configured to maintain a subject's blood glucose within a particular range. As the blood glucose rises or falls, the blood glucose control system can administer a particular amount of insulin or an anti-regulatory agent to the subject to return the subject's blood glucose value to within the desired range or to bring it closer to a desired setpoint. As noted above, it may take some time for the drug to be absorbed into the subject's bloodstream. Accordingly, a bi-exponential PK model can be used to determine the amount of insulin or anti-regulatory agent to administer. The bi-exponential PK model can predict the subject's blood glucose value over time when the insulin or anti-regulatory agent is administered. The parameter values of the bi-exponential PK model can be set by a healthcare provider based on default values obtained through clinical trials and / or based on an individualized treatment plan for the subject that can be determined based on the subject's clinical trials and / or based on an evaluation by the subject's healthcare provider based on the subject's tests.

[0181] However, as noted above, subjects can vary from one another. Accordingly, clinical data can determine optimal or recommended values for an average subject through one or more tests, but the determined data may not be optimal for a particular subject. Further, an individualized treatment plan is typically based on measurements at particular points in time. These measurements at particular points in time can provide good guidelines for therapy, but the optimal parameter values for a subject can vary at different times of the day due to various activities, due to changes in the subject over a lifetime, or due to any number of other reasons.

[0182] The glucose value control system 510 of the present disclosure can implement a method or process for autonomously and / or automatically modifying one or more control parameters of a control algorithm to modify the therapy provided to a subject using the glucose value control system 510. The method can be executed by a hardware processor 530 and / or a controller 518 that controls the administration of the therapy. The system can provide a therapy (e.g., insulin) to the subject in response to the determination of the subject's blood glucose value. The blood glucose value can be determined based at least in part on a glucose value signal obtained from a glucose value sensor operably connected to the subject. The determination of the therapy (e.g., the amount of insulin or an antiregulatory agent) can be based at least in part on the blood glucose value and / or a biexponential model. Further, the determination of the therapy can be based at least in part on the value or setting of one or more control parameters of the blood glucose control system. The one or more control parameters can be, or can correspond to, one or more parameters of a biexponential PK model or any other model or control algorithm used to control the administration of therapy to the subject.

[0183] System 510 can provide therapy based on the value or setting of one or more control parameters. The value or setting of the one or more control parameters can be based on the initial configuration of the blood glucose control system 510 by a healthcare provider, the subject, or other user. Further, the initial configuration can be based on clinical data or subject-specific data obtained. In some cases, the control parameter can be the time constant used by the control algorithm of the blood glucose control system. This time constant can be used in the calculation of insulin accumulation in the subject by the control algorithm. Further, the control parameter can be used to control the insulin administration response of the control algorithm to the subject's blood glucose excursions as indicated by the glucose value signal obtained from the glucose value sensor. In some cases, the control parameter can be Tmax or related to Tmax. For example, the control parameter can be an estimated value of Tmax or a portion of Tmax (e.g., 0.5). As described above, Tmax can be the peak time of insulin absorption or the time until the insulin concentration from the insulin dose reaches the maximum concentration in the subject's blood and can be the time until the insulin concentration from the insulin dose reaches the maximum concentration in the subject's blood.

[0184] Further, the control parameter can be associated with a setpoint or target blood glucose value, or a blood glucose range. For example, the control parameter can be related to the point in time when the estimated amount of "insulin on board" (e.g., the amount of insulin in the subject determined by a model of insulin accumulation and / or utilization in the subject) falls below a threshold. As another example, the control parameter can be the clearance time of the insulin bolus (e.g., an estimated value of the amount of time the administered insulin bolus is utilized by the subject). In some cases, the control parameter can be related to T corresponding to the time when the insulin concentration in the plasma reaches half of the maximum concentration in the plasma. 1 / 2 In some cases, the control parameter can be related to Tmax or T 1 / 2 and can be a parameter used to calculate Tmax or T.

[0185] The system can determine the effect of the supplied therapy. This effect can be determined by analyzing the blood glucose control of the subject indicated by the glucose value signal received from the glucose value signal. In some cases, the system can measure or determine the effect of the supplied therapy over time. Further, in some cases, the system may continue to supply therapy to the subject over multiple therapy delivery times or instances, and may average or otherwise aggregate the measured or determined effects of the therapy over the multiple therapy delivery times or instances.

[0186] Based at least in part on the supplied therapy and the determined effect of the therapy (e.g., the change in blood glucose value due to the therapy), the system 510 can autonomously determine a modification to one or more control parameters. For example, the system may modify the Tmax value used by the blood glucose control system to determine an insulin therapy for providing to the subject. The direction of modification of the control parameter value (e.g., increase or decrease) may depend on the determined effect of the initial or previous control parameter value of the control parameter. Further, the direction of modification of the control parameter value may depend on the difference between the effect of the blood glucose therapy and the expected effect of the blood glucose therapy.

[0187] Using the modified control parameter, the system 510 can determine the therapy to be delivered to the subject 512 at the therapy delivery time. Similar to the initial control parameter, the therapy can be delivered during one or more therapy delivery times based on the modified control parameter. The system can determine the effect of the therapy delivered based on the modified control parameter using one or more of the embodiments described above with respect to the therapy delivered using the initial control parameter.

[0188] The system can compare the measured or determined effects of the therapy delivered using the initial control parameters with the effects of the therapy delivered using the modified control parameters. Based on this comparison, the system can determine which control parameter values are suitable for the subject. The comparison can be performed in real time or substantially in real time. Further, the comparison can be performed by the system 510 without user operation. Preferred control parameter values are generally control parameters that bring the subject's blood glucose value closer to the desired range or set point of the subject. In some cases, the comparison can be based on a statistical analysis or a regression-based analysis. The system can have values that set or maintain the control parameters to generate a blood glucose value closer to the desired range or set point of the subject for subsequent therapy.

[0189] In some cases, the system 510 can repeat the process for various control parameter values, enabling the system to improve the subject's blood glucose control over time. In subsequent executions of the process, the initial control parameter value may not be the initial value, but rather the value last selected for the control parameter based on the determined effect of the control parameter. It may be.

[0190] In some cases, the determination of a second or modified value of the control parameter, or the modification of the control parameter, can be triggered based on the subject's glucose value not meeting a threshold. Alternatively, or in addition, the process of modifying the control parameter value can be triggered based on the difference between the expected glucose value of the subject above the threshold and the expected glucose value of the subject after therapy.

[0191] Using the embodiments described herein, the value of the control parameter can be automatically modified by the control algorithm used for the subject's blood glucose control without the subject or user interacting with the blood glucose control system. In other words, the blood glucose control system can automatically adjust and / or improve the control parameters used by the control algorithm for the subject's blood glucose control.

[0192] As described above, the blood glucose control system can provide both insulin therapy and counterregulatory agent therapy to a subject. In some cases, the blood glucose control system can provide insulin therapy only. In some such cases, the blood glucose control system can output an indication of the amount of counterregulatory agent that can be or should be administered to the subject based on the detected state of the subject.

[0193] The active control parameter values used by the control parameters can remain active until the occurrence of a subsequent therapy modification process. In some cases, the execution of the therapy modification process is continuously executed using control parameter values that are modified based at least in part on the determined effects of past control parameter values. In other cases, the therapy modification process is executed until the determined effect of the therapy meets a desired threshold (e.g., when the detected blood glucose value is within the threshold of a set value or a median set value). In some cases, the therapy modification process is executed a set number of times and the control parameter values that provide the best results (e.g., closest to the desired blood glucose value) are set as the active control parameters for subsequent therapy. In some cases, different sites on the subject (e.g., back, stomach, leg, or arm) can result in different blood glucose absorption rates. Thus, in some such cases, the therapy modification process can be executed each time the blood glucose control system is moved to a different site on the subject.

[0194] Exemplary Automatic Blood Glucose Control Improvement Process FIG. 13 presents a flowchart of an exemplary automated blood glucose control improvement process according to a particular embodiment. Process 1300 can be executed by any system that can autonomously and / or automatically modify a control algorithm and / or control parameters that affect the execution of the control algorithm based on feedback (e.g., from a blood glucose signal) regarding the therapy administered to subject 512. For example, process 1300 may be executed by one or more elements of glucose value control system 510. In some cases, at least certain operations of process 1300 may be executed by a separate computing system that receives blood glucose data from glucose value control system 510. Although one or more different systems may execute one or more operations of process 1300, for simplicity of discussion and without limiting the present disclosure, process 1300 will be described with respect to a particular system.

