SYSTEMS FOR DETERMINING INSULIN ON BOARD AND RECOMMENDING INSULIN THERAPY, AND RELATED METHODS

Abstract

A system is provided with an insulin delivery device configured to deliver insulin to a user of the system and a computer-based control unit associated with the insulin delivery device. The computer-based control unit includes a user interface and a computer-based processor. The computer-based processor is configured to calculate a relative insulin on board value for a specific time by calculating a first value that represents a reference insulin on board value at the specific time, calculating a second value that represents an automated insulin on board value at the specific time, and subtracting one of the first and second values from the other. The automated insulin on board value represents at least one insulin delivery automatically specified by the computer-based control unit. Methods of use are also disclosed.

Claims

1. An insulin delivery system, comprising: a glucose monitor; an insulin delivery device; and a remote device in wireless communication with the glucose monitor and the insulin delivery device, the remote device comprising: at least one processor; and a non-transitory computer-readable storage medium storing instructions thereon that, when executed by the processor, cause the remote device to: determine an estimated insulin-on-board (IOB) based at least partially on insulin delivery information related to a person with diabetes (PWD); and determine a relative IOB that represents a difference between a reference IOB and the estimated IOB, the reference IOB representing an amount of insulin required to maintain blood glucose stasis of the PWD; and determine a recommended bolus dose of insulin, comprising: based at least partially on the determined relative IOB, projecting future blood glucose levels for one or more changes to basal insulin delivery to the PWD; and based at least partially on projected future blood glucose levels, determining whether the recommended bolus dose of insulin is necessary to achieve a target blood glucose level.

2. The insulin delivery system of claim 1, wherein the remote device further comprises instructions that, when executed by the processor, cause the remote device to receive measured blood glucose levels of the PWD from the glucose monitor.

3. The insulin delivery system of claim 1, wherein the remote device further comprises instructions that, when executed by the processor, cause the remote device to, responsive to determining that the recommended bolus dose of insulin is necessary to achieve a target blood glucose level, provide the recommended bolus dose of insulin to the PWD.

4. The insulin delivery system of claim 1, wherein the remote device further comprises instructions that, when executed by the processor, cause the remote device to, responsive to determining that the recommended bolus dose of insulin is unnecessary to achieve a target blood glucose level, discard the recommended bolus dose of insulin.

5. The insulin delivery system of claim 1, wherein the remote device further comprises instructions that, when executed by the processor, cause the remote device to: project a first set of future blood glucose levels based, at least in part, on an anticipated meal intake; and project a second set of future blood glucose levels responsive to the assumed one or more changes to basal insulin delivery to the PWD.

6. The insulin delivery system of claim 5, wherein the remote device further comprises instructions that, when executed by the processor, cause the remote device to determine a meal bolus dose based, at least in part, on a difference between the second set of future blood glucose levels and the target blood glucose level.

7. The insulin delivery system of claim 1, wherein the remote device further comprises instructions that, when executed by the processor, cause the remote device to: receive measured blood glucose levels of the PWD from the glucose monitor; and responsive to determining that the receive measured blood glucose levels of the PWD are outside of a target range of blood glucose levels, determine a correction dose of insulin.

8. The insulin delivery system of claim 1, wherein the assumed one or more changes to basal insulin delivery comprise one of an increase in basal insulin delivery or a decrease in basal insulin delivery.

9. The insulin delivery system of claim 1, wherein determining that the recommended bolus dose of insulin is necessary to achieve a target blood glucose level comprises: determining that received measured blood glucose levels are outside of a target range for blood glucose levels; and determining that that delivery of the recommended bolus dose of insulin will bring the blood glucose levels of the PWD within the target range for blood glucose levels.

10. The insulin delivery system of claim 1, wherein determining that the recommended bolus dose of insulin is necessary to achieve a target blood glucose level comprises determining that delivery of the recommended bolus dose of insulin will compensate for projected increased blood glucose levels due to an anticipated meal and will maintain blood glucose levels of the PWD within a target range for blood glucose levels.

11. A method for managing insulin delivery, comprising: determining an estimated insulin-on-board (IOB) based at least partially on insulin delivery information related to a person with diabetes (PWD); determining a relative IOB that represents a difference between a reference IOB and the estimated IOB, the reference IOB representing an amount of insulin required to maintain blood glucose stasis of the PWD; determining a recommended bolus dose of insulin, comprising: based at least partially on the determined relative IOB, projecting future blood glucose levels for one or more changes to basal insulin delivery to the PWD; and based at least partially on projected future blood glucose levels, determining whether the recommended bolus dose of insulin is necessary to achieve a target blood glucose level.

12. The method of claim 11, further comprising, responsive to determining that the recommended bolus dose of insulin is necessary to achieve a target blood glucose level, providing the recommended bolus dose of insulin to the PWD.

13. The method of claim 11, further comprising, responsive to determining that the recommended bolus dose of insulin is unnecessary to achieve a target blood glucose level, discarding the recommended bolus dose of insulin.

