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1
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Wang W, Wang S, Zhang Y, Geng Y, Li D, Liu S. Multivariable identification based MPC for closed-loop glucose regulation subject to individual variability. Comput Methods Biomech Biomed Engin 2025; 28:37-50. [PMID: 37982220 DOI: 10.1080/10255842.2023.2282952] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 07/29/2023] [Accepted: 11/02/2023] [Indexed: 11/21/2023]
Abstract
The controller is important for the artificial pancreas to guide insulin infusion in diabetic therapy. However, the inter- and intra-individual variability and time delay of glucose metabolism bring challenges to control glucose within a normal range. In this study, a multivariable identification based model predictive control (mi-MPC) is developed to overcome the above challenges. Firstly, an integrated glucose-insulin model is established to describe insulin absorption, glucose-insulin interaction under meal disturbance, and glucose transport. On this basis, an observable glucose-insulin dynamic model is formed, in which the individual parameters and disturbances can be identified by designing a particle filtering estimator. Next, embedded with the identified glucose-insulin dynamic model, a mi-MPC method is proposed. In this controller, plasma glucose concentration (PGC), an important variable and indicator of glucose regulation, is estimated and controlled directly. Finally, the method was tested on 30 in-silico subjects produced by the UVa/Padova simulator. The results show that the mi-MPC method including the model, individual identification, and the controller can regulate glucose with the mean value of 7.45 mmol/L without meal announcement.
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Affiliation(s)
- Weijie Wang
- College of Mechanical and Vehicle Engineering, Taiyuan University of Technology, Shanxi, China
- Department of Endocrinology, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Shanxi, China
| | - Shaoping Wang
- School of Automation Science and Electrical Engineering, Beihang University, Beijing, China
- Beijing Advanced Innovation Center for Big Data-based Precision Medicine, Beijing, China
| | - Yuwei Zhang
- School of Automation Science and Electrical Engineering, Beihang University, Beijing, China
| | - Yixuan Geng
- School of Automation Science and Electrical Engineering, Beihang University, Beijing, China
| | - Deng'ao Li
- College of Data Science, Taiyuan University of Technology, Shanxi, China
| | - Shiwei Liu
- Department of Endocrinology, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Shanxi, China
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2
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Bhatia A, Hanna J, Stuart T, Kasper KA, Clausen DM, Gutruf P. Wireless Battery-free and Fully Implantable Organ Interfaces. Chem Rev 2024; 124:2205-2280. [PMID: 38382030 DOI: 10.1021/acs.chemrev.3c00425] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Abstract
Advances in soft materials, miniaturized electronics, sensors, stimulators, radios, and battery-free power supplies are resulting in a new generation of fully implantable organ interfaces that leverage volumetric reduction and soft mechanics by eliminating electrochemical power storage. This device class offers the ability to provide high-fidelity readouts of physiological processes, enables stimulation, and allows control over organs to realize new therapeutic and diagnostic paradigms. Driven by seamless integration with connected infrastructure, these devices enable personalized digital medicine. Key to advances are carefully designed material, electrophysical, electrochemical, and electromagnetic systems that form implantables with mechanical properties closely matched to the target organ to deliver functionality that supports high-fidelity sensors and stimulators. The elimination of electrochemical power supplies enables control over device operation, anywhere from acute, to lifetimes matching the target subject with physical dimensions that supports imperceptible operation. This review provides a comprehensive overview of the basic building blocks of battery-free organ interfaces and related topics such as implantation, delivery, sterilization, and user acceptance. State of the art examples categorized by organ system and an outlook of interconnection and advanced strategies for computation leveraging the consistent power influx to elevate functionality of this device class over current battery-powered strategies is highlighted.
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Affiliation(s)
- Aman Bhatia
- Department of Biomedical Engineering, The University of Arizona, Tucson, Arizona 85721, United States
| | - Jessica Hanna
- Department of Biomedical Engineering, The University of Arizona, Tucson, Arizona 85721, United States
| | - Tucker Stuart
- Department of Biomedical Engineering, The University of Arizona, Tucson, Arizona 85721, United States
| | - Kevin Albert Kasper
- Department of Biomedical Engineering, The University of Arizona, Tucson, Arizona 85721, United States
| | - David Marshall Clausen
- Department of Biomedical Engineering, The University of Arizona, Tucson, Arizona 85721, United States
| | - Philipp Gutruf
- Department of Biomedical Engineering, The University of Arizona, Tucson, Arizona 85721, United States
- Department of Electrical and Computer Engineering, The University of Arizona, Tucson, Arizona 85721, United States
- Bio5 Institute, The University of Arizona, Tucson, Arizona 85721, United States
- Neuroscience Graduate Interdisciplinary Program (GIDP), The University of Arizona, Tucson, Arizona 85721, United States
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3
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Dalla Libera A, Toffanin C, Drecogna M, Galderisi A, Pillonetto G, Cobelli C. In silico design and validation of a time-varying PID controller for an artificial pancreas with intraperitoneal insulin delivery and glucose sensing. APL Bioeng 2023; 7:026105. [PMID: 37229215 PMCID: PMC10205143 DOI: 10.1063/5.0145446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 04/20/2023] [Indexed: 05/27/2023] Open
Abstract
Type 1 diabetes (T1D) is a chronic autoimmune disease featured by the loss of beta cell function and the need for lifetime insulin replacement. Over the recent decade, the use of automated insulin delivery systems (AID) has shifted the paradigm of treatment: the availability of continuous subcutaneous (SC) glucose sensors to guide SC insulin delivery through a control algorithm has allowed, for the first time, to reduce the daily burden of the disease as well as to abate the risk for hypoglycemia. AID use is still limited by individual acceptance, local availability, coverage, and expertise. A major drawback of SC insulin delivery is the need for meal announcement and the peripheral hyperinsulinemia that, over time, contributes to macrovascular complications. Inpatient trials using intraperitoneal (IP) insulin pumps have demonstrated that glycemic control can be improved without meal announcement due to the faster insulin delivery through the peritoneal space. This calls for novel control algorithms able to account for the specificities of IP insulin kinetics. Recently, our group described a two-compartment model of IP insulin kinetics demonstrating that the peritoneal space acts as a virtual compartment and IP insulin delivery is virtually intraportal (intrahepatic), thus closely mimicking the physiology of insulin secretion. The FDA-accepted T1D simulator for SC insulin delivery and sensing has been updated for IP insulin delivery and sensing. Herein, we design and validate-in silico-a time-varying proportional integrative derivative controller to guide IP insulin delivery in a fully closed-loop mode without meal announcement.
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Affiliation(s)
- Alberto Dalla Libera
- Department of Woman and Child's Health, University of Padova, 35128 Padova, Italy
| | - Chiara Toffanin
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy
| | - Martina Drecogna
- Department of Woman and Child's Health, University of Padova, 35128 Padova, Italy
| | | | - Gianluigi Pillonetto
- Department of Information Engineering, University of Padova, 35131 Padova, Italy
| | - Claudio Cobelli
- Department of Woman and Child's Health, University of Padova, 35128 Padova, Italy
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4
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Renard E. Automated insulin delivery systems: from early research to routine care of type 1 diabetes. Acta Diabetol 2023; 60:151-161. [PMID: 35994106 DOI: 10.1007/s00592-022-01929-5] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 06/22/2022] [Indexed: 01/24/2023]
Abstract
Automated insulin delivery (AID) systems, so-called closed-loop systems or artificial pancreas, are based upon the concept of insulin supply driven by blood glucose levels and their variations according to body glucose needs, glucose intakes and insulin action. They include a continuous glucose monitoring device which provides a signal to a control algorithm tuning insulin delivery from an infusion pump. The control algorithm is the key of the system since it commands insulin administration in order to maintain blood glucose in a predefined target range and close to a near-normal glucose level. The last two decades have shown dramatic advances toward the use in free life of AID systems for routine care of type 1 diabetes through step-by-step demonstrations of feasibility, safety and efficacy in successive hospital, transitional and outpatient trials. Because of the constraints of pharmacokinetics and dynamics of subcutaneous insulin delivery, the currently available AID systems are all 'hybrid' or 'semi-automated' insulin delivery systems with a need of meal and exercise announcements in order to anticipate rapid glucose variations through pre-meal bolus or pre-exercise reduction of infusion rate. Nevertheless, these AID systems significantly improve time spent in a near-normal range with a reduction of the risk of hypoglycemia and the mental load of managing diabetes in everyday life, representing a milestone in insulin therapy. Expected progression toward fully automated, further miniaturized and integrated, possibly implantable on long-term and more physiological closed-loop systems paves the way for a functional cure of type 1 diabetes.
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Affiliation(s)
- Eric Renard
- Department of Endocrinology, Diabetes, Nutrition, Montpellier University Hospital, Montpellier, France.
- INSERM Clinical Investigation Centre CIC 1411, Montpellier, France.
- Department of Physiology, Institute of Functional Genomics, CNRS, INSERM, University of Montpellier, Montpellier, France.
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5
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Viroonluecha P, Egea-Lopez E, Santa J. Evaluation of blood glucose level control in type 1 diabetic patients using deep reinforcement learning. PLoS One 2022; 17:e0274608. [PMID: 36099285 PMCID: PMC9469983 DOI: 10.1371/journal.pone.0274608] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 08/30/2022] [Indexed: 11/18/2022] Open
Abstract
Diabetes mellitus is a disease associated with abnormally high levels of blood glucose due to a lack of insulin. Combining an insulin pump and continuous glucose monitor with a control algorithm to deliver insulin is an alternative to patient self-management of insulin doses to control blood glucose levels in diabetes mellitus patients. In this work, we propose a closed-loop control for blood glucose levels based on deep reinforcement learning. We describe the initial evaluation of several alternatives conducted on a realistic simulator of the glucoregulatory system and propose a particular implementation strategy based on reducing the frequency of the observations and rewards passed to the agent, and using a simple reward function. We train agents with that strategy for three groups of patient classes, evaluate and compare it with alternative control baselines. Our results show that our method is able to outperform baselines as well as similar recent proposals, by achieving longer periods of safe glycemic state and low risk.
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Affiliation(s)
- Phuwadol Viroonluecha
- Universidad Politecnica de Cartagena (UPCT), Department of Information Technologies and Communications, Cartagena, Spain
- * E-mail:
| | - Esteban Egea-Lopez
- Universidad Politecnica de Cartagena (UPCT), Department of Information Technologies and Communications, Cartagena, Spain
| | - Jose Santa
- Universidad Politecnica de Cartagena (UPCT), Department of Electronics, Computer Technology and Projects, Cartagena, Spain
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Lo Presti J, Galderisi A, Doyle FJ, Zisser HC, Dassau E, Renard E, Toffanin C, Cobelli C. Intraperitoneal Insulin Delivery: Evidence of a Physiological Route for Artificial Pancreas From Compartmental Modeling. J Diabetes Sci Technol 2022; 17:751-756. [PMID: 35144503 DOI: 10.1177/19322968221076559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND Intraperitoneal insulin delivery has proven to safely overcome a major limit of subcutaneous delivery-meal announcement-and has been able to optimize glycemic control in adults under controlled experimental conditions. In addition, intraperitoneal delivery avoids peripheral hyperinsulinemia resulting from the subcutaneous route and restores a physiological liver gradient. METHODS Relying on a unique data set of intraperitoneal closed-loop insulin delivery obtained with a Model Predictive Controller (MPC), we develop a compartmental model of intraperitoneal insulin kinetics, which, once included in the UVa/Padova T1D simulator, will facilitate the investigation of various control strategies, for example, the simpler Proportional Integral Derivative controller versus MPC. RESULTS Intraperitoneal insulin kinetics can be described with a 2-compartment model including liver and plasma. CONCLUSION Intraperitoneal insulin transit is fast enough to render irrelevant the addition of a peritoneal compartment, proving the peritoneum being a virtual-not actual-transit space for insulin delivery.