[0195] Process 1300 can be executed automatically and without user interaction. In some cases, a user can trigger process 1300 via a command or interaction with a user interface. However, once process 1300 is triggered, process 1300 can be executed automatically. Further, process 1300 can be executed continuously, periodically, or in response to a trigger. The trigger can be time-based and / or based on a measurement of the subject's glucose value. For example, the trigger may correspond to a determination that the subject's glucose value is different from a predicted glucose value, predicted by a glucose value control algorithm based on the administration of a drug, and exceeds a threshold. Further, the trigger can be based on the activation or initial use of glucose value control system 510 by subject 512.

[0196] ​Process 1300 begins at block 1302, where glucose value control system 510 receives a glucose value signal corresponding to the glucose value of subject 512. The glucose value signal can be received from a glucose sensor that can measure the value of glucose in the blood of the subject. For example, the sensor may be a continuous glucose monitoring (CGM) sensor. Block 1302 may include one or more of the embodiments described above with respect to block 802 or 902.

[0197] At block 1304, glucose value control system 510 provides a first therapy to subject 512 during a first therapy period. The first therapy may be based at least in part on the glucose value signal and a first value of a control parameter. The control parameter may include any control parameter that affects the operation of glucose value control system 510 and / or the performance of the control algorithm of glucose value control system 510. The control algorithm may include any control algorithm used to determine the dosage of a drug (e.g., insulin) to be administered to subject 512. In other words, controller 518 or processor 530 may use the control algorithm to generate a dosage control signal based at least in part on the value of the control parameter (e.g., the first value of block 1304) to cause delivery device 514 to administer a dosage of insulin or other drug.

[0198] In some cases, the control algorithm may be based on a PK model (Equation 2). Further, in some cases, the control parameter may be Tmax, which can be calculated using Equation 3. In other cases, the control parameter may be T 1 / 2 which may be related to the amount of time it takes for the dosage of insulin in the bloodstream to decrease to half of the maximum concentration in the blood resulting from the dosage administered to subject 512. In some cases, the control parameter corresponds to the time it takes for the insulin in the subject's plasma to reach a specific concentration level after administration of the insulin dosage. Further, in some cases, the control parameter is a parameter that affects the determination of Tmax, such as time constant α 1 and α 2It can be one or more of them. In some implementations, the control parameter can be used by a control algorithm to account for and / or determine the accumulation of insulin (or other agent) in subject 512 and / or the decrease in the rate of insulin (or other agent) in subject 512. In some cases, the control parameter can be used to control the insulin administration response of the control algorithm to the blood glucose excursion of the subject as indicated by the glucose value signal received at block 1302.

[0199] In some cases, the control parameter can be the time constant α used in the calculation of Tmax 1 and α 2 It can be related to at least one time constant used in the calculation of the accumulation of insulin in the subject by a control algorithm, such as one or more of them. In some cases, the control parameter can correspond to the rate of decrease of insulin in subject 512. In some cases, the control parameter can be related to a target set value or a target set value range for maintaining or attempting to maintain the blood glucose level of subject 512.

[0200] The first therapy can correspond to a single administration of insulin to subject 512. This single administration of insulin can be any type of insulin administered for any reason. For example, the insulin dosage can be a basal insulin dosage, a priming dosage, a dosage supplied in response to a meal announcement, or a corrective dosage of insulin. Further, the first therapy can be an agent other than insulin, such as an antidiabetic agent (e.g., glucagon). In some cases, the first therapy can be the dosage of a plurality of agents (e.g., insulin and / or antidiabetic agent) supplied or administered to subject 512 over a first therapy period. Further, the plurality of agent dosages can include various types of agent dosages, such as one or more basal dosages, one or more meal dosages related to a meal announcement, one or more corrective dosages, etc.

[0201] The first treatment period can be a period corresponding to a single drug dosage. Alternatively, the first treatment period can be a period that includes multiple drug dosages. Further, the first treatment period of time can be a period related to a defined length of time. Alternatively, or in addition, the first treatment period can be defined based on multiple drug periods. In other words, the period can vary based on the amount of time required to deliver or administer a specified number of dosages of a drug (of any kind or a particular kind).

[0202] The first value can be selected based on past treatments or past implementations of process 1300. In some cases, the first value is selected based on a baseline value. The baseline value can be associated with clinical data or determined based on the initial operation of the glucose value control system 510 for a certain period before the execution of process 1300. Alternatively, or in addition, the first value can be selected based on the clinical data of subject 512 or a specific prescription. In some cases, the first value can be based on the clinical data of an average user or an average user who shares specific physiological data with subject 512. In some cases, the first value is determined based on the evaluation of the healthcare provider of subject 512. Further, the first value can be determined based on the injection site of the glucose value control system 510 (e.g., back, stomach, leg, etc.). In some cases, the first value can be selected based on the demographics or characteristics of subject 512. For example, the first value can be based on the gender, weight, build, or age of subject 512.

[0203] In block 1306, the glucose value control system 510 determines a first effect that at least partially corresponds to or results from the first therapy. Determining the first effect may include receiving a glucose value signal from a glucose value sensor operably connected to the subject. This glucose value signal may be a subsequent or updated glucose reading that is newer than the glucose value signal received in block 1302. The glucose value signal received in block 1302 may be used to determine the therapy to be administered to the subject 512, and the glucose value signal received in block 1306 may be used to determine the result of the administered therapy. It should be understood that the glucose value signal may be received continuously or periodically and can be used for both determining the therapy to be administered and determining the effect of the administered therapy.

[0204] In some cases, determining the first effect may include analyzing the glycemic control of blood glucose in the subject indicated by the glucose value signal. Analyzing the glycemic control of blood glucose in the subject may include tracking the blood glucose value of the subject 512 over time. Further, analyzing the glycemic control of blood glucose in the subject may include comparing the blood glucose value of the subject 512 over time to the predicted blood glucose of the subject 512 over time predicted based on a control algorithm using a selected value of a control parameter. Comparing the blood glucose value of the subject 512 over time to the predicted blood glucose value may include determining whether, or to what extent, the accumulation and / or decrease of insulin (or other agent) based on the blood glucose value signal obtained from the CGM sensor matches the predicted accumulation or decrease of insulin (or other agent).

[0205] In block 1308, the glucose value control system 510 generates a second value of the control parameter. This second value can be determined autonomously. Further, in some cases, the second value can be determined automatically. In some cases, the second value is determined at least in part based on the user who triggers the blood glucose control improvement process 1300. The second value can be an increase or decrease in the control parameter compared to the first value. The second value can be limited to a specific maximum change from the first value. Further, the second value can be selected at least in part based on the first effect. For example, if the first effect corresponding to the first value results in a blood glucose level closer to the upper range of the set value range, the second value may be selected to be a blood glucose value closer to the center of the set value range. Further, the second value can be selected at least in part based on the characteristics of the subject 512, such as age, weight, gender, or any other characteristic that can affect blood glucose management. In some cases, the second value can be determined at least in part based on an evaluation or input of the subject 512 regarding the first value or the first effect. For example, if the subject 512 experiences fluctuations, dizziness, lightheadedness, nausea, or discomfort during the first treatment period, the subject 512 may indicate how the subject 512 feels, for example, via the user interface of the glucose value control system 510. The second value can be selected at least in part based on the evaluation provided by the subject 512 in an attempt to relieve the symptoms perceived by the subject 512. If the first effect corresponding to the first value results in a blood glucose level closer to the upper range of the set value range, the second value may be selected to be a blood glucose value closer to the center of the set value range. Further, the second value can be selected at least in part based on the characteristics of the subject 512, such as age, weight, gender, or any other characteristic that can affect blood glucose management. In some cases, the second value can be determined at least in part based on an evaluation or input of the subject 512 regarding the first value or the first effect. For example, if the subject 512 experiences fluctuations, dizziness, lightheadedness, nausea, or discomfort during the first treatment period, the subject 512 may indicate how the subject 512 feels, for example, via the user interface of the glucose value control system 510. The second value can be selected at least in part based on the evaluation provided by the subject 512 in an attempt to relieve the symptoms perceived by the subject 512.

[0206] In some cases, the second value of the control parameter can be generated based at least in part on the baseline value of the control parameter and the output of a function defined based on the target blood glucose control. The glucose value signal can represent an indicator of the target's blood glucose control during the first therapy period. The baseline value of the control parameter can correspond to the first value used to provide therapy at block 1304. This baseline value can be the last known optimal value for the subject prior to any changes to the subject (e.g., changes in weight, insulin type, or metabolic changes, etc.). Alternatively, or in addition, the baseline value can be a value determined by a healthcare provider. In some cases, the second value of the control parameter is based at least in part on the blood glucose control indicated by the glucose value signal.