14. The method of claim 11, further comprising: projecting a first set of future blood glucose levels based, at least in part, on an anticipated meal intake; and projecting a second set of future blood glucose levels responsive to the assumed one or more changes to basal insulin delivery to the PWD.

15. The method of claim 14, further comprising determining a meal bolus dose based, at least in part, on a difference between the second set of future blood glucose levels and the target blood glucose level.

16. The method of claim 11, further comprising: receiving measured blood glucose levels of the PWD from a glucose monitor; and responsive to determining that the received measured blood glucose levels of the PWD are outside of a target range of blood glucose levels, determining a correction dose of insulin.

17. The method of claim 11, wherein projecting future blood glucose levels assuming one or more changes to basal insulin delivery to the PWD comprises: assuming an increase in basal insulin delivery; or assuming a decrease in basal insulin delivery.

18. The method of claim 11, wherein determining that the recommended bolus dose of insulin is necessary to achieve a target blood glucose level comprises: determining that received measured blood glucose levels are outside of a target range for blood glucose levels; and determining that that delivery of the recommended bolus dose of insulin will bring the blood glucose levels of the PWD within the target range for blood glucose levels.

19. The method of claim 11, wherein determining that the recommended bolus dose of insulin is necessary to achieve a target blood glucose level comprises determining that delivery of the recommended bolus dose of insulin will compensate for projected increased blood glucose levels due to an anticipated meal and will maintain blood glucose levels of the PWD within a target range for blood glucose levels.

20. A remote device for assisting in insulin delivery, the remote device comprising: at least one processor; and a non-transitory computer-readable storage medium storing instructions thereon that, when executed by the processor, cause the remote device to: determine an estimated insulin-on-board (IOB) for a person with diabetes (PWD); and determine a difference between a reference IOB and the estimated IOB, the reference IOB representing an amount of insulin required to maintain blood glucose stasis of the PWD; and based at least partially on the difference between the reference IOB and the estimated IOB, project future blood glucose levels assuming one or more changes to basal insulin delivery to the PWD; and based at least partially on projected future blood glucose levels, determining whether an unscheduled bolus dose of insulin will be necessary to achieve a target blood glucose level for the PWD.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0026] FIG. 1 is a schematic view of an exemplary system adapted to implement one or more of the techniques disclosed herein.

[0027] FIG. 2A is a plot showing one implementation of insulin absorption for multiple values of duration of insulin action.

[0028] FIG. 2B is another plot showing linear implementation of insulin absorption for multiple values of duration of insulin action.

[0029] FIG. 3 is an exemplary representation of the behavior of the system in FIG. 1.

[0030] FIG. 4 is another exemplary representation of the behavior of the system in FIG. 1.

[0031] FIG. 5A illustrates an exemplary calculation of insulin on board for the system in FIG. 1.

[0032] FIG. 5B illustrates an exemplary visualization of future glucose changes for the system in FIG. 1.

[0033] FIG. 6A illustrates another exemplary calculation of insulin on board for the system in FIG. 1.

[0034] FIG. 6B illustrates another exemplary visualization of future glucose changes for the system in FIG. 1.

DETAILED DESCRIPTION

[0035] FIG. 1 is a schematic view of an exemplary system 100 adapted to implement one or more of the techniques disclosed herein.

[0036] The illustrated system 100 includes a glucose monitoring/measuring device 102, an insulin delivery device such as an insulin pump (or insulin delivery device) 104 and a controller 106. The controller 106 has a user interface 108, an internal computer-based processor and internal computer-based memory storage capacity.

[0037] In the illustrated implementation, the glucose monitoring/measuring device 102, the insulin pump 104 and the controller 106 are configured so that they can communicate with each other using wireless communication channels 110a, 110b (e.g., using wireless communication technologies). However, in other implementations, information may be transferred between the components illustrated in FIG. 1 using a wired connection or may, in some instances, be transferred by the user or caregiver him or herself. For example, if the glucose monitoring/measuring device 102 is a monitor that simply presents blood glucose reading on a visual display, for example, but is not able to transmit the reading directly to the controller 106, then the person using the system 100 may view the displayed blood glucose reading and enter that reading manually at the controller 106. In other implementations (not shown), any one of the glucose monitoring/measuring device 102, the insulin pump 104 and the controller 106 can be combined with another of the devices in a single integrated unit, or all three may be combined. For example, some implementations incorporate the controller 106 into the insulin delivery device 104. In combined devices, insulin delivery protocols may be provided by a dedicated computer-based processor, or a single processor may control the insulin delivery protocols, glucose monitoring, insulin delivery device functions and/or user interface functions.

[0038] In various implementations, the glucose monitoring/measuring device 102 can be a continuous glucose monitor, a blood glucose meter, an intravenous blood glucose measurement device, or other device adapted to provide an indication of blood glucose levels in the user. In some implementations, the level of glucose in the user's blood may never be directly measured. Rather, the glucose level in the user's interstitial fluid or other bodily fluid or tissue may be measured, and at some point may (or may not) be converted into an equivalent glucose level of whole blood, plasma or serum. It is to be understood that the use herein of the terminology “blood glucose” level may mean actual blood glucose level or a surrogate glucose level, depending on the context.

