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: Disclosed are techniques to establish initial settings for an automatic insulin delivery device. An adjusted total daily insulin (TDI) factor usable to calculate a TDI dosage may be determined. The adjusted TDI factor may be a TDI per unit of a physical characteristic of the user (e.g., weight) times a reduction factor. The adjusted TDI factor may be compared to a maximum algorithm delivery threshold. Based on the comparison result, the application or algorithm may set a TDI dosage and output a control signal. Blood glucose measurement values may be collected from a sensor over a period of time. A level of glycated hemoglobin of the blood may be determined based on the obtained blood glucose measurement values. In response to the level of glycated hemoglobin, the set TDI dosage may be modified. A subsequent control signal including the modified TDI dosage may be output to actuate delivery of insulin.

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: The exemplary embodiments may provide a correction factor (CF) for a user that is dynamically adjustable based on current glucose level. In some exemplary embodiments, the CF of the user is adjusted based on the current glucose level of the user. As the current glucose level of the user increases to be above a threshold, the CF may be adjusted to reflect a decrease in the insulin sensitivity of the user. This adjustment may cause the control system to increase the amount of insulin delivered to the user as the glucose level of the user exceeds the threshold. Similarly, the CF of the user may be adjusted based on the current target glucose level of the user or based on a combination of the current glucose level of the user and the current target glucose level of the user.

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: Exemplary embodiments may configure the glucose cost component of a cost function used in determining basal insulin delivery doses to be limited by the maximum physiological rate of glucose level change over a time period so that the cost function more accurately reflects the physical limits of change due to insulin action, As a result, the glucose cost component of the cost function may more accurately reflect the response of a user to basal insulin deliveries, resulting in better insulin control for the user. Exemplary embodiments may modify the aggressiveness of a control approach based on a current target glucose level versus a nominal target glucose level for which the control approach was designed.

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 are a drug delivery system, a drug delivery device, a controller and a number of techniques to personalize the delivery of a bolus dosage. In an example, a drug delivery system may include a processor and a memory. The memory may be operable to store instructions that, when executed by the processor, cause the processor to receive a request to deliver a bolus dosage, retrieve a history of glucose measurement values, extract features from the history of glucose measurement values, assign a value to extracted features and calculate a personalized factor, and based on the personalized factor or factors, modify a calculation for an amount of a medicament to deliver. Additionally or alternatively, the personalized factor may be used to modify parameter settings of a medicament delivery algorithm. The described systems may track a user's personalized factor over a period of time.

Abstract: The exemplary embodiments may provide a drug delivery device that receives glucose level values for a user (e.g., a diabetic patient) and based on the glucose level values, determines when the user has consumed a meal. In some embodiments, the drug delivery device may calculate an appropriate bolus dose and automatically deliver the drug bolus to the user. In some embodiments, instead of detecting the meal, the user may announce the meal, such as by activating an element on the drug delivery device or on a management device for the drug delivery device. Responsive to the meal announcement, the drug delivery device may calculate the drug bolus dose and deliver the drug bolus. In conjunction with the delivery of the drug bolus, the drug delivery device may relax one or more safety constraints for a relaxation period following the drug bolus delivery so that additional basal drug may be delivered, if needed, under relaxed constraints.

Abstract: Disclosed are a system, methods and computer-readable medium products that provide safety constraints for an insulin-delivery management program. Various examples provide safety constraints for a control algorithm-based drug delivery system that provides automatic delivery of a drug based on sensor input. Glucose measurement values may be received at regular time intervals from a sensor. A processor may predict future glucose values based on prior glucose measurement values. The safety constraints assist in safe operation of the drug delivery system during various operational scenarios. In some examples, predicted future glucose values may be used to implement safety constraints that mitigate under-delivery or over-delivery of the drug while not overly burdening the user of the drug delivery system and without sacrificing performance of the drug delivery system. Other safety constraints are also disclosed.