[0207] The second value of the control parameter can be selected based on the performance of a regression analysis between the time it takes for subcutaneously administered insulin to be absorbed into the subject's blood and the blood glucose control function. The blood glucose control function can be based at least in part on the glucose value signal. In some cases, the regression analysis is performed between Tmax or T 1 / 2 and the time constant α 1 and α 2 for one or more of them.

[0208] At block 1310, the glucose value control system 510 changes the control parameter to the second value. Changing the control parameter to the second value changes the operation or execution of the control algorithm. This change in the execution of the control algorithm can result in a change in one or more factors related to the provision of therapy to the subject 512. For example, the change in the execution of the control algorithm can result in a change in the amount of drug delivered, the timing of drug delivery, the rate at which the drug dosage is delivered to the subject 512, the target setpoint or target range for the subject's blood glucose, the threshold used in determining whether to deliver the drug (e.g., the threshold difference from the target setpoint), or a change in any other factor that can affect the therapy delivered to the subject 512. In some cases, the second value can be a modification of Tmax or T 1 / 2 and Tmax and / or T 1 / 2It should be understood that it can be at least partially based on the physiological or biochemical state of the subject 512. Accordingly, either setting of the first value and the second value for Tmax or T 1 / 2 can refer to representing Tmax and / or T 1 / 2 or setting a parameter of the control algorithm corresponding thereto. For example, the setting of the first value and the second value may include setting the control parameter to a value determined or estimated to be Tmax and / or T 1 / 2 for the subject 512. However, the set value may be different from the actual Tmax and / or T 1 / 2 of the subject 512. Further, since Tmax and / or T 1 / 2 can be different for each subject, it is not always possible to explicitly set or determine the Tmax and / or T 1 / 2 of the subject. Instead, Tmax and / or T 1 / 2 can be estimated or determined by comparing the effects and / or blood glucose values determined for different control parameter values corresponding at least in part to Tmax and / or T 1 / 2 . Using process 1300, the control parameter can iteratively approach the actual Tmax and / or T 1 / 2 of the subject 512, or within the threshold of the actual Tmax and / or T 1 / 2 of the subject 512. Alternatively, using process 1300, the control parameter (such as one or more of the time constants α 1 and α 2 ) can iteratively approach a value corresponding to the actual Tmax and / or T 1 / 2 of the subject 512. approach.

[0209] In block 1312, the glucose value control system 510 provides a second therapy to the subject 512 during a second therapy period. The second therapy is at least partially based on updated control parameters, which are updated to a second value in block 1310. Similar to the first therapy, the second therapy may refer to one or more drug dosages. Further, the second therapy period may refer to a specific time, a time for delivering a specific number of drug dosages, or a specific number of drug dosages. In some cases, block 1312 may include one or more of the embodiments described with respect to block 1304 and use the second value for the control parameters over the second therapy period.

[0210] In block 1314, the glucose value control system 510 determines a second effect that at least partially corresponds to the second therapy. Block 1314 may include one or more of the embodiments described with respect to block 1306, but for the second therapy.

[0211] In block 1316, glucose value control system 510 selects one of a first value or a second value based at least in part on a comparison of a first effect and a second effect. The comparison of the first effect and the second effect can be performed autonomously without an operation by a user. Glucose value control system 510 selects one of the first value or the second value to be the current value or active value of a control parameter based on whether the first effect or the second effect results in improved care of subject 512 (e.g., closer to a desired set value over a longer period, or lower variation in blood glucose levels, or any other factor that a healthcare provider may use to evaluate the success of diabetes management). In some cases, glucose value control system 510 selects a third value relative to the current value or active value of the control parameter. The third value can be selected based on a comparison of the first effect and the second effect. For example, if it is determined that the first effect is more preferable than the second effect, the third value may be selected based on a change to the first value in a direction opposite to a change added to the first value to obtain the second value. For example, in the previous example where it is determined that the first effect is more preferable than the second effect, if the first value is selected to correspond to a Tmax of 60 minutes and the second value is selected to correspond to a Tmax of a longer period (e.g., 65 minutes or 70 minutes), the third value may be selected to correspond to a Tmax of a shorter period (e.g., 50 minutes or 55 minutes).

[0212] In comparing the first effect and the second effect, it may include determining whether the first value or the second value has brought the glucose value of the subject 512 closer to the target set value and / or maintained the glucose value of the subject 512 within the target range for a longer period. In some cases, in comparing the first effect and the second effect, it may include determining whether the first value or the second value has resulted in a more stable blood glucose value of the subject 512 or a lower variation in the blood glucose value of the subject 512. In some cases, in comparing the first effect and the second effect, it may include determining whether the first value or the second value has resulted in more excursions and / or larger excursions of the blood glucose value of the subject 512 from the target blood glucose range.

[0213] The comparison of the first effect and the second effect can be performed in real time or substantially in real time, taking into account the processing rate of the hardware processor 530 or the glucose value control system 510. Thus, in some cases, the comparison of the first effect and the second effect can be performed at the time of determination of the second effect.

[0214] In some embodiments, the comparison of the first effect and the second effect may include a statistical comparison or statistical analysis of the first effect and the second effect. The statistical comparison may include performing a regression analysis of at least the first effect and the second effect. In some cases, the comparison of the first effect and the second effect may include determining whether the second therapy has resulted in a statistically significant improvement in therapy (e.g., blood glucose control) compared to the first therapy. A statistically significant improvement may vary depending on the subject or the state of the subject. This comparison can also include determining whether there has been a statistically significant increase in risk factors (e.g., hypoglycemia) during the second therapy period compared to the first therapy period.

[0215] In some cases, values for more appropriately managing the blood glucose of subject 512 can be output to the user (e.g., the subject or a parent). Next, the user can configure the glucose value control system 510 based on the selected control parameter values. Alternatively, or in addition, the glucose value control system 510 can automatically modify the values of the control parameters. In some cases, the user may be provided with an opportunity to confirm the modification. In other cases, the modification can be made automatically without confirmation. However, the modification can be presented to the user (e.g., the subject or a healthcare provider) and / or recorded in the therapy log.

[0216] In some cases, the comparison is performed by another computing system that communicates with the glucose value control system 510. For example, the glucose value control system 510 may transmit data determined from a glucose value signal or a glucose value signal indicating the effect of blood glucose control to another computing system such as a local computing system, a smartphone, or a cloud-based computing system. Further, the glucose value control system 510 can transmit data related to the control parameter values and the administration of the drug to subject 512 to the computing system. The computing system can determine the values of the control parameters for better managing the blood glucose level of subject 512. The computing system can configure the glucose value control system 510 with the selected values. Alternatively, or in addition, the selected values can be output to the user who can configure the glucose value control system 510 using the selected values.

[0217] In block 1318, the glucose value control system 510 provides therapy to the subject 512 based on the selected value of the control parameter selected in block 1316. The therapy provided in block 1318 can be provided during a third therapy period, which is at some point after the first and second therapy periods. Thus, during the first two periods, the first and second values can be used for the control parameter respectively to determine values that result in better outcomes or improved care for the subject 512. During subsequent periods, the values that resulted in better outcomes for the subject 512 can be used to provide future care for the subject 512. Alternatively, in an attempt to find a value of the control parameter that can provide a better or improved level of care (e.g., closer to the desired target glucose value over a longer period) for the subject 512 using a new value that is neither the first value nor the second value, subsequent care can be provided.

[0218] Providing therapy to the subject 512 based on the selected value may include configuring the glucose value control system 510 to provide therapy to the subject 512 during a third therapy period based at least in part on the active control parameter value. In some cases, the process 1300 can be terminated by configuring the glucose value control system 510 to provide therapy to the subject 512 based at least in part on the active control parameter value. In other cases, the process 1300 can be repeated. Repeating the process 1300 may include using the selected value (e.g., the first or second value from a previous iteration of the process 1300) as the first value when performing the operations associated with block 1304. The second value generated in block 1308 can be a new value that was not used during the previous iteration of the process 1300.

[0219] Process 1300 can be repeated until the difference between the first effect and the second effect becomes smaller than the threshold difference. Alternatively, or in addition, process 1300 can be periodically repeated a specific number of times in response to a command or in response to determining that the blood glucose of target 512 does not meet a specific threshold for a specific period of time.