[0039] The insulin “pump” 104 can be any type of insulin delivery device. In general, the insulin pump is a medical device used for the administration of insulin, for example, in the treatment of diabetes. The pump can have a variety of possible configurations. In some implementations, for example, the insulin pump 104 includes a pump (with controls, processing module, batteries, etc.), a disposable reservoir for insulin (which may be inside the pump), and a disposable infusion set, including a cannula for subcutaneous insertion (under the skin) and a tubing system to interface the insulin reservoir to the cannula. In some implementations, however, the pump may not include one or more of these components. For example, in some implementations, the pump will not have tubing. Also, in some implementations, the pump will not include a disposable reservoir. In other configurations, the pump may be controlled by a handheld device or by an application loaded onto a mobile phone or other mobile computing device. It is to be understood that, depending on the context, the use herein of the terminology “pump” or “delivery device” may refer to conventional insulin pumps available on the market today, or may refer to other insulin delivery devices such as insulin pens, automated inhalers, variable rate insulin skin patches and other such delivery devices, whether or not they are commercially available today. It is envisioned that the devices, systems and methods disclosed herein may also be applied to other insulin delivery methods, such as intravenous insulin delivery in an intensive care unit, and may also find use in delivering other medicines or fluids to a user. In such other systems, analyte(s) other than glucose may be monitored in a user's body to aid in determining the desired amount of medicine or fluid to be delivered to the user.

[0040] The controller 106 can be any type of computer-based device configured to implement and/or facilitate the functionalities disclosed herein. In some implementations, the controller 106 is a smartphone executing the Android™ operating system. However, the controller 106 can be any type of smartphone (or other device) executing any type of operating system. In general, a smartphone is a mobile phone built on a mobile operating system, with more advanced computing capability connectivity than a feature phone. Many modern smartphones also include high-resolution touchscreens and web browsers that display web pages. High-speed data access can be provided by Wi-Fi and/or mobile broadband. In a typical implementation, the insulin delivery device 104 is adapted to deliver insulin to a user (e.g., a person with diabetes). Typically, the user has the ability to set a default basal insulin delivery schedule to provide a continuous, background dose of insulin to provide for the basic metabolic needs of the individual. The basal delivery, once set, will provide the pre-programmed dose of insulin unless directed otherwise by the user such as by suspending delivery or by instructing the insulin pump to deliver a temporary basal rate which differs from the pre-programmed rate for a period of time. A typical insulin pump implementation is also adapted to allow the user to program bolus doses of insulin, either to be delivered immediately or to be spread over a period of time, sometimes referred to as an extended bolus.

[0041] Semi-automated or automated systems may have a variety of modes in which they can operate. Typically, one of these modes is a default or zero-automation mode where the system provides no automation and the user is wholly responsible for their insulin dosing. In the default mode, an automated system provides a schedule of basal insulin delivery that we refer to as the default basal delivery program. The default mode may be triggered, for example, when the system does not have a continuous glucose sensor actively providing glucose information. Or it may be the result of some other condition that the system deems unsafe for automated delivery such as a degraded continuous glucose sensor signal.

[0042] The determination of what the default basal delivery program is may vary across implementations. In some implementations, the default basal delivery schedule can be a fixed schedule of insulin delivery that the user inputs. In other implementations, the system may vary the default basal delivery schedule over time to optimize the basal insulin that is delivered when the system operates in its default, zero-automation mode. In some implementations, the default basal program includes or consists of a vector of day-time pairs coupled with a rate of insulin delivery between that time period and the next time period.

[0043] As used herein, a “user” is typically a person who receives insulin from the inventive devices, systems and methods disclosed herein. In some implementations, actions may be performed by a “caregiver” who is a person or persons different from the “user”. For example, the caregiver may be a parent, other family member, teacher, physician, clinician, advisor, or other person(s) assisting the user with management of his or her diabetes. In some implementations, actions ascribed to a caregiver must be performed by the caregiver(s) and may not be performed by the user. In other implementations, the user and the caregiver are one and the same person, and there is no other person directly involved in the delivery of insulin to the user.

[0044] In some implementations, the system 100 provides for automated delivery modes wherein the system is configured to automatically dose insulin. The automated or semi-automated algorithm that the system uses to determine the amount of insulin to deliver at any point in time may vary greatly across implementations. In a typical implementation, however, the user will find it valuable to gain some understanding of the nature of the automated insulin delivery; how much or how little insulin is being delivered and at what time it has been delivered. For example, a user may find this information valuable if the automation is only partial automation and the user is still required to make insulin dosing decisions concurrent with the automation. Another scenario where this information may be useful is when the system 100 finds it necessary to turn off the automation and switch to a default insulin delivery mode after which the user is solely responsible for managing the insulin delivery. In this situation, a user would find it helpful to understand what the automation has been doing up until the point of transition to manual-mode.

