A method and system for dynamically customizing an insulin onboard profile and providing advisories for improving insulin action time

Abstract

Rather than using a conventional static IOB profile based on population averages, exemplary embodiments may dynamically adjust an insulin on board (IOB) profile for a user of a drug delivery system to customize the IOB profile for the user based on recent glucose value history and insulin delivery. Exemplary embodiments may calculate an insulin duration of action (DIA) for the user from a customized insulin decay curve. Exemplary embodiments may generate and send a notification to the user to help reduce the user's DIA and / or to suppress an increase in the user's DIA. Exemplary embodiments may be aimed at not unduly restricting insulin delivery for the contribution of an insulin bolus to the IOB.

Description

Technical Field

[0001] Related Applications This application claims the benefit of U.S. Provisional Patent Application No. 63 / 343,739, filed May 19, 2022, the entire contents of which are incorporated herein by reference.

Background Art

[0002] An automated insulin delivery (AID) system delivers small amounts of insulin to a user at frequent intervals, such as every five minutes. Such an AID system may include control software that delivers such an insulin dosage after determining the amount of insulin administration. In some conventional AID systems, the control software attempts to maintain the user's glucose value at a target glucose value. The control software periodically receives measured glucose values from a glucose sensor. The control software predicts the user's glucose value over a period, such as the next 12 operating cycles of the delivery device, based on the history of glucose values and the history of insulin delivery. Based on these predictions, the control software may select an insulin delivery dosage.

[0003] When making predictions and determining the next insulin delivery dosage, the control software may refer to the user's insulin on board (IOB). IOB refers to an estimate of insulin that has not yet acted in the user's body in that it has not yet affected the user's glucose value.

[0004] Conventional AID systems rely on the user's IOB curve (sometimes referred to as the "insulin decay curve") when predicting the user's future glucose values and determining the basal insulin delivery dose. Conventional IOB curves are fixed and based on population averages. FIG. 1 depicts two types of conventional IOB curves at plot 100. Plot 100 shows the percentage of insulin delivery remaining as IOB over time. Plot 100 shows a straight-line curve 102. The straight-line curve 102 shows a linear decay and is available with different decay rates. The second type of curve 104 depicted in FIG. 1 is known as the Elsenz curve, which is a non-linear curve. The Elsenz curve is also available with different decay rates. The AID system may select one of these curves at a specified decay rate and use the selected curve when controlling the operation of the AID system. Summary of the Invention Problems to be Solved by the Invention

[0005] Conventional AID systems may unduly limit insulin delivery after a large insulin bolus is administered, based on the resulting increased IOB value. As a result, the response of the AID system to rapidly rising glucose values may be limited. The control software has conventionally been required to limit insulin delivery until the IOB returns to a level below the amount of corrective insulin required. This constraint does not take into account that such large boluses typically accompany the user's meal intake, and for this reason, the large insulin bolus may already be accounted for in the glucose-insulin kinetics. Therefore, further restricting the operation of the control software due to the IOB contributed by the meal bolus may not be optimal. Means for Solving the Problems

[0006] According to a first aspect of the invention, a drug delivery system for delivering insulin to a user may include a non-transitory computer-readable storage medium storing computer program instructions and a processor configured to execute the computer program instructions. When executed, the computer program instructions may cause the processor to create a model of the interaction between an analyte and a drug customized for the user based on the history of analyte levels and the history of drug delivery. Also, when executed, the computer program instructions may cause the processor to determine the standard impulse response of the model, determine a display of the user's drug load over time from the standard impulse response after delivering a specified amount of the drug, and use the display when determining the dosage of the drug to be administered to the user output by the drug delivery system.

[0007] The drug delivery system may further include a tank for storing the drug. Exemplary drugs that may be used include insulin, glucagon-like peptide-1 receptor agonists (GLP-1), glucose-dependent insulinotropic polypeptide (GIP), or other hormones and / or combinations of drugs such as two or more of insulin, GLP-1, and GIP, or other homologous hormones. Although the present disclosure may refer to "insulin", "insulin-loaded", "insulin action time", etc., it should be understood that the drugs listed above and other drugs may be used. The analyte level may be a glucose value and / or a ketone value. The display may be a curve, a function, an equation, a set of equations, a table, or a storage that holds a value indicating the user's drug load over time after a specified amount of the drug has been delivered. The computer program instructions may cause the processor to initiate delivery of a specified amount of the drug to the user. In some embodiments, the drug may be insulin, and the model may be a glucose prediction model that predicts the user's future glucose values based on the user's previous glucose values and insulin delivery. The computer program instructions may update the display to account for the user's most recent analyte level value and may use the updated display when determining the user's next drug dosage output by the drug delivery device. The display of the user's drug load over time after a specified amount of the drug has been delivered may be a non-linear curve.