[0220] As described, process 1300 can be used to modify one or more control parameters that affect insulin delivery. However, process 1300 is not limited to itself and can be used to modify one or more control parameters that affect the delivery of other agents such as counterregulatory agents (e.g., glucagon). In some cases, process 1300 can be used to recommend changes in the delivery of insulin and / or counterregulatory agents without modifying the delivery. This can be advantageous for generating recommendations regarding counterregulatory agents in non-bihormonal glucose value control system 510 that does not support counterregulatory agents or supports the use of counterregulatory agents but does not have available counterregulatory agents.

[0221] Furthermore, when using process 1300 to modify multiple control parameters, at least two or more control parameters can be related to each other. For example, if the control parameters include time constants α 1 and α 2 are included, there is a relationship between α 1 and α 2 , and modifying α 1 may also modify α 2 . For example, α 2 may be equal to 1.5 times α 1 .

[0222] The value of the control parameter set as an active parameter in block 1316 (e.g., the first value or the second value) can be used by a control algorithm to provide therapy to the subject 512 over a specific period or until the process 1300 is repeated. As described above, in some cases, the process 1300 can be repeated periodically and / or in response to a trigger such as a blood glucose value or an average blood glucose value over a certain period, or an indicator of a site change for connection to the subject 512 of the glucose value control system 510.

[0223] Exemplary case study As described above, the peak time of insulin absorption can be referred to as Tmax. If the type of insulin is different, the time to the peak of absorption into the subject's blood can occur, or different times can occur for each subject. For example, in one exemplary case study, the total Tmax between subjects for Humalog and Novolog, which are rapid-acting insulins, was determined to be about 65 minutes, while for Fiasp, an ultra-rapid-acting insulin that shares the active ingredient with Novolog but has a different formulation to reduce the time to peak absorption, the total Tmax between subjects was determined to have a Tmax of about 40 minutes. However, when using an automatic blood glucose control system (such as the glucose value control system 510) with a control parameter corresponding to Tmax set at 65 minutes, there was no statistical improvement in the average glucose value or the frequency of hypoglycemia when using rapid-acting insulin or ultra-rapid-acting insulin.

[0224] However, when adjusting the values of the control parameters of the automatic blood glucose control system to use different Tmax settings, in one case study, it was shown that when using Fiasp, an ultra-rapid-acting insulin, to lower Tmax, the average glucose value decreased. In the case study, three cohorts of eight people each were used to test the effect of modifying Tmax when using a blood glucose control system that used Fiasp as the drug. The first cohort used a blood glucose control system composed of a Tmax of 65 minutes per week, followed by a Tmax of 50 minutes per week. The second cohort compared a Tmax of 65 minutes for the first week to a Tmax of 40 minutes for the second week. The third cohort compared a Tmax of 65 minutes for one week to a Tmax of 30 minutes for one week. By comparing the changes in Tmax within and between each cohort, it was demonstrated that when Tmax decreased, the average glucose value decreased and there was no statistically significant increase or decrease in hypoglycemia on average.

[0225] However, when Tmax is shorter than physiological insulin absorption, the blood glucose control system can stack or administer multiple doses of insulin within a certain period, increasing the risk of hypoglycemia. This can occur because when Tmax is set lower than the actual peak insulin absorption time, the blood glucose control system may incorrectly identify the hypoglycemic concentration as the maximum blood glucose concentration.

[0226] By using Process 1300 in combination with the use of autoregression and comparing the effects of various Tmax settings, the Tmax settings for a subject and / or a specific type of insulin can be optimized. Autoregression can be performed by comparing the average glucose values of the subject and determining whether there is a significant difference in the average glucose values of subsequent periods using a Tmax value different from that of the previous evaluation period. If the subsequent or newer value used for Tmax results in an improved effect, the control parameter of the blood glucose control system 510 corresponding to Tmax can be set to the newer value. After collecting the glucose signal of the subject 512 at the default value or past value of Tmax for a certain period, the value of Tmax can be decreased by a significant amount (e.g., a decrease of 10 minutes) from the initial Tmax. The autoregression process may include collecting blood glucose data from the subject related to past time. The system can perform a real-time regression analysis between a past data set with large Tmax data and a current data set with small Tmax data. If the controller of the blood glucose control system determines that there is a statistically significant improvement (e.g., an improvement exceeding a threshold) in the average glucose value of the subject with little or no increase in hypoglycemic events or risk events, the system can adopt or recommend a lower Tmax value as the preferred Tmax. This process can be repeated using further reductions in Tmax. In some cases, each reduction in Tmax may be smaller than the previous reduction. Further, if it is determined that there is no improvement in the average glucose value of the subject and / or if the risk of hypoglycemia or hypoglycemic events increases, the system may use the past Tmax or select a Tmax between the new Tmax and the past Tmax. Thus, by using Process 1300, the system can iteratively modify Tmax to find the optimal value for the subject and / or the selected type of insulin. Further, by performing the autoregression process in real time, the maintenance of the subject's diabetes can be improved more quickly and accurately compared to a delayed analysis that may occur during a clinical trial. Since the physiological changes of the subject may not be captured in real time, the accuracy of the clinical trial may decrease.

[0227] In some cases, other types of biomedical data obtained by one or more sensors of a medical device can be analyzed using the real-time autoregressive process described above. Further, autoregressive analysis can be used to make additional recommendations for the subject. For example, if it is determined that the actual Tmax of a particular insulin is higher than expected for the subject, the subject may be recommended to modify their diet in a particular way.

[0228] Furthermore, as described above, the autoregression can be obtained based on glucose value measurements of the subject that can be obtained from a CGM. However, the present disclosure is not limited thereto. In some cases, the autoregression can be performed on additional biomedical data, such as data received from a smartwatch (blood pressure, heart rate, etc.), a weight sensor, or other types of biomedical sensors. By adapting process 1300 to perform autoregression on other data, a quantitatively objective analysis of the biometric data can be performed, which can be used by a healthcare provider to care for the subject.

[0229] Exemplary Simulations Embodiments of an automatic glucose value control system 510 that can be adapted for use with embodiments of the present disclosure are described in International Publication No. WO2015 / 1165 published on August 6, 2015, U.S. Patent No. 9,833,570 issued on December 5, 2017, and U.S. Patent No. 7,806,854 issued on October 5, 2010, the disclosures of each of which are hereby incorporated by reference in their entirety for all purposes.

[0230] Since the utilization rate of insulin is limited, the automatic glucose control system 510 can autonomously administer the insulin dose and take into account the online accumulation of the insulin dose (the "residual insulin"). The time course of the activity of the insulin dose, and thus the accumulation, can be modeled by a biexponential pharmacokinetic (PK) model represented by Equation 2 using a pre-set time constant. An important clinical significance associated with the PK model is the time it takes for the insulin dose (e.g., subcutaneous administration) to reach its peak in terms of its presence or effect in the blood. The peak time is referred to as Tmax. In effect, the setting of the time constant of the PK model can be used to set the Tmax that is essentially assumed by the model, and conversely, setting the Tmax can set the time constant of the PK model. Since the value of the time constant can be used to determine the online calculation of the accumulation of insulin by the control system, the value of the time constant can, as a result, control the insulin administration response of the control system to a given glucose excursion. Therefore, varying the Tmax (and thus the time constant) can be regarded as a setting knob for online controlling the magnitude of the insulin dose (e.g., aggressive or conservative) of the control system.

[0231] In certain embodiments, the control system implements a method for online adaptation of the Tmax (and thus the time constant) setting of the PK model of the control system. This method can be performed by a control system that periodically performs online evaluation and calculation to generate recommendations for modification of Tmax, or by a control system that autonomously adjusts Tmax online. In either case, the calculation can be based on the performance of the control system over a certain time range or period. Whether occurring autonomously or issued as a recommendation, the online adaptation of Tmax can be based on the glucose control performance of the control system over a certain time interval, including trends in the degree and / or duration of occurrence of glucose values, average glucose values, or low glucose values (hypoglycemia) and / or high glucose values (hyperglycemia). Alternatively, this calculation can be based on the use of counterregulatory agents, and other intended uses of counterregulatory agents are available (e.g., in an insulin-only system, or when the counterregulatory agent or its delivery channel is temporarily unavailable). In this method, upper and / or lower limits (static or dynamic) can be imposed on the range within which Tmax can vary. The degree of adaptation of Tmax to a given situation may vary, for example, depending on the particular insulin being administered by the control system.