[0045] A key metric that patients using intensive insulin therapy rely upon to understand their insulin dosing is an estimate of how much insulin has been recently delivered to the user's body but has yet to act on the user's blood glucose level. This quantity is commonly referred to as insulin-on-board (IOB). The estimate of IOB is helpful to patients because it can take hours after insulin is delivered for the blood glucose lowering action of the insulin delivery to complete. During this time period, it may prove beneficial to a user to incorporate knowledge of this prior insulin delivery into the user's dosing decisions.

[0046] In a typical implementation, the system 100 can estimate IOB for the user based on information about recent actual insulin deliveries from the insulin delivery device 104 and insulin absorption information (e.g., the user's insulin absorption curve, and the user's duration of insulin action (DIA) which defines how long it takes for 100% absorption, etc.) that may be specific to the user.

[0047] FIGS. 2A and 2B show illustrative examples of IOB absorption curves for various DIAs. The y-axes on the graphs show the fraction of insulin remaining on board from a dose of insulin and the x-axes show the hours elapsed since the delivery. Typically, the system 100 allows the user to configure the DIA to their specific insulin formulation and their personal response rate. For example, curve 202 shows an exemplary absorption profile for a DIA of 3 hours while curve 204 shows an absorption profile of 5 hours. The exemplary insulin action curves in FIG. 2A are adapted from Mudaliar, et al., “Insulin Aspart (B28 Asp-Insulin): A Fast-Acting Analog of Human Insulin,” Diabetes Care 22:1501-1506, 1999. Other implementations may use other action curves such as a linear absorption profile as shown in FIG. 2B.

[0048] In traditional systems without any automation (i.e., systems that only provide a pre-programmed basal rate of insulin delivery and manually programmed bolus deliveries but no automated changes to the basal rate or automated bolus deliveries), insulin-on-board calculations typically do not include the basal rate insulin deliveries. Such basal deliveries typically are intended to maintain the current blood glucose level, not to raise or to lower it, and not to offset the effect of a meal, etc., as does a bolus delivery. As such, the basal rate of insulin can be considered an effective reference insulin delivery schedule that seeks to maintain static blood glucose levels. In implementations with automation, a reference schedule of insulin delivery is a useful tool to calculate the IOB of the automated deliveries.

[0049] A reference schedule of insulin delivery allows for incorporating both increases and reductions in insulin delivery into the IOB calculation. The methods described herein allow for a more complete understanding of automated or semi-automated insulin delivery by providing transparency into automated reductions in insulin delivery as well as increases in delivery. In some implementations, the default basal rate is used as a reference insulin delivery schedule, while other implementations may use a different insulin delivery schedule that may or may not be related to the default basal rate. Typically, the reference insulin delivery schedule is, to the best of the system's knowledge, the schedule of insulin delivery that will maintain a constant level of blood glucose in a steady state condition.

[0050] Typically, traditional IOB calculations do not include basal delivery because the basal delivery matches the reference insulin delivery schedule in these systems (to the best of the user's knowledge) and thus it should not have any effect (either to raise or to lower) on the user's blood glucose level regardless of how much basal insulin is “on-board.” It follows that since the basal insulin deliveries are not expected to affect the user's blood glucose level, they aren't relevant to future dosing recommendations and should not be included in IOB calculations.

[0051] Considered another way, the reference insulin delivery schedule is the amount of insulin the system 100 would expect to exactly offset the user's metabolic needs to maintain blood glucose stasis absent any disturbances (such as meal, stress, etc.). Thus, although there may be basal insulin that has been dosed but has not yet been absorbed, a typical implementation would not anticipate the basal insulin dose to have any blood glucose lowering effect since it will be cancelled out by the metabolic needs of the person.

[0052] Typically, the calculation of insulin-on-board may include some or all of the following: meal related bolus insulin; correction related bolus insulin; extended bolus delivery; and, in some implementations, manually programmed temporary basal rates. A meal related bolus of insulin is a point dose of insulin taken primarily to offset the consumption of glucose increasing food such as carbohydrates. A correction related bolus delivery is a point in time dose of insulin that attempts to correct for a high blood glucose level back to the target range. An extended or square wave bolus is a bolus that is evenly dosed over a period of time, usually to offset a longer absorption meal. A temporary basal rate is a period of time when the user instructs the system 100 to deliver either more or less than the preset basal rate in the system.

[0053] Insulin on board for a point delivery of insulin (such as a bolus) may be determined by multiplying the amount of the insulin delivery by the fraction of absorption remaining as determined by the time since the delivery, the absorption curve and the DIA. A typical absorption curve will define a fraction of insulin remaining on the y-axis by the time since bolus on the x-axis as illustrated in FIGS. 2A and 2B.

[0054] FIG. 3 shows an exemplary IOB calculation for a 5 unit bolus taken at 9:00 AM with the system configured to have a DIA of 4 hours. The y-axis is the insulin-on-board remaining from the bolus and the x-axis is the time. At 9:00 AM, the IOB equals the full 5 units of insulin since the dose was just given. By 10:30 AM, the IOB remaining is about 2.5 units. According to the illustrated example, the full insulin action of the bolus tails off around 1:00 PM or 4 hours after the bolus was initially given.

