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Ming W, Guo X, Zhang G, Liu Y, Wang Y, Zhang H, Liang H, Yang Y. Recent advances in the precision control strategy of artificial pancreas. Med Biol Eng Comput 2024; 62:1615-1638. [PMID: 38418768 DOI: 10.1007/s11517-024-03042-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 02/03/2024] [Indexed: 03/02/2024]
Abstract
The scientific diagnosis and treatment of patients with diabetes require frequent blood glucose testing and insulin delivery to normoglycemia. Therefore, an artificial pancreas with a continuous blood glucose (BG) monitoring function is an urgent research target in the medical industry. The problem of closed-loop algorithmic control of the BG with a time delay is a key and difficult issue that needs to be overcome in the development of an artificial pancreas. Firstly, the composition, structure, and control characteristics of the artificial pancreas are introduced. Subsequently, the research progress of artificial pancreas control algorithms is reviewed, and the characteristics, advantages, and disadvantages of proportional-integral-differential control, model predictive control, and artificial intelligence control are compared and analyzed to determine whether they are suitable for the practical application of the artificial pancreas. Additionally, key advancements in areas such as blood glucose data monitoring, adaptive models, wearable devices, and fully automated artificial pancreas systems are also reviewed. Finally, this review highlights that meal prediction, control safety, integration, streamlining the optimization of control algorithms, constant temperature preservation of insulin, and dual-hormone artificial pancreas are issues that require further attention in the future.
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Affiliation(s)
- Wuyi Ming
- Henan Key Lab of Intelligent Manufacturing of Mechanical Equipment, Zhengzhou University of Light Industry, 450002, Zhengzhou, China
| | - Xudong Guo
- Henan Key Lab of Intelligent Manufacturing of Mechanical Equipment, Zhengzhou University of Light Industry, 450002, Zhengzhou, China
| | - Guojun Zhang
- Guangdong HUST Industrial Technology Research Institute, 523808, Dongguan, China
| | - Yinxia Liu
- Prenatal Diagnosis Center of Dongguan Kanghua Hospital, 523808, Dongguan, China
| | - Yongxin Wang
- Zhengzhou Phray Technology Co., Ltd, 450019, Zhengzhou, China
| | - Hongmei Zhang
- Zhengzhou Phray Technology Co., Ltd, 450019, Zhengzhou, China
| | - Haofang Liang
- Zhengzhou Phray Technology Co., Ltd, 450019, Zhengzhou, China
| | - Yuan Yang
- Laboratory of Regenerative Medicine in Sports Science, School of Sports Science, South China Normal University, 510631, Guangzhou, China.
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Danne T, Heinemann L, Bolinder J. New Insulins, Biosimilars, and Insulin Therapy. Diabetes Technol Ther 2022; 24:S35-S57. [PMID: 35475698 DOI: 10.1089/dia.2022.2503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
- Thomas Danne
- Diabetes-Zentrum für Kinder and Jugendliche, Kinder- und Jugendkrankenhaus AUF DER BULT, Hannover, Germany
| | | | - Jan Bolinder
- Department of Medicine, Karolinska University Hospital Huddinge, Karolinska Institutet, Stockholm, Sweden
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Ware J, Hovorka R. Recent advances in closed-loop insulin delivery. Metabolism 2022; 127:154953. [PMID: 34890648 PMCID: PMC8792215 DOI: 10.1016/j.metabol.2021.154953] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2021] [Revised: 11/05/2021] [Accepted: 11/24/2021] [Indexed: 02/03/2023]
Abstract
Since the discovery of insulin 100 years ago, we have seen considerable advances across diabetes therapies. The more recent advent of glucose-responsive automated insulin delivery has started to revolutionise the management of type 1 diabetes in children and adults. Evolution of closed-loop insulin delivery from research to clinical practice has been rapid, and multiple systems are now commercially available. In this review, we summarise key evidence on currently available closed-loop systems and those in development. We comment on dual-hormone and do-it-yourself systems, as well as reviewing clinical evidence in special populations such as very young children, older adults and in pregnancy. We identify future directions for research and barriers to closed-loop adoption, including how these might be addressed to ensure equitable access to this novel therapy.
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Affiliation(s)
- Julia Ware
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom; Department of Paediatrics, University of Cambridge, Cambridge, United Kingdom
| | - Roman Hovorka
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom; Department of Paediatrics, University of Cambridge, Cambridge, United Kingdom.