[0232] The described method can be equally applicable regardless of whether the continuous glucose monitor (which can provide an input glucose signal to the control system) is online or offline. For example, the methods disclosed herein may be applicable to the systems described in International Publication No. WO2015 / 116524. Further, the described method can coexist with other aspects of the system, whether activated or not, such as having a glucose target that is automatically adapted by the system, as in the systems described in International Publication No. WO2017 / 027459, published February 16, 2017, which is incorporated herein by reference for all purposes, but not limited thereto.

[0233] As described above, the absorption of subcutaneously administered insulin into the blood can be governed by the biexponential PK model of Equation 2. The setting of the time constants in the PK model can be set to measure the retention effect of the amount of insulin accumulated in the subcutaneously administered dose, which is the total area ( [Number] dose U 0 that can describe the measured value of the total action over time by), and can represent the measured value of the consumed part of U 0 . It can be interpreted as the difference between [Number] and. The peak time Tmax of the absorption of the insulin dose into the blood can be given by Equation 3. Therefore, by setting Tmax, the time constants of the PK model can be set, whereby the magnitude (e.g., aggressive or conservative) of the online insulin administration response of the control system to a given glucose profile can be directly controlled. Without being so limited, for simplicity, α 1 and α 2 are related. For example, assume that α 2 = 1.5α 1 .

[0234] Figures 14A - 14C show simulations showing the effects that increasing or decreasing the Tmax setting, or the value of the control parameter corresponding to Tmax, can have on the online insulin administration response of the glucose value control system to a given glucose profile.

[0235] Figure 14A shows a simulation of the blood glucose control of a subject with Tmax set to 65 minutes. Graph 1402A shows the blood glucose values of the subject over 24 hours. Range 1404 shows the desired target set value range of the subject's blood glucose values (e.g., 70 - 120 mg / dL). Further, range 1406 shows the range of the subject's glucose values related to hypoglycemia or the risk of hypoglycemia (e.g., less than 60 mg / dL). Graph 1410B shows the administration of a drug (insulin or glucagon) to the subject over the same 24 - hour period as Graph 1402A, based at least in part on the blood glucose values shown in Graph 1402A.

[0236] Figure 14B shows a simulation of the blood glucose control of a subject with Tmax set to 15 minutes. Graph 1410B corresponds to Graph 1410A, but with Tmax set to 15 minutes instead of 65 minutes. As shown by comparing Graph 1410B with 1410A, reducing Tmax to 15 minutes can result in an increase in insulin administration.

[0237] Figure 14C shows a simulation of the blood glucose control of a subject with Tmax set to 130 minutes. Graph 1410C corresponds to Graph 1410A, but with Tmax set to 130 minutes instead of 65 minutes. As shown by comparing Graph 1410C with 1410A, increasing Tmax to 130 minutes can result in a decrease in insulin administration. An increase or decrease in the dosing of insulin (or counterregulatory agents) can affect the care of subject 512 and can affect whether the symptoms experienced by the subject (e.g., dizziness, nausea, etc.) are due to the maintenance of the subject's diabetes.

[0238] The simulations shown in FIGS. 14A-14C illustrate one non-limiting example of modifying control parameters. In some cases, different dosages may lead to different CGM excursions, which in turn may vary the insulin-glucagon dosage. Nevertheless, these simulations demonstrate the ability of Tmax as a setting in determining dosing by the glucose value control system 510.

[0239] In some implementations, the value of Tmax can be automatically varied online based on blood glucose control within a backward time window. For example, Tmax can be described using the formula

Number

Number

Number

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Number

[0240] Exemplary embodiments Embodiments of the present disclosure can be described in view of the following clauses. Clause 1. A computer-implemented method for generating an index of total glycemic therapy over a period in a subject using a drug pump configured to deliver at least to insulin therapy, the method comprising A hardware processor configured to generate a dosage control signal for the drug pump configured to deliver at least insulin therapy to the subject, receiving the glucose value of the subject; determining that a trigger event has occurred to increase the blood glucose level of the subject, at least in part based on the glucose value, the trigger event including that there is an imminent risk of hypoglycemia in the subject or that there is an episode of hypoglycemia in the subject; determining an amount of an antagonist regulator in response to the imminent risk of hypoglycemia or the episode of hypoglycemia; determining a dosage of glucotherapy, at least in part based on the amount of the antagonist regulator; tracking the determined dosage of glucotherapy over a period including a plurality of hypoglycemia risk events or hypoglycemia episodes to generate an indicator of the total glucotherapy over the period; outputting the indicator of the total glucotherapy; A method, comprising. Clause 2. The computer-implemented method according to clause 1, further comprising providing the amount of the antagonist regulator to the subject in response to the imminent risk of hypoglycemia or the episode of hypoglycemia. Clause 3. The computer-implemented method according to clause 1, further comprising providing the amount of the antagonist regulator to the subject in response to the glucose value that meets or is below a threshold glucose value. Clause 4. The computer-implemented method according to clause 3, wherein the threshold glucose value is set based on the subject's risk tolerance for hypoglycemia events. Clause 5. The computer-implemented method according to clause 1, wherein the indicator of the total glucotherapy corresponds to a decrease in glucosides consumed by the subject. Clause 6. The computer-implemented method according to clause 1, wherein the indicator of the total glucotherapy corresponds to a decrease in glucosides achievable by the availability of the antagonist regulator. Clause 7. The computer-implemented method according to clause 1, wherein the indicator of the total carbohydrate therapy corresponds to the amount of the antagonist regulator provided to the subject as a substitute for carbohydrates. Clause 8. The computer-implemented method according to clause 1, wherein the indicator of the total carbohydrate therapy includes an indicator of the carbohydrate range. Clause 9. Determining the dosage of the carbohydrate therapy comprises accessing a mapping between the antagonist regulator and carbohydrates, and determining the dosage of the carbohydrate therapy based at least in part on the mapping and the amount of the antagonist regulator. The computer-implemented method according to clause 1, comprising. Clause 10. The computer-implemented method according to clause 9, wherein the mapping is based at least in part on the type of carbohydrates. Clause 11. The computer-implemented method according to clause 9, wherein the mapping is generated based on a clinical comparison between the antagonist regulator and the carbohydrates. Clause 12. The computer-implemented method according to clause 9, wherein the mapping is based at least in part on the physiological characteristics of the subject. Clause 13. The computer-implemented method according to clause 9, wherein the mapping is based at least in part on the type of the antagonist regulator. Clause 14. The computer-implemented method according to clause 9, wherein the mapping includes a mathematical formula associating the antagonist regulator with the carbohydrates. Clause 15. The mapping includes a first mapping when the drug pump includes a biphasic pump configured to deliver antagonist regulator therapy to the subject, and the mapping includes a second mapping when the drug pump is not configured to deliver the antagonist regulator therapy to the subject. The computer-implemented method according to clause 9. Clause 16. The computer-implemented method according to clause 1, wherein the indicator of the total carbohydrate therapy includes one or more of an indicator of calories, an indicator of carbohydrates, a measured value of sugars, an indicator of the amount of food, or an indicator of the weight of the subject resulting from the carbohydrate therapy. Clause 17. An automatic blood glucose control system configured to generate an index of total carbohydrate therapy over a period of time for a subject, the automatic blood glucose control system comprising: A drug delivery interface configured to operably connect to a drug pump configured to inject a drug into the subject, the drug comprising at least insulin, and a drug delivery interface; A memory configured to store specific computer-executable instructions; A hardware processor in communication with the memory, the hardware processor executing the specific computer-executable instructions to at least: Receive a glucose value of the subject; Determine that a trigger event has occurred to increase the blood glucose value of the subject based at least in part on the glucose value, the trigger event including the presence of an imminent risk of hypoglycemia or the presence of an episode of hypoglycemia in the subject; Determine an amount of an antagonist regulator in response to the imminent risk of hypoglycemia or the episode of hypoglycemia; Determine a dosage of carbohydrate therapy based at least in part on the amount of the antagonist regulator; Track the determined dosage of carbohydrate therapy over a period including a plurality of hypoglycemia risk events or hypoglycemia episodes to generate an index of the total carbohydrate therapy over the period; Output the index of the total carbohydrate therapy; And a hardware processor configured to perform the above; An automatic blood glucose control system comprising the above. Clause 18. The hardware processor is further configured to operate a control algorithm for automatically generating an antagonist regulator dosing signal configured to operate the drug pump to control a blood glucose value in the subject based at least in part on a glucose value signal received from a glucose value sensor operably connected to the subject, the glucose value indicating that the glucose value does not meet a threshold corresponding to the trigger event, in the automatic blood glucose control system according to Clause 17. Clause 19. The memory is further configured to store a mapping between the antagonist regulator and the saccharide, and the hardware processor is configured to access the mapping from the memory, determine a dosage of the saccharide therapy based at least in part on the mapping and the amount of the antagonist regulator, The automatic blood glucose control system according to Clause 17, further configured to perform the above operations. Clause 20. The automatic blood glucose control system according to Clause 19, wherein the mapping includes an algorithm associating the antagonist regulator with the saccharide.