[0008] According to another aspect of the invention, a drug delivery system for delivering insulin to a user may include a non-transitory computer-readable storage medium storing computer program instructions and a processor configured to execute the computer program instructions. The computer program instructions may cause the processor to determine an estimated value of the user's insulin action duration, compare the estimated value of the user's insulin action duration to a threshold, and generate a notification of a recommendation to reduce the user's insulin action duration if the estimated value of the user's insulin action duration exceeds the threshold.

[0009] The notification may be output to the display device by executing computer program instructions by a processor. The drug delivery system may have a medical device of the body such as a drug delivery device fixed to the user, and the advice may advise the user to change the position of the drug delivery device to reduce scarring. The advice may advise the position of the user's drug delivery device that does not normally or is not much subjected to compression by contact. The advice may also advise the use of insulin that acts more quickly. The advice may advise the avoidance of the intake of certain foods such as a particular type of food or a list of foods.

[0010] According to another aspect of the invention, a drug delivery system for delivering insulin to a user may include a non-transitory computer-readable storage medium storing computer program instructions and a processor configured to execute the computer program instructions. By using the processor to execute the computer program instructions, determining an estimated value of the user's insulin action duration, updating the estimated value of the user's insulin action duration over time, and generating an advisory notification to reduce a change in the user's insulin action duration when the estimated value of the insulin action duration changes significantly over time. Thus, the insulin action duration may be dynamic and automatically adjusted for the user, as opposed to a static or fixed or "set" DIA.

[0011] When the estimated value of the insulin action duration increases, the advice may be to change the location where the drug delivery device, which is part of the drug delivery system, is fixed to the user. The advice may be to change the eating pattern to a previous eating pattern that has provided acceptable glucose value control to the user. The estimated value of the insulin action duration may be decreasing, and the advice may be to maintain the current location where the drug delivery device is fixed to the user. The drug delivery device may be an insulin pump attached to the user.

Brief Description of the Drawings

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DETAILED DESCRIPTION OF THE INVENTION

[0033] Exemplary embodiments may dynamically and automatically adjust the IOB profile to customize for the user of the drug delivery device an IOB profile based on the history of recent glucose values and insulin delivery, rather than a conventional static IOB profile derived from population averages. This dynamic customization may improve the glucose value management performance of the drug delivery device for the user by more accurately capturing the user's IOB over time. The user's IOB profile is dynamic in that it may be automatically updated at regular intervals or in response to other trigger events.

[0034] For the user, the customized IOB profile may be generated as an insulin decay curve in an exemplary embodiment. The process of customizing the IOB profile begins with creating a custom model of the insulin-glucose interaction. This model may predict the user's future glucose values based on past glucose values and weight coefficients. The impulse response of the model (e.g., the response to a bolus pulse) may be calculated and the impulse response may be converted into a customized insulin decay curve.

[0035] Exemplary embodiments may calculate a user's DIA from a customized insulin decay curve. Assuming there is a relationship between the time within a desired glucose value range and the DIA, exemplary embodiments may compare the user's DIA to one or more thresholds to determine whether the user can take any measures to reduce the DIA when needed. Exemplary embodiments may generate and output to the user a notification to help reduce the user's DIA. Further, exemplary embodiments may monitor the rate of change of the user's DIA. If the DIA increases over time, recommendations may be generated and output to the user to take measures to reverse the increase, decelerate the increase, or stop the increase, and / or return to a more acceptable DIA. If the DIA decreases, recommendations may be generated and transmitted to recommend continued use of the current selections that affect the DIA to decrease the DIA, maintain an ideal DIA, or prevent the DIA from increasing.

