Meal and correction bolus size adjustment based on rate of change of blood glucose

Abstract

A system, method, and computer readable medium product are disclosed that provide bolus dose calculations through a control algorithm based medication delivery system that provides automatic delivery of medication, such as insulin, based on sensor input. Blood glucose measurements can be received from a sensor at regular time intervals. Using the blood glucose measurements, a control algorithm can perform various calculations and determinations to provide an appropriate bolus dose. The appropriate bolus dose can be used to respond to trends in a blood glucose measurement trajectory. In addition, the bolus dose can also be determined by the disclosed devices, systems, methods, and / or computer readable medium products in response to an indication by a user that a meal has been consumed.

Description

Technical Field

[0001] The described example provides a feature for drug delivery systems that takes into account the rate of change in blood glucose measurements.

[0002] Related applications

[0003] This application claims priority to U.S. Patent Application Serial No. 16 / 570,125, filed September 13, 2019, entitled "BLOOD GLUCOSE RATE OF CHANGEMODULATION OF MEAL AND CORRECTION INSULIN BOLUS QUANTITY". The contents of the above application are incorporated herein by reference in their entirety. Background Technology

[0004] Medication or therapeutic delivery systems typically deliver medications or therapeutics to users based on their health status. However, due to the complexity and dynamism of the body's response to insulin, it is not uncommon for patients to end up in a state of hypoglycemia or hyperglycemia after providing themselves with a meal or corrective bolus. This outcome is undesirable for many reasons: hypoglycemia carries an immediate risk of serious medical events (seizures, coma, death), while hyperglycemia carries long-term negative health effects and a risk of ketoacidosis. Whether a patient ends up with hypoglycemia, hyperglycemia, or within the range after a bolus depends on many factors, including the rate and direction of your blood glucose changes. If patients use a typical finger prick test to assess their blood glucose, they typically do not have information on the rate of change of blood glucose due to the infrequent nature of the test. If patients wear a continuous glucose monitor (CGM), they usually have enough data to obtain an accurate value for the rate of change of blood glucose. However, due to the lag time between 1) the body's interstitial fluid response to blood glucose changes, 2) the CGM providing the blood glucose value, and 3) the patient's use of the data to determine the insulin dosage, there can be a significant difference between the CGM blood glucose value that the patient uses to calculate their insulin treatment and the patient's actual blood glucose value. This difference can lead to either hypoglycemia or hyperglycemia in patients after insulin therapy, depending on the magnitude and direction of the rate of change in blood glucose. Of the two, hypoglycemia is considered the less desirable and more dangerous outcome.

[0005] Systems that apply a percentage increase / decrease to the final insulin dose based on the rate of change are available. These systems allocate an additional (or reduced) percentage, such as plus or minus 30%, of insulin based on the patient's rate of change in blood glucose. While this has proven effective, full regulation remains suboptimal and ineffective for corrective boluses, particularly those taken to compensate for dietary expenditure. Therefore, there is a need to provide more effective corrective bolus doses that can result in a reduction in the amount of time a patient may be in a state of hypoglycemia. Summary of the Invention

[0006] Disclosed is an example of a non-transitory computer-readable medium implemented with processor-executable programming code. The processor, when executing the programming code, is operable to perform functions including receiving multiple blood glucose measurements over a period of time. A corrected bolus dose can be calculated based on the latest of the multiple blood glucose measurements. The rate of change of blood glucose values ​​can be determined based on the multiple blood glucose measurements over a period of time. The determined rate of change and the latest blood glucose measurement can be used to calculate the corrected bolus dose. Functions can be applied to the corrected bolus dose and the corrected bolus dose, and based on the output from the function, a final insulin value can be determined. The determined final insulin value can be used to set the insulin bolus dose, and insulin delivery can be initiated based on the set insulin bolus dose.

[0007] A device including a processor, memory, and transceiver is disclosed. The processor, when performing artificial pancreas application, is operable to control insulin delivery and perform functions. These functions include acquiring multiple blood glucose measurements. The processor calculates a corrected bolus dose based on the latest blood glucose measurement among the multiple measurements. The rate of change of blood glucose values ​​can be determined based on the multiple blood glucose measurements over a period of time. The determined rate of change and the latest blood glucose measurement can be used to calculate the corrected bolus dose. Functions can be applied to both the corrected bolus dose and the corrected bolus dose. The final insulin value can be determined based on the output from the functions.

[0008] A method is disclosed that includes receiving multiple blood glucose measurements over a period of time. A processor can determine the corrected insulin bolus dose required by the user based on an evaluation of the multiple blood glucose measurements. The final insulin value for the corrected bolus dose can be obtained based on the output of a function. The function generates its output using a selected blood glucose measurement from the multiple measurements, the user's target blood glucose value, and an insulin regulation factor. The insulin bolus dose can be set based on the obtained final insulin value, and insulin delivery can be initiated according to the set insulin bolus dose. Attached Figure Description

[0009] Figure 1 A flowchart is shown as an example procedure for determining the bolus injection dose used to correct blood glucose levels.

[0010] Figure 2 A functional block diagram of a drug delivery system suitable for implementing the example processes and techniques described herein is shown.

[0011] Figure 3 The diagram illustrates a flowchart of an example process for determining the bolus dose to be administered in response to dietary consumption.

[0012] Figure 4The diagram illustrates another example of a process for determining the bolus injection dose used to correct blood glucose levels.

[0013] Figure 5 The diagram illustrates the methods used to obtain final insulin values, such as... Figure 4 The flowchart shows an example sub-process for calculating the final insulin value.

[0014] Figure 6A and Figure 6B The diagram illustrates a flowchart of another example sub-process used to obtain the final insulin value.

[0015] Figure 7 The diagram illustrates a flowchart of another example sub-process used to obtain the final insulin value. Detailed Implementation

[0016] Various examples provide methods, systems, devices, and computer-readable media for reducing the risk of hypoglycemia by taking into account the rate of change in glucose. For example, there may be a potential delay of several minutes or tens of minutes between an individual's actual blood glucose status relative to a blood glucose measurement output by a CGM and the time when the patient will administer a bolus injection based on the blood glucose measurement output by the CGM. In the disclosed examples, the delay between the individual's actual blood glucose status and the patient's bolus time can be considered as optimizing treatment. For example, the current blood glucose value received from the CGM can be forward-predicted, assuming a constant rate of change over certain minutes. This predicted blood glucose value can be used to calculate the bolus determination (time and amount).

