Abstract: Systems and methods are provided for adjusting a standing insulin medicament dosage regimen for a subject. Fasting events are Device for adjusting a standing insulin regimen identified using autonomous timestamped glucose measurements of the subject in a first data set. A second data set, from one or more insulin pens used to apply the standing regimen, comprises records, each record comprising a timestamped event specifying an amount of injected insulin medicament. Each fasting event is characterized as adherent or nonadherent. A fasting event is adherent when the second data set includes one or more records that temporally and quantitatively establish adherence with the standing regimen during the fasting event. Conversely, a fasting event is nonadherent when the second data set fails to temporally and quantitatively establish adherence with the standing regimen.

Abstract: A device, system and method is provided for predicting risk of hypoglycemia and adjusting an insulin medicament dose size for a subject being on pen based multi-daily injections. A first algorithm is provided for computing a first insulin dose size based on a plurality of timestamped blood glucose (BG) measurements and insulin injected dose sizes. A risk prediction module is adapted to, based on machine learning algorithms, predict risk of hypoglycemia based on the timestamped BG measurements and calculate a second insulin dose size resulting in a non-hypoglycemic state. In case the second dose size is lower than the first dose size, the first dose size is automatically adjusted down to the second dose size and communicated as the recommended dose size to the subject.

Abstract: A subject is prescribed short and long acting insulin medicament regimens. When a qualified fasting event occurs, the basal insulin sensitivity estimate of the subject is updated using (i) an expected fasting blood glucose level based upon the long acting insulin medicament dosing specified by the long acting regimen during the fasting event, (ii) glucose measurements contemporaneous with the fasting event and (iii) a prior insulin sensitivity factor. A basal insulin sensitivity factor curve is calculated from the updated basal insulin sensitivity estimate. A bolus insulin sensitivity estimate of the subject is updated upon occurrence of a correction bolus with a short acting insulin medicament using (i) an expected blood glucose level based upon the correction bolus, (ii) glucose measurements after occurrence of the correction bolus, and (iii) a prior insulin sensitivity factor. A bolus insulin sensitivity factor curve is calculated from the updated bolus insulin sensitivity estimate.

Abstract: System and methods are disclosed for monitoring adherence to a prescribed insulin regimen for a subject. A data set comprising a plurality of metabolic events the subject engaged is obtained. Each metabolic event comprises a timestamp of the event and a first classification that is one of insulin regimen adherent and nonadherent. Each respective metabolic event is then further classified using a second classification, based upon the timestamp of the metabolic event. The second classification has a temporal periodicity represented by a plurality of periodic elements. Metabolic events are binned on the basis of the second classification thereby obtaining a plurality of subsets of the metabolic events, each subset for a different periodic element. For each respective subset, a respective representation of adherence to the insulin regimen is communicated, the representation of adherence being collectively based upon the first classification of metabolic events in the respective subset.

Abstract: Systems and methods for communicating a dose history configured for representing an average and a variability of a distribution of injections with a blood glucose regulating medicament applied by a subject with a treatment regimen. Past records are obtained from insulin pens applying the treatment regimen. Each record specifies an amount and type of medicament injected, the type being one of a blood glucose regulating medicament, and a timestamp. Assigning single-shape polygons (231) to each record, wherein single-shape polygons (231) is configured for visualizing a polygon (261) with a two-dimensional shape, in a displayed mode. The single-shape polygons are used to create a set of multi-shape data structures comprising corresponding multi-shape polygons (244), configured for visualizing a polygon (265) with a two-dimensional shape, in the displayed mode (260).

Abstract: Systems and methods for treating a subject are provided. A first dataset comprising timestamped autonomous glucose measurements of the subject over a first time course is obtained. A second dataset, associated with a standing insulin regimen for the subject over the first time course and comprising insulin medicament records, is also obtained. Each record comprises a timestamped administration event including an amount and type of insulin medicament administered into the subject by an insulin delivery device. The first and second datasets serve to calculate a glycaemic risk measure and an insulin sensitivity factor of the subject during the first time course, which are used to obtain a basal rate titration schedule and a fasting blood glucose profile model over a subsequent second time course for the subject. The model predicts the fasting blood glucose level of the subject based upon amounts of insulin medicament administered into the subject.

Abstract: A device (250) for estimating the risk of a future hypoglycemic event for a subject with a standing insulin regimen (206), wherein the standing insulin regimen comprises one or more types of insulin medicament dosage regimen (208), wherein each of the one or more types of insulin medicament dosage regimen (208) comprises a type of insulin medicament (210) defining one or more types of insulin medicaments. Using the evaluation of a glucose concentration, a first time derivative and an insulin on board for the subject in a current metabolic state, and the evaluation of a glucose concentration, a first derivative and a historical insulin on board to estimate a hypoglycemic risk measure.

Abstract: A subject is prescribed short and long acting insulin medicament regimens. When a qualified fasting event occurs, the basal insulin sensitivity estimate of the subject is updated using (i) an expected fasting blood glucose level based upon the long acting insulin medicament dosing specified by the long acting regimen during the fasting event, (ii) glucose measurements contemporaneous with the fasting event and (iii) a prior insulin sensitivity factor. A basal insulin sensitivity factor curve is calculated from the updated basal insulin sensitivity estimate. A bolus insulin sensitivity estimate of the subject is updated upon occurrence of a correction bolus with a short acting insulin medicament using (i) an expected blood glucose level based upon the correction bolus, (ii) glucose measurements after occurrence of the correction bolus, and (iii) a prior insulin sensitivity factor. A bolus insulin sensitivity factor curve is calculated from the updated bolus insulin sensitivity estimate.