[0055] To calculate insulin on board for a continuous delivery of insulin such as a basal delivery or an extended bolus, the continuous delivery of insulin may be discretized into very small bolus deliveries of insulin. For example, if an extended bolus is given to dose 6 units of insulin over the next hour, the extended bolus delivery can be discretized into 60 boluses of 1/60th of the dose or 0.1 units each, delivered at minute 1, 2, 3, . . . , 60 of the hour. The exact interval of the discretization may vary across implementations and typically will work sufficiently well as long as the length of each sub-period is very small relative to the DIA. Once discretized, the IOB for each individual discretized bolus may be calculated as described above, and then summed together to compute the IOB for the entire continuous delivery. During the continuous delivery, only doses that have already occurred would be included in this calculation. Alternatively, if an implementation's insulin action curve may be represented by a mathematical function, it is possible to perform the above discrete integral by mathematically integrating the insulin action curve over the delivery period.

[0056] FIG. 4 illustrates the calculation of the IOB for the 6 unit extended bolus delivery discussed above. The 1 hour extended bolus is started at 5:00 PM with the DIA of the system 100 configured to be 5 hours. The IOB increases between 5:00 PM and 6:00 PM as the insulin is dosed. At 6:00 PM, the IOB is less than the full 6 units because some of the action of the insulin dosed between 5:00 PM and 6:00 PM has already completed. The IOB drops to about 3 units remaining at approximately 7:15 PM showing that about half of the absorption is complete at that time. The IOB does not return to 0 until around 11:00 PM when the 5 hour DIA for the final discretized boluses at 6 PM complete.

[0057] In some implementations, the system 100 allows for semi-automated or automated insulin dosing. As noted above, an implementation with automation may compute the IOB for the insulin delivered as part of the automated delivery. In some implementations, this IOB may be presented as an independent automated delivery IOB calculation while in other implementations, the automated delivery IOB is summed with the other, manual delivery IOB calculations to give a net total IOB calculation.

[0058] To calculate the IOB for semi-automated or automated dosing systems, some implementations will compare the actual automated insulin dosing history to the reference delivery schedule over the automated delivery time period to find the difference between the two. Typically, if the automated insulin delivery differs from the reference insulin delivery schedule, the system would expect there to be a residual blood glucose effect that should be reflected in an IOB calculation. This residual effect may be either positive or negative depending on how much and when the automated dosing occurred relative to the reference insulin delivery. Calculating the IOB in this manner will be referred to as a relative-IOB.

[0059] For example, take an automated delivery that allows the basal rate to vary between x and y units per hour where the reference delivery schedule would call for z units of basal delivery per hour. Some implementations calculate a relative-IOB for this type of automated delivery by computing the IOB for both the automated delivery (IOB_automated) and for the reference delivery over the same time period (IOB_reference) and then taking the difference, IOB_automated-IOB_reference to find the relative-IOB to assign to the period of the automated delivery. Typically, the IOB_automated and IOB_reference calculations will include all insulin dosing including basal insulin doses during the time period under consideration. The same calculation may be performed by first taking the difference between the automated delivery and the reference delivery schedules to create a difference-in-delivery schedule. The IOB may be calculated on the difference-in-delivery schedule to compute the relative-IOB for the automated delivery. That is, the relative-IOB calculation holds under the distributive property of mathematics. It will be apparent to those of ordinary skill in this art that other variations to these calculations may be made without departing from the scope and spirit of the appended claims. Note that in cases where the IOB_automated is less than the IOB_reference, the relative-IOB calculated for such automated delivery period is negative. A negative relative-IOB may be added to any other IOB from other deliveries (positive or negative) in a simple additive manner to calculate the total IOB for the user.

[0060] A negative relative-IOB reflects that the user has received less insulin than the reference delivery would have delivered. Since standard insulin therapy provides for the reference basal delivery to keep glucose values at static levels, the delivery of less than the reference basal delivery results in a deficit of insulin relative to what the user would need to keep glucose levels static. This deficit results in an expected subsequent rise in glucose values. The magnitude of this expected rise equals the absolute value of the insulin deficit amount, or relative-IOB, multiplied by the user's insulin sensitivity factor (ISF), where the ISF is the amount that a user's blood glucose level will decrease when dosed with 1 unit of insulin.

[0061] In some implementations, the benefit of computing the relative-IOB of an automated delivery is that it allows the user or caregiver to more easily understand and quantify what the net effect is of the therapy changes caused by a particular automated delivery. Depending on the implementation and the scenario, the particular automated delivery may deliver more or less than the reference delivery schedule. The relative-IOB calculation allows the user to see if the net effect of the automated delivery is an increase (positive IOB) or decrease (negative IOB) to the reference insulin delivery schedule and what the magnitude of such change is.

