Literature DB >> 21493666

Closed loop control for type 1 diabetes.

Boris Kovatchev.   

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Year:  2011        PMID: 21493666      PMCID: PMC3230108          DOI: 10.1136/bmj.d1911

Source DB:  PubMed          Journal:  BMJ        ISSN: 0959-8138


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In the linked randomised crossover studies (doi:10.1136/bmj.d1855), Hovorka and colleagues compare the safety and efficacy of overnight closed loop insulin delivery with conventional insulin pumps in adults with type 1 diabetes.1 Automated closed loop control, known as an “artificial pancreas,” has the potential to greatly improve the health and lives of people with type 1 diabetes. The idea is not new—it can be traced back to developments that took place decades ago, when studies using intravenous glucose measurement and infusion of insulin and glucose showed that external blood glucose regulation was possible.2 3 Although these systems resulted in excellent glucose control, they were cumbersome and unsuitable for long term or outpatient use.4 5 With the advent of minimally invasive subcutaneous continuous glucose monitoring, research and drug company efforts have been focused on the development of subcutaneous artificial pancreas systems. These systems link a continuous glucose monitor and a subcutaneous insulin infusion pump via a control algorithm, which retrieves continuous glucose monitoring data in real time (for example, every five minutes) and uses a mathematical formula to compute insulin delivery rates that are then transmitted to the insulin pump.6 So far, several studies have reported encouraging results.7 8 9 10 Almost all of the studies reported that closed loop control was better than standard insulin infusion pump treatment in terms of three outcomes: increased time within a target range, reduced incidence of hypoglycaemia, and better overnight control. Hovorka and colleagues report two randomised crossover clinical trials that looked at 24 adults with type 1 diabetes to compare the safety and efficacy of overnight closed loop insulin delivery with that of conventional insulin pump therapy. The two protocols used a medium sized meal (60 g carbohydrate) or a large size meal (100 g carbohydrate plus alcohol). As in previous studies, closed loop insulin delivery significantly increased the time that plasma glucose was in the target range (3.91-8.0 mmol/L). In the context of ongoing research these trials have several new features: Firstly, the randomised crossover trial design is virtually unique in the field of closed loop control. Because this design is the gold standard for clinical research, the results set a benchmark for future studies. The only other randomised controlled trial of closed loop control was recently presented at the 4th International Conference on Advanced Technologies and Treatments for Diabetes.11 This study recruited 24 adults and adolescents with type 1 diabetes in the United States and in France and achieved results similar to those reported by Hovorka and colleagues—more time within the target range of 3.9-10 mmol/L and a threefold reduction in hypoglycaemia. Secondly, the control algorithm used by Hovorka and colleagues belongs to an advanced class of closed loop control technologies known as model predictive control. Algorithm designs for closed loop control have generally used either proportional-integral-derivative control6 7 or model predictive control.8 9 10 Proportional-integral-derivative control algorithms are reactive, responding to changes in glucose levels with adjustment in insulin delivery. Model predictive control algorithms are built over a model of the human metabolic system. Such algorithms are therefore proactive and insulin can be delivered in anticipation of changes in glucose concentrations. This compensates partially for the time delays inherent in subcutaneous glucose control (the time delay in insulin action, which can amount to 60 minutes or more). For this reason, model predictive control has become the approach of choice more recently. The algorithm developed by Hovorka and colleagues has certain distinct features, such as real time adaptation of the underlying model to changing patient parameters implemented as a selection from several predefined models. However, because details have not been given in this or in previous publications,8 this potential advantage remains to be evaluated. Thirdly, this is one of the first studies to test realistic meal scenarios and challenge the participants with a large dinner that included alcohol. As such, the study is a clear advance in the quest for an ambulatory artificial pancreas. However, as the authors admit, one limitation is the exclusively manual control of the closed loop control system. The closed loop control system relied on study personnel to transmit data manually from the continuous glucose monitor to the computer running the closed loop control, and to transmit insulin injection recommendations from the computer to the insulin pump. In fully automated systems these processes are handled by data transmission and pump control devices, respectively. The authors used manual control in their previous trials for well known reasons, including technological and regulatory barriers.8 However, manual transfer of continuous glucose monitoring data and manual control of the insulin pump place human factors into the closed loop control system and limit the investigation to testing only the control algorithm, not the closed loop control system as a whole. The testing of other key components, such as sensor-pump communication and error mitigation, would require much more effort and thorough system validation. Studies using fully automated systems have already been reported and offer hope for the future of ambulatory systems. 6 7 11 12 Finally, despite the sophistication of the control algorithm and the significant reduction in nocturnal hypoglycaemia, four episodes of severe hypoglycaemia (<3mmol/L) occurred, three of which the authors thought were attributable to the preceding prandial insulin dose and could not be prevented by the closed loop suspending insulin delivery. This finding reinforces the recently proposed idea that a dedicated hypoglycaemia safety system—a separate algorithm responsible solely for the assessment and mitigation of the risk of hypoglycaemia—may need to accompany closed loop control.12 Such safety systems already exist, and have proved useful.11 12 In conclusion, closed loop control is in its infancy, with the first in-clinic studies now being reported. Preliminary results have been promising—the most notable improvement is in overnight control of type 1 diabetes, with improvements in safety and a reduction in nocturnal hypoglycaemia being reported. These improvements result from the fine adjustment of insulin delivery provided by closed loop control overnight being superior to a generally fixed basal rate and less likely to cause hypoglycaemia. The first application of closed loop control is therefore likely to be in glucose regulation overnight, a step that has the potential to improve dramatically the safety of insulin delivery during crucial, generally unsupervised, periods.
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4.  Multinational study of subcutaneous model-predictive closed-loop control in type 1 diabetes mellitus: summary of the results.