[0036] Exemplary embodiments may aim not to unduly restrict insulin delivery due to the contribution of insulin boluses to IOB. In some exemplary embodiments, the IOB used by the control software may be separated between the IOB due to bolus delivery and the IOB due to AID delivery (such as basal insulin delivery). Thus, the user may have different (simultaneous) insulin action times. The IOB due to bolus delivery may be based on the DIA specific to the insulin bolus. The IOB due to basal delivery may be based on the DIA specific to basal insulin or the AID delivery of basal insulin. The DIA specific to the insulin bolus may be shorter than the DIA due to AID delivery to avoid insulin delivery being constrained for a long time due to the contribution of the insulin bolus to IOB. A composite IOB value reflecting a short DIA for bolus delivery and a long DIA for basal delivery may be used. Further, the DIA specific to the insulin bolus may be dynamically changed based on the actual insulin bolus activity. The DIA specific to the insulin bolus may become shorter as the recent cumulative insulin bolus delivery increases, and may become longer as the recent cumulative insulin bolus delivery decreases.

[0037] FIG. 2 shows a block diagram of an exemplary drug delivery system 200 suitable for delivering insulin and drugs such as those described above to a user 208 according to an exemplary embodiment. The drug delivery system 200 may include a drug delivery device 202. The drug delivery device 202 may be wearable and attached to the body of the user 208 or carried by the user 208. The drug delivery device 202 may be directly coupled to the user without a tube (e.g., directly attached to a body part and / or skin of the user via an adhesive, etc.) or may be carried by the user with the drug delivery device 202 connected to an injection site where the drug is injected using a needle and / or cannula (e.g., may be placed in a belt or pocket). The surface of the drug delivery device 202 may include an adhesive to facilitate attachment to the user 208.

[0038] The drug delivery device 202 may include a processor 210. The processor 210 may be, for example, a microprocessor, a logic circuit, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), or a microcontroller. The processor 210 may hold the date and time, similar to other functions such as calculations. The processor 210 may be operable to execute a control application 216 encoded by computer program instructions stored in a storage device 214, and this control application 216 enables the processor 210 to instruct the operation of the drug delivery device 202. The control application 216 may be a single program, multiple programs, modules, libraries, etc. The processor 210 may execute computer program instructions stored in the storage device 214 for a user interface (UI) 217 that may include one or more display screens displayed on a display 227. The display 227 may display information to the user 108 and, in some cases, may receive input from the user 208, such as when the display 227 is a touch screen.

[0039] The control application 216 may control the delivery of the drug to the user 208 according to a control approach as described herein. The control application may use a glucose prediction model as described below to predict the future glucose value of the user 208. The storage device 214 may hold the user's history 211, such as the history of basal delivery, the history of bolus delivery, and / or other histories such as the meal event history, the exercise event history, the glucose value history, the other analyte level history, etc. Further, the processor 210 may be operable to receive data or information. The storage device 214 may include both a primary storage device and a secondary storage device. The storage device 214 may include a random access memory (RAM), a read only memory (ROM), an optical storage device, a magnetic storage device, a removable storage medium, a solid state storage device, etc.

[0040] The drug delivery device 202 may include a tray or cradle and / or one or more housings that house various components including a pump 213, a power source (not shown), and a tank 212 that stores drugs for delivery to a user 208. A fluid path to the user 208 may be provided, and the drug delivery device 202 may discharge drugs from the tank 212 to deliver the drugs to the user 208 via the fluid path using the pump 213. The fluid path may include, for example, a tube that connects the drug delivery device 202 to the user 208 (e.g., a tube that connects a cannula to the tank 212), and may include a conduit to a separate injection site. The drug delivery device 202 may have, for example, an operating cycle of every 5 minutes, which calculates and delivers a basal dose of the drug as needed. These procedures are repeated for each cycle.

[0041] For example, there may be one or more communication links with one or more devices physically separated from the drug delivery device 202, including a management device 204 for the user and / or the user's caregiver, one or more sensors 206, a smartwatch 230, a fitness monitor 232, and / or other various wearable devices 234. The communication link may include any known communication protocol or standard, such as Bluetooth®, Wi-Fi®, a short-range wireless communication standard, a cellular standard, or any other wireless protocol, or any wired communication link or wireless communication link that operates according to such a standard.

[0042] The drug delivery device 202 may communicate with a network 222 via a wired communication link or a wireless communication link. The network 122 may include a local area network (LAN), a wide area network (WAN), a cellular network, a Wi-Fi® network, a short-range wireless communication network, or a combination thereof. A computer device 126 may communicate with the network, and the computer device may communicate with the drug delivery device 102 or the management device 104.