[0017] The example provides a process that can be used with any additional algorithm or computer application that manages blood glucose levels and insulin therapy. Such an algorithm can be referred to as a system based on an "artificial pancreas" algorithm, or more generally, an artificial pancreas (AP) application that provides automated insulin delivery based on blood glucose sensor input received from sources such as the CGM. In the example, the artificial pancreas (AP) application, when executed by a processor, enables the system to monitor the user's glucose levels, determine the appropriate insulin level for the user based on the monitored glucose levels (e.g., blood glucose concentration or blood glucose measurement) and other information, such as information provided by the user, such as carbohydrate intake, exercise time, meal time, etc., and take actions to maintain the user's blood glucose levels within an appropriate range. An appropriate range of blood glucose levels can be considered a target blood glucose level for a particular user. For example, if the target blood glucose level falls within the range of 80 mg / dL to 120 mg / dL, which is the range that meets the clinical care standards for diabetes treatment, then that target blood glucose level can be considered acceptable. However, the AP application described herein can be able to establish a more precise target blood glucose level and can set the target blood glucose level, for example, 110 mg / dL, etc. See references. Figure 1-7As illustrated in more detail, an AP application can use monitored blood glucose levels and other information to generate commands and send those commands to medical devices, including, for example, pumps, to control the delivery of insulin bolus doses to the user, change the amount or timing of future doses, and control other functions.

[0018] Figure 1 A flowchart is shown for a process of determining a bolus injection dose for correcting blood glucose levels. Process 100 can be implemented by programming code executed by a processor. For example, the processor, when executing the programming code, can operate to perform various functions. These functions may include obtaining multiple blood glucose measurements (110). For example, this may be achieved over a period of time via a wireless signal (not shown in this example - see reference). Figure 2 The example (described in more detail by hardware and system components) receives multiple blood glucose measurements from a CGM or another device. This time interval can be approximately every 5 minutes, every minute, or some other time increment. Furthermore, a single blood glucose measurement among the multiple measurements can be received very shortly after being measured, for example, almost instantaneously, or can be transmitted in batches of two or more, etc. The processor can process each of the multiple blood glucose measurements. Based on the blood glucose measurements among the multiple blood glucose measurements, a corrected bolus dose (120) can be calculated. For example, the blood glucose measurement among the multiple blood glucose measurements used to calculate the corrected bolus dose could be the most recent blood glucose measurement. In this example, the most recent blood glucose measurement is the last blood glucose measurement received by the processor, which could be the most recent blood glucose measurement. Alternatively, any blood glucose measurement from multiple blood glucose measurements can be selected for calculating the corrected bolus dose.

[0019]

[0020] The corrected bolus dose, as shown in Equation 1, can be calculated by determining the difference between the most recent (or selected) blood glucose measurement and the target blood glucose value. The target blood glucose value can be considered as a standard of care for a specific patient, a standard of care for a large number of diabetic patients, or a specific patient's desired glucose concentration preference. In some examples, to account for a particular user's ability to manage insulin, an insulin sensitivity factor (ISF) (e.g., through multiplication, subtraction, division, and / or other mathematical operations) can be applied to the determined difference to provide a personalized insulin value. In Equation 1, the ISF is the divisor of the difference between the most recent blood glucose measurement and the target blood glucose value and can be considered as a parameter indicating how much the user's measured blood glucose value decreases per unit of insulin. In the examples, the ISF can be personalized for each user and calculated based on the corresponding clinical values ​​determined according to the user's diabetes (or other disease) treatment plan.

[0021] Personalized insulin values ​​(i.e., ((CGM - target) / ISF)) can be further modified by applying the insulin regulatory factor (IAF) to personalized insulin values ​​to generate a corrected bolus dose. In the examples, the IAF value can range from approximately 0.30 to approximately 0.70. Of course, other ranges of IAF, such as 0.25–0.65, can be used. In some examples, the corrected bolus dose can be constrained at an upper limit by a recommended bolus dose modified by the IAF, which is proportional to the trajectory of multiple blood glucose measurements. Another constraint could be that if the blood glucose trajectory remains substantially constant over approximately 25 minutes (i.e., 5 blood glucose measurement cycles of CGM), the recommended bolus dose cannot exceed what is needed to achieve the target blood glucose level.

[0022] The rate of change (RoC) of blood glucose values ​​can be determined based on multiple blood glucose measurements over a period of time (130). For example, the rate of change of blood glucose measurements can be derived from the slope. In other examples, a function fitted to a curve over time for each corresponding blood glucose measurement can be determined and used to determine the rate of change. Alternatively, the rate of change of blood glucose values ​​can be measured directly using CGM.

[0023] At point 140, the processor can use a determined rate of change and the latest blood glucose measurement to calculate a corrected bolus dose. The rate of change can be multiplied by a time parameter to determine the revised latest blood glucose measurement. For example, the processor can access a table of time parameters stored in memory. The time parameter can be selected from the table based on the predicted user response time to a dose of insulin, such as one unit, two units, etc. The time parameter (e.g., as a multiplier) can be applied to the determined rate of change to generate the predicted blood glucose measurement (i.e., (RoC) x T = predicted blood glucose measurement). The processor can use the latest blood glucose measurement and the predicted blood glucose measurement to obtain the latest blood glucose measurement. For example, the processor can obtain the latest blood glucose measurement from memory coupled to the processor, the CGM, or via another external device such as a smart accessory device. The predicted blood glucose measurement can be added to the latest blood glucose measurement (CGM) value (e.g., CGM + (RoC) x T) to obtain the revised latest blood glucose measurement. The time parameter T can be in minutes, such as 5 minutes, 15 minutes, 16 minutes, 25 minutes, etc. The processor can retrieve the user's target blood glucose value (i.e., Target) from memory coupled to the processor. The difference between the target blood glucose value and the latest modified blood glucose measurement can be determined. An insulin sensitivity factor (ISF) (as a divisor or fractional multiplier) can be applied to the determined difference to produce a corrected bolus dose, as shown in equation (Equation 2) below, which can be implemented in the programming code.