[0241] Additional embodiments of the present disclosure can be described in consideration of the following clauses. Clause 21. An automatic blood glucose control system configured to generate a backup therapy protocol including an instruction for insulin therapy derived from an autonomously determined dosage of insulin, the automatic blood glucose control system comprising: a drug delivery interface configured to be operably connected to a drug pump for injecting a drug into the subject; a memory configured to store specific computer-executable instructions; a hardware processor in communication with the memory, the hardware processor executing the specific computer-executable instructions to at least receive a glucose value signal from a sensor operably configured to determine a glucose value in the subject; generate a dosage control signal using a control algorithm configured to autonomously determine a dosage of insulin to be injected into the subject for the purpose of controlling the blood glucose of the subject based at least in part on the glucose value signal; generate a dosage control signal using a control algorithm configured to autonomously determine a dosage of insulin to be injected into the subject for the purpose of controlling the blood glucose of the subject based at least in part on the glucose value signal; Tracking the insulin therapy administered to the subject over a tracking period including at least one day by the automatic blood glucose control system, wherein tracking the insulin therapy includes storing an indicator of the autonomously determined insulin dosage delivered to the subject as basal insulin, insulin correction bolus, or insulin meal bolus, Generating at least one of a backup injection therapy protocol or a backup pump therapy protocol including an insulin therapy instruction, based at least in part on the insulin therapy administered to the subject over the tracking period, When the automatic blood glucose control system is not providing therapy to the subject, outputting on a display at least one of the backup injection therapy protocol or the backup pump therapy protocol to enable therapy to be maintained at a rate determined by the automatic blood glucose control system, A hardware processor configured to perform, An automatic blood glucose control system comprising. Clause 22. The automatic blood glucose control system according to clause 21, wherein the hardware processor is further configured to execute the specific computer-executable instructions to store at least the indicator of the autonomously determined insulin dosage delivered to the subject in the memory. Clause 23. The hardware processor is configured to execute the specific computer-executable instructions to at least, Establish a communication channel with an external computing system separate from the automatic blood glucose control system, Transmit the indicator of the autonomously determined insulin dosage delivered to the subject to the external computing system, The automatic blood glucose control system according to clause 21, which is further configured to perform. Clause 24. The external computing system is a computing system of a data center, The automatic blood glucose control system according to clause 23, wherein the hardware processor is further configured to execute the specific computer-executable instructions to control at least a radio capable of communicating with the external computing system via a wide area network. Clause 25. The automatic blood glucose control system according to clause 21, wherein the hardware processor is further configured to generate the backup injection therapy protocol by at least determining the number of units of long-acting insulin based at least in part on the average total basal insulin provided to the subject per day over the tracking period. Clause 26. The automatic blood glucose control system according to clause 21, wherein each day of the tracking period is divided into a plurality of sub-periods, and the hardware processor is further configured to generate the backup pump therapy protocol by at least determining an hourly basal rate for each of the plurality of sub-periods. Clause 27. The automatic blood glucose control system according to clause 21, wherein the hardware processor is further configured to generate the backup injection therapy protocol or the backup pump therapy protocol by at least determining the average correction bolus provided to the subject per day over the tracking period. Clause 28. The hardware processor, during the tracking period, for each meal time among a plurality of meal times per day, The automatic blood glucose control system according to clause 21, wherein the hardware processor is further configured to generate the backup injection therapy protocol or the backup pump therapy protocol by at least determining the average change in blood glucose at least partially attributable to the units of insulin provided as a correction bolus to the subject over the tracking period. Clause 29. The automatic blood glucose control system according to clause 21, wherein the hardware processor is further configured to generate the backup injection therapy protocol or the backup pump therapy protocol by at least determining the average meal-time bolus of insulin provided to the subject over the tracking period for each meal time among a plurality of meal times per day. Clause 30. The hardware processor executes the specific computer-executable instructions to at least track the antagonist therapy administered to the subject over the tracking period, wherein tracking the antagonist therapy includes storing an indicator of the autonomously determined dosage of the antagonist delivered to the subject in response to the glucose value signal, including, in at least one of the backup injection therapy protocol or the backup pump therapy protocol, an indicator of the total antagonist and / or the daily antagonist provided to the subject over the tracking period, The automatic blood glucose control system according to clause 21, further configured to perform. Clause 31. The control algorithm is further configured to autonomously determine the dosage of insulin injected into the subject for the purpose of controlling the blood glucose of the subject, based at least in part on the glucose value signal and a control parameter that is modifiable by user interaction with the control parameter selection interface element, and the hardware processor executes the specific computer-executable instructions to at least track user modifications to the control parameters over the tracking period, wherein tracking the user modifications includes storing in the therapy log whether each of the user modifications includes an increase or decrease in the control parameter from the stored control parameter value and the time at which each of the user modifications occurred, generate a report of user modifications to the control parameters, wherein the report includes a measure of the frequency of increases and decreases from the stored control parameter values, and the report is included in at least one of the backup injection therapy protocol or the backup pump therapy protocol, The automatic blood glucose control system according to clause 21, further configured to perform. A computer-implemented method for generating a backup therapy protocol that includes an insulin therapy instruction derived from an autonomously determined insulin dosage determined by an automated blood glucose control system, the method comprising: receiving, by a hardware processor of the automated blood glucose control system, a glucose value signal from a sensor operable to determine a glucose value in the subject; generating a dosage control signal using a control algorithm configured to autonomously determine a dosage of insulin to be infused into the subject for the purpose of controlling the subject's blood glucose based at least in part on the glucose value signal; tracking an insulin therapy administered to the subject over a tracking period including at least one day by the automated blood glucose control system, the tracking including storing an indicator of the autonomously determined dosage of insulin delivered to the subject; generating at least one of a backup injection therapy protocol or a backup pump therapy protocol that includes an insulin therapy instruction based at least in part on the insulin therapy administered to the subject over the tracking period; outputting, on a display, the at least one of the backup injection therapy protocol or the backup pump therapy protocol when the automated blood glucose control system is not providing therapy to the subject, to enable therapy to be maintained at a rate determined by the automated blood glucose control system; comprising. The computer-implemented method of clause 32, wherein the autonomously determined insulin dosage includes one or more of a basal insulin dosage, an insulin correction bolus, or an insulin meal bolus. An automated blood glucose control system configured to generate a report of a therapy protocol modification made by a user of the automated blood glucose control system, the automated blood glucose control system being A drug delivery interface configured to be operably connected to a drug pump for injecting a drug into a subject, A memory configured to store specific computer-executable instructions, stored control parameter values, and a therapy log, A hardware processor that communicates with the memory, the hardware processor executing the specific computer-executable instructions to at least, Receive a glucose value signal from a sensor operably configured to determine a glucose value in the subject, Generate a dosage control signal using a control algorithm configured to autonomously determine a dosage of insulin to be injected into the subject for the purpose of controlling the subject's blood glucose, based at least in part on the glucose value signal and a control parameter that is modifiable by user interaction with the control parameter selection interface element, Track user modifications to the control parameter over a tracking period that includes at least one day, where tracking the user modifications includes storing in the therapy log whether each of the user modifications includes an increase or decrease in the control parameter from the stored control parameter value and the time at which each of the user modifications occurred, Generate a report of user modifications to the control parameter, where the report includes a measure of the frequency of increases and decreases from the stored control parameter value, A hardware processor configured to perform the above, An automatic blood glucose control system comprising the above. Clause 35. The automatic blood glucose control system according to Clause 34, wherein the report further includes a percentage of user modifications that are higher or lower than the stored control parameter values over the tracking period. Clause 36. The automatic blood glucose control system according to Clause 34, wherein the report further includes the number of times insulin injection is interrupted over the tracking period. Clause 37. The automatic blood glucose control system according to clause 34, wherein the report further includes a percentage of time during which the stored control parameters are not modified by the user over the tracking period. Clause 38. The automatic blood glucose control system according to clause 34, wherein the tracking period is divided into a plurality of sub-periods, and the hardware processor is further configured to track user modifications to the control parameters for each sub-period of the tracking period, and the report includes measurements of the frequency of increases and decreases from the stored control parameter values for each sub-period of the tracking period. Clause 39. At least a first sub-period of the plurality of sub-periods is associated with a first value of the control parameter, at least a first sub-period of the plurality of sub-periods is associated with a second value of the control parameter, and the hardware processor tracks user modifications to the first value of the control parameter for the first sub-period and user modifications to the second value of the control parameter for the second sub-period, and is further configured as described in clause 38 of the automatic blood glucose control system. Clause 40. The automatic blood glucose control system according to clause 34, wherein the hardware processor is further configured to track user activities associated with the user modifications to the control parameters, and the report of the user modifications to the control parameters includes identification information of the user activities that occur during the user modifications to the control parameters.

