Artificial pancreas: an emerging approach to treat Type 1 diabetes

Chitosan-based injectable hydrogels with dual glucose sensors for precise control of insulin release and diabetes mellitus therapy

Chitosan-based injectable hydrogels were designed and fabricated through the dynamic crosslinking of dual-reversible covalent bonds (imine and phenylboronate ester) for precise insulin release. The hydrogels contain dual glucose-sensors/responsive elements, featuring high sensitivity and rapid responsiveness to glucose level variation in cumulative and half-hourly pulsed insulin release. The hydrogels demonstrated improved cytocompatibility against HSF cells and histological long-term analysis of tissue after implantation. Evaluation of the glycemic control ability in STZ-induced hyperglycemic mice revealed that the hydrogel system showed excellent glycemic control ability in the glucose tolerance test and maintained blood glucose levels in a normal range for up to 11 days after a single administration. Thus, the hydrogel system showed applicable potential in insulin replacement therapy for diabetes mellitus.

Nonmetallic N/C Nanozyme Performs Continuous Consumption of Glu for Inhibition of Colorectal Cancer Cells

Colorectal cancer (CRC) is the third leading cause of cancer-related mortality. 5-Fluorouracil (5-FU) is the first choice for treatment of CRC, but it cannot avoid the negative effects from local high glucose (Glu) in tumor. Recently, 5-FU therapy has been combined with other treatment modalities for CRC synergistic therapy. Although these combination therapy strategies are more effective in cancer therapy, the toxicity side effects to the liver and cause metabolic acidosis still exist. Herein, we report an emerging amorphous honeycomb-like nitrogen-doped carbon (N/C) nanozyme with nicotinamide adenine dinucleotide (NADH) oxidase and catalase (CAT) activity and cascade it with natural glucose dehydrogenase (GDH) to realize NAD⁺ regeneration and further hyperglycemia management. In this case, by the coupling of N/C nanozyme with natural GDH to form a N/C-GDH system, the electron transfer route can switch from Glu to a common but limited electron receptor, i.e., NAD⁺ to ubiquitous large amounts of oxygen, achieving the purpose of sustainable consumption of Glu under NAD⁺ circulation and regeneration, and importantly escaping the generation of toxic H₂O₂. The combination of the N/C-GDH system and 5-FU on CRC cells was investigated to assess their synergistic bioeffects. Notably, our results showed that the N/C-GDH system and 5-FU in combination significantly suppress the proliferation of human colon cancer cells (HCT-116) by reducing the sugar level and induced apoptosis compared with either material or drug used alone. This work expands the nanozymes in blood Glu management as well as the promising cancer cell inhibition and provides the possibility of nonmetallic nanomaterials in the realization of effective treatment of cancer.

A glucose-sensitive block glycopolymer hydrogel based on dynamic boronic ester bonds for insulin delivery

Hydrogels are good candidates to satisfy many needs for functional and tunable biomaterials. How to precisely control the gel structure and functions is crucial for the construction of sophisticated soft biomaterials comprising the hydrogels, which facilitates the impact of the surrounding environment on a unique biological function occurring. Here, glucose-responsive hydrogels comprised of 3-acrylamidophenyl boronic acid copolymerized with 2-lactobionamidoethyl methacrylate (p(APBA-b-LAMA)) were synthesized, and further evaluated as carriers for insulin delivery. The formation of (p(APBA-b-LAMA)) hydrogel was based on dynamic covalent bond using the association of boronic acid with diols. P(APBA-b-LAMA) hydrogel with the typical porous structure showed a rapid increase in equilibrium of swelling, which was up to 1856% after incubation with aqueous solution. Using insulin as a model protein therapeutic, p(APBA-b-LAMA) hydrogel exhibited high drug loading capability up to 15.6%, and also displayed glucose-dependent insulin release under physiological conditions. Additionally, the viability of NIH3T3 cells was more than 90% after treated with p(APBA-b-LAMA) hydrogel, indicating that the hydrogel had no cytotoxicity. Consequently, the novel p(APBA-b-LAMA) hydrogel has a practical application for diabetes treatment.

Phenylboronic acid-based amphiphilic glycopolymeric nanocarriers for in vivo insulin delivery

Diabetes mellitus, a disorder of glucose regulation, is a global burden affecting millions of people across the world.

Development of nanotoxicology: implications for drug delivery and medical devices

Current nanotoxicology research suffers from suboptimal in vitro models, lack of in vitro–in vivo correlations, variability within in vitro protocols, deficits in both material purity and physicochemical characterization. Reliable nanomaterial toxicity and mechanistic insights are required for health and toxicity risk assessments. Much in vitro toxicological data is inconclusive in designating whether nanomaterials for drug delivery and medical device implants are truly safe. A critique is presented to analyze the interface between toxicology and nanopharmaceuticals. Deficiencies of existing practices in toxicology are reviewed and useful emerging techniques (e.g., lab-on-a-chip, tissue engineering, atomic force microscopy, high-content analysis) are highlighted. Cross-fertilization between disciplines will aid development of biocompatible delivery and implant platforms while improvements are being suggested for better translation of nanotoxicology.