[0024]

[0025] The function can be applied to correct the bolus dose and the modified bolus dose (150). For example, the function can be a minimal function that can be operated to find the minimum value of the function's input, as shown in Equation 3 (Equation 3).

[0026] Equation 3 Output = min(corrected bolus dose, corrected bolus dose)

[0027] In this example, the input to the minimum function can be the corrected bolus dose and the adjusted bolus dose, and at 160, the output from the function, such as the output shown in Equation 3, can be used to determine the final insulin value. The final insulin value can be the volume of insulin, the amount of insulin (in insulin units), etc.

[0028] The processor can determine the final insulin value and perform further processing. For example, the determined final insulin value can be used to set the insulin bolus dose (170). In response to setting the insulin bolus dose, the processor can initiate insulin delivery (180) based on the set insulin bolus dose. As described with respect to another example, the processor can initiate insulin delivery based on the set insulin bolus dose, for example, by outputting a signal indicating the set insulin bolus dose to be received by the pump mechanism. In response to the received signal, the pump mechanism can operate to deliver the bolus dose according to the set insulin bolus dose.

[0029] Discussion can achieve Figure 1 An example of a drug delivery system process may be helpful. Figure 2 An example of a drug delivery system 200 is illustrated.

[0030] The drug delivery system 200 is operable to enable an AP (Advanced Patient Admin) application, which includes determining an injection dose, outputting an indication of the determined injection dose, and initiating insulin injection delivery based on the indicated injection dose. The drug delivery system 200 can be an automated drug delivery system that may include a medical device (pump) 202, a sensor 204, and a management device (PDM) 206. In this example, the system 200 may also include a smart accessory device 207 that can communicate with other components of the system 200 via a wired or wireless communication link.

[0031] In the example, medical device 202 can be attached to the body of a user (such as a patient or diabetic patient) and can deliver any therapeutic agent to the user, including any medication or drug, such as insulin. For example, medical device 202 can be a wearable device worn by the user. For example, medical device 202 can be directly coupled to the user (e.g., directly attached to a part of the user's body and / or skin via an adhesive). In the example, the surface of medical device 202 may include an adhesive to facilitate attachment to the user.

[0032] Medical device 202 may include multiple components to facilitate the automated delivery of medications (also known as therapeutic agents) to a user. Medical device 202 may be operable to store medications and deliver them to the user. Medical device 202 is commonly referred to as a pump or insulin pump, referring to the operation of discharging medication from reservoir 225 for delivery to the user. While these examples relate to reservoir 225 storing insulin, reservoir 225 may be operable to store other medications or therapeutic agents suitable for automated delivery, such as morphine.

[0033] In various examples, medical device 202 may be an automated, wearable insulin delivery device. For example, medical device 202 may include a reservoir 225 for storing a drug (such as insulin), a needle or cannula (not shown) for delivering the drug into the user's body (subcutaneously, intraperitoneally, or intravenously), and a pump mechanism (mechanical) 224, or other actuation mechanism, for transferring the drug from the reservoir 225 to the user's body via the needle or cannula (not shown). Pump mechanism 224 may be fluidly coupled to reservoir 225 and communicatively coupled to processor 221. Medical device 202 may also include a power source 228, such as a battery, piezoelectric device, etc., for supplying power to pump mechanism 224 and / or other components (such as processor 221, memory 223, and communication device 226). Although not shown, a power source for supplying power may similarly be included in each of sensor 204, smart accessory device 207, and management device (PDM) 206.

[0034] The blood glucose sensor 204 may be a device communicatively coupled to the processor 261 or 221 and operable to measure blood glucose values ​​at predetermined time intervals (e.g., every 5 minutes). The blood glucose sensor 204 may provide multiple blood glucose measurements to an AP application operating on the corresponding device.

[0035] Medical device 202 can provide insulin stored in storage 225 to a user based on information provided by sensor 204 and / or management device (PDM) 206 (e.g., blood glucose measurement). For example, medical device 202 may include analog and / or digital circuitry that can be implemented as a processor 221 (or controller) for controlling drug or therapeutic agent delivery. The circuitry used to implement processor 221 may include discrete dedicated logic and / or components, application-specific integrated circuits, executing software instructions, firmware, programming instructions or programming code stored in memory 223 (e.g., enabling artificial pancreas application (AP application) 229 and...). Figure 1 and Figure 3 The process example is a microcontroller or processor, or any combination thereof. For example, processor 221 may execute control algorithms, such as artificial pancreas application 229, and other programming code that may enable processor 221 to operate such that the pump delivers a dose of medication or therapeutic agent to the user at predetermined intervals or as needed to achieve a target blood glucose level. The dose size and / or timing may be programmed by the user or a third party (such as a healthcare provider, medical device manufacturer, etc.) using a wired or wireless link (such as 220) between medical device 202 and management device 206 or other devices (such as a computing device at a healthcare provider facility). In the example, the pump or medical device 202 is communicatively coupled to processor 261 of the management device via wireless link 220 or via a wireless link (such as 291 from smart accessory device 207 or 208 from sensor 204). The pump mechanism 224 of the medical device may be operable to receive an actuation signal from processor 261 and, in response to receiving the actuation signal, dispense insulin from reservoir 225 according to a set insulin bolus dose.

[0036] Other devices in system 200, such as management device 206, smart accessory device 207, and sensor 204, may also be operable to perform various functions, including controlling medical device 202. For example, management device 206 may include communication device 264, processor 261, and management device memory 263. Management device memory 263 may store instances of AP application 269, including programming code, which provides a reference when executed by processor 261. Figure 1 and Figure 3 The example describes a process example. The management device memory 263 can also store information for providing reference. Figure 1 and Figure 3-7 The example describes the process of programming code.

[0037] Smart accessory device 207 can be, for example, Apple Other wearable smart devices from other manufacturers include glasses, GPS-enabled wearable devices, wearable fitness equipment, smart clothing, etc. Similar to management device 206, smart accessory device 207 can also be operated to perform various functions, including controlling medical device 202. For example, smart accessory device 207 may include communication device 274, processor 271, and memory 273. Memory 273 may store instances of AP application 279, including those for providing reference... Figure 1 and Figure 3-7 The example describes the programming code for the process example. Memory 273 can also serve as a storage for programming code and is operable to store data related to AP application 279. Sensor 204 of system 200 can be a continuous glucose monitor (CGM) as described above, which may include processor 241, memory 243, sensing or measuring device 244, and communication device 246. Memory 243 can store instances of AP application 249 and other programming code and is operable to store data related to AP application 249. AP application 249 may also include features for providing reference... Figure 1 and Figure 3-7 The example describes the process of programming code.