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Affiliation(s)
- Jorge Lo Presti
- Department of Woman's and Child's Health, University of Padova, Padova, Italy
| | - Alfonso Galderisi
- Department of Woman's and Child's Health, University of Padova, Padova, Italy
- Hôpital Necker-Enfants Malades, Paris, France
| | - Francis J Doyle
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Howard C Zisser
- Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, CA, USA
| | - Eyal Dassau
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Eric Renard
- Department of Endocrinology, Diabetes, Nutrition and INSERM Clinical Investigation Center 1411, University Hospital of Montpellier, Montpellier, France
- Institute of Functional Genomics, CNRS, INSERM, University of Montpellier, Montpellier, France
| | - Chiara Toffanin
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Claudio Cobelli
- Department of Woman's and Child's Health, University of Padova, Padova, Italy
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7
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Moon SJ, Jung I, Park CY. Current Advances of Artificial Pancreas Systems: A Comprehensive Review of the Clinical Evidence. Diabetes Metab J 2021; 45:813-839. [PMID: 34847641 PMCID: PMC8640161 DOI: 10.4093/dmj.2021.0177] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 10/24/2021] [Indexed: 12/19/2022] Open
Abstract
Since Banting and Best isolated insulin in the 1920s, dramatic progress has been made in the treatment of type 1 diabetes mellitus (T1DM). However, dose titration and timely injection to maintain optimal glycemic control are often challenging for T1DM patients and their families because they require frequent blood glucose checks. In recent years, technological advances in insulin pumps and continuous glucose monitoring systems have created paradigm shifts in T1DM care that are being extended to develop artificial pancreas systems (APSs). Numerous studies that demonstrate the superiority of glycemic control offered by APSs over those offered by conventional treatment are still being published, and rapid commercialization and use in actual practice have already begun. Given this rapid development, keeping up with the latest knowledge in an organized way is confusing for both patients and medical staff. Herein, we explore the history, clinical evidence, and current state of APSs, focusing on various development groups and the commercialization status. We also discuss APS development in groups outside the usual T1DM patients and the administration of adjunct agents, such as amylin analogues, in APSs.
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Affiliation(s)
- Sun Joon Moon
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Inha Jung
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Cheol-Young Park
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
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8
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Jarosinski MA, Dhayalan B, Chen YS, Chatterjee D, Varas N, Weiss MA. Structural principles of insulin formulation and analog design: A century of innovation. Mol Metab 2021; 52:101325. [PMID: 34428558 PMCID: PMC8513154 DOI: 10.1016/j.molmet.2021.101325] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 08/12/2021] [Accepted: 08/17/2021] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND The discovery of insulin in 1921 and its near-immediate clinical use initiated a century of innovation. Advances extended across a broad front, from the stabilization of animal insulin formulations to the frontiers of synthetic peptide chemistry, and in turn, from the advent of recombinant DNA manufacturing to structure-based protein analog design. In each case, a creative interplay was observed between pharmaceutical applications and then-emerging principles of protein science; indeed, translational objectives contributed to a growing molecular understanding of protein structure, aggregation and misfolding. SCOPE OF REVIEW Pioneering crystallographic analyses-beginning with Hodgkin's solving of the 2-Zn insulin hexamer-elucidated general features of protein self-assembly, including zinc coordination and the allosteric transmission of conformational change. Crystallization of insulin was exploited both as a step in manufacturing and as a means of obtaining protracted action. Forty years ago, the confluence of recombinant human insulin with techniques for site-directed mutagenesis initiated the present era of insulin analogs. Variant or modified insulins were developed that exhibit improved prandial or basal pharmacokinetic (PK) properties. Encouraged by clinical trials demonstrating the long-term importance of glycemic control, regimens based on such analogs sought to resemble daily patterns of endogenous β-cell secretion more closely, ideally with reduced risk of hypoglycemia. MAJOR CONCLUSIONS Next-generation insulin analog design seeks to explore new frontiers, including glucose-responsive insulins, organ-selective analogs and biased agonists tailored to address yet-unmet clinical needs. In the coming decade, we envision ever more powerful scientific synergies at the interface of structural biology, molecular physiology and therapeutics.
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Affiliation(s)
- Mark A Jarosinski
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, 46202, IN, USA
| | - Balamurugan Dhayalan
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, 46202, IN, USA
| | - Yen-Shan Chen
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, 46202, IN, USA
| | - Deepak Chatterjee
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, 46202, IN, USA
| | - Nicolás Varas
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, 46202, IN, USA
| | - Michael A Weiss
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, 46202, IN, USA; Department of Chemistry, Indiana University, Bloomington, 47405, IN, USA; Weldon School of Biomedical Engineering, Purdue University, West Lafayette, 47907, IN, USA.
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9
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Schiavon M, Cobelli C, Dalla Man C. Modeling Intraperitoneal Insulin Absorption in Patients with Type 1 Diabetes. Metabolites 2021; 11:metabo11090600. [PMID: 34564415 PMCID: PMC8465342 DOI: 10.3390/metabo11090600] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 08/27/2021] [Accepted: 09/01/2021] [Indexed: 11/16/2022] Open
Abstract
Standard insulin therapy to treat type 1 diabetes (T1D) consists of exogenous insulin administration through the subcutaneous (SC) tissue. Despite recent advances in insulin formulations, the SC route still suffers from delays and large inter/intra-subject variability that limiting optimal glucose control. Intraperitoneal (IP) insulin administration, despite its higher invasiveness, was shown to represent a valid alternative to the SC one. To date, no mathematical model describing the absorption and distribution of insulin after IP administration is available. Here, we aim to fill this gap by using data from eight patients with T1D, treated by implanted IP pump, studied in a hospitalized setting, with frequent measurements of plasma insulin and glucose concentration. A battery of models describing insulin kinetics after IP administration were tested. Model comparison and selection were performed based on model ability to predict the data, precision of parameters and parsimony criteria. The selected model assumed that the insulin absorption from the IP space was described by a linear, two-compartment model, coupled with a two-compartment model of whole-body insulin kinetics with hepatic insulin extraction controlled by hepatic insulin. Future developments include model incorporation into the UVa/Padova T1D Simulator for testing open- and closed-loop therapies with IP insulin administration.
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Affiliation(s)
- Michele Schiavon
- Department of Information Engineering, University of Padova, 35131 Padova, Italy;
| | - Claudio Cobelli
- Department of Woman and Child’s Health, University of Padova, 35128 Padova, Italy;
| | - Chiara Dalla Man
- Department of Information Engineering, University of Padova, 35131 Padova, Italy;
- Correspondence:
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10
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Soetedjo AAP, Lee JM, Lau HH, Goh GL, An J, Koh Y, Yeong WY, Teo AKK. Tissue engineering and 3D printing of bioartificial pancreas for regenerative medicine in diabetes. Trends Endocrinol Metab 2021; 32:609-622. [PMID: 34154916 DOI: 10.1016/j.tem.2021.05.007] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 05/17/2021] [Accepted: 05/24/2021] [Indexed: 02/08/2023]
Abstract
Diabetes is a severe chronic disease worldwide. In various types of diabetes, the pancreatic beta cells fail to secrete sufficient insulin, at some point, to regulate blood glucose levels. Therefore, the replacement of dysfunctional pancreas, islets of Langerhans, or even the insulin-secreting beta cells facilitates physiological regulation of blood glucose levels. However, the current lack of sufficient donor human islets for cell replacement therapy precludes a routine and absolute cure for most of the existing diabetes cases globally. It is envisioned that tissue engineering of a bioartificial pancreas will revolutionize regenerative medicine and the treatment of diabetes. In this review, we discuss the anatomy and physiology of the pancreas, and identify the clinical considerations for engineering a bioartificial pancreas. Subsequently, we dissect the bioengineering problem based on the design of the device, the biomaterial used, and the cells involved. Last but not least, we highlight current tissue engineering challenges and explore potential directions for future work.
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Affiliation(s)
- Andreas Alvin Purnomo Soetedjo
- Stem Cells and Diabetes Laboratory, Institute of Molecular and Cell Biology (IMCB), A*STAR, Singapore; Integrative Sciences and Engineering Programme, NUS Graduate School, National University of Singapore, Singapore
| | - Jia Min Lee
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore
| | - Hwee Hui Lau
- Stem Cells and Diabetes Laboratory, Institute of Molecular and Cell Biology (IMCB), A*STAR, Singapore; School of Biological Sciences, Nanyang Technological University, Singapore
| | - Guo Liang Goh
- Singapore Centre for 3D Printing (SC3DP), School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore
| | - Jia An
- Singapore Centre for 3D Printing (SC3DP), School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore
| | - Yexin Koh
- Department of Hepatopancreatobiliary and Transplant Surgery, Singapore General Hospital, Singapore
| | - Wai Yee Yeong
- Singapore Centre for 3D Printing (SC3DP), School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore
| | - Adrian Kee Keong Teo
- Stem Cells and Diabetes Laboratory, Institute of Molecular and Cell Biology (IMCB), A*STAR, Singapore; Department of Biochemistry and Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
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11
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Bhave G, Chen JC, Singer A, Sharma A, Robinson JT. Distributed sensor and actuator networks for closed-loop bioelectronic medicine. MATERIALS TODAY (KIDLINGTON, ENGLAND) 2021; 46:125-135. [PMID: 34366697 PMCID: PMC8336425 DOI: 10.1016/j.mattod.2020.12.020] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Designing implantable bioelectronic systems that continuously monitor physiological functions and simultaneously provide personalized therapeutic solutions for patients remains a persistent challenge across many applications ranging from neural systems to bioelectronic organs. Closed-loop systems typically consist of three functional blocks, namely, sensors, signal processors and actuators. An effective system, that can provide the necessary therapeutics, tailored to individual physiological factors requires a distributed network of sensors and actuators. While significant progress has been made, closed-loop systems still face many challenges before they can truly be considered as long-term solutions for many diseases. In this review, we consider three important criteria where materials play a critical role to enable implantable closed-loop systems: Specificity, Biocompatibility and Connectivity. We look at the progress made in each of these fields with respect to a specific application and outline the challenges in creating bioelectronic technologies for the future.
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12
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Zhang Y, Wu M, Tan D, Liu Q, Xia R, Chen M, Liu Y, Xue L, Lei Y. A dissolving and glucose-responsive insulin-releasing microneedle patch for type 1 diabetes therapy. J Mater Chem B 2021; 9:648-657. [DOI: 10.1039/d0tb02133d] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
A dissolving microneedle patch for responsive insulin release and type 1 diabetes therapy.