[0242] Additional embodiments of the present disclosure can be described in consideration of the following clauses. Clause 41. A computer-implemented method for modifying a therapy provided to a subject using a blood glucose control system, the method comprising: generating, by a hardware processor configured to generate a dosage control signal for the blood glucose control system; receiving a glucose value signal from a glucose value sensor operably connected to the subject; During a first therapy period, delivering a first therapy to a subject by the blood glucose control system, wherein the first therapy is delivered based at least in part on a first value of a control parameter used by a control algorithm to generate the dosage control signal, the control parameter being used by the control algorithm to account for insulin accumulation in the subject, thereby controlling the insulin administration response of the control algorithm to blood glucose excursions in the subject indicated by the glucose value signal, and delivering; Determining a first effect that at least partially corresponds to the first therapy, wherein determining the first effect includes analyzing blood glucose control in the subject indicated by the glucose value signal, and determining; Autonomously generating a second value of the control parameter, wherein the autonomously generated second value is determined as a function based on the first value and the first effect, and generating; Modifying the control parameter from the first value to the second value; During a second therapy period, delivering a second therapy to the subject by the blood glucose control system, wherein the second therapy is delivered based at least in part on the second value of the control parameter, and changing the control parameter modifies the therapy provided to the subject, and delivering; A method comprising. Clause 42. By the hardware processor, Determining a second effect that at least partially corresponds to the second therapy; Selecting, based at least in part on a comparison of the first effect and the second effect, one of the first value of the control parameter or the second value of the control parameter as an active control parameter value; Configuring the blood glucose control system to provide therapy to the subject during a third therapy period based at least in part on the active control parameter value, wherein said selection of the active control parameter value modifies the therapy provided to the subject The computer-implemented method according to clause 41, further comprising Clause 43. The computer-implemented method according to clause 41, wherein the control parameter used by the control algorithm is related to at least one time constant used in the calculation of insulin accumulation in the subject by the control algorithm. Clause 44. The computer-implemented method according to clause 41, wherein the control parameter used by the control algorithm corresponds to the insulin decrease rate in the subject. Clause 45. The computer-implemented method according to clause 41, wherein the first therapy period includes a period corresponding to the administration of a plurality of instances of therapy, and the first therapy includes a plurality of instances of the therapy. Clause 46. The computer-implemented method according to clause 41, wherein modifying the control parameter to the second value modifies one or more of the timing or dose size of insulin administered during the second therapy period. Clause 47. The computer-implemented method according to clause 41, wherein the first value of the control parameter is based on one or more of the therapy, clinical values, or physique of the subject delivered during a period prior to the first therapy period. Clause 48. The computer-implemented method according to clause 41, wherein the control parameter used by the control algorithm corresponds to the time until insulin in the subject's plasma reaches a specific concentration level after administration of an insulin dose. Clause 49. A computer-implemented method of modifying therapy provided to a subject using a blood glucose control system, the method comprising by a hardware processor configured to generate a dose control signal for the blood glucose control system During a first therapy period, causing the glucose control system to deliver a first therapy to a subject, the first therapy being delivered based at least in part on a first value of a control parameter used by a control algorithm to generate the dosage control signal; Determining a first effect corresponding at least in part to the first therapy, the determining including receiving a glucose value signal from a glucose value sensor operably connected to the subject; Automatically generating a second value of the control parameter based at least in part on a baseline value of the control parameter and an output of a function defined based on the glucose control of the subject, the glucose value signal including an indicator of the glucose control of the subject during the first therapy period; Modifying the control parameter from the first value to the second value; During a second therapy period, causing the glucose control system to deliver a second therapy to the subject, the second therapy being delivered based at least in part on the second value of the control parameter, and changing the control parameter modifying the therapy provided to the subject; A method comprising. Clause 50. By the hardware processor, Determining a second effect corresponding at least in part to the second therapy; Selecting, as an active control parameter value, one of the first value of the control parameter or the second value of the control parameter based at least in part on a comparison of the first effect and the second effect; Configuring the glucose control system to provide therapy to the subject during a third therapy period based at least in part on the active control parameter value, the selecting of the active control parameter value modifying the therapy provided to the subject; The computer-implemented method according to clause 49, further comprising. Clause 51. The computer-implemented method according to clause 49, wherein the first therapy comprises a plurality of instances of therapy administered over the first therapy period. Clause 52. The computer-implemented method according to clause 49, wherein the control parameter used by the control algorithm corresponds to the time until insulin in the subject's blood reaches a specific concentration level due to the administration of an insulin dose. Clause 53. A computer-implemented method for modifying a therapy provided to a subject using a blood glucose control system, the method comprising: by a hardware processor configured to generate a dosage control signal for the blood glucose control system, causing the blood glucose control system to deliver a first therapy to the subject during a first therapy period wherein the first therapy is delivered based at least in part on a first value of a control parameter used by a control algorithm to generate the dosage control signal; determining a first effect corresponding at least in part to the first therapy, the determining comprising receiving a glucose value signal from a glucose value sensor operably connected to the subject; automatically generating a second value of the control parameter, the automatically generated second value being determined as a function based at least in part on a baseline value; modifying the control parameter from the first value to the second value; causing the blood glucose control system to deliver a second therapy to the subject during a second therapy period, the second therapy being delivered based at least in part on the second value of the control parameter, and modifying the control parameter modifies the therapy provided to the subject; determining a second effect corresponding at least in part to the second therapy; automatically comparing the first effect and the second effect without human action; Based at least in part on the comparison of the first effect and the second effect, selecting one of the first value of the control parameter or the second value of the control parameter as an active control parameter value; Configuring the blood glucose control system to provide therapy to the subject during a third therapy period based at least in part on the active control parameter value, wherein the selection of the active control parameter value modifies the therapy provided to the subject; A method comprising. Clause 54. The computer-implemented method according to clause 53, wherein the second value of the control parameter is based at least in part on blood glucose control indicated by the glucose value signal. Clause 55. The computer-implemented method according to clause 53, wherein the baseline value includes the first value of the control parameter. Clause 56. The computer-implemented method according to clause 53, wherein the first value of the control parameter is determined based at least in part on the baseline value. Clause 57. The computer-implemented method according to clause 53, further comprising performing the comparison of the first effect and the second effect, wherein the comparison is performed substantially in real time in response to the determination of the second effect. Clause 58. The computer-implemented method according to clause 53, further comprising performing the comparison of the first effect and the second effect, wherein the comparison of the first effect and the second effect includes performing a statistical comparison of the first effect and the second effect. Clause 59. The computer-implemented method according to clause 53, further comprising performing the comparison of the first effect and the second effect, wherein the comparison of the first effect and the second effect includes performing at least a regression analysis of the first effect and the second effect. Clause 60. The second value of the control parameter can be selected based on performing a regression analysis between the time when the subcutaneously administered insulin is absorbed into the blood of the subject and the blood glucose control function, where the blood glucose control function is at least partially based on the glucose value signal, the computer-implemented method according to clause 53.

[0243] Term It should be understood that not all objectives or advantages may necessarily be achieved by the specific embodiments described herein. Thus, for example, one of ordinary skill in the art will recognize that a particular embodiment may be configured to operate in a manner that achieves or optimizes one advantage or group of advantages taught herein without necessarily achieving other objectives or advantages that may be taught or suggested herein. will be recognized.

[0244] All processes described herein can be embodied in software code modules executed by a computing system that includes one or more computers or processors and can be fully automated therewith. The code modules can be stored in any type of non-transitory computer-readable medium or other computer storage device. Some or all of the methods can be embodied in dedicated computer hardware. Further, the computing system can include an automated blood glucose system, a portable drug delivery system, or a portable medical device, implemented as part of, or in communication with, them.