[0038] Instructions for determining the delivery of a drug or therapeutic agent to a user (e.g., as a bolus dose) (e.g., the size and / or timing of any dose of the drug or therapeutic agent) can originate from the local medical device 202 or can originate from a remote location and be provided to the medical device 202. In the example of determining the delivery of the drug or therapeutic agent locally, programming instructions for an instance such as an artificial pancreas application 229 stored in memory 223 coupled to the medical device 202 can be used to make the determination by the medical device 202. Furthermore, the medical device 202 can be operable to communicate with a cloud-based service 211 via communication device 226 and communication link 288.

[0039] Alternatively, remote commands can be provided to the medical device 202 via a wired or wireless link by a management device (PDM) 206 or an intelligent assistive device 207. The management device (PDM) 206 has a processor 261 that executes instances of the artificial pancreas application 269, and the intelligent assistive device 207 has a processor 271 that executes instances of the artificial pancreas application 269, as well as additional programming code for controlling various devices such as the medical device 202, the intelligent assistive device 207, and / or the sensor 204. The medical device 202 can execute any received commands (originating internally or from the management device 206) to deliver medication or therapeutic agents to the user. In this way, medication or therapeutic agents can be delivered to the user automatically.

[0040] In various examples, medical device 202 can communicate with management device 206 via wireless link 220. Management device 206 can be an electronic device, such as, for example, a smartphone, tablet, dedicated diabetes treatment management device, etc. Management device 206 can be a wearable wireless accessory device. Wireless links 208, 220, 222, 291, 292, and 293 can be any type of wireless link provided by any known wireless standard. As an example, wireless links 208, 220, 222, 291, 292, and 293 can enable communication between medical device 202, management device 206, and sensor 204 based on, for example... Communication using near-field communication standards, cellular standards, or any other wireless optical or radio frequency protocols.

[0041] Sensor 204 may be a glucose sensor operable to measure blood glucose and output a blood glucose value or data representing a blood glucose value. For example, sensor 204 may be a glucose monitor or a continuous glucose monitor (CGM). Sensor 204 may include a processor 241, a memory 243, a sensing / measuring device 244, and a communication device 246. The communication device 246 of sensor 204 may include one or more sensing elements, electronic transmitters, receivers, and / or transceivers for communicating with management device 206 via wireless link 222 or with medical device 202 via link 208. Sensing / measuring device 244 may include one or more sensing elements, such as glucose measurement, heart rate monitors, etc. Processor 241 may include discrete dedicated logic and / or components, application-specific integrated circuits, microcontrollers or processors that execute software instructions, firmware, programming instructions stored in memory (such as memory 243), or any combination thereof. For example, memory 243 may store instances of AP applications 249 executable by processor 241.

[0042] Although sensor 204 is depicted as separate from medical device 202, in various examples, sensor 204 and medical device 202 may be incorporated into the same unit. That is, in various examples, sensor 204 may be part of medical device 202 and contained within the same housing as medical device 202 (e.g., sensor 204 may be located within or embedded in medical device 202). Glucose monitoring data (e.g., measured blood glucose values) determined by sensor 204 may be provided to medical device 202, smart accessory device 207, and / or management device 206, and may be used to determine the insulin bolus dose for automated delivery of insulin by medical device 202.

[0043] Sensor 204 can also be coupled to a user via, for example, an adhesive, and can provide information or data about one or more medical conditions and / or physical attributes of the user. The information or data provided by sensor 204 can be used to regulate the drug delivery operation of medical device 202.

[0044] In the example, management device 206 may be a personal diabetes manager. Management device 206 may be used to program or regulate the operation of medical device 202 and / or sensor 204. Management device 206 may be any portable electronic device, including, for example, a dedicated controller such as processor 261, a smartphone, or a tablet. In the example, management device (PDM) 206 may include processor 261, management device memory 263, and communication device 264. Management device 206 may contain analog and / or digital circuitry, which may be implemented as processor 261 (or controller) for performing processes to manage a user's blood glucose levels and for controlling the delivery of medications or therapeutic agents to the user. Processor 261 may also be operable to execute programming code stored in management device memory 263. For example, management device memory 263 may be operable to store an artificial pancreas application 269 that can be executed by processor 261. Processor 261 may be operable to perform various functions when executing artificial pancreas application 269, such as regarding... Figure 1 and Figure 3 The functions described in the examples are as follows. Communication device 264 may be a receiver, transmitter, or transceiver operating according to one or more radio frequency protocols. For example, communication device 264 may include a cellular transceiver and a Bluetooth transceiver, which enables management device 206 to communicate with a data network via the cellular transceiver and with sensor 204 and medical device 202. Each transceiver of communication device 264 may be operable to transmit signals containing information that can be used or generated by an AP application, etc. Communication devices 226, 246, and 276 of each medical device 202, sensor 204, and smart accessory device 207 may also be operable to transmit signals containing information that can be used or generated by an AP application, etc.

[0045] Medical device 202 can communicate with sensor 204 via wireless link 208 and with management device 206 via wireless link 220. Sensor 204 and management device 206 can communicate via wireless link 222. Smart accessory device 207, when present, can communicate with medical device 202, sensor 204, and management device 206 via wireless links 291, 292, and 293 respectively. Wireless links 208, 220, 222, 291, 292, and 293 can be any type of wireless link operating using known wireless standards or proprietary standards. As an example, wireless links 208, 220, 222, 291, 292, and 293 can provide communication via various communication devices 226, 246, and 264. A communication link using Wi-Fi, near-field communication standards, cellular standards, or any other wireless protocol. In some examples, medical device 202 and / or management device 206 may include user interfaces 227 and 268, respectively, such as a keyboard, touchscreen display, joystick, button, microphone, speaker, monitor, etc., operable to allow user input of information and allow management device output of information to be presented to the user.

[0046] In various examples, drug delivery system 200 may be an insulin drug delivery system. In various examples, medical device 202 may be as described in U.S. Patent Nos. 7,303,549, 7,137,964, or 6,740,059. (Insulet Corporation, Billerica, MA) Insulin delivery devices, each of which is incorporated herein by reference in its entirety.

