Abstract: Exemplary embodiments may address the problem of missing blood glucose concentration readings from a glucose monitor that transmits blood glucose concentration readings over a wireless connection due to problems with the wireless connection. In the exemplary embodiments, an automated insulin delivery (AID) device uses an estimate in place of a missing blood glucose concentration reading in determining a predicted future blood glucose concentration reading for a user. Thus, the AID device is able to operate normally in generating insulin delivery settings despite not receiving a current blood glucose concentration reading for a current cycle. There is no need to suspend delivery of insulin to the user due to the missing blood glucose concentration reading.

Abstract: A medicament delivery system, process and techniques are provided. The medicament delivery system may include a wearable medicament delivery device, a memory storing programming instructions, and a processor. The processor may be operable to execute the programming instructions, which cause the processor to receive an available medicament delivery history of a user, and determine whether the available medicament delivery history spans an extent of time greater than a first glucose history duration. The processor, in response to a determination that the extent of time spanned by the available medicament delivery history is greater than the first glucose history duration, determines an average daily medicament delivered. The processor calculates a trust value of the available medicament delivery history, and utilizes the trust value to determine a total daily medicament value of the user.

Abstract: In an aspect, an adhesive patch is presented. The adhesive patch has a top surface configured to adhere to a wearable medical device. The adhesive patch has a bottom surface opposite the top surface, wherein the bottom surface includes an adhesive layer configured to adhere to a user's skin. The adhesive patch has a first perforation extending through the top and bottom surfaces, the first perforation configured to receive a piercing element from the wearable medical device.

Abstract: Exemplary embodiments may address the problem of missing blood glucose concentration readings from a glucose monitor that transmits blood glucose concentration readings over a wireless connection due to problems with the wireless connection. In the exemplary embodiments, an automated insulin delivery (AID) device uses an estimate in place of a missing blood glucose concentration reading in determining a predicted future blood glucose concentration reading for a user. Thus, the AID device is able to operate normally in generating insulin delivery settings despite not receiving a current blood glucose concentration reading for a current cycle. There is no need to suspend delivery of insulin to the user due to the missing blood glucose concentration reading.

Abstract: Disclosed herein are systems and methods for the delivery of a co-formulation of insulin and a second drug, such as GLP-1, using an automated insulin delivery system. In a first embodiment, a dose of insulin is calculated by a medication delivery algorithm and a reduction factor is applied to account for the effect of second drug on the user's daily insulin requirement. In a second embodiment of the invention, a total amount of the second drug administered to the user during the past 24 hours is used to modify the correction factor and the insulin-to-carbohydrate ratio used by the medication delivery algorithm to cause a reduction in the insulin delivered to the user to account for the effect of the administration of the second drug portion of the co-formulation.

Abstract: Disclosed herein are systems and methods for the delivery of a co-formulation of insulin and a second drug, such as GLP-1, using an automated insulin delivery system. In a first embodiment, a dose of insulin is calculated by a medication delivery algorithm and a reduction factor is applied to account for the effect of second drug on the user's daily insulin requirement. In a second embodiment of the invention, a total amount of the second drug administered to the user during the past 24 hours is used to modify the correction factor and the insulin-to-carbohydrate ratio used by the medication delivery algorithm to cause a reduction in the insulin delivered to the user to account for the effect of the administration of the second drug portion of the co-formulation.

Abstract: The exemplary embodiments attempt to identify impending hypoglycemia and/or hyperglycemia and take measures to prevent the hypoglycemia or hyperglycemia. Exemplary embodiments may provide a drug delivery system for delivering insulin and glucagon as needed by a user of the drug delivery system. The drug delivery system may deploy a control system that controls the automated delivery of insulin and glucagon to a patient by the drug delivery system. The control system seeks among other goals to avoid the user experiencing hypoglycemia or hyperglycemia. The control system may employ a clinical decision support algorithm as is described below to control delivery of insulin and glucagon to reduce the risk of hypoglycemia or hyperglycemia and to provide alerts to the user when needed. The control system assesses whether the drug delivery system can respond enough to avoid hypoglycemia or hyperglycemia and generates alerts when manual action is needed to avoid hypoglycemia or hyperglycemia.