[0043] The drug delivery system 200 may have one or more sensors 206 that detect the level of one or more analytes. The (one or more) sensors 206 may be coupled to the user 208, for example, by an adhesive or the like, and may provide information or data regarding one or more medical conditions, physical attributes, or analyte levels of the user 208. The (one or more) sensors 206 may be physically separate from or an integrated component of the drug delivery device 202. The (one or more) sensors 206 may include, for example, glucose monitors such as continuous glucose monitors (CGMs) and / or non-invasive glucose monitors. The (one or more) sensors 206 may include ketone sensors, other analyte sensors, heart rate monitors, respiratory rate monitors, motion sensors, temperature sensors, sweat sensors, blood pressure sensors, alcohol sensors, and the like. Some sensors 206 may detect characteristics of components of the drug delivery device 202. For example, the sensors 206 of the drug delivery device may include voltage sensors, current sensors, temperature sensors, and the like.

[0044] The drug delivery system 200 may or may not have a management device 204. In some embodiments, the drug delivery device 202 can manage itself and thus does not require a management device. The management device 204 may be a dedicated device such as a dedicated personal diabetes manager (PDM) device. The management device 204 may be a programmed general-purpose device such as any portable electronic device including a dedicated controller such as, for example, a processor, a microcontroller, etc. The management device 204 may be used to program or adjust the operation of the drug delivery device 202 and / or the sensor(s) 206. The management device 204 may be, for example, any portable electronic device including a dedicated device, a smartphone, a smartwatch or a tablet. In the example depicted, the management device 204 may have a processor 219 and a storage device 218. The processor 219 may execute a process for managing the user's glucose value and controlling the delivery of drugs to the user 208. The drug delivery device 202 may supply data from the sensor 206 and other data to the management device 204. The data may be stored in the storage device 218. The processor 219 may be operable to execute program code stored in the storage device 218. For example, the storage device 218 may be operable to store one or more control applications 120 for execution by the processor 219. The storage device 218 may be operable to store history information such as drug delivery information, analyte level information, user input information, output information or other history information. The control application 220 may play a role in controlling the drug delivery device 202 such as the control of automatic drug delivery (ADD) (or, for example, automatic insulin delivery (AID)) of drugs to the user 208. The storage device 218 may store the control application 220, a history 221 as described above for the drug delivery device 202 and other data and / or programs.

[0045] To display information, a display 240 such as a touch screen may be provided. The display 240 may display a user interface (UI) 223. The display 240 may be used to receive input as when it is a touch screen. The management device 204 may further have input elements 225 such as a keyboard, buttons, knobs, etc. to receive input from the user 208.

[0046] The management device 204 may communicate with a network 224 such as a LAN or WAN or a combination of those networks via a wired communication link or a wireless communication link. The management device 204 may communicate with one or more servers or cloud services 228 via the network 224. In some embodiments, data such as sensor values may be sent directly from the drug delivery device 202 or from the management device 204 to one or more cloud services / servers 228 for storage and processing.

[0047] Other devices, such as smartwatch 230, fitness monitor 232, and wearable device 234, may be part of the drug delivery system 200. These devices 230, 232, and 234 may communicate with the drug delivery device 202 and / or the management device 204 for receiving information and / or issuing commands to the drug delivery device 202. These devices 230, 232, and 234 may execute computer program instructions, for example, to perform part of the control functions executed by the processor 210 or the processor 219 via the control applications 216 and 220. These devices 230, 232, and 234 may have a display for displaying information. The display may display a user interface for providing user input such as a request to change or suspend a dosage or a request to deliver a drug bolus, start or confirmation, or may display a user interface for displaying an output such as a change in the dosage (e.g., basal delivery amount) determined by the processor 210 or the management device 204. These devices 230, 232, and 234 may have a wireless communication connection with the sensor 206 for directly receiving analyte measurement data. Other delivery devices 205, such as a drug delivery pen (e.g., insulin pen), may be configured (e.g., when determining IOB) or provided for delivering drugs to the user 208.

[0048] The functions described later for the exemplary embodiments may be under the control of or executed by the control application 216 of the drug delivery device 202 or the control application 220 of the management device 204. In some embodiments, the functions may be under the control of or executed, in whole or in part, by the cloud service / server 228, the computer device 226, or other enumerated devices, and the other enumerated devices include the smartwatch 230, the fitness monitor 232, or another wearable device 234.

[0049] In the closed-loop mode, the control applications 216, 220 continuously determine the drug delivery amount for the user 208 based on the feedback loop. For example, in the case of an insulin delivery device, the purpose of the closed-loop mode is to bring the user's glucose value to the target glucose value or to keep the user's glucose value within a range of glucose values.