[0062] FIGS. 5A and 5B show an example relative-IOB calculation for a temporary attenuation of insulin delivery. This scenario could occur for example during an automated attenuation of insulin delivery or a manual temporary basal rate set by the user. In the illustrated example, the basal insulin delivery is attenuated by the automated system due to a decline in glucose levels. The DIA is configured to be 5 hours in the illustrated system.

[0063] Referring to FIGS. 5A and 5B the left y-axes show the calculated relative-IOB for the automated attenuation of delivery as illustrated by line 502. The x-axes show the time of day. The right y-axis in FIG. 5A shows the rate of insulin delivery in units per hour. In this illustrated example, the reference delivery rate is 1 unit per hour and the automated delivery schedule is shown by dashed line of 504. The right y-axis in FIG. 5B illustrates the cumulative expected change in blood glucose level for a user with an ISF of 50 mg/dL/unit, as illustrated by curve 506.

[0064] In the illustrated example, FIG. 5A shows the attenuation of insulin commences at 12:00 when the insulin delivery rate drops from 1 unit per hour to 0 units per hour. Line 502 shows that the absolute magnitude of the relative-IOB increases as the time period continues until 13:00 where the attenuation ceases and the delivery rate once again matches the reference basal delivery rate of 1 unit per hour. In this illustrated example, because the automated delivery is less than the reference delivery of 1 unit per hour, the calculated IOB for the automated delivery is less than the calculated IOB for the reference delivery. This results in a negative relative-IOB, implying that the blood glucose level is expected to rise as a result of the attenuation of insulin delivery.

[0065] FIG. 5B shows, in curve 506, the cumulative expected rise in blood glucose level that is implied by the negative relative-IOB illustrated by line 502. The effects of the attenuation begin to appear at approximately 12:40 when the effects of the first missing doses of insulin would have begun to act. The effect of the insulin attenuation increases substantially between 13:00 and 15:00 and continues to show small effects until the DIA of the last missing dose is reached at about 18:00.

[0066] The illustrated example shows how this relative information may be useful to a user. In the case of an automated insulin delivery attenuation, the missing insulin, relative to the reference delivery, will continue to have an effect for hours to come. If, for example, the automated attenuation was a result of a user's blood glucose level being near hypoglycemic levels, the negative relative-IOB could give the user information that may be helpful in reducing or even to dispensing with a carbohydrate ingestion intervention to raise blood glucose levels since the relative-IOB already implies a future rise in blood glucose levels. In another scenario where the user plans to eat a meal, knowledge that an insulin delivery attenuation may have already offset a low blood glucose level may be helpful to a bolus calculator which would otherwise reduce the prandial insulin bolus to account for the low blood glucose level.

[0067] The incorporation of the future effects of an attenuation of insulin such as illustrated in FIGS. 5A and 5B are not possible with the standard calculation of IOB that one will find discussed in prior art. The novel inclusion of both a reference insulin delivery schedule and the actual insulin delivery in the calculation of the IOB allows for automated attenuations of insulin to be seamlessly integrated into a user's bolus calculations and insulin therapy decisions. More accurate estimates of IOB will result in superior outcomes than in systems where such reductions in insulin delivery are excluded from the IOB calculation.

[0068] FIGS. 6A and 6B illustrate yet another example of the calculation of relative-IOB for automated insulin delivery. In the exemplary system, the system 100 is configured to have a DIA of 5 hours and a reference basal delivery of 1 unit per hour. The x-axes show the time of day. The left y-axes show the calculated relative-IOB for the automated delivery at each point in time, as illustrated by curve 602. The right y-axis in FIG. 6A shows the rate of automated insulin delivery as illustrated by dashed line 604, and the right y-axis in FIG. 6B shows the projected cumulative change in glucose levels from the start of the example at 11:00, as illustrated by curve 606.

[0069] Referring to FIG. 6A, we see that the automated system increases the insulin delivery rate from the reference level of 1 unit per hour to 3 units per hour at 11:30. This rate is held for 1 hour until 12:30. As shown by curve 602, the relative-IOB at 12:30 has risen from 0 to almost 2 units. The 2 units of IOB reflects the additional 2 units per hour that the automated delivery has provided between 11:30 and 12:30 that is over and above the reference delivery rate. The relative-IOB is less than 2 units at 12:30 because some of the addition insulin delivered has already acted.

[0070] Between 12:30 and 13:00 the relative-IOB (see curve 602) decreases as the insulin works to lower the blood glucose level as illustrated by curve 606 in FIG. 6B. At 13:00, the system attenuates insulin delivery to 0 units per hour. This immediately begins to decrease the relative-IOB for the user as can be seen by the sharp change in the rate of decline of curve 602 at 13:00. Between 13:00 and 14:30 the automated delivery rate is 0. During this time period, the calculated relative-IOB (see curve 602) is decreasing rapidly as the initial augmented dosing acts on the glucose levels and the negative relative-IOB from the attenuation is added to the IOB calculation, both causing a decrease in the net relative-IOB (see curve 602).