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Affiliation(s)
- Yujie Zhang
- School of Power and Mechanical Engineering & The Institute of Technological Science
- Wuhan University
- Wuhan
- China
| | - Mingxin Wu
- School of Power and Mechanical Engineering & The Institute of Technological Science
- Wuhan University
- Wuhan
- China
| | - Di Tan
- School of Power and Mechanical Engineering & The Institute of Technological Science
- Wuhan University
- Wuhan
- China
| | - Quan Liu
- School of Power and Mechanical Engineering & The Institute of Technological Science
- Wuhan University
- Wuhan
- China
| | - Re Xia
- School of Power and Mechanical Engineering & The Institute of Technological Science
- Wuhan University
- Wuhan
- China
| | - Min Chen
- Department of Internal Medicine & Geriatrics
- Wuhan University Zhongnan Hospital
- Wuhan 430071
- China
| | - Yuangang Liu
- College of Chemical Engineering
- Huaqiao University
- Xiamen 361021
- China
| | - Longjian Xue
- School of Power and Mechanical Engineering & The Institute of Technological Science
- Wuhan University
- Wuhan
- China
| | - Yifeng Lei
- School of Power and Mechanical Engineering & The Institute of Technological Science
- Wuhan University
- Wuhan
- China
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13
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Yu X, Sun X, Zhao Y, Liu J, Li H. Fault detection of continuous glucose measurements based on modified k-medoids clustering algorithm. Neural Comput Appl 2020. [DOI: 10.1007/s00521-020-05432-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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14
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Dias CC, Kamath S, Vidyasagar S. Design of dual hormone blood glucose therapy and comparison with single hormone using MPC algorithm. IET Syst Biol 2020; 14:241-251. [PMID: 33095745 PMCID: PMC8687303 DOI: 10.1049/iet-syb.2020.0053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 08/01/2020] [Accepted: 08/10/2020] [Indexed: 11/20/2022] Open
Abstract
The complete automated control and delivery of insulin and glucagon in type 1 diabetes is the developing technology for artificial pancreas. This improves the quality of life of a diabetic patient with the precise infusion. The amount of infusion of these hormones is controlled using a control algorithm, which has the prediction property. The control algorithm model predictive control (MPC) predicts one step ahead and infuses the hormones continuously according to the necessity for the regulation of blood glucose. In this research, the authors propose a MPC control algorithm, which is novel for a dual hormone infusion, for a mathematical model such as Sorenson model, and compare it with the insulin alone or single hormone infusion developed with MPC. Since they aim for complete automatic control and regulation, unmeasured disturbances at a random time are integrated and the performance evaluation is projected through statistical analysis. The blood glucose risk index (BGRI) and control variability grid analysis (CVGA) plot gives the additional evaluation for the comparative results of the two controllers claiming 88% performance by dual hormone evaluated through CVGA plot and 2.05 mg/dl average tracking error, 2.20 BGRI. The MPC developed for dual hormone significantly performs better and the time spent in normal glycaemia is longer while eliminating the risk of hyperglycaemia and hypoglycaemia.
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Affiliation(s)
- Cifha Crecil Dias
- Department of Instrumentation and Control, Manipal Academy of Higher Education, Manipal Institute of Technology, Manipal, India.
| | - Surekha Kamath
- Department of Instrumentation and Control, Manipal Academy of Higher Education, Manipal Institute of Technology, Manipal, India
| | - Sudha Vidyasagar
- Department of Medicine, Manipal Academy of Higher Education, Kasturba Medical College, Manipal, India
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15
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Fabris C, Kovatchev B. The closed‐loop artificial pancreas in 2020. Artif Organs 2020; 44:671-679. [DOI: 10.1111/aor.13704] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Accepted: 04/06/2020] [Indexed: 12/13/2022]
Affiliation(s)
- Chiara Fabris
- Center for Diabetes Technology University of Virginia Charlottesville VA USA
| | - Boris Kovatchev
- Center for Diabetes Technology University of Virginia Charlottesville VA USA
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16
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17
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Karsaz A. Chattering -free hybrid adaptive neuro-fuzzy inference system-particle swarm optimisation data fusion-based BG-level control. IET Syst Biol 2020; 14:31-38. [PMID: 31931479 DOI: 10.1049/iet-syb.2018.5019] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
In this study, a closed-loop control scheme is proposed for the glucose-insulin regulatory system in type-1 diabetic mellitus (T1DM) patients. Some innovative hybrid glucose-insulin regulators have combined artificial intelligence such as fuzzy logic and genetic algorithm with well known Palumbo model to regulate the blood glucose (BG) level in T1DM patients. However, most of these approaches have focused on the glucose reference tracking, and the qualitative of this tracking such as chattering reduction of insulin injection has not been well-studied. Higher-order sliding mode (HoSM) controllers have been employed to attenuate the effect of chattering. Owing to the delayed nature and non-linear property of glucose-insulin mechanism as well as various unmeasurable disturbances, even the HoSM methods are partly successful. In this study, data fusion of adaptive neuro-fuzzy inference systems optimised by particle swarm optimisation has been presented. The excellent performance of the proposed hybrid controller, i.e. desired BG-level tracking and chattering reduction in the presence of daily glucose-level disturbances is verified.
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Affiliation(s)
- Ali Karsaz
- Department of Electrical and Electronic Engineering, Khorasan Institute of Higher Education, Mashhad, Iran.
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18
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Lal RA, Ekhlaspour L, Hood K, Buckingham B. Realizing a Closed-Loop (Artificial Pancreas) System for the Treatment of Type 1 Diabetes. Endocr Rev 2019; 40:1521-1546. [PMID: 31276160 PMCID: PMC6821212 DOI: 10.1210/er.2018-00174] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2018] [Accepted: 02/28/2019] [Indexed: 01/20/2023]
Abstract
Recent, rapid changes in the treatment of type 1 diabetes have allowed for commercialization of an "artificial pancreas" that is better described as a closed-loop controller of insulin delivery. This review presents the current state of closed-loop control systems and expected future developments with a discussion of the human factor issues in allowing automation of glucose control. The goal of these systems is to minimize or prevent both short-term and long-term complications from diabetes and to decrease the daily burden of managing diabetes. The closed-loop systems are generally very effective and safe at night, have allowed for improved sleep, and have decreased the burden of diabetes management overnight. However, there are still significant barriers to achieving excellent daytime glucose control while simultaneously decreasing the burden of daytime diabetes management. These systems use a subcutaneous continuous glucose sensor, an algorithm that accounts for the current glucose and rate of change of the glucose, and the amount of insulin that has already been delivered to safely deliver insulin to control hyperglycemia, while minimizing the risk of hypoglycemia. The future challenge will be to allow for full closed-loop control with minimal burden on the patient during the day, alleviating meal announcements, carbohydrate counting, alerts, and maintenance. The human factors involved with interfacing with a closed-loop system and allowing the system to take control of diabetes management are significant. It is important to find a balance between enthusiasm and realistic expectations and experiences with the closed-loop system.
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Affiliation(s)
- Rayhan A Lal
- Division of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, California.,Division of Endocrinology, Department of Medicine, Stanford University School of Medicine, Stanford, California
| | - Laya Ekhlaspour
- Division of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, California
| | - Korey Hood
- Division of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, California.,Department of Psychiatry, Stanford University School of Medicine, Stanford, California
| | - Bruce Buckingham
- Division of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, California
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19
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Artificial Pancreas: Current Progress and Future Outlook in the Treatment of Type 1 Diabetes. Drugs 2019; 79:1089-1101. [DOI: 10.1007/s40265-019-01149-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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20
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Zhang Y, Wu M, Dai W, Chen M, Guo Z, Wang X, Tan D, Shi K, Xue L, Liu S, Lei Y. High drug-loading gold nanoclusters for responsive glucose control in type 1 diabetes. J Nanobiotechnology 2019; 17:74. [PMID: 31159842 PMCID: PMC6547569 DOI: 10.1186/s12951-019-0505-z] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2019] [Accepted: 05/23/2019] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND Diabetes is one of the biggest medical challenges worldwide. The key to efficiently treat type 1 diabetes is to accurately inject insulin according to the blood glucose levels. In this study, we aimed to develop an intelligent insulin-releasing gold nanocluster system that responds to environmental glucose concentrations. RESULTS We employed gold nanoclusters (AuNCs) as a novel carrier nanomaterial by taking advantage of their high drug-loading capacity. We prepared AuNCs in the protection of bovine serum albumin, and we decorated AuNCs with 3-aminophenylboronic acid (PBA) as a glucose-responsive factor. Then we grafted insulin onto the surface to obtain the glucose-responsive insulin-releasing system, AuNC-PBA-Ins complex. The AuNC-PBA-Ins complex exhibited high sensitivity to glucose concentration, and rapidly released insulin in high glucose concentration in vitro. In the type 1 diabetic mouse model in vivo, the AuNC-PBA-Ins complex effectively released insulin and regulated blood glucose level in the normoglycemic state for up to 3 days. CONCLUSIONS We successfully developed a phenylboronic acid-functionalized gold nanocluster system (AuNC-PBA-Ins) for responsive insulin release and glucose regulation in type 1 diabetes. This nanocluster system mimics the function of blood glucose regulation of pancreas in the body and may have potential applications in the theranostics of diabetes.
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Affiliation(s)
- Yujie Zhang
- School of Power and Mechanical Engineering & The Institute of Technological Sciences, Wuhan University, Wuhan, 430072, China
| | - Mingxin Wu
- School of Power and Mechanical Engineering & The Institute of Technological Sciences, Wuhan University, Wuhan, 430072, China
| | - Wubin Dai
- School of Material Science and Engineering, Wuhan Institute of Technology, Wuhan, 430205, China
| | - Min Chen
- Department of Internal Medicine & Geriatrics, Wuhan University Zhongnan Hospital, Wuhan, 430071, China
| | - Zhaoyang Guo
- School of Power and Mechanical Engineering & The Institute of Technological Sciences, Wuhan University, Wuhan, 430072, China
| | - Xin Wang
- School of Power and Mechanical Engineering & The Institute of Technological Sciences, Wuhan University, Wuhan, 430072, China
| | - Di Tan
- School of Power and Mechanical Engineering & The Institute of Technological Sciences, Wuhan University, Wuhan, 430072, China
| | - Kui Shi
- School of Power and Mechanical Engineering & The Institute of Technological Sciences, Wuhan University, Wuhan, 430072, China
| | - Longjian Xue
- School of Power and Mechanical Engineering & The Institute of Technological Sciences, Wuhan University, Wuhan, 430072, China
| | - Sheng Liu
- School of Power and Mechanical Engineering & The Institute of Technological Sciences, Wuhan University, Wuhan, 430072, China
| | - Yifeng Lei
- School of Power and Mechanical Engineering & The Institute of Technological Sciences, Wuhan University, Wuhan, 430072, China.
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21
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Chakrabarty A, Gregory JM, Moore LM, Williams PE, Farmer B, Cherrington AD, Lord P, Shelton B, Cohen D, Zisser HC, Doyle FJ, Dassau E. A New Animal Model of Insulin-Glucose Dynamics in the Intraperitoneal Space Enhances Closed-Loop Control Performance. JOURNAL OF PROCESS CONTROL 2019; 76:62-73. [PMID: 31178632 PMCID: PMC6548466 DOI: 10.1016/j.jprocont.2019.01.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
Current artificial pancreas systems (AP) operate via subcutaneous (SC) glucose sensing and SC insulin delivery. Due to slow diffusion and transport dynamics across the interstitial space, even the most sophisticated control algorithms in on-body AP systems cannot react fast enough to maintain tight glycemic control under the effect of exogenous glucose disturbances caused by ingesting meals or performing physical activity. Recent efforts made towards the development of an implantable AP have explored the utility of insulin infusion in the intraperitoneal (IP) space: a region within the abdominal cavity where the insulin-glucose kinetics are observed to be much more rapid than the SC space. In this paper, a series of canine experiments are used to determine the dynamic association between IP insulin boluses and plasma glucose levels. Data from these experiments are employed to construct a new mathematical model and to formulate a closed-loop control strategy to be deployed on an implantable AP. The potential of the proposed controller is demonstrated via in-silico experiments on an FDA-accepted benchmark cohort: the proposed design significantly outperforms a previous controller designed using artificial data (time in clinically acceptable glucose range: 97.3±1.5% vs. 90.1±5.6%). Furthermore, the robustness of the proposed closed-loop system to delays and noise in the measurement signal (for example, when glucose is sensed subcutaneously) and deleterious glycemic changes (such as sudden glucose decline due to physical activity) is investigated. The proposed model based on experimental canine data leads to the generation of more effective control algorithms and is a promising step towards fully automated and implantable artificial pancreas systems.