[0047] In various examples, the drug delivery system 200 may implement an artificial pancreas (AP) algorithm (and / or provide AP functionality) to manage or control the automatic delivery of insulin to a user (e.g., to maintain normal blood glucose levels—normal levels of glucose in the blood). The AP application may be implemented by the medical device 202 and / or sensor 204. The AP application may be used to determine the timing and dosage of insulin delivery. In various examples, the AP application may determine the timing and dosage based on known information about the user (such as the user's gender, age, weight, or height) and / or information about the user's physical attributes or condition collected (e.g., from sensor 204). For example, the AP application may determine appropriate insulin delivery based on monitoring the user's glucose levels via sensor 204. The AP application may also allow the user to adjust insulin delivery. For example, the AP application may allow the user to issue commands to the medical device 202 (e.g., via input), such as a command to deliver an insulin bolus. In some examples, the different functions of the AP application may be distributed across two or more of the management device 206, the medical device (pump) 202, or the sensor 204. In other examples, different functions of the AP application may be performed by a single device, such as management device 206, medical device (pump) 202, or sensor 204. In various examples, drug delivery system 200 may operate, or may include, the features or functions of a drug delivery system described in U.S. Patent Application No. 15 / 359,187, filed November 22, 2016, which is incorporated herein by reference in its entirety.

[0048] As described herein, drug delivery system 200 or any component thereof, such as a medical device, can be considered as providing AP functionality or implementing AP applications. Therefore, for convenience, references to AP applications (e.g., their functionality, operation, or capabilities) are used, and may refer to and / or include the operation and / or functionality of drug delivery system 200 or any of its constituent components (e.g., medical device 202 and / or management device 206). Drug delivery system 200—for example, as an insulin delivery system implementing AP applications—can be considered as a drug delivery system or an AP-based delivery system using sensor inputs (e.g., data collected by sensor 204).

[0049] In the example, one or more of devices 202, 204, 206, or 207 may be operable to communicate with cloud-based service 211 via wireless communication link 288. Cloud-based service 211 may utilize a server and data storage device (not shown). Communication link 288 may be a cellular link, Wi-Fi link, Bluetooth link, or a combination thereof established between the various devices 202, 204, 206, or 207 of system 200. The data storage device provided by cloud-based service 211 may store anonymized data, such as user weight, blood glucose measurements, age, dietary carbohydrate information, etc. Furthermore, cloud-based service 211 can process anonymized data from multiple users to provide general information related to various parameters used by AP applications. For example, a general age-based target blood glucose value can be derived from the anonymized data, which is helpful when a user first starts using a system such as 200. Cloud-based service 211 may also provide processing services to system 200, such as performing… Figure 2 The example process 100 or additional processes, such as those in the reference below. Figure 3 The processes described.

[0050] In the example, device 202 includes a communication device 264, which, as described above, may be a receiver, transmitter, or transceiver operating according to one or more radio frequency protocols (such as Bluetooth, Wi-Fi, near-field communication standards, cellular standards), enabling the respective device to communicate with the cloud-based service 211. For example, the output from sensor 204 or medical device (pump) 202 may be transmitted via the transceiver of communication device 264 to the cloud-based service 211 for storage or processing. Similarly, medical device 202, management device 206, and sensor 204 may be operable to communicate with the cloud-based service 211 via communication link 288.

[0051] In the example, a corresponding receiver or transceiver of each of the respective devices 202, 206, or 207 may be operable to receive a signal containing multiple blood glucose measurements that can be transmitted by sensor 204. A corresponding processor of each of the respective devices 202, 206, or 207 may be operable to store each of the corresponding blood glucose measurements in a corresponding memory, such as 223, 263, or 273. The corresponding blood glucose measurements may be stored as data associated with an artificial pancreas algorithm (such as 229, 249, 269, or 279). In another example, an AP application operating on any of the management device 206, the smart accessory device 207, or the sensor 204 may be operable to transmit control signals received by the medical device via a transceiver implemented by the respective communication devices 264, 274, or 246. In the example, the control signal may indicate the amount of insulin to be dispensed by the medical device 202.

[0052] This document describes various operational scenarios and examples of the processes executed by system 200. For example, system 200 can be operated to achieve... Figure 1 Example of the process. Furthermore, system 200 can be operated to implement a process that takes into account dietary correction injections. Figure 3 The illustration shows an example of a procedure for determining the dosage of a dietary correction bolus. Procedure 300 can be considered as... Figure 1 A specific implementation of process 100 is used during meals and to administer a dietary correction bolus to the user. In example process 300, a processor, such as... Figure 2 Examples 221 or 261 in the example can be operable to execute programming code to perform different functions, including determining whether to output an instruction for a dietary bolus or an instruction for a corrective bolus. Process 300 is similar to process 100 but has added parameters that take into account the amount of carbohydrates consumed by the user and the user's insulin-to-carbohydrate ratio. In process 300, a processor such as 221 or 261 can determine at 310 to deliver a dietary bolus. Consuming carbohydrates increases the user's blood glucose levels. A dietary bolus can be delivered to counteract the effects of carbohydrate intake. For example, the user may be about to consume or may have already consumed a meal, and this can be done via a user interface (such as 268, 227, or 278). Figure 2 The PDM 206, medical device 202, or smart accessory device 278 provides input indicating that a meal is about to be completed or has been completed. This indication can be used to determine when a meal booster should be delivered. For example, the processor can receive information indicating that a meal booster may be needed, such as a meal booster request input from the user, a scheduled meal time, calendar messages, GPS / Wi-Fi location determination, etc. Typically, a meal booster is administered when a meal is consumed to counteract the effects of additional carbohydrates.

[0053] At 320, in response to determining that a dietary recommendation needs to be delivered, the amount of carbohydrates can be retrieved. The amount of carbohydrates can be the expected amount of carbohydrates to be consumed (a value provided before eating), the actual amount of carbohydrates consumed (from a nutrition label on packaging, etc.), or the estimated amount of carbohydrates consumed (a value provided after eating), entered into system 200 by the user or someone familiar with the user's diet (e.g., a nutritionist, healthcare provider), etc. The amount of carbohydrates can also be received from cloud-based service 211 in response to a list of foods and approximate portion sizes entered by the user, the name of the meal offered by a restaurant participating in the service provided by the cloud-based service, etc.