[0071] The change in glucose levels, as illustrated by curve 606 in FIG. 6B, continues to decrease even after the relative-IOB becomes negative just before 14:00. At this point, the glucose levels have been lowered by about 56 mg/dL due to the initial increase in insulin dosing. As the negative, relative-IOB (see curve 602) increases in magnitude, the effects of the insulin attenuation turn the blood glucose level plot (see curve 606) to a positive slope. The projected change in glucose level (curve 606) reaches a nadir at approximately 14:30, after which the glucose levels shown by curve 606 increase in line with the remaining negative, relative-IOB (see curve 602) from the insulin attenuation.

[0072] The illustrated example provides a simple window into the power of how the methods described herein can help to distill the salient effects of a complex set of automated dosing history that a typical automated or semi-automated implementation of the system 100 may engage in. Additionally, the methods may be used to combine both automated and manual insulin dosing histories seamlessly. The methods are agnostic as to the agent, human or machine, that takes the dosing or attenuation action. The methods described herein may be used to sum virtually any combination of automated insulin dosing including, but not limited to: meal boluses; correction boluses; an increase or decrease in basal rate (either automated or manual); and extended boluses. The methods may effectively incorporate basal rate differences of any magnitude and the changes in the exemplary systems in FIGS. 5A, 5B, 6A and 6B are for illustrative purposes only.

[0073] FIGS. 6A and 6B again show the limitations of prior art of IOB calculation. A standard calculation of IOB only incorporates insulin dosing greater than the pre-programmed basal rate (e.g., boluses) and does not take into account basal rate changes. As illustrated in FIGS. 6A and 6B, an automated or semi-automated system may have a complex set of automated actions that includes both increases and decreases of insulin delivery relative to a reference insulin delivery schedule. A system without the ability to integrate both increases and attenuations of insulin into the IOB calculation will not be able to accurately report the true IOB in an individual. The methods described herein can incorporate virtually any combination of increased, decreased, automated or manual dosing changes into the calculation of IOB and thus will be a valuable addition to the art and to future semi-automated and automated systems.

[0074] The methods may be further used to visualize the projected future action of the prior dosing (automated, manual or a combination of the two) as shown by curves 506 and 606 in FIGS. 5B and 6B, respectively. The future glucose level projections may be created by calculating the projected change in IOB at each future time period and then by multiplying the change by the user's ISF. This multiplication will give a projected change in blood glucose level vector for each future period of time. In these implementations, the projected change in IOB for a time period is the increase or decrease in IOB for all dosing adjustments administered prior to the time period. The IOB for a future time may be calculated using the standard IOB calculation but using a future time in lieu of the present time for the insulin absorption lookup on the insulin absorption curve. A cumulative projected glucose change curve such as curves 506 and 606 in FIGS. 5B and 6B, respectively, may be calculated by summing the set of future periods of interest.

[0075] In some implementations, the relative-IOB for automated dosing may be provided to a user separate and apart from the IOB from the manually programmed user doses. In other implementations, all of the IOB' s for the system are combined together to provide a net IOB for the user. These values may be particularly useful if integrated into a bolus wizard or calculator.

[0076] A bolus calculator is a tool found in a typical insulin delivery device that helps a user to determine a correct insulin dose at a particular point in time based on a number of variables. The calculator may be used to determine if a correction dose is required and/or how many units of insulin should be taken for a certain amount of carbohydrates to be ingested. In a typical implementation, the bolus calculator uses a user's current blood glucose level, target glucose level, anticipated carbohydrates to be ingested and the current insulin on board for the user. How these variables are used in the calculation of the suggested bolus varies from implementation to implementation.

[0077] The use of the relative-IOB of automated dosing may be beneficial in many cases for users of insulin bolus calculators. As described herein, the relative-IOB resulting from automated deliveries may have a material effect on a user's future blood glucose level and thus including it in the bolus calculator may prove beneficial to the user. How the relative-IOB is used may vary among implementations: an implementation may choose to combine all IOB or it may consider the human dosed IOB differently from the automated, relative-IOB. The introduction of negative IOB's may further differentiate how different implementations choose to implement the information into their bolus recommendations. Some implementations may consider the negative relative-IOB contributions differently from the positive relative-IOB contributions.

[0078] In other implementations, the previously described automated delivery and associated automated IOB may be replaced with an “overall” delivery and associated overall IOB. In some embodiments, this overall delivery includes both the automated delivery and the manual delivery of insulin scheduled by the user or caregiver. For example, an overall delivery could include a temporary basal rate of x units of insulin per hour that is manually specified to be different from a reference delivery schedule of z units of basal delivery per hour. In these implementations, a relative-IOB for this type of overall delivery is calculated by computing the IOB for both the overall delivery (IOB_overall) and for the reference delivery over the same time period (IOB_reference) and then taking the difference, IOB_overall-IOB_reference to find the relative-IOB to assign to the period of the overall delivery. Typically, the IOB_overall and IOB_reference calculations will include all insulin dosing including basal insulin doses during the time period under consideration. The same calculation may be performed by first taking the difference between the overall delivery and the reference delivery schedules to create a difference-in-delivery schedule. The IOB may be calculated on the difference-in-delivery schedule to compute the relative-IOB for the overall delivery. That is, the relative-IOB calculation holds under the distributive property of mathematics. It will be apparent to those of ordinary skill in this art that other variations to these calculations may be made without departing from the scope and spirit of the appended claims. In some of these implementations, the overall insulin on board value takes into account all insulin delivered to the user prior to a specific time that is believed to not have been completely absorbed by the user prior to that specific time, including any and all basal doses delivered to the user.