[0050] In some embodiments, the drug delivery device 202 does not need to deliver a single drug alone. Instead, the drug delivery device 202 may deliver one drug such as insulin to lower the user's 208 glucose value and also deliver another drug such as glucagon to raise the user's 208 glucose value. The drug delivery device 202 may deliver a glucagon-like peptide (GLP)-1 receptor agonist drug to lower glucose or to delay gastric emptying to delay the postprandial glucose spike. In other embodiments, the drug delivery device 202 may deliver other drugs that replace pramlintide or insulin. In other embodiments, the drug delivery device 202 may deliver concentrated insulin. In some embodiments, the drug or drugs delivered by the drug delivery device may be a combination of two or more of the drugs identified above. In a preferred embodiment, the drug delivery device delivers insulin. Thus, throughout this application, insulin and insulin delivery devices are referred to, but those skilled in the art will understand that drugs other than insulin can be delivered instead of or in addition to insulin.

[0051] As described above, the exemplary embodiments may provide an IOB profile that is dynamically customized for each user. The IOB profile is customized for the user based on the history of insulin delivery and the history of glucose values. The IOB profile is dynamic in that it may be updated periodically in the exemplary embodiments to adapt to the user's needs.

[0052] In an exemplary embodiment, a user's IOB profile may be captured by an insulin decay curve that depicts over time the remaining insulin effect of the insulin dosage delivered to each user. FIG. 3 shows a flowchart 300 of exemplary steps that may be performed in an exemplary embodiment in such customization and use of an insulin decay curve in an AID system. First, at 302, a display of the user's insulin load, such as an insulin decay curve, is determined for the user from the glucose value history and the insulin delivery history. More generally, the display may be a curve, function, formula, set of formulas, table, or storage that holds values indicating the user's drug load over time after a specified amount of drug has been delivered. Since the actual data of the user can be used, the display may be customized for the user. The display may be used by an AID control system (e.g., control applications 216 or 220) in predicting the user's future glucose values. These future glucose values may be used in determining the response of the control system to the current and predicted states. The determination of the response may, in some embodiments, include determining a basal insulin delivery dosage for delivery to the user, including cessation of delivery of basal insulin delivery to the user.

[0053] FIG. 4 shows a flowchart 400 of exemplary steps that may be performed in an exemplary embodiment in determining a display, where the display is a custom insulin decay curve for the user. At 402, a custom model of the insulin-glucose interaction is determined. FIG. 5 shows a flowchart 500 of exemplary steps that may be performed in an exemplary embodiment in determining a custom model of the insulin-glucose interaction. The model may be characterized as a recursive model of past glucose values and past insulin delivery. For example, the model may be expressed as follows.

Number

Equation

Equation

Equation

[0054] Such a model of insulin-glucose interaction may be updated. FIG. 6 shows a flowchart 600 of exemplary steps that may be performed in an exemplary embodiment when updating the model. At 602, a trigger event occurs. FIG. 7 shows an example 702 of such a trigger event. For example, the start 704 of a new cycle may function as a trigger to update the model. The elapse of time, multiple times, intervals such as one day or multiple days (such as three days) 706 or the replacement of a disposable pump device or a part of a pump device (e.g., after three days or 3.5 days) may function as a trigger event. The presence of sufficiently new data 708 such as a sufficient amount of history of new glucose values may function as a trigger event. The detection of a very large change 710 in the difference between the predicted glucose value and the actual glucose value may also function as a trigger event. It should be understood that combinations of these trigger events 704, 706, 708, and 710 may be used as trigger events. Additionally, other trigger events not shown may be used.

[0055] When determining the model, specific data of the history of glucose values may be omitted from consideration. FIG. 8 shows a flowchart 800 of exemplary steps that may be performed in an exemplary embodiment to account for perturbations when determining the model. At 802, glucose values affected by the impact of historical perturbations may be identified. Examples of perturbations include meals and exercise. At 804, the glucose values affected by the impact of perturbations are removed from the history used to determine the model. The affected glucose values may be values after a meal for a certain period (e.g., 30 minutes, 1 hour, 2 hours, or 3 hours) or values after the start of exercise for a certain period (e.g., 30 minutes, 1 hour, or 2 hours) or values after the end of exercise for a certain period (e.g., 30 minutes or 1 hour).