[0054] At 330, the processor can retrieve the insulin-to-carbohydrate ratio (ICR) value (e.g., grams per unit of insulin) representing the number of grams of carbohydrates and the number of insulin units. The ICR value can be stored in memory, such as... Figure 2 The corresponding devices 202, 204, 206, and 207 are 223, 243, 263, or 273. The ICR can be updated according to settings in the AP application. For example, the ICR can be updated with each blood glucose measurement reported to the AP application by sensor 204, or it can be updated daily using multiple blood glucose measurements by the corresponding processor executing the AP application in any of the medical device 202, management device 206, or smart accessory device 207. The AP application can generate dietary parameters (340) using the retrieved amount of carbohydrates and the insulin-to-carbohydrate ratio. For example, the AP application can be operable to calculate dietary parameters using, for example, the amount of carbohydrates (CHO) in grams divided by the ICR to derive dietary parameters with multiple insulin units as values.

[0055] At 350, the processor-executed AP application can generate a diet-corrected bolus dose for insulin pump devices (such as CGMs) by dividing the difference between the blood glucose measurement from the CGM and the target blood glucose value by the ISF, adding the dietary parameters and the difference, and multiplying the sum of the dietary parameters and the difference by the user's IAF. Figure 2 The output of the medical device 202 is shown in Equation 4 below.

[0056]

[0057] An AP application executed by a processor can generate a dietary-corrected bolus dose (360) by adding dietary parameters to a corrected bolus dose. For example, an AP application executed by a processor can generate a dietary-corrected bolus dose by adding dietary parameters to a corrected bolus dose (as referenced above). Figure 1 The above) is used to generate a dietary-modified bolus dose for use by insulin pump devices (such as, Figure 2 The output of the medical device 202 is shown in Equation 5 below.

[0058]

[0059] In addition to the dietary corrected bolus dose being used in place of the corrected bolus dose and the dietary modified bolus dose being used in place of the modified bolus dose to determine the minimum, the function in step 150 of process 100 is also applied to determine the dietary bolus dose, as shown in Equation 6 below (370).

[0060] Equation 6 Output = min(Dietary Corrected Injection Dose, Dietary Corrected Injection Dose)

[0061] Based on the dietary bolus dose output from the function in Equation 6, the insulin bolus dose setting is equal to the dietary bolus dose (380). In response to a control signal generated by the AP application based on the set insulin bolus dose, the medical device 202 can administer an insulin bolus to the user.

[0062] In the foregoing example, the calculation of the corrected bolus or dietary corrected bolus dose is described as being included in the programming code of the AP application. However, the foregoing example can be implemented as additional programming for use in applications from different service providers that deliver functionality similar to the AP application described herein.

[0063] Additional methods for calculating insulin bolus injections are also disclosed. For example, procedures that include specific modifications to the general procedure are disclosed. Figure 4 An example of a general process is shown in the figure. Figure 4 The process 400 includes receiving multiple blood glucose measurements over a period of time at 415. As mentioned, the multiple blood glucose measurements can be taken by the CGM over a period of time. For example, a sensor, such as 204, can measure the user's blood glucose every 5 minutes for several days (e.g., until the sensor's power is depleted) and provide the results to an AP application running on a medical device or management device.

[0064] A processor on a medical device or management device can determine the corrected insulin bolus dose required by a user based on an assessment of multiple blood glucose measurements (415). In the example, the medical device processor can determine the corrected insulin bolus dose required by a user based on an assessment of multiple blood glucose measurements (425). For example, the processor can be operable to access information from a data storage device, which may be, for example, a memory coupled to the processor, other devices in the system, such as sensors, medical devices, smart accessory devices, management devices, cloud-based services, etc. Alternatively or additionally, the processor can be operable to compute or derive information that can be used to determine the corrected bolus dose. In the example, the processor can apply a function to multiple blood glucose measurements selected from multiple blood glucose measurements, the user's target blood glucose value, and an insulin regulator. At 435, the processor can obtain the final insulin value for the corrected bolus dose based on the output of the function. The final insulin value may be the volume of insulin used to determine the insulin bolus dose, the amount of insulin (in units of insulin), etc. For example, the insulin bolus dose can be set based on the obtained final insulin value (445). At 455, insulin delivery can be initiated according to the set insulin bolus dose. For example, processor 221 can generate a control signal that is applied to pump mechanism 224 to dispense a certain amount of insulin according to a set insulin bolus dose.

[0065] The step of obtaining the final insulin value at 435 can be performed using different process examples. Figure 5 The diagram illustrates a flowchart of an example sub-process for obtaining a final insulin value, which can be performed by a processor application process. Process 500 can be implemented via, for example, programming code as part of an AP application, that enables the processor to calculate the difference between a selected blood glucose measurement and the user's target blood glucose value (510). The processor can determine which of the calculated difference or the maximum corrected blood glucose value is the lower blood glucose value (520). At 530, when the lower blood glucose value is determined, an insulin regulator can be applied to the lower blood glucose value. The result of applying the insulin regulator to the lower blood glucose value can be output (540).

[0066] Alternatively, in Figure 6A and Figure 6B In another example shown, the step of obtaining the final insulin value at 435 can be performed by the processor executing programming code that enables the processor to perform the functions of process 600. For example, at 610, the processor can calculate the difference between the selected blood glucose measurement and the user's target blood glucose value. It can be determined which of the calculated difference or the maximum corrected blood glucose value is the lower blood glucose value (620). The maximum corrected blood glucose value can be a fixed clinical medical value, such as 100 mg / dL, which can be modified from 0 to 300 mg / dL based on user preferences, implicitly based on the user's maximum bolus setting and clinical parameters of insulin sensitivity factors, as seen in Equation 7 below.

[0067]

[0068] In other examples, the maximum corrected blood glucose value can be specific to a particular user. For example, the maximum corrected blood glucose value can be determined based on the user's history of administered doses and an analysis of the user's response to each corresponding administered dose. At 620, it can be determined by a direct comparison of the individual values ​​of the difference and the maximum corrected blood glucose value, or by applying a deviation weighting to the difference, the maximum corrected blood glucose value, or both (e.g., percentages such as 80 / 20, 60 / 40, direct deviation weighting such as 0.2, etc.).