Insulin-loaded hydroxyapatite combined with macrophage activity to deliver insulin for diabetes mellitus

InsHAP is engulfed by macrophages and the lysosome/endosome hybrid is broken down by osmosis, which facilitates delivery of insulin into the bloodstream.

MD-Logic overnight control for 6 weeks of home use in patients with type 1 diabetes: randomized crossover trial

OBJECTIVE

We evaluated the effect of the MD-Logic system on overnight glycemic control at patients' homes.

RESEARCH DESIGN AND METHODS

Twenty-four patients (aged 12-43 years; average A1c 7.5 ± 0.8%, 58.1 ± 8.4 mmol/mol) were randomly assigned to participate in two overnight crossover periods, each including 6 weeks of consecutive nights: one under closed loop and the second under sensor-augmented pump (SAP) therapy at patients' homes in real-life conditions. The primary end point was time spent with sensor glucose levels below 70 mg/dL (3.9 mmol/L) overnight.

RESULTS

Closed-loop nights significantly reduced time spent in hypoglycemia (P = 0.02) and increased the percentage of time spent in the target range of 70-140 mg/dL (P = 0.003) compared with nights when the SAP therapy was used. The time spent in substantial hyperglycemia above 240 mg/dL was reduced by a median of 52.2% (interquartile range [IQR] 4.8, 72.9%; P = 0.001) under closed-loop control compared with SAP therapy. Overnight total insulin doses were lower in the closed-loop nights compared with the SAP nights (P = 0.04). The average daytime glucose levels after closed-loop operation were reduced by a median of 10.0 mg/dL (IQR -2.7, 19.2; P = 0.017) while lower total insulin doses were used (P = 0.038). No severe adverse events occurred during closed-loop control; there was a single event of severe hypoglycemia during a control night.

CONCLUSIONS

The long-term home use of automated overnight insulin delivery by the MD-Logic system was found to be a feasible, safe, and an effective tool to reduce nocturnal hypoglycemia and improve overnight glycemic control in subjects with type 1 diabetes.

Phenylboronate-diol crosslinked glycopolymeric nanocarriers for insulin delivery at physiological pH

Research into polymers with glucose-sensitivity in physiological conditions has expanded recently due to their therapeutic potential in diabetes. Herein, to explore the glucose-responsive properties of a new polymer under physiological conditions, we synthesized an amphiphilic block glycopolymer based on phenylboronic acid and a carbohydrate, which was named poly(d-gluconamidoethyl methacrylate-block-3-acrylamidophenylboronic acid) (p(AAPBA-b-GAMA)). Based on the cross-linking between the diol groups of the carbohydrates and phenylboronic acid, the glycopolymers self-assembled to form nanoparticles (NPs). The glucose-sensitivity was revealed by the swelling behavior of the NPs at different glucose concentrations and was found to be dependent on the glucose level. The morphology of the NPs revealed by transmission electron microscopy showed that the NPs were spherical in shape with good dispersity. The cell viability of the NPs investigated by MTT assay was more than 90%, indicating that the glycopolymers had good cytocompatibility. Insulin could be loaded onto the glycopolymer NPs with high efficiency (up to 10%), and insulin release increased with enhancement of the glucose level in the medium. Such a glucose-responsive glycopolymer is an excellent candidate that holds great potential in the treatment of diabetes.

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

Since the discovery of insulin, great progress has been made to improve the accuracy and safety of automated insulin delivery systems to help patients with type 1 diabetes achieve their treatment goals without causing hypoglycaemia. In recent years, bioengineering technology has greatly advanced diabetes management, with the development of blood glucose meters, continuous glucose monitors, insulin pumps and control systems for automatic delivery of one or more hormones. New insulin analogues have improved subcutaneous absorption characteristics, but do not completely eliminate the risk of hypoglycaemia. Insulin effect is counteracted by glucagon in non-diabetic individuals, while glucagon secretion in those with type 1 diabetes is impaired. The use of glucagon in the artificial pancreas is therefore a logical and feasible option for preventing and treating hypoglycaemia. However, commercially available glucagon is not stable in aqueous solution for long periods, forming potentially cytotoxic fibrils that aggregate quickly. Therefore, a more stable formulation of glucagon is needed for long-term use and storage in a bi-hormonal pump. In addition, a model of glucagon action in type 1 diabetes is lacking, further limiting the inclusion of glucagon into systems employing model-assisted control. As a result, although several investigators have been working to help develop bi-hormonal systems for patients with type 1 diabetes, most continue to utilize single hormone systems employing only insulin. This article seeks to focus on the attributes of glucagon and its use in bi-hormonal systems.