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: A drug delivery system including a memory storing programming code operable to control delivery of a drug, a user interface operable to accept an input indicating a perceived glucose state of a user, and a processor operable to execute the programming code. When executed, the programming code causes the processor to: receive a perceived state signal from the user interface indicating the perceived glucose state of the user, evaluate the perceived glucose state of the user indicated by the perceived state signal using a glucose measurement value corresponding in time to when the perceived state signal was received, determine an adjustment to a drug delivery algorithm, and utilize the adjustment in a determination of a drug delivery dosage to be administered to a user.

Abstract: The exemplary embodiments may provide a drug delivery device that receives glucose level values for a user (e.g., a diabetic patient) and based on the glucose level values, determines when the user has consumed a meal. In some embodiments, the drug delivery device may calculate an appropriate bolus dose and automatically deliver the drug bolus to the user. In some embodiments, instead of detecting the meal, the user may announce the meal, such as by activating an element on the drug delivery device or on a management device for the drug delivery device. Responsive to the meal announcement, the drug delivery device may calculate the drug bolus dose and deliver the drug bolus. In conjunction with the delivery of the drug bolus, the drug delivery device may relax one or more safety constraints for a relaxation period following the drug bolus delivery so that additional basal drug may be delivered, if needed, under relaxed constraints.

Abstract: Exemplary embodiments provide an approach to predicting meal and/or exercise events for an insulin delivery system that otherwise does not otherwise identify such events. The insulin delivery system may use a model of glucose insulin interactions that projects estimated future glucose values based on the history of glucose values and insulin deliveries for the user. The predictions of meal events and/or exercise events may be based on residuals between actual glucose values and predicted glucose values. The exemplary embodiments may calculate a rate of change of the residuals over a period of time and compare the rate of change to thresholds to determine whether there likely has been a meal event or an exercise event. The insulin delivery system may then take measures to account for the meal or exercise by the user.

Abstract: Disclosed are a system, methods and computer-readable medium products that provide safety constraints for an insulin-delivery management program. Various examples provide safety constraints for a control algorithm-based drug delivery system that provides automatic delivery of a drug based on sensor input. Glucose measurement values may be received at regular time intervals from a sensor. A processor may predict future glucose values based on prior glucose measurement values. The safety constraints assist in safe operation of the drug delivery system during various operational scenarios. In some examples, predicted future glucose values may be used to implement safety constraints that mitigate under-delivery or over-delivery of the drug while not overly burdening the user of the drug delivery system and without sacrificing performance of the drug delivery system. Other safety constraints are also disclosed.

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 techniques to establish initial settings for an automatic insulin delivery device. An adjusted total daily insulin (TDI) factor usable to calculate a TDI dosage may be determined. The adjusted TDI factor may be a TDI per unit of a physical characteristic of the user (e.g., weight) times a reduction factor. The adjusted TDI factor may be compared to a maximum algorithm delivery threshold. Based on the comparison result, the application or algorithm may set a TDI dosage and output a control signal. Blood glucose measurement values may be collected from a sensor over a period of time. A level of glycated hemoglobin of the blood may be determined based on the obtained blood glucose measurement values. In response to the level of glycated hemoglobin, the set TDI dosage may be modified. A subsequent control signal including the modified TDI dosage may be output to actuate delivery of insulin.

Abstract: The present invention discloses a waveform file processing method, storage medium, and device, wherein the method comprises a storage step, and such storage step comprises the following sub-steps: obtain a waveform file that comprises at least one waveform signal; assign a basic index value based on the waveform signal, and adopt the variable-length encoding method to, in a memory, encode the said waveform file as a resolvable serialized structure; when the memory consumed by the serialized structure reaches the threshold, trigger the compression and persistence for the current serialized structure, and obtain the waveform processing file. The present invention uses a unique organization mode to locally or remotely generate a waveform file of a specific format so that the efficiency of subsequent storage, reading, and debugging based on the waveform database file of the said format is significantly improved.

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.