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Affiliation(s)
- Ankush Chakrabarty
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA
| | | | - L. Merkle Moore
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN
| | - Philip E. Williams
- Section of Surgical Sciences, Vanderbilt University School of Medicine, Nashville, TN
| | - Ben Farmer
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN
| | - Alan D. Cherrington
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN
| | | | | | - Don Cohen
- Physiologic Devices, Inc., Alpine, CA
| | - Howard C. Zisser
- Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, CA
| | - Francis J. Doyle
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA
| | - Eyal Dassau
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA
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22
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Yeung KTD, Reddy M, Purkayastha S. Surgical options for glycaemic control in Type 1 diabetes. Diabet Med 2019; 36:414-423. [PMID: 30575115 DOI: 10.1111/dme.13885] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/18/2018] [Indexed: 12/14/2022]
Abstract
In recent years, bariatric surgery, also referred to as metabolic surgery, has become the most successful treatment option in those with Type 2 diabetes and obesity. There are some similarities in the pathological pathways in Type 1 and Type 2 diabetes, but the use of surgery in Type 1 diabetes remains unestablished and controversial. The treatment and management of Type 1 diabetes can be very challenging but recent advances in surgical interventions and technology has the potential to expand and optimize treatment options. This review discusses the current status of some surgical options available to people with Type 1 diabetes. These include implantable continuous glucose monitoring systems, continuous intraperitoneal insulin infusion pumps, closed-loop insulin delivery systems (also known as the artificial pancreas system) utilizing the latter two modalities of glucose monitoring and insulin delivery, and bariatric or metabolic surgery. Whole pancreas and islet transplantation are beyond the scope of this review but are briefly discussed.
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Affiliation(s)
- K T D Yeung
- Department of Surgery and Cancer, Imperial College, London, UK
- St Mary's Hospital, Imperial College Healthcare NHS Trust, UK
| | - M Reddy
- St Mary's Hospital, Imperial College Healthcare NHS Trust, UK
- Division of Diabetes, Endocrinology and Metabolism, Imperial College, London, UK
| | - S Purkayastha
- Department of Surgery and Cancer, Imperial College, London, UK
- St Mary's Hospital, Imperial College Healthcare NHS Trust, UK
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23
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Zhang Y, Wu M, Dai W, Li Y, Wang X, Tan D, Yang Z, Liu S, Xue L, Lei Y. Gold nanoclusters for controlled insulin release and glucose regulation in diabetes. NANOSCALE 2019; 11:6471-6479. [PMID: 30892368 DOI: 10.1039/c9nr00668k] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Diabetes has become the third threat to public health worldwide. Traditional treatments of diabetes require frequent blood glucose testing and insulin injections, which not only bring great pain to patients but also exhibit difficulty in controlling the blood glucose accurately. In order to solve these problems, we developed a smart glucose-responsive insulin delivery system responding to the environmental glucose concentration based on gold nanoclusters (GNCs). First, we prepared GNCs as high drug-loading nanocarriers, and we decorated GNCs with phenylboronic acid molecules (4-carboxyphenylboronic acid (PBA) and 4-carboxy-3-fluorophenylboronic acid (FPBA)) as responsive ligands; then, we grafted insulin on the surface to form glucose-responsive insulin-release nanocomplexes GNC-PBA-Ins and GNC-FPBA-Ins, respectively. In the in vitro test, these complexes exhibited high sensitivity to glucose concentrations and rapidly released insulin in a hyperglycemic state. In type 1 diabetic mice in vivo, these complexes could maintain the blood glucose levels of mice in a normoglycemic range for up to 48 h without peaks of hyperglycemia or hypoglycemia, where the GNC-FPBA-Ins complex showed a better regulation of glucose than the GNC-PBA-Ins complex. These gold nanocluster systems mimic the function of the natural pancreas for blood glucose control, which has great potentials for the diagnosis and treatment of diabetes in the future.
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Affiliation(s)
- Yujie Zhang
- The Institute of Technological Sciences & School of Power and Mechanical Engineering, Wuhan University, Wuhan 430072, China.
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24
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Navigating Two Roads to Glucose Normalization in Diabetes: Automated Insulin Delivery Devices and Cell Therapy. Cell Metab 2019; 29:545-563. [PMID: 30840911 DOI: 10.1016/j.cmet.2019.02.007] [Citation(s) in RCA: 69] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2018] [Revised: 02/12/2019] [Accepted: 02/13/2019] [Indexed: 12/23/2022]
Abstract
Incredible strides have been made since the discovery of insulin almost 100 years ago. Insulin formulations have improved dramatically, glucose levels can be measured continuously, and recently first-generation biomechanical "artificial pancreas" systems have been approved by regulators around the globe. However, still only a small fraction of patients with diabetes achieve glycemic goals. Replacement of insulin-producing cells via transplantation shows significant promise, but is limited in application due to supply constraints (cadaver-based) and the need for chronic immunosuppression. Over the past decade, significant progress has been made to address these barriers to widespread implementation of a cell therapy. Can glucose levels in people with diabetes be normalized with artificial pancreas systems or via cell replacement approaches? Here we review the road ahead, including the challenges and opportunities of both approaches.
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25
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Mechanics of controlled release of insulin entrapped in polyacrylic acid gels via variable electrical stimuli. Drug Deliv Transl Res 2019; 9:783-794. [DOI: 10.1007/s13346-019-00620-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
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26
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Feng J, Hajizadeh I, Yu X, Rashid M, Turksoy K, Samadi S, Sevil M, Hobbs N, Brandt R, Lazaro C, Maloney Z, Littlejohn E, Philipson LH, Cinar A. Multi-level Supervision and Modification of Artificial Pancreas Control System. Comput Chem Eng 2018; 112:57-69. [PMID: 30287976 PMCID: PMC6166877 DOI: 10.1016/j.compchemeng.2018.02.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Artificial pancreas (AP) systems provide automated regulation of blood glucose concentration (BGC) for people with type 1 diabetes (T1D). An AP includes three components: a continuous glucose monitoring (CGM) sensor, a controller calculating insulin infusion rate based on the CGM signal, and a pump delivering the insulin amount calculated by the controller to the patient. The performance of the AP system depends on successful operation of these three components. Many APs use model predictive controllers that rely on models to predict BGC and to calculate the optimal insulin infusion rate. The performance of model-based controllers depends on the accuracy of the models that is affected by large dynamic changes in glucose-insulin metabolism or equipment performance that may move the operating conditions away from those used in developing the models and designing the control system. Sensor errors and missing signals will cause calculation of erroneous insulin infusion rates. And the performance of the controller may vary at each sampling step and each period (meal, exercise, and sleep), and from day to day. Here we describe a multi-level supervision and controller modification (ML-SCM) module is developed to supervise the performance of the AP system and retune the controller. It supervises AP performance in 3 time windows: sample level, period level, and day level. At sample level, an online controller performance assessment sub-module will generate controller performance indexes to evaluate various components of the AP system and conservatively modify the controller. A sensor error detection and signal reconciliation module will detect sensor error and reconcile the CGM sensor signal at each sample. At period level, the controller performance is evaluated with information collected during a certain time period and the controller is tuned more aggressively. At the day level, the daily CGM ranges are further analyzed to determine the adjustable range of controller parameters used for sample level and period level. Thirty subjects in the UVa/Padova metabolic simulator were used to evaluate the performance of the ML-SCM module and one clinical experiment is used to illustrate its performance in a clinical environment. The results indicate that the AP system with an ML-SCM module has a safer range of glucose concentration distribution and more appropriate insulin infusion rate suggestions than an AP system without the ML-SCM module.
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Affiliation(s)
- Jianyuan Feng
- Department of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL, USA
| | - Iman Hajizadeh
- Department of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL, USA
| | - Xia Yu
- Department of Control Theory and Control Engineering, Northeastern University, Shenyang, Liaoning China
| | - Mudassir Rashid
- Department of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL, USA
| | - Kamuran Turksoy
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA
| | - Sediqeh Samadi
- Department of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL, USA
| | - Mert Sevil
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA
| | - Nicole Hobbs
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA
| | - Rachel Brandt
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA
| | - Caterina Lazaro
- Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL, USA
| | - Zacharie Maloney
- Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL, USA
| | | | - Louis H Philipson
- Departments of Medicine and Pediatrics - Section of Endocrinology, University of Chicago, Chicago, IL, USA
| | - Ali Cinar
- Department of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL, USA
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA
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27
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Gingras V, Taleb N, Roy-Fleming A, Legault L, Rabasa-Lhoret R. The challenges of achieving postprandial glucose control using closed-loop systems in patients with type 1 diabetes. Diabetes Obes Metab 2018; 20:245-256. [PMID: 28675686 PMCID: PMC5810921 DOI: 10.1111/dom.13052] [Citation(s) in RCA: 70] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/09/2017] [Revised: 06/27/2017] [Accepted: 06/29/2017] [Indexed: 01/17/2023]
Abstract
For patients with type 1 diabetes, closed-loop delivery systems (CLS) combining an insulin pump, a glucose sensor and a dosing algorithm allowing a dynamic hormonal infusion have been shown to improve glucose control when compared with conventional therapy. Yet, reducing glucose excursion and simplification of prandial insulin doses remain a challenge. The objective of this literature review is to examine current meal-time strategies in the context of automated delivery systems in adults and children with type 1 diabetes. Current challenges and considerations for post-meal glucose control will also be discussed. Despite promising results with meal detection, the fully automated CLS has yet failed to provide comparable glucose control to CLS with carbohydrate-matched bolus in the post-meal period. The latter strategy has been efficient in controlling post-meal glucose using different algorithms and in various settings, but at the cost of a meal carbohydrate counting burden for patients. Further improvements in meal detection algorithms or simplified meal-priming boluses may represent interesting avenues. The greatest challenges remain in regards to the pharmacokinetic and dynamic profiles of available rapid insulins as well as sensor accuracy and lag-time. New and upcoming faster acting insulins could provide important benefits. Multi-hormone CLS (eg, dual-hormone combining insulin with glucagon or pramlintide) and adjunctive therapy (eg, GLP-1 and SGLT2 inhibitors) also represent promising options. Meal glucose control with the artificial pancreas remains an important challenge for which the optimal strategy is still to be determined.
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Affiliation(s)
- Véronique Gingras
- Institut de Recherches Cliniques de Montréal, Montreal, Quebec, Canada
- Department of nutrition, Université de Montréal, Montreal, Quebec, Canada
| | - Nadine Taleb
- Institut de Recherches Cliniques de Montréal, Montreal, Quebec, Canada
- Department of biomedical sciences, Université de Montréal, Montreal, Quebec, Canada
| | - Amélie Roy-Fleming
- Institut de Recherches Cliniques de Montréal, Montreal, Quebec, Canada
- Department of nutrition, Université de Montréal, Montreal, Quebec, Canada
| | - Laurent Legault
- Institut de Recherches Cliniques de Montréal, Montreal, Quebec, Canada
- Montreal Children’s Hospital, McGill University Health Center, Montreal, Quebec, Canada
| | - Rémi Rabasa-Lhoret
- Institut de Recherches Cliniques de Montréal, Montreal, Quebec, Canada
- Department of nutrition, Université de Montréal, Montreal, Quebec, Canada
- Montreal Diabetes Research Center (MDRC), Montreal, Quebec, Canada
- Research Center of the Université de Montréal Hospital Center (CRCHUM), Montreal, Quebec, Canada
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28
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Cao Z, Gondhalekar R, Dassau E, Doyle FJ. Extremum Seeking Control for Personalized Zone Adaptation in Model Predictive Control for Type 1 Diabetes. IEEE Trans Biomed Eng 2017; 65:1859-1870. [PMID: 29989925 DOI: 10.1109/tbme.2017.2783238] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Zone model predictive control has proven to be an effective closed-loop method to regulate blood glucose for people with type 1 diabetes (T1D). In this paper, we present a universal model-free optimization scheme for adapting the zone for T1D patients individually. The adaptation is based on a clinical glycemic risk index named relative regularized glycemic penalty index (rrGPI), which is calculated from glucose measurements by a continuous glucose monitor. The scheme's objective is to minimize rrGPI by simultaneously modulating a controller's blood glucose target zone's upper bound and lower bound. The adaptation mechanism is based on extremum seeking control, in which the zone boundaries are driven by gradient estimation obtained by continuously sinusoidally modulating and demodulating the rrGPI readings. To improve the adaptation method's robustness against uncertainties, a decaying feedback gain and a vanishing dither signal are employed. in-silico trials suggested that the personalized optimized zone can be reached within a week of adaptation. Both for announced and unannounced meals, the proposed method outperforms the fixed zone [80, 140] mg/dL, which has been employed in the authors' clinical trials. It is also shown that the developed method has strong robustness against real-life uncertainties.