Abstract: Systems and methods are provided for optimizing short acting insulin medicament dosage timing relative to a meal event for a subject. Glucose measurements of the subject over a time course and the timing of the measurements are obtained. Meal events in the time course and information regarding when dosages were injected into the subject relative to the meal events is obtained. Bins, each for a different time range for when a dosage is injected relative to a meal event, are constructed. Each bin is assigned glucose measurements in one or more periods within the time course in which the subject injected the dosage within the time range associated with the bin. A glycaemic risk measure is determined for each bin with the assigned measurements and used to identify an optimal relative time range for the subject. This is communicated to a health care practitioner or to the subject.

Abstract: Systems and methods for treating a subject are provided. A first dataset comprising timestamped autonomous glucose measurements of the subject over a first time course is obtained. A second dataset, associated with a standing insulin regimen for the subject over the first time course and comprising insulin medicament records, is also obtained. Each record comprises a timestamped injection event including an amount and type of insulin medicament injected into the subject by an insulin pen. The first and second datasets serve to calculate a glycaemic risk measure and an insulin sensitivity factor of the subject during the first time course, which are used to obtain a basal titration schedule and a fasting blood glucose profile model over a subsequent second time course for the subject. The model predicts the fasting blood glucose level of the subject based upon amounts of basal insulin medicament injected into the subject.

Abstract: Systems and methods for adjusting a short acting dosage for a prospective meal for a subject with a standing regimen are provided. The standing regimen comprises short acting and long acting regimens. Past records are obtained from insulin pens applying the standing regimen. Each record specifies an amount and type of medicament injected, the type being one of short and long acting, and a timestamp. Responsive to the prospective meal at time (t0), total insulin on board (IOBtotal) is calculated as the sum of IOBbolus and IOBbasal, with IOBbolus being the total amount of short acting medicament injected, indicated by records having timestamps within a duration of the short acting medicament to t0, and IOBbasal being the total amount of long acting medicament injected, indicated by records having timestamps within the duration of the long acting medicament to t0. IOBtotal serves to calculate the short acting dosage for the meal.

Abstract: Systems and methods are provided for adjusting a basal/bolus ratio in a standing insulin regimen for a subject that comprises daily amounts of basal and bolus insulin medicaments that define an initial basal/bolus ratio. A data set comprising glucose measurements of the subject with a respective timestamp for each such measurement over a time course is obtained. One or more fasting events are identified in the time course. A temporal glucose gradient is computed for each fasting event using the glucose measurements in the data set within the fasting event time period. Fasting event glucose gradients are used to determine whether to recommend adjustment to the basal/bolus ratio for the subject without change to the daily total insulin medicament. The recommended adjustment to the basal/bolus ratio is communicated when the determination is made to make the recommended adjustment to the basal/bolus ratio for the subject.

Abstract: Systems and methods are provided for monitoring adherence to an insulin medicament dosage regimen for a subject. A data set comprising a plurality of metabolic events the subject engaged in within a period of time is obtained. Each respective metabolic event comprises a timestamp of the event and a characterization that is one of insulin regimen adherent and insulin regimen nonadherent. A plurality of primary adherence values is calculated, each respective adherence value representing a corresponding time window in a plurality of time windows within the period of time. Each time window is of a same first fixed duration. Each respective adherence value is computed by dividing a number of insulin regimen adherent events by a total number of events that have timestamps in the time window corresponding to the respective adherence value. The adherence values across the period of time are communicated thereby monitoring adherence to the insulin regimen.

Abstract: Systems and methods are provided for adjusting long acting insulin medicament dosages for a subject. A plurality of timestamped glucose measurements of the subject and insulin injection data is obtained. A first glycaemic risk measures is determined, where the first risk glycaemic risk measure is i) glucose level variability across the glucose measurements, (ii) a variability in fasting glucose levels calculated from the glucose measurements, (iii) a minimum observed glucose measurement in the plurality of glucose measurements (iv) rate of change in ISF, or (v) adherence values. A fasting blood glucose target function is computed based upon at least the first glycaemic risk measure thereby obtaining an updated target fasting blood glucose level that is between a minimum and maximum target fasting blood glucose level. The long acting insulin medicament dosage is adjusted based upon the updated target fasting blood glucose level.

Abstract: Systems and methods for evaluating insulin medicament dosage regimen adherence by a subject are provided. A description of metabolic events the subject engaged in is obtained. Each event comprises a timestamp and a classification that is one of insulin regimen adherent and insulin regimen nonadherent. Events are binned into consecutive time windows on the basis of time to obtain a plurality of subsets. Adherence values are computed. Each adherence value is for a subset and is computed by dividing the insulin regimen adherent events by the total number of events in the subset. Adherence values are combined into a composite value by a process that comprises downweighting a first adherence value, representing a first time window, with respect to a second adherence value, representing a second time window, when the first time window occurs in time before the second time window. The composite value is communicated as a single representation.