What Is an Artificial Pancreas?
The pancreas is a key organ that maintains glucose homeostasis in the body by producing various hormones including insulin and glucagon.1 In type 1 diabetes, however, the autoimmune destruction of pancreatic b-cells results in insulin deficiency, requiring individuals to rely on exogenous insulin for glucose control.2
An artificial pancreas is a system that aims to mimic the pancreas’ normal function in regulating glucose levels in diabetes.3 It is one of the most advanced technologies used for type 1 diabetes management. An artificial pancreas system consists of three parts: the continuous glucose monitor, the control algorithm, and the insulin pump.2,4,5
- Continuous Glucose Monitor (CGM) – CGMs work by attaching the sensor to the subcutaneous tissue. Continuous data on the rate and direction of change of glucose is provided to the user by the CGM.
- Control Algorithm – An external processor with a control algorithm receives real-time glucose readings from the CGM and can make calculations to dispense the correct dosage of insulin through the insulin pump. There are several different types of control algorithms, but their underlying principles are similar: to correct and predict highs and lows in blood glucose levels.
- Insulin Pump – An insulin pump, also known as the continuous subcutaneous insulin infusion (CSII), subcutaneously delivers insulin based on the dosage set by the control algorithm.
Individuals play an important role in using the artificial pancreas system.2 Although most of the process can be automated with the advancement in technology, user involvement is currently required. For instance, single-hormone (ie, insulin-only) artificial pancreas systems can adjust basal and prandial insulin doses automatically, but they require manual bolus insulin delivery during mealtimes. Dual-hormone (ie, insulin and glucagon) and multi-hormone artificial pancreas systems are also developing, which may allow full automation in the future.6
Benefits of Using the Artificial Pancreas
Diabetes is a complex chronic disease that requires constant self-management and can leave individual feeling overwhelmed with the burdens of self-care.7–10 Studies have shown that this can lead to diabetes distress and other mental health disorders. By allowing partial automation of glucose control, the artificial pancreas system has the potential to alleviate the burdens of self-management while also improving glycemic regulation.11
Meta-analyses and systematic reviews on the use of artificial pancreas have shown favorable results in glycemic control.2 A large number of studies in both the adult and pediatric populations have shown that artificial pancreas results in better meal glucose levels, less time in hypoglycemic and hyperglycemic states, and more time in target glucose range.12–14
Challenges to Using the Artificial Pancreas
Although the artificial pancreas system is one of the most advanced technologies in managing type 1 diabetes, challenges and concerns remain.2 For instance, the CGM obtains glucose readings from the interstitial fluid through sensors in the subcutaneous tissue.4 However, the physiological lag from intravascular to interstitial fluid (which can be up to 10 minutes in individuals with type 1 diabetes) has long been cited as a potential concern in accurately obtaining true glucose levels. Additionally, currently used insulin analogues have a relatively slow onset (10-15 minutes) and prolonged duration of action (4-6 hours), limiting how promptly the artificial pancreas system can address rising glucose levels while avoiding hypoglycemia.2 The development of newer formulations of insulin analogues may help circumvent this issue in the future.
Despite these challenges, the data on the artificial pancreas is promising. The National Institute for Health and Care Excellence recently announced its recommendation of hybrid closed-loop systems – a form of artificial pancreas – in its draft guidance for the management of type 1 diabetes after reviewing evidence from randomized controlled trials and real-world data.15
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