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29
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Dassau E, Renard E, Place J, Farret A, Pelletier MJ, Lee J, Huyett LM, Chakrabarty A, Doyle FJ, Zisser HC. Intraperitoneal insulin delivery provides superior glycaemic regulation to subcutaneous insulin delivery in model predictive control-based fully-automated artificial pancreas in patients with type 1 diabetes: a pilot study. Diabetes Obes Metab 2017; 19:1698-1705. [PMID: 28474383 PMCID: PMC5742859 DOI: 10.1111/dom.12999] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2017] [Revised: 04/27/2017] [Accepted: 04/27/2017] [Indexed: 01/15/2023]
Abstract
AIMS To compare intraperitoneal (IP) to subcutaneous (SC) insulin delivery in an artificial pancreas (AP). RESEARCH DESIGN AND METHODS Ten adults with type 1 diabetes participated in a non-randomized, non-blinded sequential AP study using the same SC glucose sensing and Zone Model Predictive Control (ZMPC) algorithm adjusted for insulin clearance. On first admission, subjects underwent closed-loop control with SC delivery of a fast-acting insulin analogue for 24 hours. Following implantation of a DiaPort IP insulin delivery system, the identical 24-hour trial was performed with IP regular insulin delivery. The clinical protocol included 3 unannounced meals with 70, 40 and 70 g carbohydrate, respectively. Primary endpoint was time spent with blood glucose (BG) in the range of 80 to 140 mg/dL (4.4-7.7 mmol/L). RESULTS Percent of time spent within the 80 to 140 mg/dL range was significantly higher for IP delivery than for SC delivery: 39.8 ± 7.6 vs 25.6 ± 13.1 ( P = .03). Mean BG (mg/dL) and percent of time spent within the broader 70 to 180 mg/dL range were also significantly better for IP insulin: 151.0 ± 11.0 vs 190.0 ± 31.0 ( P = .004) and 65.7 ± 9.2 vs 43.9 ± 14.7 ( P = .001), respectively. Superiority of glucose control with IP insulin came from the reduced time spent in hyperglycaemia (>180 mg/dL: 32.4 ± 8.9 vs 53.5 ± 17.4, P = .014; >250 mg/dL: 5.9 ± 5.6 vs 23.0 ± 11.3, P = .0004). Higher daily doses of insulin (IU) were delivered with the IP route (43.7 ± 0.1 vs 32.3 ± 0.1, P < .001) with no increased percent time spent <70 mg/dL (IP: 2.5 ± 2.9 vs SC: 4.1 ± 5.3, P = .42). CONCLUSIONS Glycaemic regulation with fully-automated AP delivering IP insulin was superior to that with SC insulin delivery. This pilot study provides proof-of-concept for an AP system combining a ZMPC algorithm with IP insulin delivery.
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MESH Headings
- Adult
- Algorithms
- Blood Glucose/analysis
- Diabetes Mellitus, Type 1/blood
- Diabetes Mellitus, Type 1/therapy
- Female
- France
- Glycated Hemoglobin/analysis
- Humans
- Hyperglycemia/prevention & control
- Hypoglycemia/chemically induced
- Hypoglycemia/prevention & control
- Hypoglycemic Agents/administration & dosage
- Hypoglycemic Agents/adverse effects
- Hypoglycemic Agents/therapeutic use
- Infusions, Parenteral
- Infusions, Subcutaneous
- Insulin Infusion Systems/adverse effects
- Insulin Lispro/administration & dosage
- Insulin Lispro/adverse effects
- Insulin Lispro/therapeutic use
- Insulin, Regular, Human/administration & dosage
- Insulin, Regular, Human/adverse effects
- Insulin, Regular, Human/therapeutic use
- Male
- Middle Aged
- Pancreas, Artificial/adverse effects
- Pilot Projects
- Proof of Concept Study
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Affiliation(s)
- Eyal Dassau
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts
- Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, California
| | - Eric Renard
- Department of Endocrinology, Diabetes, Nutrition and INSERM Clinical Investigation Center 1411, University Hospital of Montpellier, Montpellier, France
- Department of Psychology, Institute of Functional Genomics, CNRS UMR5203, INSERM U1191, University of Montpellier, Montpellier, France
| | - Jérôme Place
- Department of Psychology, Institute of Functional Genomics, CNRS UMR5203, INSERM U1191, University of Montpellier, Montpellier, France
| | - Anne Farret
- Department of Endocrinology, Diabetes, Nutrition and INSERM Clinical Investigation Center 1411, University Hospital of Montpellier, Montpellier, France
- Department of Psychology, Institute of Functional Genomics, CNRS UMR5203, INSERM U1191, University of Montpellier, Montpellier, France
| | - Marie-José Pelletier
- Department of Endocrinology, Diabetes, Nutrition and INSERM Clinical Investigation Center 1411, University Hospital of Montpellier, Montpellier, France
| | - Justin Lee
- Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, California
| | - Lauren M. Huyett
- Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, California
| | - Ankush Chakrabarty
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts
| | - Francis J. Doyle
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts
- Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, California
| | - Howard C. Zisser
- Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, California
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Abstract
While only used initially in cases with resistance to subcutaneous insulin therapy, intraperitoneal insulin therapy provides an overall more stable glucose control than subcutaneous insulin therapy thanks to its pharmacokinetics as pointed by Garcia-Verdugo et al from the experience of implantable insulin pumps. The expansion of these devices has been limited by underdelivery issues and high cost. The availability of a new percutaneous access to intraperitoneal route could allow a similar glucose control with less constraints of follow-up and expected lower cost. Currently reported clinical experience does not allow a reliable assessment of its main risk of infection which could impair its sustained usability. Because intraperitoneal insulin could allow a fully automated closed-loop insulin delivery, a specific interest for its means of performance is relevant.
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Affiliation(s)
- Eric Renard
- Montpellier University Hospital, Department of Endocrinology, Diabetes, Nutrition, Montpellier, France
- Institute of Functional Genomics, University of Montpellier, Montpellier, France
- INSERM Clinical Investigation Centre, Montpellier, France
- Eric Renard, MD, PhD, Department of Endocrinology, Diabetes, Nutrition, Montpellier University Hospital, Lapeyronie Hospital, Avenue Doyen Gaston Giraud, 34295 Montpellier cedex 5, France.
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Abstract
In recent years, continuous intraperitoneal insulin infusion (CIPII) has become a favored treatment alternative for patients with subcutaneous insulin resistance, mainly due to its ability of mimicking physiological conditions of insulin absorption. CIPII has been shown to improve glycemic control as well as to reduce hypoglycemic events and to lead to increased patient satisfaction and quality of life (QoL). Among CIPII delivery systems, Diaport stands out due to its low side effects, its demonstrated clinical efficacy and the potential for integration into closed-loop systems.
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Affiliation(s)
| | | | - Oliver Schnell
- Sciarc Institute, Baierbrunn, Germany
- Forschergruppe Diabetes e.V., Munich-Neuherberg, Germany
- Oliver Schnell, MD, Forschergruppe Diabetes e.V., Ingolstädter Landstraße 1, 85764 Munich-Neuherberg, Germany.
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Turksoy K, Frantz N, Quinn L, Dumin M, Kilkus J, Hibner B, Cinar A, Littlejohn E. Automated Insulin Delivery-The Light at the End of the Tunnel. J Pediatr 2017; 186:17-28.e9. [PMID: 28396030 DOI: 10.1016/j.jpeds.2017.02.055] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2016] [Revised: 02/13/2017] [Accepted: 02/20/2017] [Indexed: 12/28/2022]
Affiliation(s)
- Kamuran Turksoy
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL
| | - Nicole Frantz
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL
| | - Laurie Quinn
- College of Nursing, University of Illinois at Chicago, Chicago, IL
| | - Magdalena Dumin
- Biological Sciences Division, University of Chicago, Chicago, IL
| | - Jennifer Kilkus
- Biological Sciences Division, University of Chicago, Chicago, IL
| | - Brooks Hibner
- Biological Sciences Division, University of Chicago, Chicago, IL
| | - Ali Cinar
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL; Biological Sciences Division, University of Chicago, Chicago, IL; Department of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL
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Abstract
In the past years the development of an artificial pancreas (AP) has made great progress and many activities are ongoing in this area of research. The major step forward made in the last years was moving the evaluation of AP systems from highly controlled experimental conditions to daily life conditions at the home of patients with diabetes; this was also the aim of the European Union-funded AP@home project. Over a time period of 5 years a series of clinical studies were performed that culminated in 2 "final studies" during which an AP system was used by patients in their home environment for 2 or 3 months without supervision by a physician, living their normal lives. Two different versions of the AP system developed within this project were evaluated. A significant improvement in glycated hemoglobin was observed during closed-loop conditions despite the fact that during the control period the patients used the best currently available therapeutic option. In addition, a "single-port AP system" was developed within the project that combines continuous glucose monitoring and insulin infusion at a single tissue site. By using such a combined device the patients not only have to carry one less device around, the number of access points through the skin is also reduced from 2 to 1. In summary, close cooperation of 12 European partners, both academic centers and industry, enabled the development and evaluation of AP systems under daily life conditions. The next step is to develop these into products in cooperation with commercial partners.
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Affiliation(s)
- Lutz Heinemann
- Profil Institut für Stoffwechselforschung GmbH, Neuss, Germany
| | - Carsten Benesch
- Profil Institut für Stoffwechselforschung GmbH, Neuss, Germany
| | - J Hans DeVries
- Academic Medical Center, University of Amsterdam, the Netherlands
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Turksoy K, Roy A, Cinar A. Real-Time Model-Based Fault Detection of Continuous Glucose Sensor Measurements. IEEE Trans Biomed Eng 2016; 64:1437-1445. [PMID: 26930674 DOI: 10.1109/tbme.2016.2535412] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
OBJECTIVE Faults in subcutaneous glucose concentration readings with a continuous glucose monitoring (CGM) may affect the computation of insulin infusion rates that can lead to hypoglycemia or hyperglycemia in artificial pancreas control systems for patients with type 1 diabetes (T1D). METHODS Multivariable statistical monitoring methods are proposed for detection of faults in glucose concentration values reported by a subcutaneous glucose sensor. A nonlinear first principle glucose/insulin/meal dynamic model is developed. An unscented Kalman filter is used for state and parameter estimation of the nonlinear model. Principal component analysis models are developed and used for detection of dynamic changes. K-nearest neighbor classification algorithm is used for diagnosis of faults. Data from 51 subjects are used to assess the performance of the algorithm. RESULTS The results indicate that the proposed algorithm works successfully with 84.2% sensitivity. Overall, 155 (out of 184) of the CGM failures are detected with a 2.8-min average detection time. CONCLUSION A novel algorithm that integrates data-driven and model-based methods is developed. The proposed method is able to detect CGM failures with a high rate of success. SIGNIFICANCE The proposed fault detection algorithm can decrease the effects of faults on insulin infusion rates and reduce the potential for hypo- or hyperglycemia for patients with T1D.
