Modeling beta-cell insulin secretion--implications for closed-loop glucose homeostasis

Recent advances in the precision control strategy of artificial pancreas

The scientific diagnosis and treatment of patients with diabetes require frequent blood glucose testing and insulin delivery to normoglycemia. Therefore, an artificial pancreas with a continuous blood glucose (BG) monitoring function is an urgent research target in the medical industry. The problem of closed-loop algorithmic control of the BG with a time delay is a key and difficult issue that needs to be overcome in the development of an artificial pancreas. Firstly, the composition, structure, and control characteristics of the artificial pancreas are introduced. Subsequently, the research progress of artificial pancreas control algorithms is reviewed, and the characteristics, advantages, and disadvantages of proportional-integral-differential control, model predictive control, and artificial intelligence control are compared and analyzed to determine whether they are suitable for the practical application of the artificial pancreas. Additionally, key advancements in areas such as blood glucose data monitoring, adaptive models, wearable devices, and fully automated artificial pancreas systems are also reviewed. Finally, this review highlights that meal prediction, control safety, integration, streamlining the optimization of control algorithms, constant temperature preservation of insulin, and dual-hormone artificial pancreas are issues that require further attention in the future.

A methodical survey of mathematical model-based control techniques based on open and closed loop control approach for diabetes management

Disturbance of blood sugar level is controlled through well-known biomechanical feedback loops: high levels of glucose in blood facilitate to release insulin from the pancreas which accelerates the absorption rate of cellular glucose. Low glucose levels encourage to release pancreatic glucagon which induces glycogen breakdown to glucose in the liver. These bio-control systems do not function properly in diabetic patients. Though the control of disease seems intuitively easy, in real life, due to many differences in structure by diet and fasting, exercise, medications, patient’s profile and other stressors, it is not that easy. The mathematical models of the glucose-insulin regulatory system follow the patient’s physiological conditions which make it difficult to identify and estimate all the model parameters. In this paper, we have given a systematic literature review on mathematical models of the diabetic patients, and various kinds of disease control techniques through the development of open and closed loop insulin deliver command system and optimization of exogenous insulin rate. It demonstrates the open and closed loop type model-based control strategies underlying the assumptions of the concerned models. The combination of mathematical model with control strategies such as genetic algorithm (GA), neural network (NN), sliding mode controller (SMC), model predictive controller (MPC), and fuzzy logic control (FLC) has been considered, which provides an overview of this area, highlighting the control profile over the diabetic model with promising clinical results, outlining key challenges, and identifying needs for the future research. Also, the significance of these control algorithms has been discussed in the presence of the noises, the controller’s robustness and various other disturbances. It provides substantial information on diabetes management through various control techniques.

Blood glucose regulation and control of insulin and glucagon infusion using single model predictive control for type 1 diabetes mellitus

This study elaborates on the design of artificial pancreas using model predictive control algorithm for a comprehensive physiological model such as the Sorensen model, which regulates the blood glucose and can have a longer control time in normal glycaemic region. The main objective of the proposed algorithm is to eliminate the risk of hyper and hypoglycaemia and have a precise infusion of hormones: insulin and glucagon. A single model predictive controller is developed to control the bihormones, insulin, and glucagon for such a development unmeasured disturbance is considered for a random time. The simulation result for the proposed algorithm performed good regulation lowering the hypoglycaemia risk and maintaining the glucose level within the normal glycaemic range. To validate the performance of the tracking of output and setpoint, average tracking error is used and 4.4 mg/dl results are obtained while compared with standard value (14.3 mg/dl).

Homeostasis as a proportional-integral control system

According to medical guidelines, the distinction between "healthy" and "unhealthy" patients is commonly based on single, discrete values taken at an isolated point in time (e.g., blood pressure or core temperature). Perhaps a more robust and insightful diagnosis can be obtained by studying the functional interdependence of such indicators and the homeostasis that controls them. This requires quasi-continuous measurements and a procedure to map the data onto a parsimonious control model with a degree of universality. The current research illustrates this approach using glucose homeostasis as a target. Data were obtained from 41 healthy subjects wearing over-the-counter glucose monitors, and projected onto a simple proportional-integral (PI) controller, widely used in engineering applications. The indicators quantifying the control function are clustered for the great majority of subjects, while a few outliers exhibit less responsive homeostasis. Practical implications for healthcare and education are further discussed.

Design principles of the paradoxical feedback between pancreatic alpha and beta cells

Mammalian glucose homeostasis is controlled by the antagonistic hormones insulin and glucagon, secreted by pancreatic beta and alpha cells respectively. These two cell types are adjacently located in the islets of Langerhans and affect each others’ secretions in a paradoxical manner: while insulin inhibits glucagon secretion from alpha cells, glucagon seems to stimulate insulin secretion from beta cells. Here we ask what are the design principles of this negative feedback loop. We systematically simulate the dynamics of all possible islet inter-cellular connectivity patterns and analyze different performance criteria. We find that the observed circuit dampens overshoots of blood glucose levels after reversion of glucose drops. This feature is related to the temporal delay in the rise of insulin concentrations in peripheral tissues, compared to the immediate hormone action on the liver. In addition, we find that the circuit facilitates coordinate secretion of both hormones in response to protein meals. Our study highlights the advantages of a paradoxical paracrine feedback loop in maintaining metabolic homeostasis.

Efficacy and safety of the artificial pancreas in the paediatric population with type 1 diabetes

BACKGROUND

Type 1 diabetes (DM1) is one of the most common chronic diseases in childhood and requires life-long insulin therapy and continuous health care support. An artificial pancreas (AP) or closed-loop system (CLS) have been developed with the aim of improving metabolic control without increasing the risk of hypoglycaemia in patients with DM1. As the impact of APs have been studied mainly in adults, the aim of this review is to evaluate the efficacy and safety of the AP in the paediatric population with DM1.

MAIN BODY

The real advantage of a CLS compared to last-generation sensor-augmented pumps is the gradual modulation of basal insulin infusion in response to glycaemic variations (towards both hyperglycaemia and hypoglycaemia), which has the aim of improving the proportion of time spent in the target glucose range and reducing the mean glucose level without increasing the risk of hypoglycaemia. Some recent studies demonstrated that also in children and adolescents an AP is able to reduce the frequency of hypoglycaemic events, an important limiting factor in reaching good metabolic control, particularly overnight. However, the advantages of the AP in reducing hyperglycaemia, increasing the time spent in the target glycaemic range and thus reducing glycated haemoglobin are less clear and require more clinical trials in the paediatric population, in particular in younger children.

CONCLUSIONS

Although the first results from bi-hormonal CLS are promising, long-term, head-to-head studies will have to prove their superiority over insulin-only approaches. More technological progress, the availability of more fast-acting insulin, further developments of algorithms that could improve glycaemic control after meals and physical activity are the most important challenges in reaching an optimal metabolic control with the use of the AP in children and adolescents.