Authors:  Boris Kovatchev; Claudio Cobelli; Eric Renard; Stacey Anderson; Marc Breton; Stephen Patek; William Clarke; Daniela Bruttomesso; Alberto Maran; Silvana Costa; Angelo Avogaro; Chiara Dalla Man; Andrea Facchinetti; Lalo Magni; Giuseppe De Nicolao; Jerome Place; Anne Farret
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Journal:  Sci Transl Med       Date:  2010-04-14       Impact factor: 17.956

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Journal:  IEEE Trans Biomed Eng       Date:  1981-10       Impact factor: 4.538

7.  Feasibility of automating insulin delivery for the treatment of type 1 diabetes.

Authors:  Garry M Steil; Kerstin Rebrin; Christine Darwin; Farzam Hariri; Mohammed F Saad
Journal:  Diabetes       Date:  2006-12       Impact factor: 9.461

8.  Manual closed-loop insulin delivery in children and adolescents with type 1 diabetes: a phase 2 randomised crossover trial.

Authors:  Roman Hovorka; Janet M Allen; Daniela Elleri; Ludovic J Chassin; Julie Harris; Dongyuan Xing; Craig Kollman; Tomas Hovorka; Anne Mette F Larsen; Marianna Nodale; Alessandra De Palma; Malgorzata E Wilinska; Carlo L Acerini; David B Dunger
Journal:  Lancet       Date:  2010-02-04       Impact factor: 79.321

9.  Fully automated closed-loop insulin delivery versus semiautomated hybrid control in pediatric patients with type 1 diabetes using an artificial pancreas.

Authors:  Stuart A Weinzimer; Garry M Steil; Karena L Swan; Jim Dziura; Natalie Kurtz; William V Tamborlane
Journal:  Diabetes Care       Date:  2008-02-05       Impact factor: 19.112

10.  Overnight closed loop insulin delivery (artificial pancreas) in adults with type 1 diabetes: crossover randomised controlled studies.