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McAdams BH, Rizvi AA. An Overview of Insulin Pumps and Glucose Sensors for the Generalist. J Clin Med 2016; 5:jcm5010005. [PMID: 26742082 PMCID: PMC4730130 DOI: 10.3390/jcm5010005] [Citation(s) in RCA: 61] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2015] [Revised: 12/16/2015] [Accepted: 12/24/2015] [Indexed: 01/22/2023] Open
Abstract
Continuous subcutaneous insulin, or the insulin pump, has gained popularity and sophistication as a near-physiologic programmable method of insulin delivery that is flexible and lifestyle-friendly. The introduction of continuous monitoring with glucose sensors provides unprecedented access to, and prediction of, a patient’s blood glucose levels. Efforts are underway to integrate the two technologies, from “sensor-augmented” and “sensor-driven” pumps to a fully-automated and independent sensing-and-delivery system. Implantable pumps and an early-phase “bionic pancreas” are also in active development. Fine-tuned “pancreas replacement” promises to be one of the many avenues that offers hope for individuals suffering from diabetes. Although endocrinologists and diabetes specialists will continue to maintain expertise in this field, it behooves the primary care physician to have a working knowledge of insulin pumps and sensors to ensure optimal clinical care and decision-making for their patients.
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Affiliation(s)
- Brooke H McAdams
- Fellow in Endocrinology, University of South Carolina School of Medicine, Columbia, SC 29203, USA.
| | - Ali A Rizvi
- Medicine and Director, Endocrinology Division, University of South Carolina School of Medicine, Two Medical Park, Suite 502, Columbia, SC 29203, USA.
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Stavdahl Ø, Fougner AL, Kölle K, Christiansen SC, Ellingsen R, Carlsen SM. The Artificial Pancreas: A Dynamic Challenge. ACTA ACUST UNITED AC 2016. [DOI: 10.1016/j.ifacol.2016.07.280] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Zisser H, Dassau E, Lee JJ, Harvey RA, Bevier W, Doyle FJ. Clinical results of an automated artificial pancreas using technosphere inhaled insulin to mimic first-phase insulin secretion. J Diabetes Sci Technol 2015; 9:564-72. [PMID: 25901023 PMCID: PMC4604530 DOI: 10.1177/1932296815582061] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
OBJECTIVE The purpose of this study was to investigate whether or not adding a fixed preprandial dose of inhaled insulin to a fully automated closed loop artificial pancreas would improve the postprandial glucose control without adding an increased risk of hypoglycemia. RESEARCH DESIGN AND METHODS Nine subjects with T1DM were recruited for the study. The patients were on closed-loop control for 24 hours starting around 4:30 pm. Mixed meals (~50 g CHO) were given at 6:30 pm and 7:00 am the following day. For the treatment group each meal was preceded by the inhalation of one 10 U dose of Technosphere Insulin (TI). Subcutaneous insulin delivery was controlled by a zone model predictive control algorithm (zone-MPC). At 11:00 am, the patient exercised for 30 ± 5 minutes at 50% of predicted heart rate reserve. RESULTS The use of TI resulted in increasing the median percentage time in range (70-180 mg/dl, BG) during the 5-hour postprandial period by 21.6% (81.6% and 60% in the with/without TI cases, respectively, P = .06) and reducing the median postprandial glucose peak by 33 mg/dl (172 mg/dl and 205 mg/dl in the with and without TI cases, respectively, P = .004). The median percentage time in range 80-140 mg/dl during the entire study period was 67.5% as compared to percentage time in range without the use of TI of 55.2% (P = .03). CONCLUSIONS Adding preprandial TI (See video supplement) to an automated closed-loop AP system resulted in superior postprandial control as demonstrated by lower postprandial glucose exposure without addition hypoglycemia.
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Affiliation(s)
- Howard Zisser
- Sansum Diabetes Research Institute, Santa Barbara, CA, USA Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, CA, USA
| | - Eyal Dassau
- Sansum Diabetes Research Institute, Santa Barbara, CA, USA Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, CA, USA Institute for Collaborative Biotechnologies, University of California, Santa Barbara, Santa Barbara, CA, USA
| | - Justin J Lee
- Sansum Diabetes Research Institute, Santa Barbara, CA, USA Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, CA, USA
| | - Rebecca A Harvey
- Sansum Diabetes Research Institute, Santa Barbara, CA, USA Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, CA, USA
| | - Wendy Bevier
- Sansum Diabetes Research Institute, Santa Barbara, CA, USA
| | - Francis J Doyle
- Sansum Diabetes Research Institute, Santa Barbara, CA, USA Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, CA, USA Institute for Collaborative Biotechnologies, University of California, Santa Barbara, Santa Barbara, CA, USA
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39
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An artificial pancreas for automated blood glucose control in patients with Type 1 diabetes. Ther Deliv 2015; 6:609-19. [DOI: 10.4155/tde.15.12] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
Automated glucose control in patients with Type 1 diabetes is much-coveted by patients, relatives and healthcare professionals. It is the expectation that a system for automated control, also know as an artificial pancreas, will improve glucose control, reduce the risk of diabetes complications and markedly improve patient quality of life. An artificial pancreas consists of portable devices for glucose sensing and insulin delivery which are controlled by an algorithm residing on a computer. The technology is still under development and currently no artificial pancreas is commercially available. This review gives an introduction to recent progress, challenges and future prospects within the field of artificial pancreas research.
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40
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Cobelli C, Man CD, Pedersen MG, Bertoldo A, Toffolo G. Advancing our understanding of the glucose system via modeling: a perspective. IEEE Trans Biomed Eng 2015; 61:1577-92. [PMID: 24759285 DOI: 10.1109/tbme.2014.2310514] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
The glucose story begins with Claude Bernard's discovery of glycogen and milieu interieur, continued with Banting's and Best's discovery of insulin and with Rudolf Schoenheimer's paradigm of dynamic body constituents. Tracers and compartmental models allowed moving to the first quantitative pictures of the system and stimulated important developments in terms of modeling methodology. Three classes of multiscale models, models to measure, models to simulate, and models to control the glucose system, are reviewed in their historical development with an eye to the future.
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Tan G, Elefanty AG, Stanley EG. β-cell regeneration and differentiation: how close are we to the 'holy grail'? J Mol Endocrinol 2014; 53:R119-29. [PMID: 25385843 DOI: 10.1530/jme-14-0188] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Diabetes can be managed by careful monitoring of blood glucose and timely delivery of exogenous insulin. However, even with fastidious compliance, people with diabetes can suffer from numerous complications including atherosclerosis, retinopathy, neuropathy, and kidney disease. This is because delivery of exogenous insulin coupled with glucose monitoring cannot provide the fine level of glucose control normally provided by endogenous β-cells in the context of intact islets. Moreover, a subset of people with diabetes lack awareness of hypoglycemic events; a status that can have grave consequences. Therefore, much effort has been focused on replacing lost or dysfunctional β-cells with cells derived from other sources. The advent of stem cell biology and cellular reprogramming strategies have provided impetus to this work and raised hopes that a β-cell replacement therapy is on the horizon. In this review, we look at two components that will be required for successful β-cell replacement therapy: a reliable and safe source of β-cells and a mechanism by which such cells can be delivered and protected from host immune destruction. Particular attention is paid to insulin-producing cells derived from pluripotent stem cells because this platform addresses the issue of scale, one of the more significant hurdles associated with potential cell-based therapies. We also review methods for encapsulating transplanted cells, a technique that allows grafts to evade immune attack and survive for a long term in the absence of ongoing immunosuppression. In surveying the literature, we conclude that there are still several substantial hurdles that need to be cleared before a stem cell-based β-cell replacement therapy for diabetes becomes a reality.
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Affiliation(s)
- Gemma Tan
- Department of Anatomy and Developmental BiologyMonash University, Building 73, Clayton, Victoria 3800, AustraliaMurdoch Childrens Research InstituteThe Royal Children's Hospital, Flemington Road, Parkville, Victoria 3052, AustraliaDepartment of PaediatricsThe Royal Children's Hospital, University of Melbourne, Flemington Road, Parkville, Victoria 3052, Australia Department of Anatomy and Developmental BiologyMonash University, Building 73, Clayton, Victoria 3800, AustraliaMurdoch Childrens Research InstituteThe Royal Children's Hospital, Flemington Road, Parkville, Victoria 3052, AustraliaDepartment of PaediatricsThe Royal Children's Hospital, University of Melbourne, Flemington Road, Parkville, Victoria 3052, Australia
| | - Andrew G Elefanty
- Department of Anatomy and Developmental BiologyMonash University, Building 73, Clayton, Victoria 3800, AustraliaMurdoch Childrens Research InstituteThe Royal Children's Hospital, Flemington Road, Parkville, Victoria 3052, AustraliaDepartment of PaediatricsThe Royal Children's Hospital, University of Melbourne, Flemington Road, Parkville, Victoria 3052, Australia Department of Anatomy and Developmental BiologyMonash University, Building 73, Clayton, Victoria 3800, AustraliaMurdoch Childrens Research InstituteThe Royal Children's Hospital, Flemington Road, Parkville, Victoria 3052, AustraliaDepartment of PaediatricsThe Royal Children's Hospital, University of Melbourne, Flemington Road, Parkville, Victoria 3052, Australia Department of Anatomy and Developmental BiologyMonash University, Building 73, Clayton, Victoria 3800, AustraliaMurdoch Childrens Research InstituteThe Royal Children's Hospital, Flemington Road, Parkville, Victoria 3052, AustraliaDepartment of PaediatricsThe Royal Children's Hospital, University of Melbourne, Flemington Road, Parkville, Victoria 3052, Australia
| | - Edouard G Stanley
- Department of Anatomy and Developmental BiologyMonash University, Building 73, Clayton, Victoria 3800, AustraliaMurdoch Childrens Research InstituteThe Royal Children's Hospital, Flemington Road, Parkville, Victoria 3052, AustraliaDepartment of PaediatricsThe Royal Children's Hospital, University of Melbourne, Flemington Road, Parkville, Victoria 3052, Australia Department of Anatomy and Developmental BiologyMonash University, Building 73, Clayton, Victoria 3800, AustraliaMurdoch Childrens Research InstituteThe Royal Children's Hospital, Flemington Road, Parkville, Victoria 3052, AustraliaDepartment of PaediatricsThe Royal Children's Hospital, University of Melbourne, Flemington Road, Parkville, Victoria 3052, Australia Department of Anatomy and Developmental BiologyMonash University, Building 73, Clayton, Victoria 3800, AustraliaMurdoch Childrens Research InstituteThe Royal Children's Hospital, Flemington Road, Parkville, Victoria 3052, AustraliaDepartment of PaediatricsThe Royal Children's Hospital, University of Melbourne, Flemington Road, Parkville, Victoria 3052, Australia
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El Youssef J, Castle JR, Bakhtiani PA, Haidar A, Branigan DL, Breen M, Ward WK. Quantification of the glycemic response to microdoses of subcutaneous glucagon at varying insulin levels. Diabetes Care 2014; 37:3054-60. [PMID: 25139882 PMCID: PMC4207205 DOI: 10.2337/dc14-0803] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Glucagon delivery in closed-loop control of type 1 diabetes is effective in minimizing hypoglycemia. However, high insulin concentration lowers the hyperglycemic effect of glucagon, and small doses of glucagon in this setting are ineffective. There are no studies clearly defining the relationship between insulin levels, subcutaneous glucagon, and blood glucose. RESEARCH DESIGN AND METHODS Using a euglycemic clamp technique in 11 subjects with type 1 diabetes, we examined endogenous glucose production (EGP) of glucagon (25, 75, 125, and 175 μg) at three insulin infusion rates (0.016, 0.032, and 0.05 units/kg/h) in a randomized, crossover study. Infused 6,6-dideuterated glucose was measured every 10 min, and EGP was determined using a validated glucoregulatory model. Area under the curve (AUC) for glucose production was the primary outcome, estimated over 60 min. RESULTS At low insulin levels, EGP rose proportionately with glucagon dose, from 5 ± 68 to 112 ± 152 mg/kg (P = 0.038 linear trend), whereas at high levels, there was no increase in glucose output (19 ± 53 to 26 ± 38 mg/kg, P = NS). Peak glucagon serum levels and AUC correlated well with dose (r2 = 0.63, P < 0.001), as did insulin levels with insulin infusion rates (r2 = 0.59, P < 0.001). CONCLUSIONS EGP increases steeply with glucagon doses between 25 and 175 μg at lower insulin infusion rates. However, high insulin infusion rates prevent these doses of glucagon from significantly increasing glucose output and may reduce glucagon effectiveness in preventing hypoglycemia when used in the artificial pancreas.