Automated Overnight Closed-Loop Control Using a Proportional-Integral-Derivative Algorithm with Insulin Feedback in Children and Adolescents with Type 1 Diabetes at Diabetes Camp

OBJECTIVE

This study determined the feasibility and efficacy of an automated proportional-integral-derivative with insulin feedback (PID-IFB) controller in overnight closed-loop (OCL) control of children and adolescents with type 1 diabetes over multiple days in a diabetes camp setting.

RESEARCH DESIGN AND METHODS

The Medtronic (Northridge, CA) Android™ (Google, Mountain View, CA)-based PID-IFB system consists of the Medtronic Minimed Revel™ 2.0 pump and Enlite™ sensor, a control algorithm residing on an Android phone, a translator, and remote monitoring capabilities. An inpatient study was completed for 16 participants to determine feasibility. For the camp study, subjects with type 1 diabetes were randomized to either OCL or sensor-augmented pump therapy (control conditions) per night for up to 6 nights at diabetes camp.

RESULTS

During the camp study, 21 subjects completed 50 OCL nights and 52 control nights. Based on intention to treat, the median time spent in range, from 70 to 150 mg/dL, was greater during OCL at 66.4% (n = 55) versus 50.6% (n = 52) during the control period (P = 0.004). A per-protocol analysis allowed for assessment of algorithm performance with the median percentage time in range, 70-150 mg/dL, being 75.5% (n = 37) for OCL versus 47.6% (n = 32) for the control period (P < 0.001). There was less time spent in the hypoglycemic ranges <60 mg/dL and <70 mg/dL during OCL compared with the control period (P = 0.003 and P < 0.001, respectively).

CONCLUSIONS

The PID-IFB controller is effective in improving time spent in range as well as reducing nocturnal hypoglycemia during the overnight period in children and adolescents with type 1 diabetes in a diabetes camp setting.

A Computational Method to Determine Glucose Infusion Rates for Isoglycemic Intravenous Glucose Infusion Study

The results of the isoglycemic intravenous glucose infusion (IIGI) study need to mimic the dynamic glucose profiles during the oral glucose tolerance test (OGTT) to accurately calculate the incretin effect. The glucose infusion rates during IIGI studies have historically been determined by experienced research personnel using the manual ad-hoc method. In this study, a computational method was developed to automatically determine the infusion rates for IIGI study based on a glucose-dynamics model. To evaluate the computational method, 18 subjects with normal glucose tolerance underwent a 75 g OGTT. One-week later, Group 1 (n = 9) and Group 2 (n = 9) underwent IIGI studies using the ad-hoc method and the computational method, respectively. Both methods were evaluated using correlation coefficient, mean absolute relative difference (MARD), and root mean square error (RMSE) between the glucose profiles from the OGTT and the IIGI study. The computational method exhibited significantly higher correlation (0.95 ± 0.03 versus 0.86 ± 0.10, P = 0.019), lower MARD (8.72 ± 1.83% versus 13.11 ± 3.66%, P = 0.002), and lower RMSE (10.33 ± 1.99 mg/dL versus 16.84 ± 4.43 mg/dL, P = 0.002) than the ad-hoc method. The computational method can facilitate IIGI study, and enhance its accuracy and stability. Using this computational method, a high-quality IIGI study can be accomplished without the need for experienced personnel.

Day and Night Closed-Loop Control Using the Integrated Medtronic Hybrid Closed-Loop System in Type 1 Diabetes at Diabetes Camp

OBJECTIVE

To evaluate the feasibility and efficacy of a fully integrated hybrid closed-loop (HCL) system (Medtronic MiniMed Inc., Northridge, CA), in day and night closed-loop control in subjects with type 1 diabetes, both in an inpatient setting and during 6 days at diabetes camp.

RESEARCH DESIGN AND METHODS

The Medtronic MiniMed HCL system consists of a fourth generation (4S) glucose sensor, a sensor transmitter, and an insulin pump using a modified proportional-integral-derivative (PID) insulin feedback algorithm with safety constraints. Eight subjects were studied over 48 h in an inpatient setting. This was followed by a study of 21 subjects for 6 days at diabetes camp, randomized to either the closed-loop control group using the HCL system or to the group using the Medtronic MiniMed 530G with threshold suspend (control group).

RESULTS

The overall mean sensor glucose percent time in range 70-180 mg/dL was similar between the groups (73.1% vs. 69.9%, control vs. HCL, respectively) (P = 0.580). Meter glucose values between 70 and 180 mg/dL were also similar between the groups (73.6% vs. 63.2%, control vs. HCL, respectively) (P = 0.086). The mean absolute relative difference of the 4S sensor was 10.8 ± 10.2%, when compared with plasma glucose values in the inpatient setting, and 12.6 ± 11.0% compared with capillary Bayer CONTOUR NEXT LINK glucose meter values during 6 days at camp.

CONCLUSIONS

In the first clinical study of this fully integrated system using an investigational PID algorithm, the system did not demonstrate improved glucose control compared with sensor-augmented pump therapy alone. The system demonstrated good connectivity and improved sensor performance.

An artificial pancreas for automated blood glucose control in patients with Type 1 diabetes

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.

Fabrication of a Flexible Amperometric Glucose Sensor Using Additive Processes

This study details the use of printing and other additive processes to fabricate a novel amperometric glucose sensor. The sensor was fabricated using a Au coated 12.7 μm thick polyimide substrate as a starting material, where micro-contact printing, electrochemical plating, chloridization, electrohydrodynamic jet (e-jet) printing, and spin coating were used to pattern, deposit, chloridize, print, and coat functional materials, respectively. We have found that e-jet printing was effective for the deposition and patterning of glucose oxidase inks with lateral feature sizes between ~5 to 1000 μm in width, and that the glucose oxidase was still active after printing. The thickness of the permselective layer was optimized to obtain a linear response for glucose concentrations up to 32 mM and no response to acetaminophen, a common interfering compound, was observed. The use of such thin polyimide substrates allow wrapping of the sensors around catheters with high radius of curvature ~250 μm, where additive and microfabrication methods may allow significant cost reductions.

Feasibility study of a bio-inspired artificial pancreas in adults with type 1 diabetes

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.

