Abstract
People with diabetes face a life-long optimization problem: to maintain strict glycemic control without increasing their risk for hypoglycemia. Since the discovery of insulin in 1921, the external regulation of diabetes by engineering means has became a hallmark of this optimization. Diabetes technology has progressed remarkably over the past 50 years—a progress that includes the development of markers for diabetes control, sophisticated monitoring techniques, mathematical models, assessment procedures, and control algorithms. Continuous glucose monitoring (CGM) was introduced in 1999 and has evolved from means for retroactive review of blood glucose profiles to versatile reliable devices, which monitor the course of glucose fluctuations in real time and provide interactive feedback to the patient. Technology integrating CGM with insulin pumps is now available, opening the field for automated closed-loop control, known as the artificial pancreas. Following a number of in-clinic trials, the quest for a wearable ambulatory artificial pancreas is under way, with a first prototype tested in outpatient setting during the past year. This paper discusses key milestones of diabetes technology development, focusing on the progress in the past 10 years and on the artificial pancreas—still not a cure, but arguably the most promising treatment of diabetes to date.
Highlights
In health, glucose metabolism is tightly controlled by a hormonal network including the gut, the liver, the pancreas, and the brain to ensure stable fasting blood glucose (BG) levels and transient postprandial glucose uctuations
A er entering the circulation, the action of insulin is determined by the dynamics of insulin-mediated glucose utilization—a process that has been mathematically characterized by Bergman and Cobelli’s classic Minimal Model, which introduced the mathematical formulation of insulin sensitivity [15], a key metabolic parameter that has been the subject of investigation of a number of subsequent studies [64,65,66,67,68,69,70]
Several diabetes-speci c metrics are available to serve the analysis of Selfmonitoring of blood glucose (SMBG) data, including the mean amplitude of glucose excursions (MAGE, [112]), the MM-value [113], the lability index [114], and the low and high blood glucose indices (LBGI, HBGI) which re ect the risks associated with hypo- and hyperglycemia, respectively [37, 115]
Summary
Glucose metabolism is tightly controlled by a hormonal network including the gut, the liver, the pancreas, and the brain to ensure stable fasting blood glucose (BG) levels and transient postprandial glucose uctuations In diabetes, this network control is disrupted by de ciency or absence of insulin secretion and/or insulin resistance, which has to be compensated by technological means. In 1977, one of these designs [6] resulted in the rst commercial device—the Biostator [10]—a large (refrigerator-sized) device that has been used extensively for glucose-control research (Figure 1). E nal critical technology leap enabling minimally invasive closed-loop designs was made at the turn of the century with the introduction of continuous glucose monitoring (CGM, [24,25,26])—an event that started the ongoing quest for wearable arti cial pancreas.
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