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Affiliation(s)
| | | | | | - Ahmad Haidar
- Institut de Recherches Cliniques de Montréal, Montreal, Canada
| | | | | | - W Kenneth Ward
- Oregon Health & Science University, Portland, OR Legacy Health, Portland, OR
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Quemerais MA, Doron M, Dutrech F, Melki V, Franc S, Antonakios M, Charpentier G, Hanaire H, Benhamou PY. Preliminary evaluation of a new semi-closed-loop insulin therapy system over the prandial period in adult patients with type 1 diabetes: the WP6.0 Diabeloop study. J Diabetes Sci Technol 2014; 8:1177-84. [PMID: 25097057 PMCID: PMC4455472 DOI: 10.1177/1932296814545668] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
There is room for improvement in the algorithms used in closed-loop insulin therapy during the prandial period. This pilot study evaluated the efficacy and safety of the Diabeloop algorithm (model predictive control type) during the postprandial period. This 2-center clinical trial compared interstitial glucose levels over two 5-hour periods (with/without the algorithm) following a calibrated lunch. On the control day, the amount of insulin delivered by the pump was determined according to the patient's usual parameters. On the test day, 50% or 75% of the theoretical bolus required was delivered, while the algorithm, informed of carbohydrate intake, proposed changes to insulin delivery every 15 minutes using modeling to forecast glucose levels. The primary endpoint was percentage of time spent at near normoglycemia (70-180 mg/dl). Twelve patients with type 1 diabetes (9 men, age 35.6 ± 12.7 years, HbA1c 7.3 ± 0.8%) were included. The percentage of time spent in the target range was 84.5 ± 20.8 (test day) versus 69.2 ± 33.9% (control day, P = .11). The percentage of time spent in hypoglycemia < 70 mg/dl was 0.2 ± 0.8 (test) versus 4.4 ± 8.2% (control, P = .18). Interstitial glucose at the end of the test (5 hours) was 127.5 ± 40.1 (test) versus 146 ± 53.5 mg/dl (control, P = .25). The insulin doses did not differ, and no differences were observed between the 50% and 75% boluses. In a semi-closed-loop configuration with manual priming boluses (25% or 50% reduction), the Diabeloop v1 algorithm was as successful as the manual method in determining the prandial bolus, without any exposure to excessive hypoglycemic risk.
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Affiliation(s)
| | - Maeva Doron
- University Grenoble Alpes, Grenoble, France CEA, LETI, DTBS, Laboratoire électronique et systèmes pour la santé, Grenoble, France
| | - Florent Dutrech
- University Grenoble Alpes, Grenoble, France CEA, LETI, DTBS, Laboratoire électronique et systèmes pour la santé, Grenoble, France
| | - Vincent Melki
- Department of Diabetology, Toulouse Rangueil University Hospital, Toulouse, France
| | - Sylvia Franc
- Department of Diabetes, Sud-Francilien Hospital, Corbeil-Essonnes, France CERITD, Corbeil-Essonnes, France
| | - Michel Antonakios
- University Grenoble Alpes, Grenoble, France CEA, LETI, DTBS, Laboratoire électronique et systèmes pour la santé, Grenoble, France
| | - Guillaume Charpentier
- Department of Diabetes, Sud-Francilien Hospital, Corbeil-Essonnes, France CERITD, Corbeil-Essonnes, France
| | - Helene Hanaire
- Department of Diabetology, Toulouse Rangueil University Hospital, Toulouse, France
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Freckmann G, Jendrike N, Pleus S, Buck H, Bousamra S, Galley P, Thukral A, Wagner R, Weinert S, Haug C. Use of microdialysis-based continuous glucose monitoring to drive real-time semi-closed-loop insulin infusion. J Diabetes Sci Technol 2014; 8:1074-80. [PMID: 25205589 PMCID: PMC4455459 DOI: 10.1177/1932296814549828] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Continuous glucose monitoring (CGM) and automated insulin delivery may make diabetes management substantially easier, if the quality of the resulting therapy remains adequate. In this study, a semi-closed-loop control algorithm was used to drive insulin therapy and its quality was compared to that of subject-directed therapy. Twelve subjects stayed at the study site for approximately 70 hours and were provided with the investigational Automated Pancreas System Test Stand (APS-TS), which was used to calculate insulin dosage recommendations automatically. These recommendations were based on microdialysis CGM values and common diabetes therapy parameters. For the first half of their stay, the subjects directed their diabetes therapy themselves, whereas for the second half, the insulin recommendations were delivered by the APS-TS (so-called algorithm-driven therapy). During subject-directed therapy, the mean glucose was 114 mg/dl compared to 125 mg/dl during algorithm-driven therapy. Time in target (90 to 150 mg/dl) was approximately 46% during subject-directed therapy and approximately 58% during algorithm-driven therapy. When subjects directed their therapy, approximately 2 times more hypoglycemia interventions (oral administration of carbohydrates) were required than during algorithm-driven therapy. No hyperglycemia interventions (delivery of addition insulin) were necessary during subject-directed therapy, while during algorithm-driven therapy, 2 hyperglycemia interventions were necessary. The APS-TS was able to adequately control glucose concentrations in the subjects. Time in target was at least comparable or moderately higher during closed-loop control and markedly fewer hypoglycemia interventions were required, thus increasing patient safety.
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Affiliation(s)
- Guido Freckmann
- Institut für Diabetes-Technologie Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Nina Jendrike
- Institut für Diabetes-Technologie Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Stefan Pleus
- Institut für Diabetes-Technologie Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Harvey Buck
- Roche Diagnostics Operations, Inc, Indianapolis, IN, USA
| | | | - Paul Galley
- Roche Diagnostics Operations, Inc, Indianapolis, IN, USA
| | - Ajay Thukral
- Cientive Group Incorporated, Indianapolis, IN, USA
| | - Robin Wagner
- Roche Diagnostics Operations, Inc, Indianapolis, IN, USA
| | - Stefan Weinert
- Roche Diagnostics Operations, Inc, Indianapolis, IN, USA
| | - Cornelia Haug
- Institut für Diabetes-Technologie Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
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Aathira R, Jain V. Advances in management of type 1 diabetes mellitus. World J Diabetes 2014; 5:689-696. [PMID: 25317246 PMCID: PMC4138592 DOI: 10.4239/wjd.v5.i5.689] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2014] [Revised: 06/18/2014] [Accepted: 07/17/2014] [Indexed: 02/05/2023] Open
Abstract
Treatment of type 1 diabetes mellitus has always posed a challenge to balance hyperglycemia control with hypoglycemia episodes. The quest for newer therapies is continuing and this review attempts to outline the recent developments. The insulin molecule itself has got moulded into different analogues by minor changes in its structure to ensure well controlled delivery, stable half-lives and lesser side effects. Insulin delivery systems have also consistently undergone advances from subcutaneous injections to continuous infusion to trials of inhalational delivery. Continuous glucose monitoring systems are also becoming more accurate and user friendly. Smartphones have also made their entry into therapy of diabetes by integrating blood glucose levels and food intake with calculated adequate insulin required. Artificial pancreas has enabled to a certain extent to close the loop between blood glucose level and insulin delivery with devices armed with meal and exercise announcements, dual hormone delivery and pramlintide infusion. Islet, pancreas-kidney and stem cells transplants are also being attempted though complete success is still a far way off. Incorporating insulin gene and secretary apparatus is another ambitious leap to achieve insulin independence though the search for the ideal vector and target cell is still continuing. Finally to stand up to the statement, prevention is better than cure, immunological methods are being investigated to be used as vaccine to prevent the onset of diabetes mellitus.
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van Dijk PR, Logtenberg SJJ, Gans ROB, Bilo HJG, Kleefstra N. Intraperitoneal insulin infusion: treatment option for type 1 diabetes resulting in beneficial endocrine effects beyond glycaemia. Clin Endocrinol (Oxf) 2014; 81:488-97. [PMID: 25041605 DOI: 10.1111/cen.12546] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2014] [Revised: 05/11/2014] [Accepted: 07/03/2014] [Indexed: 11/28/2022]
Abstract
Continuous intraperitoneal insulin infusion (CIPII) is a treatment option for patients with type 1 diabetes mellitus who fail to reach adequate glycaemic control despite intensive subcutaneous (SC) insulin therapy. CIPII has clear advantages over SC insulin administration in terms of pharmacokinetic and pharmacodynamic properties and has been shown to improve glycaemic regulation. Due to the delivery of insulin predominantly in the portal vein, as opposed to systemically, CIPII offers a unique research model to investigate the effects of insulin on endocrine and metabolic parameters in vivo. The aim of the present article is to provide an overview of the literature with respect to the effects of CIPII on glucose management, quality of life, complications and costs, with additional focus on metabolic and endocrine aspects. Finally, future use and research objectives are discussed.
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Bevier WC, Fuller SM, Fuller RP, Rubin RR, Dassau E, Doyle FJ, Jovanovič L, Zisser HC. Artificial pancreas (AP) clinical trial participants' acceptance of future AP technology. Diabetes Technol Ther 2014; 16:590-5. [PMID: 24811147 PMCID: PMC4135316 DOI: 10.1089/dia.2013.0365] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
BACKGROUND Artificial pancreas (AP) systems are currently an active field of diabetes research. This pilot study examined the attitudes of AP clinical trial participants toward future acceptance of the technology, having gained firsthand experience. SUBJECTS AND METHODS After possible influencers of AP technology adoption were considered, a 34-question questionnaire was developed. The survey assessed current treatment satisfaction, dimensions of clinical trial participant motivation, and variables of the technology acceptance model (TAM). Forty-seven subjects were contacted to complete the survey. The reliability of the survey scales was tested using Cronbach's α. The relationship of the factors to the likelihood of AP technology adoption was explored using regression analysis. RESULTS Thirty-six subjects (76.6%) completed the survey. Of the respondents, 86.1% were either highly likely or likely to adopt the technology once available. Reliability analysis of the survey dimensions revealed good internal consistency, with scores of >0.7 for current treatment satisfaction, convenience (motivation), personal health benefit (motivation), perceived ease of use (TAM), and perceived usefulness (TAM). Linear modeling showed that future acceptance of the AP was significantly associated with TAM and the motivation variables of convenience plus the individual item benefit to others (R(2)=0.26, P=0.05). When insulin pump and continuous glucose monitor use were added, the model significance improved (R(2)=0.37, P=0.02). CONCLUSIONS This pilot study demonstrated that individuals with direct AP technology experience expressed high likelihood of future acceptance. Results support the factors of personal benefit, convenience, perceived usefulness, and perceived ease of use as reliable scales that suggest system adoption in this highly motivated patient population.