Automated control of an adaptive bihormonal, dual-sensor artificial pancreas and evaluation during inpatient studies

Automated control of blood glucose in patients with type-1 diabetes has not yet been fully implemented. The aim of this study was to design and clinically evaluate a system that integrates a control algorithm with off-the-shelf subcutaneous sensors and pumps to automate the delivery of the hormones glucagon and insulin in response to continuous glucose sensor measurements. The automated component of the system runs an adaptive proportional derivative control algorithm which determines hormone delivery rates based on the sensed glucose measurements and the meal announcements by the patient. We provide details about the system design and the control algorithm, which incorporates both a fading memory proportional derivative controller (FMPD) and an adaptive system for estimating changing sensitivity to insulin based on a glucoregulatory model of insulin action. For an inpatient study carried out in eight subjects using Dexcom SEVEN PLUS sensors, prestudy HbA1c averaged 7.6, which translates to an estimated average glucose of 171 mg/dL. In contrast, during use of the automated system, after initial stabilization, glucose averaged 145 mg/dL and subjects were kept within the euglycemic range (between 70 and 180 mg/dL) for 73.1% of the time, indicating improved glycemic control. A further study on five additional subjects in which we used a newer and more reliable glucose sensor (Dexcom G4 PLATINUM) and made improvements to the insulin and glucagon pump communication system resulted in elimination of hypoglycemic events. For this G4 study, the system was able to maintain subjects' glucose levels within the near-euglycemic range for 71.6% of the study duration and the mean venous glucose level was 151 mg/dL.

Algorithms for a closed-loop artificial pancreas: the case for proportional-integral-derivative control

Closed-loop insulin delivery continues to be one of most promising strategies for achieving near-normal control of blood glucose levels in individuals with diabetes. Of the many components that need to work well for the artificial pancreas to be advanced into routine use, the algorithm used to calculate insulin delivery has received a substantial amount of attention. Most of that attention has focused on the relative merits of proportional-integral-derivative versus model-predictive control. A meta-analysis of the clinical data obtained in studies performed to date with these approaches is conducted here, with the objective of determining if there is a trend for one approach to be performing better than the other approach. Challenges associated with implementing each approach are reviewed with the objective of determining how these approaches might be improved. Results of the meta-analysis, which focused predominantly on the breakfast meal response, suggest that to date, the two approaches have performed similarly. However, uncontrolled variables among the various studies, and the possibility that future improvements could still be effected in either approach, limit the validity of this conclusion. It is suggested that a more detailed examination of the challenges associated with implementing each approach be conducted.

The artificial pancreas: is it important to understand how the β cell controls blood glucose?

It has been more than 7 years since the first fully automated closed-loop insulin delivery system that linked subcutaneous insulin delivery and glucose sensing was published. Since the initial report, the physiologic insulin delivery (PID) algorithm used to emulate the β cell has been modified from the original proportional-integral-derivative terms needed to fit the β cell's biphasic response to a hyperglycemic clamp to include terms emulating cephalic phase insulin release and the effect of insulin per se to inhibit insulin secretion. In this article, we compare the closed-loop glucose profiles obtained as each new term has been added, reassess the ability of the revised PID model to describe the β cells' insulin response to a hyperglycemic clamp, and look for the first time at its ability to describe the response to a hypoglycemic clamp. We also consider changes that might be added to the model based on perfused pancreas data. We conclude that the changes introduced in the PID model have systematically improved the closed-loop meal response. We note that the changes made do not adversely affect the ability of the model to fit hyperglycemic clamp data but are necessary to fit the response to a hypoglycemic clamp. Finally, we note a number of β cell characteristics observed in the perfused pancreas have not been included in the model. We suggest that continuing the effort to understand and incorporate aspects of how the β cell achieves glucose control can provide valuable insights into how improvements in future artificial pancreas algorithms might be achieved.

β-Cell lipotoxicity in response to free fatty acid elevation in prepubertal youth: African American versus Caucasian contrast

Prepubertal African American (AA) youth compared with their Caucasian (C) peers have higher insulin secretion, which correlates positively with free fatty acid (FFA) concentration. In our continued efforts to explain the racial disparity in insulinemia, and because FFAs modulate insulin secretion, we hypothesized that AA youth would have a greater response to FFA-induced β-cell insulin secretion than C youth. We compared the short-term effects of FFA elevation on fasting and glucose-stimulated C-peptide-modeled insulin secretion in prepubertal normal-weight AA versus C peers during a 2-h hyperglycemic clamp (12.5 mmol/L) on two occasions: 1) infusion of normal saline and 2) infusion of 20% intralipid (IL). During IL infusion, insulin sensitivity (IS) declined comparably in AA and C youth. Glucose sensitivity of first- and second-phase insulin secretion showed a significant condition × race interaction being higher in AA youth. Disposition index, β-cell function relative to IS, declined with IL infusion in AA and C youth, with a significantly greater decrease in Cs compared with AAs. In conclusion, AA and C prepubertal youth both demonstrated a decline in β-cell function relative to IS during IL infusion, indicative of acute lipotoxicity. The greater decline in C youth compared with AAs may suggest that C youth are more susceptible to β-cell lipotoxicity than AA youth, or alternatively, that AA youth are hypersensitive to FFA stimulation of β-cell insulin secretion, consistent with our theory.

β-Cell lipotoxicity after an overnight intravenous lipid challenge and free fatty acid elevation in African American versus American white overweight/obese adolescents

OBJECTIVE

Overweight/obese (OW/OB) African American (AA) adolescents have a more diabetogenic insulin secretion/sensitivity pattern compared with their American white (AW) peers. The present study investigated β-cell lipotoxicity to test whether increased free fatty acid (FFA) levels result in greater β-cell dysfunction in AA vs AW OW/OB adolescents.

RESEARCH DESIGN AND METHODS

Glucose-stimulated insulin secretion was modeled, from glucose and C-peptide concentrations during a 2-hour hyperglycemic (225 mg/dL) clamp in 22 AA and 24 AW OW/OB adolescents, on 2 occasions after a 12-hour overnight infusion of either normal saline or intralipid (IL) in a random sequence. β-Cell function relative to insulin sensitivity, the disposition index (DI), was examined during normal saline and IL conditions. Substrate oxidation was evaluated with indirect calorimetry and body composition and abdominal adiposity with dual-energy X-ray absorptiometry and magnetic resonance imaging at L4-L5, respectively.

RESULTS

Age, sex, body mass index, total and sc adiposity were similar between racial groups, but visceral adiposity was significantly lower in AAs. During IL infusion, FFAs and fat oxidation increased and insulin sensitivity decreased similarly in AAs and AWs. β-Cell glucose sensitivity of first- and second-phase insulin secretion did not change significantly during IL infusion in either group, but DI in each phase decreased significantly and similarly in AAs and AWs.

CONCLUSIONS

Overweight/obese AA and AW adolescents respond to an overnight fat infusion with significant declines in insulin sensitivity, DI, and β-cell function relative to insulin sensitivity, suggestive of β-cell lipotoxicity. However, contrary to our hypothesis, there does not seem to be a race differential in β-cell lipotoxicity. Longer durations of FFA elevation may unravel such race-related contrasts.

