Fully Integrated Artificial Pancreas in Type 1 Diabetes

Modular Closed-Loop Glucose Control Maintains Near Normoglycemia

Marc Breton; Anne Farret; Daniela Bruttomesso; Stacey Anderson; Lalo Magni; Stephen Patek; Chiara Dalla Man; Jerome Place; Susan Demartini; Simone Del Favero; Chiara Toffanin; Colleen Hughes-Karvetski; Eyal Dassau; Howard Zisser; Francis J. Doyle III; Giuseppe De Nicolao; Angelo Avogaro; Claudio Cobelli; Eric Renard; Boris Kovatchev


Diabetes. 2012;61(9):2230-2237. 

In This Article


These two randomized crossover studies of CLC in type 1 diabetic patients demonstrate 1) the feasibility of fully integrated subcutaneous CLC in a clinical setting, 2) the utility of modular architecture for designing different CLC system functional configurations, 3) the ability of two CTR algorithms to provide increased safety and effectiveness of glucose control as compared with CSII managed by the patients, and 4) the ability of CTR to mitigate hypoglycemia even when challenged by exercise, particularly overnight.

In terms of feasibility, we showed that fully integrated CLC can be accomplished in the clinic using Insulet Omnipod and Dexcom Seven Plus (or Abbott Free Style Navigator) CGM connected to a laptop running the APS software and a CTR algorithm. One path toward CLC systems suitable for outpatient use can be charted by our modular approach: starting with a relatively simpler SSM operating alone, then adding more complex range control modules, and ultimately moving to control to target to approximate glycemic excursions in health. In addition to validated algorithmic components, initial outpatient studies will likely require back-end servers and communication tools for remote monitoring and intervention. Finally, to cope with the changing environmental conditions and with the physiological/behavioral changes of the patient, the future ambulatory artificial pancreas will have to adapt to the changes in an individual's biobehavioral parameters over time. Possible methods to cope with changing daily conditions include individual controller calibration strategies and run-to-run control algorithms,[31,32] as well as behavioral analysis and profiling of patient lifestyle.[33,34] These approaches find their natural application in the upper layer of the modular architecture.

The two CTR systems tested here share the same lower architectural layer (SSM) but differ in the middle layer (range control module). In particular, sCTR is designed as an adjunct to CSII therapy: it operates only when the patient's risk for hypo- or hyperglycemia warrants adjustment of insulin delivery and resumes the usual CSII treatment when the danger has passed. eCTR includes the same safety module as sCTR but augmented by insulin-on-board constraints[29] and a range control module, based on MPC. eCTR aims to achieve tight glycemic control via take over of patient management of CSII (i.e., it is designed to control basal rate and to leave residual interaction only to trigger premeal insulin boluses, with insulin amount automatically calculated based on an estimate of meal intake).

As intended, sCTR improved patient safety, as shown by a significant decrease in the frequency of hypoglycemic events, and at the same time increased the time spent in near normoglycemia. This improvement was most prominent for patients with suboptimal CSII self-therapy: when we compared patients with below- versus above-median time in near normoglycemia on CSII, we determined that patients in poor control had greater benefits increasing their time in near normoglycemia from 39.5 to 65.4% (P = 0.002), while patients with a better control maintained their time in near normoglycemia (80.9 vs. 82.6%). In other words, sCTR was most beneficial for subjects with poorer glycemic control at baseline.

In eCTR, the combination of a safety and an aggressive range control reduced significantly the average glucose, as well as glucose variability overnight—results not reported to date with CLC (Figs. 4 and 5, upper panels)—and achieved close to 100% time within target range overnight and nearly 80% time spent within the tight range of 4.4–7.8 mmol/L. It is important to note that eCTR reduced simultaneously average glycemia and glucose variability, which suggests that improved glycemic control would be possible using eCTR without concurrent increase in the risk for hypoglycemia.

Previous studies report significant increase in time within target overnight[15] and reduction in glucose variability as shown by a recent across-trial meta-analysis.[35] The studies presented here are therefore a step forward in the advancement of CLC, reporting improvement in both average glucose and glucose variability. Despite differences in control architecture and experimental protocol, it is also worthwhile to compare our results with those reported in a 24-h study of CLC using insulin and glucagon without premeal boluses.[16] In a first set of experiments that had comparable mean BG (7.8–8.3 mmol/L), 5 out of 11 subjects in that study (44%) experienced hypoglycemia despite glucagon injection.[16] Here we show that the SSM was similarly effective in preventing hypoglycemia without glucagon use: in our study 1, a total of 8 out of 25 patients (32%) experienced hypoglycemia during closed loop. Of note, in a second set of experiments, the glucagon system prevented all hypoglycemic events, but at the expense of increasing average glucose to 9.1 mmol/L.[16]

It should also be noted that interday metabolic variations could lead to different outcomes in the same patient tested twice. This effect artificially increases variability during statistical analysis and can result in nonsignificant findings, particularly with a small number of subjects (such as in study 2). This limitation is intrinsic to pilot studies and cannot be avoided without multiple repeated admissions, both in open and closed loop for each subject, or without long-term outpatient experiments. Other limitations of the research presented here include short-term hospital-based studies, exact meal timing and balanced food composition, and standardized exercise. While these limitations, to a large extent, are mitigated by the randomized crossover design of our protocols, all of them gradually will be surmounted in subsequent work.

In conclusion, sCTR and eCTR represent sequential modular approaches toward and tightening of automated glycemic control. Therefore, specific clinical applications for each algorithm configuration can be speculated: for example, patients with both poor control and high BG variability, particularly at night, would benefit from using sCTR. In contrast, patients who are in good self-control with CSII, but who wish to further improve their therapy, would be potential candidates for eCTR. In other words, the modular approach to APSs prompts a compelling new concept: assembly from available modules of CLC algorithms tailored to individual patient needs. Further outpatient studies in larger patient groups and with longer duration therefore will be needed to bring CLC into mainstream clinical practice. Nevertheless, we believe that the modular CTR approach proposed here is an important step toward the development of a viable artificial pancreas, a foundation for stepwise deployment of CLC in home-based studies, and of high relevance to the future treatment of type 1 diabetes aiming to improve quality of life and prevention of long-term complications.