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Affiliation(s)
- Wendy C. Bevier
- Sansum Diabetes Research Institute, Santa Barbara, California
| | - Serena M. Fuller
- Department of Family and Consumer Sciences, University of Arkansas Division of Agriculture Research and Extension, Little Rock, Arkansas
| | - Ryan P. Fuller
- Department of Speech Communication, University of Arkansas at Little Rock, Little Rock, Arkansas
| | - Richard R. Rubin
- Departments of Medicine and Pediatrics, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Eyal Dassau
- Sansum Diabetes Research Institute, Santa Barbara, California
- Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, California
- Institute for Collaborative Biotechnologies, University of California Santa Barbara, Santa Barbara, California
| | - Francis J. Doyle
- Sansum Diabetes Research Institute, Santa Barbara, California
- Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, California
- Institute for Collaborative Biotechnologies, University of California Santa Barbara, Santa Barbara, California
| | - Lois Jovanovič
- Sansum Diabetes Research Institute, Santa Barbara, California
- Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, California
- Biomolecular Science & Engineering Program, University of California Santa Barbara, Santa Barbara, California
| | - Howard C. Zisser
- Sansum Diabetes Research Institute, Santa Barbara, California
- Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, California
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Reddy M, Herrero P, El Sharkawy M, Pesl P, Jugnee N, Thomson H, Pavitt D, Toumazou C, Johnston D, Georgiou P, Oliver N. Feasibility study of a bio-inspired artificial pancreas in adults with type 1 diabetes. Diabetes Technol Ther 2014; 16:550-7. [PMID: 24801544 PMCID: PMC4135321 DOI: 10.1089/dia.2014.0009] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
BACKGROUND This study assesses proof of concept and safety of a novel bio-inspired artificial pancreas (BiAP) system in adults with type 1 diabetes during fasting, overnight, and postprandial conditions. In contrast to existing glucose controllers in artificial pancreas systems, the BiAP uses a control algorithm based on a mathematical model of β-cell physiology. The algorithm is implemented on a miniature silicon microchip within a portable hand-held device that interfaces the components of the artificial pancreas. MATERIALS AND METHODS In this nonrandomized open-label study each subject attended for a 6-h fasting study followed by a 13-h overnight and post-breakfast study on a separate occasion. During both study sessions the BiAP system was used, and microboluses of insulin were recommended every 5 min by the control algorithm according to subcutaneous sensor glucose levels. The primary outcome was percentage time spent in the glucose target range (3.9-10.0 mmol/L). RESULTS Twenty subjects (55% male; mean [SD] age, 44 [10] years; duration of diabetes, 22 [12] years; glycosylated hemoglobin, 7.4% [0.7%] [57 (7) mmol/mol]; body mass index, 25 [4] kg/m(2)) participated in the fasting study, and the median (interquartile range) percentage time in target range was 98.0% (90.8-100.0%). Seventeen of these subjects then participated in the overnight/postprandial study, where 70.7% (63.9-77.4%) of time was spent in the target range and, reassuringly, 0.0% (0.0-2.3%) of time was spent in hypoglycemia (<3.9 mmol/L). CONCLUSIONS The BiAP achieves safe glycemic control during fasting, overnight, and postprandial conditions.
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Affiliation(s)
- Monika Reddy
- Division of Diabetes, Endocrinology and Metabolism, Imperial College London, London, United Kingdom
| | - Pau Herrero
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Institute of Biomedical Engineering, Imperial College London, London, United Kingdom
| | - Mohamed El Sharkawy
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Institute of Biomedical Engineering, Imperial College London, London, United Kingdom
| | - Peter Pesl
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Institute of Biomedical Engineering, Imperial College London, London, United Kingdom
| | - Narvada Jugnee
- Division of Diabetes, Endocrinology and Metabolism, Imperial College London, London, United Kingdom
| | - Hazel Thomson
- Division of Diabetes, Endocrinology and Metabolism, Imperial College London, London, United Kingdom
| | - Darrell Pavitt
- Division of Diabetes, Endocrinology and Metabolism, Imperial College London, London, United Kingdom
| | - Christofer Toumazou
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Institute of Biomedical Engineering, Imperial College London, London, United Kingdom
| | - Desmond Johnston
- Division of Diabetes, Endocrinology and Metabolism, Imperial College London, London, United Kingdom
| | - Pantelis Georgiou
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Institute of Biomedical Engineering, Imperial College London, London, United Kingdom
| | - Nick Oliver
- Division of Diabetes, Endocrinology and Metabolism, Imperial College London, London, United Kingdom
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Russell SJ, El-Khatib FH, Sinha M, Magyar KL, McKeon K, Goergen LG, Balliro C, Hillard MA, Nathan DM, Damiano ER. Outpatient glycemic control with a bionic pancreas in type 1 diabetes. N Engl J Med 2014; 371:313-325. [PMID: 24931572 PMCID: PMC4183762 DOI: 10.1056/nejmoa1314474] [Citation(s) in RCA: 387] [Impact Index Per Article: 35.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
BACKGROUND The safety and effectiveness of automated glycemic management have not been tested in multiday studies under unrestricted outpatient conditions. METHODS In two random-order, crossover studies with similar but distinct designs, we compared glycemic control with a wearable, bihormonal, automated, "bionic" pancreas (bionic-pancreas period) with glycemic control with an insulin pump (control period) for 5 days in 20 adults and 32 adolescents with type 1 diabetes mellitus. The automatically adaptive algorithm of the bionic pancreas received data from a continuous glucose monitor to control subcutaneous delivery of insulin and glucagon. RESULTS Among the adults, the mean plasma glucose level over the 5-day bionic-pancreas period was 138 mg per deciliter (7.7 mmol per liter), and the mean percentage of time with a low glucose level (<70 mg per deciliter [3.9 mmol per liter]) was 4.8%. After 1 day of automatic adaptation by the bionic pancreas, the mean (±SD) glucose level on continuous monitoring was lower than the mean level during the control period (133±13 vs. 159±30 mg per deciliter [7.4±0.7 vs. 8.8±1.7 mmol per liter], P<0.001) and the percentage of time with a low glucose reading was lower (4.1% vs. 7.3%, P=0.01). Among the adolescents, the mean plasma glucose level was also lower during the bionic-pancreas period than during the control period (138±18 vs. 157±27 mg per deciliter [7.7±1.0 vs. 8.7±1.5 mmol per liter], P=0.004), but the percentage of time with a low plasma glucose reading was similar during the two periods (6.1% and 7.6%, respectively; P=0.23). The mean frequency of interventions for hypoglycemia among the adolescents was lower during the bionic-pancreas period than during the control period (one per 1.6 days vs. one per 0.8 days, P<0.001). CONCLUSIONS As compared with an insulin pump, a wearable, automated, bihormonal, bionic pancreas improved mean glycemic levels, with less frequent hypoglycemic episodes, among both adults and adolescents with type 1 diabetes mellitus. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases and others; ClinicalTrials.gov numbers, NCT01762059 and NCT01833988.).
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Affiliation(s)
- Steven J Russell
- Diabetes Unit and Department of Medicine, Massachusetts General Hospital and Harvard Medical School (S.J.R., M.S., K.L.M, L.G.G., C.B., M.A.H., D.M.N.), and the Department of Biomedical Engineering, Boston University (F.H.E.-K., K.M., E.R.D.) - both in Boston
| | - Firas H El-Khatib
- Diabetes Unit and Department of Medicine, Massachusetts General Hospital and Harvard Medical School (S.J.R., M.S., K.L.M, L.G.G., C.B., M.A.H., D.M.N.), and the Department of Biomedical Engineering, Boston University (F.H.E.-K., K.M., E.R.D.) - both in Boston
| | - Manasi Sinha
- Diabetes Unit and Department of Medicine, Massachusetts General Hospital and Harvard Medical School (S.J.R., M.S., K.L.M, L.G.G., C.B., M.A.H., D.M.N.), and the Department of Biomedical Engineering, Boston University (F.H.E.-K., K.M., E.R.D.) - both in Boston
| | - Kendra L Magyar
- Diabetes Unit and Department of Medicine, Massachusetts General Hospital and Harvard Medical School (S.J.R., M.S., K.L.M, L.G.G., C.B., M.A.H., D.M.N.), and the Department of Biomedical Engineering, Boston University (F.H.E.-K., K.M., E.R.D.) - both in Boston
| | - Katherine McKeon
- Diabetes Unit and Department of Medicine, Massachusetts General Hospital and Harvard Medical School (S.J.R., M.S., K.L.M, L.G.G., C.B., M.A.H., D.M.N.), and the Department of Biomedical Engineering, Boston University (F.H.E.-K., K.M., E.R.D.) - both in Boston
| | - Laura G Goergen
- Diabetes Unit and Department of Medicine, Massachusetts General Hospital and Harvard Medical School (S.J.R., M.S., K.L.M, L.G.G., C.B., M.A.H., D.M.N.), and the Department of Biomedical Engineering, Boston University (F.H.E.-K., K.M., E.R.D.) - both in Boston
| | - Courtney Balliro
- Diabetes Unit and Department of Medicine, Massachusetts General Hospital and Harvard Medical School (S.J.R., M.S., K.L.M, L.G.G., C.B., M.A.H., D.M.N.), and the Department of Biomedical Engineering, Boston University (F.H.E.-K., K.M., E.R.D.) - both in Boston
| | - Mallory A Hillard
- Diabetes Unit and Department of Medicine, Massachusetts General Hospital and Harvard Medical School (S.J.R., M.S., K.L.M, L.G.G., C.B., M.A.H., D.M.N.), and the Department of Biomedical Engineering, Boston University (F.H.E.-K., K.M., E.R.D.) - both in Boston
| | - David M Nathan
- Diabetes Unit and Department of Medicine, Massachusetts General Hospital and Harvard Medical School (S.J.R., M.S., K.L.M, L.G.G., C.B., M.A.H., D.M.N.), and the Department of Biomedical Engineering, Boston University (F.H.E.-K., K.M., E.R.D.) - both in Boston
| | - Edward R Damiano
- Diabetes Unit and Department of Medicine, Massachusetts General Hospital and Harvard Medical School (S.J.R., M.S., K.L.M, L.G.G., C.B., M.A.H., D.M.N.), and the Department of Biomedical Engineering, Boston University (F.H.E.-K., K.M., E.R.D.) - both in Boston
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Turksoy K, Cinar A. Adaptive control of artificial pancreas systems - a review. JOURNAL OF HEALTHCARE ENGINEERING 2014; 5:1-22. [PMID: 24691384 DOI: 10.1260/2040-2295.5.1.1] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Artificial pancreas (AP) systems offer an important improvement in regulating blood glucose concentration for patients with type 1 diabetes, compared to current approaches. AP consists of sensors, control algorithms and an insulin pump. Different AP control algorithms such as proportional-integral-derivative, model-predictive control, adaptive control, and fuzzy logic control have been investigated in simulation and clinical studies in the past three decades. The variability over time and complexity of the dynamics of blood glucose concentration, unsteady disturbances such as meals, time-varying delays on measurements and insulin infusion, and noisy data from sensors create a challenging system to AP. Adaptive control is a powerful control technique that can deal with such challenges. In this paper, a review of adaptive control techniques for blood glucose regulation with an AP system is presented. The investigations and advances in technology produced impressive results, but there is still a need for a reliable AP system that is both commercially viable and appealing to patients with type 1 diabetes.
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Affiliation(s)
- Kamuran Turksoy
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA
| | - Ali Cinar
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA Department of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL, USA
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