An Actor-Critic based controller for glucose regulation in type 1 diabetes

A novel adaptive approach for glucose control in individuals with type 1 diabetes under sensor-augmented pump therapy is proposed. The controller, is based on Actor-Critic (AC) learning and is inspired by the principles of reinforcement learning and optimal control theory. The main characteristics of the proposed controller are (i) simultaneous adjustment of both the insulin basal rate and the bolus dose, (ii) initialization based on clinical procedures, and (iii) real-time personalization. The effectiveness of the proposed algorithm in terms of glycemic control has been investigated in silico in adults, adolescents and children under open-loop and closed-loop approaches, using announced meals with uncertainties in the order of ±25% in the estimation of carbohydrates. The results show that glucose regulation is efficient in all three groups of patients, even with uncertainties in the level of carbohydrates in the meal. The percentages in the A+B zones of the Control Variability Grid Analysis (CVGA) were 100% for adults, and 93% for both adolescents and children. The AC based controller seems to be a promising approach for the automatic adjustment of insulin infusion in order to improve glycemic control. After optimization of the algorithm, the controller will be tested in a clinical trial.

Wearable and implantable pancreas substitutes

A lifelong-implanted and completely automated artificial or bioartificial pancreas (BAP) is the holy grail for type 1 diabetes treatment, and could be a definitive solution even for other severe pathologies, such as pancreatitis and pancreas cancer. Technology has made several important steps forward in the last years, providing new hope for the realization of such devices, whose feasibility is strictly connected to advances in glucose sensor technology, subcutaneous and intraperitoneal insulin pump development, the design of closed-loop control algorithms for mechatronic pancreases, as well as cell and tissue engineering and cell encapsulation for biohybrid pancreases. Furthermore, smart integration of the mentioned components and biocompatibility issues must be addressed, bearing in mind that, for mechatronic pancreases, it is most important to consider how to recharge implanted batteries and refill implanted insulin reservoirs without requiring periodic surgical interventions. This review describes recent advancements in technologies and concepts related to artificial and bioartificial pancreases, and assesses how far we are from a lifelong-implanted and self-working pancreas substitute that can fully restore the quality of life of a diabetic (or other type of) patient.

Development of a fully automated closed loop artificial pancreas control system with dual pump delivery of insulin and glucagon

Patients with diabetes have difficulty controlling their blood sugar and suffer from acute effects of hypoglycemia and long-term effects of hyperglycemia, which include disease of the eyes, kidneys and nerves/feet. In this paper, we describe a new system that is used to automatically control blood sugar in people with diabetes through the fully automated measurement of blood glucose levels and the delivery of insulin and glucagon via the subcutaneous route. When a patient's blood sugar goes too high, insulin is given to the patient to bring his/her blood sugar back to a normal level. To prevent a patient's blood sugar from going too low, the patient is given a hormone called glucagon which raises the patient's blood sugar. While other groups have described methods for automatically delivering insulin and glucagon, many of these systems still require human interaction to enter the venous blood sugar levels into the control system. This paper describes the development of a fully automated closed-loop dual sensor bi-hormonal artificial pancreas system that does not require human interaction. The system described in this paper is comprised of two sensors for measuring glucose, two pumps for independent delivery of insulin and glucagon, and a laptop computer running a custom software application that controls the sensor acquisition and insulin and glucagon delivery based on the glucose values recorded. Two control algorithms are designed into the software: (1) an algorithm that delivers insulin and glucagon according to their proportional and derivative errors and proportional and derivative gains and (2) an adaptive algorithm that adjusts the gain factors based on the patient's current insulin sensitivity as determined using a mathematical model. Results from this work may ultimately lead to development of a portable, easy to use, artificial pancreas device that can enable far better glycemic control in patients with diabetes.

A bio-inspired glucose controller based on pancreatic β-cell physiology

INTRODUCTION

Control algorithms for closed-loop insulin delivery in type 1 diabetes have been mainly based on control engineering or artificial intelligence techniques. These, however, are not based on the physiology of the pancreas but seek to implement engineering solutions to biology. Developments in mathematical models of the β-cell physiology of the pancreas have described the glucose-induced insulin release from pancreatic β cells at a molecular level. This has facilitated development of a new class of bio-inspired glucose control algorithms that replicate the functionality of the biological pancreas. However, technologies for sensing glucose levels and delivering insulin use the subcutaneous route, which is nonphysiological and introduces some challenges. In this article, a novel glucose controller is presented as part of a bio-inspired artificial pancreas.

METHODS

A mathematical model of β-cell physiology was used as the core of the proposed controller. In order to deal with delays and lack of accuracy introduced by the subcutaneous route, insulin feedback and a gain scheduling strategy were employed. A United States Food and Drug Administration-accepted type 1 diabetes mellitus virtual population was used to validate the presented controller.

RESULTS

Premeal and postmeal mean ± standard deviation blood glucose levels for the adult and adolescent populations were well within the target range set for the controller [(70, 180) mg/dl], with a percent time in range of 92.8 ± 7.3% for the adults and 83.5 ± 14% for the adolescents.

CONCLUSIONS

This article shows for the first time very good glucose control in a virtual population with type 1 diabetes mellitus using a controller based on a subcellular β-cell model.

Closed-loop artificial pancreas: current studies and promise for the future

PURPOSE OF REVIEW

The availability of glucose sensors and insulin pumps has enabled the development of devices and software to partially or completely automate insulin delivery. Over the last 2 years, the number of centers developing and evaluating such systems, as well as the number of reports of these studies in the literature, have expanded dramatically. The purpose of this review is to highlight the progress along multiple fronts to develop automated systems to improve control of type 1 diabetes.

RECENT FINDINGS

Multiple approaches, including automated suspension for actual or impending hypoglycemia, automated augmentation for hyperglycemia, as well as hybrid and full closed-loop control, are in parallel development. So far, early hypoglycemia prevention studies and small inpatient feasibility studies have demonstrated the potential for reducing hypoglycemia and improving overall diabetes control.

SUMMARY

Current sensors, pumps, and control algorithms show promise for use in a closed-loop system but have been limited to inpatient studies. The next phase of development should focus on their evaluation in controlled short-term outpatient safety and efficacy trials.

Evidence for early defects in insulin sensitivity and secretion before the onset of glucose dysregulation in obese youths: a longitudinal study

We sought to determine whether obese adolescents with high-"normal" 2-h post-oral glucose tolerance test glucose levels display defects in insulin secretion and sensitivity associated with future development of impaired glucose tolerance (IGT). Insulin sensitivity was measured by hyperinsulinemic-euglycemic clamp and insulin secretion by applying mathematical modeling during the hyperglycemic clamp in 60 normal glucose tolerance (NGT) obese adolescents, divided into three groups based on the 2-h glucose values (<100, 100-119, 120-139 mg/dL), and in 21 IGT obese adolescents. Glucose tolerance was reevaluated after 2 years. Insulin sensitivity decreased significantly across 2-h glucose NGT categories, while the highest NGT category and IGT group were similar. First-phase insulin secretion decreased across NGT categories, while no difference was found between the highest NGT group and IGT subjects. Second-phase secretion was similar across all NGT and IGT groups. The disposition index ((C)DI) decreased across NGT categories, while no difference was observed between the highest NGT and IGT subjects. Age and (C)DI were the best predictors of 2-h glucose after two years. Across rising categories of normal 2-h glucose levels, NGT obese adolescents exhibit significant impairment of β-cell function relative to insulin sensitivity associated with the development of IGT.