Abstract: Disclosed are processes and techniques implementable by a drug delivery system to maintain optimal drug delivery for a patient according to a treatment plan. The disclosed techniques enable a new drug delivery device that is exchanged for a previous drug delivery device to operate using analyte-based drug delivery control immediately during initialization instead of having to wait for a warm-up period. For example, a drug delivery device may include a processor and a memory storing instructions that, when executed by the processor, operate the drug delivery device to receive a present analyte measurement value from an analyte sensor during an initialization of the drug delivery device, receive backfill values measured by the analyte sensor prior to the initialization, calculate a dosage of a drug using the present analyte measurement value and the backfill values, and deliver the dosage of the drug. Other embodiments are described.

Abstract: Disclosed are a device, system, methods and computer-readable medium products that provide an updated insulin-to-carbohydrate ratio and an updated total daily insulin. The described processes may be used for periodic updating of the insulin-to-carbohydrate ratio and the total daily insulin. The insulin-to-carbohydrate ratio and/or the total may be used in the calculation of new doses of insulin that a drug delivery device may be commanded to deliver to a user.

Abstract: A wearable drug delivery device, techniques, and computer-readable media that provide an application that implements a diabetes treatment plan for a user are described. The drug delivery device may include a controller operable to direct operation of the wearable drug delivery device. The controller may provide a selectable activity mode of operation for the user. Operation of the drug delivery device in the activity mode of operation may reduce a likelihood of hypoglycemia during times of increased insulin sensitivity for the user and may reduce a likelihood of hyperglycemia during times of increased insulin requirements for the user. The activity mode of operation may be manually activated by the user or may be activated automatically by the controller. The controller may automatically activate the activity mode of operation based on a detected activity level of the user and/or a detected location of the user.

Abstract: Compensation may be provided for the varying accuracy levels of a sensor over time. As a result of the compensation, the medicament delivery device may perform better. The sensor may provide input to a medicament delivery device, and the input may be used to determine a dose of medicament to be delivered to a user by the medicament delivery device. A degree of inaccuracy of sensor values may be determined based on when in the lifetime a sensor value is generated. Glucose level values read by a glucose monitor, such as a CGM, may be directly modified before being used by an automated insulin delivery (AID) control of an insulin delivery device. The compensation for the inaccuracy of the glucose level values from the glucose monitor instead may be achieved by modifying a weight coefficient of a glucose cost component of a cost function in one example.

Abstract: The exemplary embodiments attempt to identify impending hypoglycemia and/or hyperglycemia and take measures to prevent the hypoglycemia or hyperglycemia. Exemplary embodiments may provide a drug delivery system for delivering insulin and glucagon as needed by a user of the drug delivery system. The drug delivery system may deploy a control system that controls the automated delivery of insulin and glucagon to a patient by the drug delivery system. The control system seeks among other goals to avoid the user experiencing hypoglycemia or hyperglycemia. The control system may employ a clinical decision support algorithm as is described below to control delivery of insulin and glucagon to reduce the risk of hypoglycemia or hyperglycemia and to provide alerts to the user when needed. The control system assesses whether the drug delivery system can respond enough to avoid hypoglycemia or hyperglycemia and generates alerts when manual action is needed to avoid hypoglycemia or hyperglycemia.

Abstract: A drug delivery system including a memory storing programming code operable to enable delivery of insulin and a processor operable to execute the programming code. When executed, the programming code causes the processor to: calculate a first aggregate insulin-on-board amount for a user based on a plurality of individual insulin-on-board estimates made over a first period of time, determine that the first aggregate insulin-on-board amount is greater than a maximum depot formation threshold amount, determine a first residual amount of insulin remaining in the first aggregate insulin-on-board amount, increase a subsequent calculation of an individual insulin-on-board estimate based on the first residual amount of insulin, and utilize the subsequent calculation of the individual insulin-on-board estimate in a calculation of a second aggregate insulin-on-board amount over a second period of time.