[0056] Referring back to FIG. 4, at 404, a model having weight coefficients may be used to create an impulse response for the model. FIG. 9 shows a flowchart 900 of exemplary steps that may be performed in an exemplary embodiment to create an impulse response for each of the first options. At 902, an initial glucose value condition is set. At 904, an insulin input value may be simulated and the calculation of a predicted glucose value may be determined using the model. At 906, the predicted glucose value is converted into an impulse response. The impulse response is an output (e.g., a glucose value) generated when an impulse input (e.g., an insulin bolus dose or an insulin basal dose) is presented to the model.

[0057] Another option for generating an impulse response of a model having determined parameters (i.e., weight coefficients) is shown in a flowchart 1000 of FIG. 10 of exemplary steps that may be performed in an exemplary embodiment. At 1002, a zero-state impulse response may be calculated. The zero-state impulse response is G(0)=G(1)=G(2)=0, G(3)=K, where for k≧1

Equation

[0058] FIG. 11 shows an example of a plot 1100 of impulse response curves. Each curve is for a different user. Thus, curve 1102 is for a first user, curve 1104 is for a second user, and so on. As can be seen from the impulse response curves, insulin activity rapidly rises sharply after delivery and then decreases over time.

[0059] Referring again to FIG. 4, at 406, an insulin decay curve is generated from the user's impulse response curve. FIG. 12 shows a flowchart 1200 of exemplary steps that may be performed in an exemplary embodiment to convert an impulse response to an IOB curve. The steps depicted are for determining the IOB curve from cycle k onwards. At 1202, the integral of the curve from cycle k to the end is determined. This represents the total insulin remaining in the user's body that can still affect the user's glucose value. At 1204, the integral of the entire impulse response curve is determined. This represents the total insulin delivered. At 1206, for each cycle k, the integral value of the impulse response curve at cycle k is divided by the integral value of the entire response curve to obtain the IOB for each cycle k such that a normalized insulin decay curve in the range from 1 to 0 is generated.

[0060] FIG. 13 shows a plot 1300 of an exemplary impulse response curve. At cycle 3 specified by line 1302, as indicated by arrow 1304, the integral of the curve 1306 from cycle 3 onwards (i.e., the area under the curve), divided by the integral of the entire curve 1306, is used to determine the user's insulin decay curve associated with curve 1306. In other words, the area under the curve is calculated to evaluate the IOB, and the area under the curve to the right of line 1302 is compared to the total area under the entire curve (e.g., curve 1306). And if the area under the curve to the right of this line 1302 is 30% of the total area under curve 1306, then 30% of the insulin activity or IOB remains.

[0061] When plotting the remaining area under the curve over time, the result is the IOB curve, i.e., the graph shown in FIG. 14 representing the remaining IOB for impulses (originally given at time 0) at different times for different users. Thus, FIG. 14 shows a plot 1400 of the resulting insulin decay curves 1402 for a plurality of users. Plot 1400 shows the relative IOB of the user over time. Each of the curves 1402 starts at 1 and decays to 0 over time.

[0062] Exemplary embodiments may analyze the obtained customized insulin decay curve to provide the user with advice for improving the user's time in range. Time in range indicates the duration that the user's glucose value remains within a defined range (e.g., 100 mg / dL to 150 mg / dL) surrounding the user's target glucose value. The user's time in range can be correlated with the DIA. The DIA is the time from when insulin is injected until all of the metabolic effects of the insulin have ended (e.g., the time span of the insulin decay curve until the insulin effect becomes 0 after injection). As the DIA gets shorter, the DIA correlates with a better time in range, and the user's DIA reflects lifestyle and body physiology.

[0063] FIG. 15 shows an exemplary flowchart 1500 of exemplary steps that may be performed in an exemplary embodiment to provide advice to a user to improve the time within a range based on the user's insulin action time (DIA). At 1502, the user's DIA is calculated. At 1504, for example, a check is made as to whether the user's DIA is too long, for example, by comparing the user's DIA with a threshold value. If the DIA is too long, at 1506, one or more pieces of advice may be provided to the user as detailed below. The advice may take the form of a message communicated to the user, for example, by displaying a message on the display devices 227 and / or 240. Alternatively or in combination with a text message, an audio message may be output to the user, or a video message may be output via the display devices 227 and / or 240. Further, a notification may be sent via a messaging service such as SMS or via email. In some embodiments, the advice may be displayed on a web page accessible to the user. If the DIA is not too long (for example, if the DIA calculated by the user does not exceed the threshold value), it may not be necessary to send the advice.