[0069] At 630, the bolus dose of the insulin regulator (such as IAF as shown in the example using Equation 1 or Equation 4 above) can be determined by applying it to the lower blood glucose value determined at 620.

[0070] A blood glucose measurement value can be selected from multiple blood glucose measurements (640). The processor can select a blood glucose measurement value based on multiple factors. For example, the selected blood glucose measurement value can be the most recently received blood glucose measurement value from the CGM (i.e., the latest blood glucose measurement value) or, for example, a blood glucose measurement value entered by the user into the medical device, a blood glucose measurement value received in the past 15 minutes, 25 minutes, or other time periods, etc.

[0071] At 650, the rate of change of blood glucose measurements can be determined based on multiple blood glucose measurements received over a period of time. Many known methods can be used to determine the rate of change. [Go to...] Figure 6B The rate of change correction factor (660) can be determined by multiplying the rate of change determined at 650 by a time parameter. The rate of change of the blood glucose measurement can be expressed in milligrams per deciliter per unit time. The time parameter, such as T in Equation 2, can be a time value expressed in time units, such as minutes (e.g., 5, 10, 15, or 25 minutes). Alternatively, fractions converting the time units to seconds or hours can be used. In the example, the processor executing the programming code can generate a modified blood glucose measurement by adding the rate of change correction factor to the selected blood glucose measurement (670). At 680, the processor executing the programming code can determine the difference between the modified blood glucose measurement and the target blood glucose value. At 690, the processor executing the programming code can determine which of the determined difference between the modified blood glucose measurement and the target blood glucose value, or the bolus dose of the adjustment factor, is the corresponding minimum. The processor can output the corresponding minimum as a first insulin correction value to provide the bolus dose indication to the drug delivery device (699).

[0072] In another alternative, Figure 7 The diagram illustrates a flowchart of another example sub-process used to obtain the final insulin value. (See diagram for example.) Figure 7As shown in the example, the step of obtaining the final insulin value at 435 can be performed by a processor executing programming code that enables the processor to perform the functions of process 700. For example, at 710, the processor can calculate the difference between the selected blood glucose measurement and the user's target blood glucose value to determine the measurement-target blood glucose difference. A prediction of the blood glucose value at a specific time corresponding to the time when the selected blood glucose measurement was measured can be made by the processor at 720. This prediction can be based on previous user blood glucose measurements, history of insulin administration doses, etc. The difference between the predicted blood glucose value and the user's target blood glucose value can be calculated to determine the predicted target blood glucose difference (730). The processor executing the programming code can be operable to determine which of the measurement-target blood glucose difference and the predicted target blood glucose difference is the lower blood glucose value (740). This can be determined using various methods, such as direct comparison or other processes. In response to determining in 740 which corresponding value is the lower blood glucose value, an insulin regulator can be applied to the lower blood glucose value to provide the final blood glucose value (750). For example, a lower blood glucose level can be multiplied or divided by an insulin regulatory factor, or some other operation or function can apply the insulin regulatory factor to a lower blood glucose level.

[0073] In response to determining the final blood glucose value, the processor can output an indication of the final blood glucose value at 760 to deliver the bolus dose to the drug delivery device. The output indication can be used to generate an indication applied to a pump mechanism (such as...). Figure 2 The signal (224) is used to deliver the bolus dose to the drug delivery device.

[0074] The techniques described herein for providing safety constraints for drug delivery systems (e.g., system 200 or any component thereof) can be implemented in hardware, software, or any combination thereof. For example, system 200 or any component thereof can be implemented in hardware, software, or any combination thereof. Software-related implementations of the techniques described herein may include, but are not limited to, firmware, specialized software, or any other type of computer-readable instructions executable by one or more processors. Hardware-related implementations of the techniques described herein may include, but are not limited to, integrated circuits (ICs), application-specific integrated circuits (ASICs), field-programmable arrays (FPGAs), and / or programmable logic devices (PLDs). In some embodiments, the techniques described herein and / or any system or component described herein can be implemented using a processor that executes computer-readable instructions stored on one or more memory components.

[0075] Some embodiments of the disclosed apparatus may be implemented, for example, using a storage medium, a computer-readable medium, or an article of manufacture capable of storing instructions or instruction sets, which, if executed by a machine (i.e., a processor or microcontroller), can cause the machine to perform methods and / or operations according to embodiments of this disclosure. Such a machine may include, for example, any suitable processing platform, computing platform, computing device, processing device, computing system, processing system, computer, processor, etc., and may be implemented using any suitable combination of hardware and / or software. Computer-readable media or articles of manufacture may include, for example, any suitable type of memory cell, memory, memory article, memory medium, storage device, storage article, storage medium, and / or storage cell, such as memory (including non-transitory memory), removable or non-removable media, erasable or non-erasable media, writable or rewritable media, digital or analog media, hard disk, floppy disk, optical disc read-only memory (CD-ROM), recordable optical disc (CD-R), rewritable optical disc (CD-RW), optical disc, magnetic media, magneto-optical media, removable memory cards or discs, various types of digital multifunction discs (DVDs), tapes, capsule-type cassette tapes, etc. Instructions may include any suitable type of code, such as source code, compiled code, interpreted code, executable code, static code, dynamic code, encrypted code, programming code, etc., implemented using any suitable high-level, low-level, object-oriented, visual, compiled, and / or interpreted programming language. Programming code implemented on a non-transitory computer-readable medium enables the processor to perform functions, such as those described herein, when executing the program code.

[0076] The foregoing has described certain examples of this disclosure. However, it is explicitly stated that this disclosure is not limited to those examples, but rather that additions and modifications to the content explicitly described herein are also included within the scope of the disclosed examples. Furthermore, it should be understood that the features of the various examples described herein are not mutually exclusive and can exist in various combinations and substitutions, even those not expressed herein, without departing from the spirit and scope of the disclosed examples. Indeed, variations, modifications, and other implementations of the content described herein will occur to those skilled in the art without departing from the spirit and scope of the disclosed examples. Therefore, the disclosed examples should not be defined solely by the foregoing illustrative description.