Closed-loop insulin delivery utilizing pole placement to compensate for delays in subcutaneous insulin delivery

BACKGROUND

We have previously used insulin feedback (IFB) as a component of a closed-loop algorithm emulating the β cell. This was based on the observation that insulin secretion is inhibited by insulin concentration. We show here that the effect of IFB is to make a closed-loop system behave as if delays in the insulin pharmacokinetic (PK)/pharmacodynamic (PD) response are reduced. We examine whether the mechanism can be used to compensate for delays in the subcutaneous PK/PD insulin response.

METHOD

Closed-loop insulin delivery was performed in seven diabetic dogs using a proportional-integral-derivative model of the β cell modified by model-predicted IFB. The level of IFB was set using pole placement. Meal responses were obtained on three occasions: without IFB (NONE), reference IFB (REF), and 2xREF, with experiments performed in random order. The ability of the insulin model to predict insulin concentration was evaluated by correlation with the measured profile and results reported as R(2). The ability of IFB to improve the meal response was evaluated by comparing peak and nadir postprandial glucose and area under the curve (AUC; repeated measures analysis of variance with post hoc test for linear trend).

RESULTS

Insulin concentration was well predicted by the model (median R(2) = 0.87, 0.79, and 0.90 for NONE, REF, and 2xREF, respectively). Peak postprandial glucose (294 ± 15, 243 ± 21, and 247 ± 16 mg/dl) and AUC (518.2 ± 36.13, 353.5 ± 45.04, and 280.3 ± 39.37 mg/dl · min) decreased with increasing IFB (p < .05, linear trend). Nadir glucose was not affected by IFB (76 ± 5.4, 68 ± 7.3, and 72 ± 4.3 mg/dl; p = .63).

CONCLUSIONS

Insulin feedback provides an effective mechanism to compensate for delay in the insulin PK/PD profile.

A local glucose-and oxygen concentration-based insulin secretion model for pancreatic islets

BACKGROUND

Because insulin is the main regulator of glucose homeostasis, quantitative models describing the dynamics of glucose-induced insulin secretion are of obvious interest. Here, a computational model is introduced that focuses not on organism-level concentrations, but on the quantitative modeling of local, cellular-level glucose-insulin dynamics by incorporating the detailed spatial distribution of the concentrations of interest within isolated avascular pancreatic islets.

METHODS

All nutrient consumption and hormone release rates were assumed to follow Hill-type sigmoid dependences on local concentrations. Insulin secretion rates depend on both the glucose concentration and its time-gradient, resulting in second-and first-phase responses, respectively. Since hypoxia may also be an important limiting factor in avascular islets, oxygen and cell viability considerations were also built in by incorporating and extending our previous islet cell oxygen consumption model. A finite element method (FEM) framework is used to combine reactive rates with mass transport by convection and diffusion as well as fluid-mechanics.

RESULTS

The model was calibrated using experimental results from dynamic glucose-stimulated insulin release (GSIR) perifusion studies with isolated islets. Further optimization is still needed, but calculated insulin responses to stepwise increments in the incoming glucose concentration are in good agreement with existing experimental insulin release data characterizing glucose and oxygen dependence. The model makes possible the detailed description of the intraislet spatial distributions of insulin, glucose, and oxygen levels. In agreement with recent observations, modeling also suggests that smaller islets perform better when transplanted and/or encapsulated.

CONCLUSIONS

An insulin secretion model was implemented by coupling local consumption and release rates to calculations of the spatial distributions of all species of interest. The resulting glucose-insulin control system fits in the general framework of a sigmoid proportional-integral-derivative controller, a generalized PID controller, more suitable for biological systems, which are always nonlinear due to the maximum response being limited. Because of the general framework of the implementation, simulations can be carried out for arbitrary geometries including cultured, perifused, transplanted, and encapsulated islets.

The effect of insulin feedback on closed loop glucose control

CONTEXT

Initial studies of closed-loop proportional integral derivative control in individuals with type 1 diabetes showed good overnight performance, but with breakfast meal being the hardest to control and requiring supplemental carbohydrate to prevent hypoglycemia.

OBJECTIVE

The aim of this study was to assess the ability of insulin feedback to improve the breakfast-meal profile.

DESIGN AND SETTING

We performed a single center study with closed-loop control over approximately 30 h at an inpatient clinical research facility.

PATIENTS

Eight adult subjects with previously diagnosed type 1 diabetes participated.

INTERVENTION

Subjects received closed-loop insulin delivery with supplemental carbohydrate as needed.

MAIN OUTCOME MEASURES

Outcome measures were plasma insulin concentration, model-predicted plasma insulin concentration, 2-h postprandial and 3- to 4-h glucose rate-of-change following breakfast after 1 d of closed-loop control, and the need for supplemental carbohydrate in response to nadir hypoglycemia.

RESULTS

Plasma insulin levels during closed loop were well correlated with model predictions (R = 0.86). Fasting glucose after 1 d of closed loop was not different from nighttime target (118 ± 9 vs. 110 mg/dl; P = 0.38). Two-hour postbreakfast glucose was 132 ± 16 mg/dl with stable values 3-4 h after the meal (0.03792 ± 0.0884 mg/dl · min, not different from 0; P = 0.68) and at target (97 ± 6 mg/dl, not different from 90; P = 0.28). Three subjects required supplemental carbohydrates after breakfast on d 2 of closed loop.

CONCLUSIONS/INTERPRETATION

Insulin feedback can be implemented using a model estimate of concentration. Proportional integral derivative control with insulin feedback can achieve a desired breakfast response but still requires supplemental carbohydrate to be delivered in some instances. Studies assessing more optimal control configurations and safeguards need to be conducted.

Physiologic insulin delivery with insulin feedback: a control systems perspective

Individuals with type 1 diabetes mellitus must effectively manage glycemia to avoid acute and chronic complications related to aberrations of glucose levels. Because optimal diabetes management can be difficult to achieve and burdensome, research into a closed-loop insulin delivery system has been of interest for several decades. This paper provides an overview, from a control systems perspective, of the research and development effort of a particular algorithm--the external physiologic insulin delivery system. In particular the introduction of insulin feedback, based on β-cell physiology, is covered in detail. A summary of human clinical trials is provided in the context of the evolution of this algorithm, and this paper outlines some of the research avenues that show particular promise.