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Corbett JP, Garcia-Tirado J, Colmegna P, Diaz Castaneda JL, Breton MD. Using an Online Disturbance Rejection and Anticipation System to Reduce Hyperglycemia in a Fully Closed-Loop Artificial Pancreas System. J Diabetes Sci Technol 2022; 16:52-60. [PMID: 34861786 PMCID: PMC8875044 DOI: 10.1177/19322968211059159] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
INTRODUCTION Hyperglycemia following meals is a recurring challenge for people with type 1 diabetes, and even the most advanced available automated systems currently require manual input of carbohydrate amounts. To progress toward fully automated systems, we present a novel control system that can automatically deliver priming boluses and/or anticipate eating behaviors to improve postprandial full closed-loop control. METHODS A model predictive control (MPC) system was enhanced by an automated bolus system reacting to early glucose rise and/or a multistage MPC (MS-MPC) framework to anticipate historical patterns. Priming was achieved by detecting large glycemic disturbances, such as meals, and delivering a fraction of the patient's total daily insulin (TDI) modulated by the disturbance's likelihood (bolus priming system [BPS]). In the anticipatory module, glycemic disturbance profiles were generated from historical data using clustering to group days with similar behaviors; the probability of each cluster is then evaluated at every controller step and informs the MS-MPC framework to anticipate each profile. We tested four configurations: MPC, MPC + BPS, MS-MPC, and MS-MPC + BPS in simulation to contrast the effect of each controller module. RESULTS Postprandial time in range was highest for MS-MPC + BPS: 60.73 ± 25.39%, but improved with each module: MPC + BPS: 56.95±25.83 and MS-MPC: 54.83 ± 26.00%, compared with MPC: 51.79 ± 26.12%. Exposure to hypoglycemia was maintained for all controllers (time below 70 mg/dL <0.5%), and improvement came primarily from a reduction in postprandial time above range (MS-MPC + BPS: 39.10 ± 25.32%, MPC + BPS: 42.99 ± 25.81%, MS-MPC: 45.09 ± 25.96%, MPC: 48.18 ± 26.09%). CONCLUSIONS The BPS and anticipatory disturbance profiles improved blood glucose control and were most efficient when combined.
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Affiliation(s)
- John P. Corbett
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA, USA
- John P. Corbett, PhD, Center for Diabetes Technology, University of Virginia, 560 Ray C. Hunt Drive, Charlottesville, VA 22903, USA.
| | - Jose Garcia-Tirado
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA, USA
| | - Patricio Colmegna
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA, USA
| | | | - Marc D. Breton
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA, USA
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Tsoukas MA, Majdpour D, Yale JF, Fathi AE, Garfield N, Rutkowski J, Rene J, Legault L, Haidar A. A fully artificial pancreas versus a hybrid artificial pancreas for type 1 diabetes: a single-centre, open-label, randomised controlled, crossover, non-inferiority trial. LANCET DIGITAL HEALTH 2021; 3:e723-e732. [PMID: 34580055 DOI: 10.1016/s2589-7500(21)00139-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 06/14/2021] [Accepted: 06/23/2021] [Indexed: 12/20/2022]
Abstract
BACKGROUND For people with type 1 diabetes, there is currently no automated insulin delivery system that does not require meal input. We aimed to assess the efficacy of a novel faster-acting insulin aspart (Fiasp) plus pramlintide fully closed-loop system that does not require meal input. METHODS In this open-label, randomised controlled, crossover, non-inferiority trial we compared the Fiasp (Novo Nordisk, Bagsværd, Denmark) plus pramlintide closed-loop system with no meal input (fully artificial pancreas) and the Fiasp-alone closed-loop system with precise carbohydrate counting (hybrid artificial pancreas). Adults (≥18 years) who had a clinical diagnosis of type 1 diabetes for at least 12 months, had glycated haemoglobin 12% or lower, and had been on insulin pump therapy for at least 6 months were enrolled at McGill University Health Centre, Montreal, QC, Canada. The Fiasp plus pramlintide fully closed-loop system delivered pramlintide in a basal-bolus manner with a fixed ratio of 10 μg:U relative to insulin. A research staff member counted the carbohydrate content of meals to input in the hybrid closed-loop system. Participants completed the two full-day crossover interventions in a random order allocated by a computer-generated code implementing a blocked randomisation (block size of four). The primary outcome was the percentage of time spent within the glucose target range (3·9-10·0 mmol/L), with a 6% non-inferiority margin, assessed in all participants who completed both interventions. This trial is registered with ClinicalTrials.gov, NCT03800875. FINDINGS Between Feb 8, 2019, and Sept 19, 2020, we enrolled 28 adults, of whom 24 completed both interventions and were included in analyses. The percentage of time spent in the target range was 74·3% (IQR 61·5-82·8) with the fully closed-loop system versus 78·1% (66·3-87·5) with the hybrid Fiasp-alone closed-loop system (paired difference 2·6%, 95% CI -2·4 to 12·2; non-inferiority p=0·28). Eight (33%) participants had at least one hypoglycaemia event (<3·3 mmol/L) with the fully closed-loop system compared with 14 (58%) participants with the hybrid closed-loop system (2200-2200 h). Non-mild nausea was reported by three (13%) participants and non-mild bloating by one (4%) participant with the fully closed-loop system compared with zero participants with the hybrid closed-loop system. INTERPRETATION The Fiasp plus pramlintide fully closed-loop system was not non-inferior to the Fiasp-alone hybrid closed-loop system for the overall percentage of time in the glucose target range. However, participants still spent a high percentage of time within the target range with the fully-closed loop system. Outpatient studies comparing the fully closed-loop hybrid systems with patient-estimated, rather than precise, carbohydrate counting are warranted. FUNDING Diabetes Canada.