[0079] A number of embodiments of the present disclosure have been described. Nevertheless, it will be understood that various modifications may be made without departing from the spirit and scope of the disclosure.

[0080] For example, this specification contains many specific implementation details. However, these should not be construed as limitations on the scope of any inventions or of what may be claimed, but rather as descriptions of features specific to particular embodiments of the present disclosure. Certain features that are described in this specification in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination. Moreover, although features may be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can in some cases be excised from the combination, and the claimed combination may be directed to a subcombination or variation of a subcombination.

[0081] Similarly, while operations are depicted in the drawings and descriptions in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or described, or in sequential order, or that all illustrated or described operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be advantageous. Moreover, the separation of various system components in the embodiments described above should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.

[0082] Processors suitable for the execution of a computer program include, by way of example, both general and special purpose microprocessor structures, and any one or more processors of any kind of digital computer. Generally, a processor will receive instructions and data from a read only memory or a random access memory or both. The elements of a computer are a processor for performing actions in accordance with instructions and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto optical discs, or optical discs. However, a computer need not have such devices. Moreover, a computer can be embedded in another device, e.g., an insulin pump, an electronic pump controller, a continuous glucose monitor, a mobile telephone or a personal digital assistant (PDA), to name just a few.

[0083] Devices suitable for storing computer program instructions and data include all forms of non volatile memory, media and memory devices, including, by way of example, semiconductor memory devices, e.g., EPROM, EEPROM, and flash memory devices; magnetic discs, e.g., internal hard disks or removable disks; magneto optical discs; and CD ROM and DVD-ROM discs. The processor and the memory can be supplemented by, or incorporated in, special purpose logic circuitry.

[0084] To provide for interaction with a user, embodiments of the subject matter described in this specification can be implemented on a computer having a display device, e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor, for displaying information to the user and a keyboard and a pointing device, e.g., a mouse or a trackball, by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback, e.g., visual feedback, auditory feedback, or tactile feedback; and input from the user can be received in any form, including acoustic, speech, or tactile input. In addition, a computer can interact with a user by sending documents to and receiving documents from a device that is used by the user; for example, by sending web pages to a web browser on a user's client device in response to requests received from the web browser. Thus, a user interface of the inventive systems and methods described herein may be remote from a computer-based processor of the system, and may be operated by a user and/or a caregiver.

[0085] Aspects of the disclosure can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment containing both hardware and software elements. In some embodiments, aspects of the disclosure are implemented in software, which includes, but is not limited to, firmware, resident software, microcode, etc. Furthermore, the aspects of the disclosure can take the form of a computer program product accessible from a computer-usable or computer-readable medium providing program code for use by or in connection with a computer or any instruction execution system. For the purposes of this description, a computer-usable or computer-readable medium can be any tangible apparatus that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.

[0086] As used herein, a computer-readable medium or computer-readable storage medium, or the like, is intended to include hardware (e.g., registers, random access memory (RAM), non-volatile (NV) storage, to name a few), but may or may not be limited to hardware. The medium can be an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system (or apparatus or device) or a propagation medium. Examples of a computer-readable medium include a semiconductor or solid state memory, magnetic tape, a removable computer diskette, a random access memory (RAM), a read-only memory (ROM), a rigid magnetic disk and an optical disc. Current examples of optical discs include compact disc-read-only memory (CD-ROM), compact disc-read/write (CD-R/W). Some portions of the detailed description may be presented in terms of algorithms and symbolic representations of operations on data or data bits that may be, for example, within a computer memory. An algorithm is here, and generally, conceived to be a self-consistent sequence of operations leading to a desired result. The operations are those requiring physical manipulations of physical quantities. Usually, though not necessarily, these quantities take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared, and otherwise manipulated. It has proven convenient at times, principally for reasons of common usage, to refer to these signals as bits, values, elements, symbols, characters, terms, numbers, or the like.

[0087] It should be borne in mind, however, that these and similar terms are to be associated with the appropriate physical quantities and are merely convenient labels applied to these quantities. Unless specifically stated otherwise or as apparent from context, it is appreciated that throughout the description, discussions utilizing terms such as “processing” or “computing” or “calculating” or “determining” or “displaying” or the like, refer to the action and processes of a computer system, or similar electronic computing device, computer-based processor, etc., which manipulates and transforms data represented as physical (electronic) quantities within the computer system's registers and memories into other data similarly represented as physical quantities within the computer system's memories or registers or other such information storage, transmission or display devices.

[0088] Other embodiments are within the scope of the appended claims.