Toward closing the loop: an update on insulin pumps and continuous glucose monitoring systems

This article reviews current pump and continuous glucose monitoring therapy and what will be required to integrate these systems into closed-loop control. Issues with sensor accuracy, lag time, and calibration are discussed as well as issues with insulin pharmacodynamics, which result in a delayed onset of insulin action in a closed-loop system. A stepwise approach to closed-loop therapy is anticipated, where the first systems will suspend insulin delivery based on actual or predicted hypoglycemia. Subsequent systems may control to range, limiting the time spent in hyperglycemia by mitigating the effects of a missed food bolus or underestimate of consumed carbohydrates, while minimizing the risk of hypoglycemia.

Acute response in vivo of a fiber-optic sensor for continuous glucose monitoring from canine studies on point accuracy

The objective of this study was to evaluate the acute response of Sencil(™), a fiber-optic sensor, in point accuracy for glucose monitoring in vivo on healthy dogs under anesthesia. A total of four dogs with clinically normal glycemia were implanted with one sensor each in the chest region to measure the interstitial glucose concentration during the ovariohysterectomy procedure. The data was acquired every 10 seconds after initiation, and was compared to the concentration of venous plasma glucose sampled during the surgery procedures for accuracy of agreement analysis. In the four trials with a range of 71-297 mg/dL plasma glucose, the collected 21 pairs of ISF readings from the Sencil™ and the plasma reference showed superior dispersion of residue values than the conventional system, and a linear correlation (the Pearson correlation coefficient is 0.9288 and the y-intercept is 14.22 mg/dL). The MAD (17.6 mg/dL) and RMAD (16.16%) of Sencil™ measurements were in the comparable range of the conventional system. The Clarke error grid analysis indicated that 100% of the paired points were in the clinically acceptable zone A (61.9%) and B (38.1%).

Closed-loop insulin delivery using a subcutaneous glucose sensor and intraperitoneal insulin delivery: feasibility study testing a new model for the artificial pancreas

OBJECTIVE

Attempts to build an artificial pancreas by using subcutaneous insulin delivery from a portable pump guided by an subcutaneous glucose sensor have encountered delays and variability of insulin absorption. We tested closed-loop intraperitoneal insulin infusion from an implanted pump driven by an subcutaneous glucose sensor via a proportional-integral-derivative (PID) algorithm.

RESEARCH DESIGN AND METHODS

Two-day closed-loop therapy (except for a 15-min pre-meal manual bolus) was compared with a 1-day control phase with intraperitoneal open-loop insulin delivery, according to randomized order, in a hospital setting in eight type 1 diabetic patients treated by implanted pumps. The percentage of time spent with blood glucose in the 4.4-6.6 mmol/l range was the primary end point. RESULTS During the closed-loop phases, the mean +/- SEM percentage of time spent with blood glucose in the 4.4-6.6 mmol/l range was significantly higher (39.1 +/- 4.5 vs. 27.7 +/- 6.2%, P = 0.05), and overall dispersion of blood glucose values was reduced among patients. Better closed-loop glucose control came from the time periods excluding the two early postprandial hours with a higher percentage of time in the 4.4-6.6 mmol/l range (46.3 +/- 5.3 vs. 28.6 +/- 7.4, P = 0.025) and lower mean blood glucose levels (6.9 +/- 0.3 vs. 7.9 +/- 0.6 mmol/l, P = 0.036). Time spent with blood glucose <3.3 mmol/l was low and similar for both investigational phases.

CONCLUSIONS

Our results demonstrate the feasibility of intraperitoneal insulin delivery for an artificial beta-cell and support the need for further study. Moreover, according to a semiautomated mode, the features of the pre-meal bolus in terms of timing and amount warrant further research.

Artificial pancreas: an emerging approach to treat Type 1 diabetes

Intensive insulin therapy aimed at achieving normal glucose levels significantly reduces the complications that are associated with diabetes but is also associated with an increased risk of low glucose levels (hypoglycemia). The growing use of continuous glucose monitors has stimulated the development of the artificial pancreas, a closed-loop insulin-delivery system aimed at restoring near-normal glucose levels while reducing the risk of hypoglycemia. The artificial pancreas comprises three components: a continuous glucose monitor, an insulin infusion pump and a control algorithm delivering insulin according to real-time glucose readings. In this article, we review closed-loop glucose control, including its components, development, testing and clinical application.

Nonlinear modeling of the dynamic effects of infused insulin on glucose: comparison of compartmental with Volterra models

This paper presents the results of a computational study that compares simulated compartmental (differential equation) and Volterra models of the dynamic effects of insulin on blood glucose concentration in humans. In the first approach, we employ the widely accepted "minimal model" and an augmented form of it, which incorporates the effect of insulin secretion by the pancreas, in order to represent the actual closed-loop operating conditions of the system, and in the second modeling approach, we employ the general class of Volterra-type models that are estimated from input-output data. We demonstrate both the equivalence between the two approaches analytically and the feasibility of obtaining accurate Volterra models from insulin-glucose data generated from the compartmental models. The results corroborate the proposition that it may be preferable to obtain data-driven (i.e., inductive) models in a more general and realistic operating context, without resorting to the restrictive prior assumptions and simplifications regarding model structure and/or experimental protocols (e.g., glucose tolerance tests) that are necessary for the compartmental models proposed previously. These prior assumptions may lead to results that are improperly constrained or biased by preconceived (and possibly erroneous) notions-a risk that is avoided when we let the data guide the inductive selection of the appropriate model within the general class of Volterra-type models, as our simulation results suggest.

Is an automatic pump suspension feature safe for children with type 1 diabetes? An exploratory analysis with a closed-loop system

OBJECTIVES

It has been proposed that the first step towards a closed-loop artificial pancreas might be to use a continuous glucose sensor to automatically suspend the basal insulin delivery based on projected low sensor glucose values.

METHODS

We reviewed our recent experience with an artificial pancreas system, utilizing a proportional-integrative-derivative (PID) algorithm, in 17 adolescents with type 1 diabetes (T1D) to assess the safety and efficacy of this maneuver.

RESULTS

During 34 h of closed-loop automated insulin delivery, 18 pump suspensions > or =60 min (90 +/- 18 min) occurred in eight subjects. Sensor glucose levels fell from 159 +/- 42 mg/dL to a nadir of 72 +/- 13 mg/dL. Corresponding plasma glucose levels fell from 168 +/- 51 to 72 +/- 16 mg/dL, with values <60 mg/dL recorded in only four of the 18 events.

CONCLUSIONS

These data suggest that automatic pump suspension using the PID algorithm may be an effective means to prevent hypoglycemia in youth with T1D.

