Automated Insulin Delivery: The Artificial Pancreas Technical Challenges

Abstract

Background: The automation of glucose control has been an important goal of diabetes treatment for many decades. The first artificial pancreas experiences were in-hospital, closely supervised, small-scale, and short-term studies that demonstrated their superiority over continuous subcutaneous insulin infusion therapy. At present, long-term outpatient studies are being conducted in free-living scenarios. Areas of Uncertainty: The integration of multiple devices increases patients' burden and the probability of technical risks. Control algorithms must be robust to manage disturbance variables, such as physical exercise, meal composition, stress, illness, and circadian variations in insulin sensitivity. Extra layers of safety could be achieved through remote supervision. Dual-hormone systems reduce the incidence and duration of hypoglycemia, but the availability of stable pumpable glucagon needs to be solved. Faster insulin analogues are expected to improve all types of artificial pancreas. Therapeutic Advances: Artificial pancreas safety and feasibility are being demonstrated in outpatient studies. Artificial pancreas use increases the time of sensor-measured glucose in near-normoglycemia and reduces the risk of hyperglycemia and hypoglycemia. The benefits are observed both in single- and dual-hormone algorithms and in full- or semi-closed loop control. A recent meta-analysis including 41 randomized controlled trials showed that artificial pancreas use achieves a reduction of time in hyperglycemia (2 hours less than control treatment) and in hypoglycemia (20 minutes less); mean levels of continuous glucose sensor fell by 8.6 mg/dL over 24 hours and by 14.6 mg/dL overnight. The OpenAPS community uses Do It Yourself artificial pancreas in the real world since 2013, and a recent retrospective cross-over study (n = 20) compared continuous glucose sensor readings before and after initiation: mean levels of blood glucose fell by 7.4 mg/dL over 24 hours and time in range increased from 75.8% to 82.2% (92 minutes more). Conclusions: The outpatient use of artificial pancreas is safe and improves glucose control in outpatients with type 1 diabetes compared with the use of any type of insulin-based treatment. The availability of open-source solutions and data sharing is needed to foster the development of new artificial pancreas approaches and to promote the wide use of Big Data tools for knowledge discovery, decision support, and personalization.

Dual‐hormone artificial pancreas for management of type 1 diabetes: Recent progress and future directions

“…In order to overcome these major challenges to the development of an artificial pancreas that fully reproduces the physiology of the endocrine pancreas, novel approaches under investigation include: (a) the use of more physiological insulin delivery routes (eg, intraperitoneal) and ultra-rapidacting insulin analogs that have enhanced absorption from subcutaneous tissue, 28,29 (b) the need for automated delivery of other hormones in addition to insulin that may better address postprandial hyperglycemia and interprandial hypoglycemia (amylin and glucagon, respectively), 8,30 and (c) the integration of such systems with advanced technologies enabling automated detection of several physiological variables capable of affecting glucose concentrations, such as meal timing and composition, exercise, stress, illnesses, sleep, and circadian variations in insulin sensitivity. 8,16,[31][32][33][34] Yet, the advent of such technologies will take time for the development of robust control algorithms and multivariable adaptive systems able to collect and elaborate information from wearable devices other than glucose sensors. 31,35 Randomized controlled trials and meta-analyses have shown that artificial pancreas systems increase the time spent in target glucose range, reduce time spent in hyperand hypoglycemia, reduce glycated hemoglobin (HbA1c), decrease mean glucose levels and glucose variability, and improve diabetes-specific positive well-being and quality of life compared with conventional insulin pump therapy and sensor-augmented pumps equipped only with low-glucose suspend feature enabling automated suspension of insulin delivery at a threshold glucose level.…”

“…Given these preliminary remarks, current artificial pancreas devices lack fully automated insulin delivery and only partly resemble the physiology of endogenous insulin secretion. In order to overcome these major challenges to the development of an artificial pancreas that fully reproduces the physiology of the endocrine pancreas, novel approaches under investigation include: (a) the use of more physiological insulin delivery routes (eg, intraperitoneal) and ultra‐rapid‐acting insulin analogs that have enhanced absorption from subcutaneous tissue, 28,29 (b) the need for automated delivery of other hormones in addition to insulin that may better address postprandial hyperglycemia and interprandial hypoglycemia (amylin and glucagon, respectively), 8,30 and (c) the integration of such systems with advanced technologies enabling automated detection of several physiological variables capable of affecting glucose concentrations, such as meal timing and composition, exercise, stress, illnesses, sleep, and circadian variations in insulin sensitivity 8,16,31‐34 . Yet, the advent of such technologies will take time for the development of robust control algorithms and multivariable adaptive systems able to collect and elaborate information from wearable devices other than glucose sensors 31,35 …”

Potentialities of Gene Therapy in Pediatric Endocrinology

“…Type 1 diabetes mellitus (T1DM) is an autoimmune disorder characterized by T-cell-mediated self-destruction of insulin-secreting islet β cells. Management of T1DM is challenging and still too frequently suboptimal even with the latest available technologies [10]. Given the strong genetic component of T1D development, gene therapy has emerged as one of the potential therapeutic alternatives to treat T1DM.…”

Generation of Virtual Patient Populations That Represent Real Type 1 Diabetes Cohorts

“…A great amount of research effort has been made in the past few decades to automate the insulin delivery for the treatment of people with T1D, leading to a rapid increase in artificial pancreas (AP) technology. A basic AP system integrates a closed-loop control algorithm, continuous glucose monitoring (CGM), and subcutaneous continuous insulin infusion for optimum blood glucose (BG) control [2]. For pre-clinical testing and validation of therapeutic strategies used in AP technology, various simulators have been developed.…”