[0077] The programmatic aspect of the technology can be considered a "product" or "article of manufacture," typically in the form of executable code and / or associated data, carried or implemented on a type of machine-readable medium. Storage-type media include any or all tangible memory or associated modules of computers, processors, etc., such as various semiconductor memories, tape drives, disk drives, etc., which can provide non-transitory storage for software programming at any time. It is important to emphasize that the summary of the specification is provided to allow the reader to quickly determine the nature of the technical disclosure. The applicant believes it will not be used to interpret or limit the scope or meaning of the claims. Furthermore, in the foregoing detailed description, various features are grouped together in a single example to simplify this disclosure. This approach to the disclosure should not be construed as reflecting an intention to claim more features than expressly enumerated in each claim. Rather, as reflected in the following claims, the inventive subject matter lies in fewer than all features of a single disclosed example. Therefore, the following claims are incorporated herein by reference, each claim existing independently as a separate example. In the appended claims, the terms “including” and “in which” are used as simple English equivalents to the corresponding terms “comprising” and “wherein”, respectively. Furthermore, the terms “first,” “second,” “third,” etc., are used merely as labels and are not intended to impose numerical requirements on their objects.

[0078] For purposes of illustration and description, the foregoing description of exemplary embodiments has been presented. It is not intended to be exhaustive or to limit this disclosure to the precise form disclosed. Many modifications and variations are possible based on this disclosure. The scope of this disclosure is not intended to be limited by this detailed description, but rather by the appended claims. Future applications claiming priority to this application may claim protection for the disclosed subject matter in different ways and may generally include any set of one or more limitations as differently disclosed or otherwise shown herein.

Claims

1. A non-transitory computer readable medium having programming code executable by a processor and the processor operable when executing the programming code to perform functions including: receiving a plurality of blood glucose measurements of a user over a period of time; computing a difference between a selected blood glucose measurement from the plurality of blood glucose measurements and a target blood glucose value of the user; applying an insulin sensitivity factor to the difference to determine a personalized insulin value; limiting the personalized insulin value by using an insulin adjustment factor to generate a corrected bolus dose; determining a rate of change of blood glucose values from the plurality of blood glucose measurements over the period of time; computing a revised bolus dose using the determined rate of change and a most recent blood glucose measurement; setting an insulin bolus dose for delivery to be a minimum of the corrected bolus dose and the revised bolus dose; and initiating delivery of insulin by generating a control signal for an amount of insulin to be expelled according to the set insulin bolus dose. a medication delivery device is attached to a user's body.

2. The non-transitory computer readable medium of claim 1, wherein, 3. The non-transitory computer readable medium of claim 1, further comprising programming code that, when executed by the processor, causes the processor to, when performing limiting the personalized insulin value by using an insulin adjustment factor to generate a corrected bolus dose: multiply the personalized insulin value by an insulin adjustment factor.

4. The non-transitory computer readable medium of claim 1, further comprising programming code that, when executed by the processor, causes the processor, in response to determining a corrected bolus dose of insulin needed by the user, to: select an insulin adjustment factor from a range of 0.3 to 0.

7.

5. The non-transitory computer readable medium of claim 1, further comprising programming code that, when executed by the processor, causes the processor to: determine a corrected bolus dose of insulin needed by the user prior to computing a difference between a selected blood glucose measurement from the plurality of blood glucose measurements and a target blood glucose value of the user.

6. The non-transitory computer readable medium of claim 1, further comprising programming code that, when executed by the processor, causes the processor to: determine a trajectory of the plurality of blood glucose measurements.

7. The non-transitory computer readable medium of claim 1, further comprising programming code that, when executed by the processor, causes the processor to: constrain a corrected bolus dose at an upper limit by a recommended bolus dose that is proportional to the trajectory of the plurality of blood glucose measurements modified by an insulin adjustment factor.

8. The non-transitory computer readable medium of claim 1, further comprising programming code that, when executed by the processor, causes the processor to: constrain a corrected bolus dose not to exceed that required to achieve a target blood glucose if a trajectory of blood glucose measurements is substantially constant over a set period of time.

9. A medical device comprising: a processor; ​ a memory storing programming code and operable to store data related to a user's diabetes treatment plan, wherein the programming code is executable by the processor; and a transceiver operable to receive and transmit signals containing information usable or generated by the programming code, wherein the processor, when executing the programming code, is operable to control delivery of insulin and perform functions including the following functions: receive a plurality of blood glucose measurements of a user over a period of time; calculate a difference between a selected blood glucose measurement from the plurality of blood glucose measurements and a target blood glucose value of the user; apply an insulin sensitivity factor to the difference to determine a personalized insulin value; limit the personalized insulin value by using an insulin adjustment factor to generate a correction bolus dose; determine a rate of change of blood glucose values from the plurality of blood glucose measurements over the period of time; calculate a revised bolus dose using the determined rate of change and a most recent blood glucose measurement; set an insulin bolus dose for delivery to be a minimum of the correction bolus dose and the revised bolus dose; and initiate delivery of insulin by generating a control signal for an amount of insulin to be expelled based on the set insulin bolus dose.

10. The medical device of claim 9, wherein the device is a medication delivery device configured to be attached to a user's body.

11. The medical device of claim 9, wherein the processor, when generating a correction bolus dose by limiting the personalized insulin value using an insulin adjustment factor, is operable to: multiply the personalized insulin value by an insulin adjustment factor.

12. The medical device of claim 9, wherein the processor is further operable to: select an insulin adjustment factor from a range of 0.3 to 0.

7.

13. The medical device of claim 9, wherein the processor is further operable to: determine a correction bolus dose of insulin needed by the user based on an evaluation of the plurality of blood glucose measurements prior to calculating a difference between a selected blood glucose measurement and a target blood glucose value of the user.

14. The medical device of claim 9, wherein the processor, when evaluating the plurality of blood glucose measurements, is further operable to: determine a trajectory of the plurality of blood glucose measurements.

15. The medical device of claim 9, wherein the processor is further operable to: constrain a correction bolus dose at an upper limit by a recommended bolus dose proportional to a trajectory of the plurality of blood glucose measurements modified by an insulin adjustment factor.

16. The medical device of claim 9, wherein the processor is further operable to: constrain a correction bolus dose not to exceed that required to achieve a target blood glucose if a trajectory of blood glucose measurements is substantially constant over a set period of time. ​

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