[0245] Many variations other than those described in this specification will be apparent from this disclosure. For example, depending on the embodiment, any particular operation, event, or function of the algorithms described herein may be performed in a different order, may be added, may be integrated, or may be completely excluded (e.g., not all of the described operations or events are necessary for the implementation of the algorithm). Further, in certain embodiments, operations or events may be performed concurrently rather than sequentially, for example, via multithreading, interrupt processing, multiple processors or processor cores, or on other parallel architectures. Further, various tasks or processes can be performed by different machines and / or computing systems that can function together.

[0246] The various illustrative logical blocks and modules described in connection with the embodiments disclosed herein can be implemented or executed by a machine such as a processing unit or processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gates or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. The processor can be a microprocessor, but in the alternative, the processor can be a controller, a microcontroller, or a state machine, or combinations thereof. The processor can include an electrical circuit configured to process computer executable instructions. In another embodiment, the processor includes an FPGA or other programmable device that performs logical operations without processing computer executable instructions. The processor can also be implemented as a combination of computing devices, such as, for example, a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in combination with a DSP core, or any other such configuration. Although described primarily in connection with digital technologies herein, the processor can also include primarily analog components. The computing environment can include any type of computer system including, but not limited to, computer systems based on a microprocessor, mainframe computer, digital signal processor, portable computing device, device controller, or computational engine within an appliance.

[0247] Unless specifically stated otherwise, conditional language, such as "can," "could," "might," or "may," among others, is understood within the context in which it is generally used to convey that certain embodiments include certain features, elements, and / or steps, while other embodiments do not. Thus, such conditional language is not generally intended to imply that features, elements, and / or steps are in any way required by one or more embodiments, or that one or more embodiments necessarily include logic for determining, with or without user input or prompts, whether those features, elements, and / or steps are to be included in or performed in any particular embodiment.

[0248] Disjunctive language, such as the phrase "at least one of X, Y, or Z," is not otherwise specified. Unless expressly stated otherwise, it is understood in the context in which it is generally used to state that an item, term, etc. can be either X, Y, or Z, or any combination thereof (e.g., X, Y, and / or Z). Thus, such disjunctive language is not intended to, and should not, generally imply that a particular embodiment requires at least one of X, at least one of Y, or at least one of Z, respectively, to be present.

[0249] Any process illustrations, elements or blocks in the flow diagrams described herein and / or shown in the accompanying drawings should be understood as potentially representing modules, segments or portions of code that include one or more executable instructions for implementing a particular logical function or element in the process. As will be appreciated by those skilled in the art, alternative implementations in which elements or functions may be omitted, performed in a different order than shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, are included within the scope of the embodiments described herein.

[0250] Unless otherwise specified, articles such as "a" or "an" should generally be interpreted as including one or more of the recited items. Thus, phrases such as "a device configured to" shall be taken to include one or more of the recited devices. Such one or more recited devices may also be collectively configured to perform the recited recitation. For example, "a processor configured to perform recitations A, B, and C" may include a first processor configured to perform recitation A that operates with a second processor configured to perform recitations B and C.

[0251] It should be emphasized that many variations and modifications can be made to the above-described embodiments, and its elements should be understood as being among other acceptable examples. All such modifications and variations are intended to be included herein within the scope of the present disclosure.

Claims

1. A computer-implemented method for generating an indicator of total carbohydrate therapy over a period of time in a subject using a drug pump configured to deliver at least insulin therapy, the method comprising: by a hardware processor configured to generate a dosage control signal for the drug pump configured to deliver at least insulin therapy to the subject, receiving a glucose value of the subject; determining that a trigger event has occurred to increase the blood glucose level of the subject, at least in part based on the glucose value, the trigger event including that there is an imminent risk of hypoglycemia in the subject or that there is an episode of hypoglycemia in the subject; determining an amount of an antagonist regulator in response to the imminent risk of hypoglycemia or the episode of hypoglycemia; determining a dosage of carbohydrate therapy, at least in part based on the amount of the antagonist regulator; tracking the determined dosage of carbohydrate therapy over a period including a plurality of hypoglycemia risk events or hypoglycemia episodes to generate an indicator of the total carbohydrate therapy over the period; outputting the indicator of the total carbohydrate therapy; A method comprising the above steps.

2. The computer-implemented method according to claim 1, further comprising providing the amount of the antagonist regulator to the subject in response to the imminent risk of hypoglycemia or the episode of hypoglycemia.

3. The computer-implemented method according to claim 1, further comprising providing the amount of the antagonist regulator to the subject in response to the glucose value meeting or falling below a threshold glucose value.

4. The computer-implemented method according to claim 3, wherein the threshold glucose value is set based on the subject's risk tolerance for hypoglycemia events.

5. The computer-implemented method according to claim 1, wherein the indicator of the total carbohydrate therapy corresponds to a decrease in carbohydrates consumed by the subject.

1.

6. The computer-implemented method according to claim 1, wherein the indicator of the total carbohydrate therapy corresponds to a decrease in carbohydrates achievable by the availability of the antagonist regulator.

7. The computer-implemented method according to claim 1, wherein the indicator of the total carbohydrate therapy corresponds to the amount of the antagonist regulator provided to the subject as a carbohydrate substitute.

8. The computer-implemented method according to claim 1, wherein the indicator of the total carbohydrate therapy includes an indicator of the range of carbohydrates.

9. Determining the dosage of the carbohydrate therapy comprises accessing a mapping between the antagonist regulator and the carbohydrate, and determining the dosage of the carbohydrate therapy based at least in part on the mapping and the amount of the antagonist regulator. The computer-implemented method according to claim 1, comprising.

10. The computer-implemented method according to claim 9, wherein the mapping is based at least in part on the type of the carbohydrate.

11. The computer-implemented method according to claim 9, wherein the mapping is generated based on a clinical comparison between the antagonist regulator and the carbohydrate.

12. The computer-implemented method according to claim 9, wherein the mapping is based at least in part on the physiological characteristics of the subject.

13. The computer-implemented method according to claim 9, wherein the mapping is based at least in part on the type of the antagonist regulator.

14. The computer-implemented method according to claim 9, wherein the mapping includes a mathematical formula associating the antagonist regulator with the carbohydrate.

15. The mapping includes a first mapping when the drug pump includes a biphasic pump configured to deliver an antagonist regulator therapy to the subject, and the mapping includes a second mapping when the drug pump is not configured to deliver the antagonist regulator therapy to the subject. The computer-implemented method according to claim 9.

16. The computer-implemented method according to claim 1, wherein the indicator of the total carbohydrate therapy includes one or more of an indicator of calories, an indicator of carbohydrates, an indicator of sugar measurements, an indicator of the amount of food, or an indicator of the weight of the subject resulting from the carbohydrate therapy.

17. An automatic blood glucose control system configured to generate an indicator of total carbohydrate therapy over a period of time in a subject, the automatic blood glucose control system comprising a drug delivery interface configured to operably connect to a drug pump configured to inject a drug into the subject, the drug including at least insulin, the drug delivery interface, and a memory configured to store specific computer-executable instructions, and a hardware processor in communication with the memory, the hardware processor executing the specific computer-executable instructions to at least Receiving the glucose value of the subject; Determining that a trigger event has occurred to increase the blood glucose value of the subject, at least partially based on the glucose value, wherein the trigger event includes the presence of an imminent risk of hypoglycemia in the subject or the presence of an episode of hypoglycemia in the subject; Determining the amount of the counterregulatory agent in response to the imminent risk of hypoglycemia or the episode of hypoglycemia; Determining the dosage of the glucotherapeutic agent at least partially based on the amount of the counterregulatory agent; Tracking the determined dosage of the glucotherapeutic agent over a period including a plurality of hypoglycemia risk events or hypoglycemia episodes to generate an indicator of the total glucotherapeutic agent over the period; Outputting the indicator of the total glucotherapeutic agent; A hardware processor configured to perform the above; An automatic blood glucose control system including the above.

18. The automatic blood glucose control system according to claim 17, wherein the hardware processor is further configured to operate a control algorithm for automatically generating a counterregulatory agent dosing signal configured to operate the drug pump to control the blood glucose value in the subject, at least partially based on a glucose value signal received from a glucose value sensor operably connected to the subject, indicating that the glucose value does not meet a threshold corresponding to the trigger event.

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