[0064] Figure 16 shows a plurality of exemplary advisories 1602. One exemplary advisory 1604 is for the user to change the location of the drug delivery device 202 attached to the user more frequently. If the drug delivery device 202 remains at or near a single location of the user for a long time, as a result, scarring may occur and it may become more difficult for the delivered insulin to be locally absorbed and metabolized, which may affect the DIA. Another advisory 1606 is to avoid the areas of the user that are frequently exposed to external pressure ( "pressure points"), such as the user's back, which may be frequently stationary and exposed to pressure against a seat or bed. Another advisory 1608 is for the user to use insulin that acts more quickly in the drug delivery device 102. This results in faster absorption and thus a shorter DIA. The last exciting advisory 1610 is to avoid the intake of certain foods, such as foods with a high fat content and / or a high carbohydrate content. These foods may extend the user's DIA. The foods to be avoided may be itemized or classified within advisory 1610.

[0065] Advisories may be generated and communicated if there is a significant deviation from the initially calculated parameters. Figure 17 shows a flowchart 1700 of exemplary steps that may be performed in an exemplary embodiment to generate advisories for specific physiological changes that improve the time within the user's range based on changes in the user's DIA. At 1702, a customized DIA is continuously calculated for the user, for example, when calculating an updated insulin decay curve. At 1704, a check is made to see if the DIA is increasing too much. This may involve determining whether the DIA has exceeded a threshold or calculating the rate of change of the user's DIA and determining that the rate of change has exceeded a threshold. At 1706, if it is determined that the user's DIA is increasing too much, advisories are generated and sent to suppress the increase (e.g., reverse the increasing trend of the DIA).

[0066] FIG. 18 shows some exemplary advisories 1802 that may be generated and communicated at 1706. Advisory 1804 proposes changing the site of the delivery device for the user. The current site may be a site that may show scarring, be subject to pressure, or may not absorb insulin well. Another advisory 1806 is for the user to repeat a lifestyle pattern that has shown a better DIA. This advisory 1806 may refer to a specific time frame or may identify actions such as better sleep and exercise patterns. Another advisory 1808 is to indicate a meal pattern that has resulted in a better DIA than before. This advisory 1808 may refer to a specific period and / or may recommend specific foods while limiting the consumption of other foods.

[0067] Referring again to FIG. 17, at 1704, if it is determined that the DIA is not increasing too much, at 1708, a check may be made as to whether the user's DIA is less than the nominal amount. If so, this is desirable and at 1710, an advisory to maintain the decrease may be generated and transmitted. FIG. 19 shows a process 1902 for making exemplary advisories. Exemplary advisory 1904 may be to maintain the drug delivery device 202 at the user's current location so that it appears to be functioning well as evidenced by the decrease in DIA.

[0068] Advisories other than those detailed above may be used. The exemplary advisories are intended as examples and not as limitations.

[0069] In an exemplary embodiment, the IOB value used by control application 216 or 220 may be separated into a bolus contribution to the IOB (designated as IOB bol ) and a basal contribution to the IOB (designated as IOB AID ). Thus, the IOB may be considered as the sum of IOB bol and IOB AID . The IOB bol value is the unique IOB bol value and the IOBAID It is useful for better constraining insulin delivery after a large insulin bolus than conventional systems that rely on a single IOB without considering values. As the user's bolus administration increases, the DIA decreases by the method described herein, such that the bolus does not overly constrain AID insulin delivery. Further, to shorten the period during which insulin delivery is constrained after a large insulin bolus, the DIA bol may be shorter than the DIA AID .

[0070] Figure 20 shows flowchart 2000 of exemplary steps that may be performed in an exemplary embodiment to calculate the IOB bol from DIA values specific to an insulin bolus designated as the DIA bol . At 2002, separate the IOB bol from the IOB AID . At 2004, calculate the IOB bol using the DIA bol and the bolus insulin delivery over the past 12 cycles.

Number

[0071] At 2006, use the IOB bol in the control system when predicting future glucose values and constraining the insulin bolus dose.

[0072] The DIA bol value may be dynamically changed based on the most recent insulin bolus delivery history. The DIA bol may be calculated as follows.