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Affiliation(s)
- Michael A Tsoukas
- Division of Endocrinology and Metabolism, Royal Victoria Hospital, McGill University Health Centre, Montreal, QC, Canada
| | - Dorsa Majdpour
- Department of Biomedical Engineering, McGill University, Montreal, QC, Canada
| | - Jean-François Yale
- Division of Endocrinology and Metabolism, Royal Victoria Hospital, McGill University Health Centre, Montreal, QC, Canada
| | - Anas El Fathi
- Department of Biomedical Engineering, McGill University, Montreal, QC, Canada
| | - Natasha Garfield
- Division of Endocrinology and Metabolism, Royal Victoria Hospital, McGill University Health Centre, Montreal, QC, Canada
| | - Joanna Rutkowski
- Department of Biomedical Engineering, McGill University, Montreal, QC, Canada
| | - Jennifer Rene
- Department of Biomedical Engineering, McGill University, Montreal, QC, Canada
| | - Laurent Legault
- Division of Endocrinology and Metabolism, Montreal Children's Hospital, McGill University Health Centre, Montreal, QC, Canada
| | - Ahmad Haidar
- Department of Biomedical Engineering, McGill University, Montreal, QC, Canada.
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Ferrito L, Passanisi S, Bonfanti R, Cherubini V, Minuto N, Schiaffini R, Scaramuzza A. Efficacy of advanced hybrid closed loop systems for the management of type 1 diabetes in children. Minerva Pediatr (Torino) 2021; 73:474-485. [PMID: 34309344 DOI: 10.23736/s2724-5276.21.06531-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Over the last years significant advances have been achieved in the development of technologies for diabetes management. Continuous subcutaneous insulin infusion (CSII), continuous glucose monitoring (CGM), predictive low glucose management (PLGM), hybrid closed loop (HCL) and advanced hybrid closed loop (AHCL) systems allow better diabetes management, thus reducing the burden of the disease and the risk of chronic complications. This review summarizes the main characteristics of the currently available HCL and AHCL systems and their primary effects in children and adolescents with type 1 diabetes (T1D). The findings of trials assessing the glucose control (time in range, HbA1c values, hypoglycemic events), the health-related quality of life and the existing limits of the use of these technologies are reported. The most recent data clearly confirm the ability of the HCL and AHCL insulin delivery systems to safely achieve a significant improvement of glucose control and quality of life in the pediatric population with T1D. Further studies are underway to overcame current barriers and future improvements in the usability of these technologies are awaited to facilitate their use in the routine clinical practice. The HCL and AHCL algorithms are the key features of today's insulin delivery systems that mark a crucial step towards fully automated closed loop systems.
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Affiliation(s)
- Lucia Ferrito
- Division of Pediatrics and Neonatology, Senigallia Hospital, Senigallia, Ancona, Italy
| | - Stefano Passanisi
- Department of Human Pathology in Adult and Developmental Age, University of Messina, Messina, Italy
| | - Riccardo Bonfanti
- Diabetes Research Institute, Department of Pediatrics, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Valentino Cherubini
- Department of Women's and Children's Health, G. Salesi Hospital, Ancona, Italy
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