Abstract: Invasive glucose sensors and noninvasive glucose sensors may be used in conjunction to improve glucose management for a user. The rate of change (ROC) of glucose levels from a noninvasive glucose sensor may be used rather than or in conjunction with a glucose level of the user from a CGM. A basal insulin delivery rate to the user may be adjusted responsive to the ROC glucose level data from the noninvasive sensor. The glucose level ROC from a noninvasive glucose sensor may be used to predict future glucose level ROCs of the user between operational cycles of an insulin delivery device and/or to identify possible hypoglycemic or hyperglycemic events. These predicted future glucose level ROCs may be used in a cost function of the control system of the insulin delivery device to select basal insulin delivery doses. Glucose level readings may be used to calibrate a noninvasive glucose level sensor.

Abstract: Disclosed are a device, system, methods and computer-readable medium products that provide an updated insulin-to-carbohydrate ratio and an updated total daily insulin. The described processes may be used for periodic updating of the insulin-to-carbohydrate ratio and the total daily insulin. The insulin-to-carbohydrate ratio and/or the total may be used in the calculation of new doses of insulin that a drug delivery device may be commanded to deliver to a user.

Abstract: Disclosed are techniques, devices and systems that provide adjustments to parameter settings of an insulin delivery algorithm based on inputs from a number of generic sensor devices. A majority of the generic sensor devices provide sensor readings that are unused as inputs to a drug deliver algorithm. The generic sensor devices may be operable to detect characteristics, such as changes in a state of a user. A processor may evaluate a sensor reading provided by a particular sensor with respect to a sensor baseline reading for the particular sensor. Using the result of the evaluation, the processor may calculate an adjustment to a parameter setting or settings of a medication delivery algorithm. A dosage of medication may be modified based on the adjustment of the parameter setting or settings.

Abstract: Safety and accuracy measures may be provided in a medicament delivery device. The medicament delivery device may be able to identify the inadvertent delivery of duplicate medicament boluses by a user. The exemplary embodiments may set limits for maximum allowable medicament bolus doses and maximum cumulative bolus doses over an interval. The exemplary embodiments may provide automatic meal detection and may use detection of meals in determining whether a user-requested medicament bolus dose should be adjusted or rejected. The exemplary embodiments may facilitate delivery of partial boluses and the delivery of remainders of the boluses contingent on acceptable glucose level trends of the user. The exemplary embodiments may resolve potential conflicts among multiple medicament delivery devices via a broker or by providing a single actor, such as a medicament delivery controller, that has sole control of dosing and delivery of medicament boluses.

Abstract: Disclosed are techniques, devices and systems that modify an insulin delivery schedule based on how sensitive a diabetic user may to fluctuations in their total daily insulin or fluctuations in their blood glucose measurement values. As a control algorithm calculates how to adapt the calculation of the user's total daily insulin, a rate of adaptivity function may be used in the calculation. The rate of adaptivity may depend on a number of factors and the disclosed techniques, devices and systems enable calculation of the rate of adaptivity to provide effective implementation or modification of a diabetic treatment plan.

Abstract: Exemplary embodiments may determine anticipated basal insulin delivery action to a user from an insulin delivery device over a future time window. Indications of the anticipated basal insulin delivery action over the future time window may be output to the user. The exemplary embodiments may determine the anticipated basal insulin delivery action over the future time window based on a rate of change (ROC) of glucose level of the user by the insulin delivery device, a most recent (“current”) glucose level for the user and insulin on board (IOB) for the user. The exemplary embodiments may also determine whether the user is likely to experience a undesired high glucose level (e.g., hyperglycemia) and/or an undesired low glucose level (e.g., hypoglycemia) during the future time window. The exemplary embodiments may output recommendations based on the projected glucose levels of the user over the future time window.

Abstract: Disclosed are techniques, devices and systems that obtain a glucose measurement history and a liquid drug delivery history. An expected drug delivery amount may be calculated based on the obtained glucose measurement history and the obtained liquid drug delivery history. A processor may calculate a plurality of respective drug delivery amounts implemented using different advisory mode algorithms. A respective advisory drug delivery amount of the plurality of respective advisory drug delivery amounts may be selected by the processor. A recommendation may be generated based on the selected respective advisory drug delivery amount.