Metabolic abnormalities underlying the different prediabetic phenotypes in obese adolescents

OBJECTIVE

The aim of this study was to define the metabolic abnormalities underlying the prediabetic status of isolated impaired fasting glucose (IFG), isolated impaired glucose tolerance (IGT), and combined IFG/IGT in obese youth.

RESEARCH DESIGN AND METHODS

We used state-of-the-art techniques (hyperinsulinemic-euglycemic and hyperglycemic clamps), applying a model of glucose-stimulated insulin secretion to the glucose and C-peptide concentration, in 40 normal glucose tolerance (NGT), 17 IFG, 23 IGT, and 11 IFG/IGT obese adolescents. Percent fat (by dual-energy x-ray absorptiometry), age, gender and ethnicity were comparable among groups.

RESULTS

Peripheral insulin sensitivity was similar between the IFG and NGT groups. In contrast, the IGT and IFG/IGT groups showed marked reductions in peripheral insulin sensitivity (P < 0.002). Basal hepatic insulin resistance index (basal hepatic glucose production x fasting plasma insulin) was significantly increased in IFG, IGT, and IFG/IGT (P < 0.009) compared with NGT. Glucose sensitivity of first-phase insulin secretion was progressively lower in IFG, IGT, and IFG/IGT compared with NGT. Glucose sensitivity of second-phase secretion showed a statistically significant defect only in the IFG/IGT group. In a multivariate regression analysis, glucose sensitivity of first-phase secretion and basal insulin secretion rate were significant independent predictors of FPG (total r(2) = 25.9%).

CONCLUSIONS

IFG, in obese adolescents, is linked primarily to alterations in glucose sensitivity of first-phase insulin secretion and liver insulin sensitivity. The IGT group is affected by a more severe degree of peripheral insulin resistance and reduction in first-phase secretion. IFG/IGT is hallmarked by a profound insulin resistance and by a new additional defect in second-phase insulin secretion.

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

OBJECTIVE

The most promising beta-cell replacement therapy for children with type 1 diabetes is a closed-loop artificial pancreas incorporating continuous glucose sensors and insulin pumps. The Medtronic MiniMed external physiological insulin delivery (ePID) system combines an external pump and sensor with a variable insulin infusion rate algorithm designed to emulate the physiological characteristics of the beta-cell. However, delays in insulin absorption associated with the subcutaneous route of delivery inevitably lead to large postprandial glucose excursions.

RESEARCH DESIGN AND METHODS

We studied the feasibility of the Medtronic ePID system in youth with type 1 diabetes and hypothesized that small manual premeal "priming" boluses would reduce postprandial excursions during closed-loop control. Seventeen adolescents (aged 15.9 +/- 1.6 years; A1C 7.1 +/- 0.8%) underwent 34 h of closed-loop control; 8 with full closed-loop (FCL) control and 9 with hybrid closed-loop (HCL) control (premeal priming bolus).

RESULTS

Mean glucose levels were 135 +/- 45 mg/dl in the HCL group versus 141 +/- 55 mg/dl in the FCL group (P = 0.09); daytime glucose levels averaged 149 +/- 47 mg/dl in the HCL group versus 159 +/- 59 mg/dl in the FCL group (P = 0.03). Peak postprandial glucose levels averaged 194 +/- 47 mg/dl in the HCL group versus 226 +/- 51 mg/dl in the FCL group (P = 0.04). Nighttime control was similar in both groups (111 +/- 27 vs. 112 +/- 28 mg/dl).

CONCLUSIONS

Closed-loop glucose control using an external sensor and insulin pump provides a means to achieve near-normal glucose concentrations in youth with type 1 diabetes during the overnight period. The addition of small manual priming bolus doses of insulin, given 15 min before meals, improves postprandial glycemic excursions.

Mixed meal simulation model of glucose-insulin system

A simulation model of the glucose-insulin system in the postprandial state can be useful for studying the pathophysiology of diabetes. Here we present a new simulation model which describes the physiological events which occur after a meal, by employing the quantitative knowledge which has become available in recent years. Model parameters were set to fit data of 204 normal subjects which underwent a triple tracer meal protocol which provided quasi model-independent estimates of major glucose and insulin fluxes. Model results are shown in describing normal daily life (breakfast, lunch, dinner) both in normal and pathophysiological situations. The potential of the model for studying type 1 diabetes is illustrated by simulating both open- and closed-loop insulin infusion strategies.

The next generation of artificial pancreas control algorithms

Creating a wearable artificial pancreas (AP) by closing the loop between a glucose sensor and an insulin infusion pump has the potential to significantly impact the complications associated with and improve the quality of life of diabetic individuals. Despite recent progress on glucose sensor and insulin infusion technologies, control algorithms built on the simple glucose value efferent and insulin dose afferent model are not efficient and reliable. Based on glucose regulatory mechanisms known to date, their impairment in the diabetic state, and fundamental principles of control theory, some corrections to the present course of research are proposed to facilitate the removal of this barrier. A greater emphasis on model predictive controllers or controllers that exploit a mathematical representation, or model, of the patient's own physiology is proposed. Whole-body physiologically based pharmacokinetics-pharmacodynamics-type models hold the best odds for enabling a successful closed-loop AP. However, two major improvements to the diabetes modeling state of the art are required to make them practical for daily care: integrating hypothalamus-pituitary-adrenal axis and gastrointestinal tract submodels. Although there are simple representations of these in current existence, large concerted efforts between experimentalists and modelers will be required to enhance their accuracy. Finally, changes in hardware that complements controller performance are suggested. For instance, the development of dual control inputs of insulin and glucagon could relax tolerances on controller accuracy.

Glucose control in pediatric intensive care unit patients using an insulin-glucose algorithm

BACKGROUND

Control of hyperglycemia in adult medical and surgical intensive care units (ICUs) has been shown to dramatically decrease morbidity and mortality. Algorithms to achieve glycemic control in the ICU setting are evolving. We have evaluated the use of a discrete proportional-integral-derivative (PID) algorithm to control hyperglycemia in pediatric ICU (PICU) patients both with and without diabetes.

METHODS

Six PICU patients [four with diabetic ketoacidosis (DKA) and two with glucocorticoid-induced hyperglycemia] with glucose values >150 mg/dL were enrolled. Their hyperglycemia was managed with a PID algorithm that provided recommendations for both changes in the intravenous insulin infusion rate and the time to obtain the next discrete glucose value. Glucose targets were adjusted based on clinical circumstances.

RESULTS

Patients (mean age 9.2 years; range 1.8-14 years) utilized the algorithm for a total of 454.4 h. Mean time to the initial glucose target was 8.7 h (range 1.3-15.1 h) in five patients. One subject with hyperosmolar DKA did not achieve target before discharge from the PICU, and another was at target when the algorithm was initiated. After the glucose target was achieved, the mean SD was 23.5 mg/dL, and glucose values were >40 mg/dL above target 13% of the time and <40 mg/dL below target 1% of the time. There were no glucose values <55 mg/dL.

