Abstract: A method, system and computer program product for correcting a nominal treatment strategy of a subject with diabetes. The method, system and computer program product may be configured for providing input whereby the input may include: open-loop therapy settings for the subject, data about glycemic state of the subject; and (optionally) data about meals and/or exercise of the subject. The method, system and computer program product may be configured for providing output, whereby the out-put may include an adjustment (correction) to the open-loop therapy settings for the subject for insulin delivery to the subject.

Abstract: In a method of recalibrating continuous glucose monitoring data from a user, operable on a digital processor, an indication from the user that the user has taken a meal is received (806). A self-monitored of blood glucose levels from the user (810) at two separate times during a day corresponding to when the user has taken a meal. A glucose signal is received from a continuous glucose monitoring sensor (818) at times corresponding to the two separate times that the user has taken a meal. Two reconstructed blood glucose values based on the glucose signal from the continuous monitoring sensor at times when the at least two self-monitored of blood glucose levels are received from the user. A linear regression is performed (822) using y=ax+b, wherein x corresponds to the two reconstructed blood glucose values and y corresponds to the two self-monitored of blood glucose levels thereby generating an estimation of a and b.

Abstract: An electronic system is provided that simulates a glucose-insulin metabolic system of a T2DM or prediabetic subject, wherein the system includes a subsystem that models dynamic glucose concentration in a T2DM or prediabetic subject, including an electronic module that models endogenous glucose production (EGP(t)), or meal glucose rate of appearance (Ra(t>>, or glucose utilization (U(t)), or renal excretion of glucose (B(t)), a subsystem that models dynamic insulin concentration in said T2DM or prediabetic subject, including an electronic module that models insulin secretion (S(t)), an electronic database containing a population of virtual T2DM or prediabetic subjects, each virtual subject having a plurality of metabolic parameters, and a processing module that calculates an effect of variation of at least one metabolic parameter value on the glucose insulin metabolic system of a virtual subject by inputting the plurality of metabolic parameter values.

Abstract: A system and method for providing optimal insulin injections to a subject, using a controller, a continuous glucose monitor, and an insulin delivery unit is disclosed. The controller possesses a discrete-time, linear model predictive control law, means for sending information to the insulin delivery unit, and means for receiving information from the CGM. The control law implemented is derived from a discrete-time model of glucose insulin dynamics and an aggressiveness parameter. The result is that using only glucose measurements obtained from sensor readings and, prior values of external insulin infusion and meal and exercise announcement the optimal insulin injection necessary to safely regulate blood glucose can be calculated.

Abstract: A simulation environment for in silico testing of monitoring methods, open-loop and closed-loop treatment strategies in type 1 diabetes. Some exemplary principal components of the simulation environment comprise, but not limited thereto, the following: 1) a “population” of in silico “subjects” with type 1 diabetes in three age groups; 2) a simulator of CGM sensor errors; 3) a simulator of insulin pumps and discrete insulin delivery; 4) an interface allowing the input of user-specified treatment scenarios; and 5) a set of standardized outcome measures and graphs evaluating the quality of the tested treatment strategies. These components can be used separately or in combination for the preclinical evaluation of open-loop or closed-loop control treatments of diabetes.