Authors:  Roman Hovorka; Kavita Kumareswaran; Julie Harris; Janet M Allen; Daniela Elleri; Dongyuan Xing; Craig Kollman; Marianna Nodale; Helen R Murphy; David B Dunger; Stephanie A Amiel; Simon R Heller; Malgorzata E Wilinska; Mark L Evans
Journal:  BMJ       Date:  2011-04-13
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1.  Report from IPITA-TTS Opinion Leaders Meeting on the Future of β-Cell Replacement.

Authors:  Stephen T Bartlett; James F Markmann; Paul Johnson; Olle Korsgren; Bernhard J Hering; David Scharp; Thomas W H Kay; Jonathan Bromberg; Jon S Odorico; Gordon C Weir; Nancy Bridges; Raja Kandaswamy; Peter Stock; Peter Friend; Mitsukazu Gotoh; David K C Cooper; Chung-Gyu Park; Phillip OʼConnell; Cherie Stabler; Shinichi Matsumoto; Barbara Ludwig; Pratik Choudhary; Boris Kovatchev; Michael R Rickels; Megan Sykes; Kathryn Wood; Kristy Kraemer; Albert Hwa; Edward Stanley; Camillo Ricordi; Mark Zimmerman; Julia Greenstein; Eduard Montanya; Timo Otonkoski
Journal:  Transplantation       Date:  2016-02       Impact factor: 4.939

2.  DiAs user interface: a patient-centric interface for mobile artificial pancreas systems.

Authors:  Patrick Keith-Hynes; Stephanie Guerlain; Benton Mize; Colleen Hughes-Karvetski; Momin Khan; Molly McElwee-Malloy; Boris P Kovatchev
Journal:  J Diabetes Sci Technol       Date:  2013-11-01

Review 3.  Closed-loop glucose control: psychological and behavioral considerations.

Authors:  Linda Gonder-Frederick; Jaclyn Shepard; Ninoska Peterson
Journal:  J Diabetes Sci Technol       Date:  2011-11-01

Review 4.  A review of artificial pancreas technologies with an emphasis on bi-hormonal therapy.

Authors:  P A Bakhtiani; L M Zhao; J El Youssef; J R Castle; W K Ward
Journal:  Diabetes Obes Metab       Date:  2013-04-21       Impact factor: 6.577

5.  The MAFB transcription factor impacts islet α-cell function in rodents and represents a unique signature of primate islet β-cells.

Authors:  Elizabeth Conrad; Chunhua Dai; Jason Spaeth; Min Guo; Holly A Cyphert; David Scoville; Julie Carroll; Wei-Ming Yu; Lisa V Goodrich; David M Harlan; Kevin L Grove; Charles T Roberts; Alvin C Powers; Guoqiang Gu; Roland Stein
Journal:  Am J Physiol Endocrinol Metab       Date:  2015-11-10       Impact factor: 4.310

6.  Safety of outpatient closed-loop control: first randomized crossover trials of a wearable artificial pancreas.

Authors:  Boris P Kovatchev; Eric Renard; Claudio Cobelli; Howard C Zisser; Patrick Keith-Hynes; Stacey M Anderson; Sue A Brown; Daniel R Chernavvsky; Marc D Breton; Lloyd B Mize; Anne Farret; Jérôme Place; Daniela Bruttomesso; Simone Del Favero; Federico Boscari; Silvia Galasso; Angelo Avogaro; Lalo Magni; Federico Di Palma; Chiara Toffanin; Mirko Messori; Eyal Dassau; Francis J Doyle
Journal:  Diabetes Care       Date:  2014-06-14       Impact factor: 19.112

7.  Design of dual hormone blood glucose therapy and comparison with single hormone using MPC algorithm.

Authors:  Cifha Crecil Dias; Surekha Kamath; Sudha Vidyasagar
Journal:  IET Syst Biol       Date:  2020-10       Impact factor: 1.615

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