Number

[0073] FIG. 21 shows a flowchart 2100 of exemplary steps that may be performed in an exemplary embodiment to determine DIA bol (i). In 2100, DIA max and DIA min may be determined. DIA bol may assume only values within the range defined by DIA max and DIA min . In 2104, the difference between DIA max and DIA min is determined to specify the magnitude of the range. In 2106, the weight may be determined based on the most recent insulin bolus delivery amount. The value

Number

[0074] Although exemplary embodiments have been described in this specification, various changes can be made in form and detail without departing from the intended scope of the appended claims.

Claims

1. A drug delivery system for delivering a drug to a user, comprising: a non-transitory computer-readable storage medium storing computer program instructions; a processor configured to: create a model of the analyte-drug interaction customized for the user based on the history of analyte levels and the history of drug delivery; determine the standard impulse response of the model; determine from the standard impulse response a display of the user's drug load over time after delivering a specified amount of the drug; use the display when determining the dosage of the drug to be administered to the user by the drug delivery system; a processor configured to execute computer program instructions that cause the processor to perform the above operations; A drug delivery system comprising the above components.

2. The drug delivery system according to claim 1, further comprising a tank for storing the drug.

3. The drug delivery system according to claim 1, wherein the drug is insulin, a glucagon-like peptide-1 agonist, pramlintide, another glucose regulator, or a combination thereof.

4. The drug delivery system according to claim 1, wherein the analyte level is a glucose value.

5. The drug delivery system according to claim 1, wherein the display is a curve, a function, an equation, a set of equations, a table, or a storage that holds a value indicating the user's drug load over time after delivering the specified amount of the drug.

6. The drug delivery system according to claim 1, wherein the computer program instructions cause the processor to initiate delivery of a specified amount of the drug to the user.

7. The drug delivery system according to claim 1, wherein the drug is insulin and the model is a glucose prediction model that predicts the user's future glucose values based on the user's previous glucose values.

8. The drug delivery system according to claim 1, further comprising updating the display to account for the user's most recent analyte level value and using the updated display when determining the user's next drug dosage output by the drug delivery device.

9. The drug delivery system according to claim 1, wherein the display of the user's drug load over time after delivering the specified amount of the drug is a non-linear curve.

10. A drug delivery system for delivering a drug to a user, comprising: A non-transitory computer-readable storage medium storing computer program instructions, a processor, determining an estimated value of the user's insulin action duration, comparing the estimated value of the user's insulin action duration with a threshold, when the estimated value of the user's insulin action duration exceeds the threshold, generating a notification of advice for reducing the user's insulin action duration, a processor configured to execute computer program instructions to cause the processor to execute, a drug delivery system comprising.

11. The drug delivery system according to claim 10, further comprising outputting the notification to a display device.

12. The drug delivery system according to claim 10, wherein the drug delivery system comprises a medical device of the body fixed to the user, and the advice advises the user to change the position of the drug delivery device to reduce scarring.

13. The drug delivery system according to claim 10, wherein the drug delivery system comprises a medical device of the body fixed to the user, and the advice advises the position of the user's drug delivery device that does not normally receive pressure by contact.

14. The drug delivery system according to claim 10, wherein the advice further advises the use of insulin that acts more quickly.

15. The drug delivery system according to claim 10, wherein the advice advises avoiding the intake of specific foods.

16. A drug delivery system for delivering a drug to a user, a non-transitory computer-readable storage medium storing computer program instructions, a processor, determining an estimated value of the user's insulin action duration, updating the estimated value of the user's insulin action duration over time, when the estimated value of the insulin action duration changes to be greater than a threshold over time, generating a notification advising to reduce the change in the user's insulin action duration, a processor configured to execute computer program instructions to cause the processor to execute, a drug delivery system comprising.

17. The drug delivery system according to claim 16, wherein the estimated value of the insulin action duration increases, the drug delivery system comprises a drug delivery device, and the advice is to change the location where the drug delivery device is fixed to the user.

18. The drug delivery system according to claim 16, wherein an estimated value of the insulin action duration increases, and the advice is to change the dietary pattern to a previous dietary pattern that has brought about acceptable glucose value control for the user.

19. The drug delivery system according to claim 16, wherein an estimated value of the insulin action duration decreases, the drug delivery system comprises a drug delivery device, and the advice is to maintain the current position where the drug delivery device is fixed to the user.

20. The drug delivery system according to claim 16, wherein the drug delivery system includes an insulin pump attached to the user.

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