CONCLUSION

The PID algorithm safely and effectively controlled hyperglycemia in a PICU, despite multiple changes in intravenous fluids, steroid doses (including high-dose pulses), and hemodialysis.

The artificial pancreas: how sweet engineering will solve bitter problems

An artificial pancreas is a closed-loop system containing only synthetic materials which substitutes for an endocrine pancreas. No artificial pancreas system is currently approved; however, devices that could become components of such a system are now becoming commercially available. An artificial pancreas will consist of functionally integrated components that will continuously sense glucose levels, determine appropriate insulin dosages, and deliver the insulin. Any proposed closed loop system will be closely scrutinized for its safety, efficacy, and economic impact. Closed loop control utilizes models of glucose homeostasis which account for the influences of feeding, stress, insulin, exercise, and other factors on blood glucose levels. Models are necessary for understanding the relationship between blood glucose levels and insulin dosing; developing algorithms to control insulin dosing; and customizing each user's system based on individual responses to factors that influence glycemia. Components of an artificial pancreas are now being developed, including continuous glucose sensors; insulin pumps for parenteral delivery; and control software, all linked through wireless communication systems. Although a closed-loop system providing glucagon has not been reported in 40 years, the use of glucagon to prevent hypoglycemia is physiologically attractive and future devices might utilize this hormone. No demonstration of long-term closed loop control of glucose in a free-living human with diabetes has been reported to date, but many centers around the world are working on closed loop control systems. It is expected that many types of artificial pancreas systems will eventually be available, and they will greatly benefit patients with diabetes.

FDA's proactive role in the development of an artificial pancreas for the treatment of diabetes mellitus

One of the critical path initiatives of the Food and Drug Administration (FDA) is to accelerate the development and availability of a safe and effective artificial pancreas for the treatment of diabetes mellitus. The FDA has established a multidisciplinary group of scientists and clinicians, in partnership with the National Institutes of Health (NIH), to address the clinical, scientific and regulatory challenges related to this unique medical product.:

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

An automated closed-loop insulin delivery system based on subcutaneous glucose sensing and subcutaneous insulin delivery was evaluated in 10 subjects with type 1 diabetes (2 men, 8 women, mean [+/-SD] age 43.4 +/- 11.4 years, duration of diabetes 18.2 +/- 13.5 years). Closed-loop control was assessed over approximately 30 h and compared with open-loop control assessed over 3 days. Closed-loop insulin delivery was calculated using a model of the beta-cell's multiphasic insulin response to glucose. Plasma glucose was 160 +/- 66 mg/dl at the start of closed loop and was thereafter reduced to 71 +/- 19 by 1:00 p.m. (preprandial lunch). Fasting glucose the subsequent morning on closed loop was not different from target (124 +/- 25 vs. 120 mg/dl, respectively; P > 0.05). Mean glucose levels were not different between the open and closed loop (133 +/- 63 vs. 133 +/- 52 mg/dl, respectively; P > 0.65). However, glucose was within the range 70-180 mg/dl 75% of the time under closed loop versus 63% for open loop. Incidence of biochemical hypoglycemia (blood glucose <60 mg/dl) was similar under the two treatments. There were no episodes of severe hypoglycemia. The data provide proof of concept that glycemic control can be achieved by a completely automated external closed-loop insulin delivery system.

Metabolic modelling and the closed-loop insulin delivery problem

The approach used by Medtronic MiniMed to close the insulin delivery loop using the subcutaneous site for both glucose sensing and insulin delivery relies on modeling insulin action and beta-cell insulin secretion. This approach is contrasted with traditional control systems engineering.

Development of a highly responsive needle-type glucose sensor using polyimide for a wearable artificial endocrine pancreas

To produce a long-life, stable, miniature glucose sensor for a wearable artificial endocrine pancreas (WAEP), we developed a novel microneedle-type glucose sensor using polyimide, designated the PI sensor (outer diameter, 0.3 mm; length, 16 mm), and investigated its characteristics in vitro and in vivo. In the in vitro study, we tested the sensor in 0.9% NaCl solution with varying glucose concentrations and observed an excellent linear relationship between the sensor output and glucose concentration (range: 0-500 mg/100 ml). In in vivo experiments, the PI sensor was inserted into the abdominal subcutaneous tissue of beagle dogs (n = 5), and interstitial fluid glucose concentrations were monitored after sensor calibration. Simultaneously, blood glucose concentrations were also monitored continuously with another PI sensor placed intravenously. The correlation and time delay between subcutaneous tissue glucose (Y) and blood glucose concentrations (X: 30-350 mg/100 ml) were Y = 1.03X + 7.98 (r = 0.969) and 6.6 +/- 1.2 min, respectively. We applied the new WAEP system/PI sensor and an intravenous insulin infusion algorithm developed previously for glycemic control in diabetic dogs. The use of the WAEP system resulted in excellent glycemic control after an oral glucose challenge of 1.5 g/kg (post-challenge blood glucose levels: 176 +/- 18 mg/100 ml at 65 min and 93 +/- 23 mg/100 ml at 240 min), without any hypoglycemia. Thus, we confirmed that our new PI sensor has excellent sensor characteristics in vitro and in vivo. The new WAEP using this sensor is potentially suitable for clinical application.

Evaluation of the effect of gain on the meal response of an automated closed-loop insulin delivery system

A continuous closed-loop insulin delivery system using subcutaneous insulin delivery was evaluated in eight diabetic canines. Continuous glucose profiles were obtained by extrapolation of blood glucose measurements. Insulin delivery rate was calculated, using a model of beta-cell insulin secretion, and delivered with a Medtronic MiniMed subcutaneous infusion pump. The model acts like a classic proportional-integral-derivative controller, delivering insulin in proportion to glucose above target, history of past glucose values, and glucose rate of change. For each dog, a proportional gain was set relative to the open-loop total daily dose (TDD) of insulin. Additional gains based on 0.5 x TDD and 1.5 x TDD were also evaluated (gain dose response). Control was initiated 4 h before the meal with a target of 6.7 mmol/l. At the time of the meal, glucose was similar for all three gains (6.0 +/- 0.3, 5.2 +/- 0.3, and 4.9 +/- 0.5 mmol/l for 0.5 x TDD, TDD, and 1.5 x TDD, respectively; P > 0.05) with near-target values restored at the end of experiments (8.2 +/- 0.9, 6.0 +/- 0.6, and 6.0 +/- 0.5, respectively). The peak postprandial glucose level decreased significantly with increasing gain (12.1 +/- 0.6, 9.6 +/- 1.0, and 8.5 +/- 0.6 mmol/l, respectively; P < 0.05). The data demonstrate that closed-loop insulin delivery using the subcutaneous site can provide stable glycemic control within a range of gain.