Glucose-responsive microgels integrated with enzyme nanocapsules for closed-loop insulin delivery

A glucose-responsive closed-loop insulin delivery system represents the ideal treatment of type 1 diabetes mellitus. In this study, we develop uniform injectable microgels for controlled glucose-responsive release of insulin. Monodisperse microgels (256 ± 18 μm), consisting of a pH-responsive chitosan matrix, enzyme nanocapsules, and recombinant human insulin, were fabricated through a one-step electrospray procedure. Glucose-specific enzymes were covalently encapsulated into the nanocapsules to improve enzymatic stability by protecting from denaturation and immunogenicity as well as to minimize loss due to diffusion from the matrix. The microgel system swelled when subjected to hyperglycemic conditions, as a result of the enzymatic conversion of glucose into gluconic acid and protonation of the chitosan network. Acting as a self-regulating valve system, microgels were adjusted to release insulin at basal release rates under normoglycemic conditions and at higher rates under hyperglycemic conditions. Finally, we demonstrated that these microgels with enzyme nanocapsules facilitate insulin release and result in a reduction of blood glucose levels in a mouse model of type 1 diabetes.

Injectable nano-network for glucose-mediated insulin delivery

Diabetes mellitus, a disorder of glucose regulation, is a global burden affecting 366 million people across the world. An artificial "closed-loop" system able to mimic pancreas activity and release insulin in response to glucose level changes has the potential to improve patient compliance and health. Herein we develop a glucose-mediated release strategy for the self-regulated delivery of insulin using an injectable and acid-degradable polymeric network. Formed by electrostatic interaction between oppositely charged dextran nanoparticles loaded with insulin and glucose-specific enzymes, the nanocomposite-based porous architecture can be dissociated and subsequently release insulin in a hyperglycemic state through the catalytic conversion of glucose into gluconic acid. In vitro insulin release can be modulated in a pulsatile profile in response to glucose concentrations. In vivo studies validated that these formulations provided improved glucose control in type 1 diabetic mice subcutaneously administered with a degradable nano-network. A single injection of the developed nano-network facilitated stabilization of the blood glucose levels in the normoglycemic state (<200 mg/dL) for up to 10 days.

Challenges and Recent Progress in the Development of a Closed-loop Artificial Pancreas

Pursuit of a closed-loop artificial pancreas that automatically controls the blood glucose of individuals with type 1 diabetes has intensified during the past six years. Here we discuss the recent progress and challenges in the major steps towards a closed-loop system. Continuous insulin infusion pumps have been widely available for over two decades, but "smart pump" technology has made the devices easier to use and more powerful. Continuous glucose monitoring (CGM) technology has improved and the devices are more widely available. A number of approaches are currently under study for fully closed-loop systems; most manipulate only insulin, while others manipulate insulin and glucagon. Algorithms include on-off (for prevention of overnight hypoglycemia), proportional-integral-derivative (PID), model predictive control (MPC) and fuzzy logic based learning control. Meals cause a major "disturbance" to blood glucose, and we discuss techniques that our group has developed to predict when a meal is likely to be consumed and its effect. We further examine both physiology and device-related challenges, including insulin infusion set failure and sensor signal attenuation. Finally, we discuss the next steps required to make a closed-loop artificial pancreas a commercial reality.

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.

Wiener sliding-mode control for artificial pancreas: a new nonlinear approach to glucose regulation

Type 1 diabetic patients need insulin therapy to keep their blood glucose close to normal. In this paper an attempt is made to show how nonlinear control-oriented model may be used to improve the performance of closed-loop control of blood glucose in diabetic patients. The nonlinear Wiener model is used as a novel modeling approach to be applied to the glucose control problem. The identified Wiener model is used in the design of a robust nonlinear sliding mode control strategy. Two configurations of the nonlinear controller are tested and compared to a controller designed with a linear model. The controllers are designed in a Smith predictor structure to reduce the effect of system time delay. To improve the meal compensation features, the controllers are provided with a simple feedforward controller to inject an insulin bolus at meal time. Different simulation scenarios have been used to evaluate the proposed controllers. The obtained results show that the new approach outperforms the linear control scheme, and regulates the glucose level within safe limits in the presence of measurement and modeling errors, meal uncertainty and patient variations.

A new virtual environment for testing and hardware implementation of closed-loop control algorithms in the artificial pancreas

This article presents a new simulation tool for designing and testing blood glucose control algorithms in patients with type 1 diabetes. The control algorithms can be designed and implemented either with textual or graphical programming languages or by importing them from several frameworks. Realistic scenarios and protocols can be customized and built through graphical user interfaces, where several outcomes are available to evaluate control performance. Sophisticated models of the glucose-insulin system, as well as representative models of the instrumentation, have been included. Unlike existing systems, this simulation tool allows integrating the control algorithms into an electronic control unit, thus reusing the entire code in a straightforward way.

Meta-analysis of overnight closed-loop randomized studies in children and adults with type 1 diabetes: the Cambridge cohort

AIM

We reviewed the safety and efficacy of overnight closed-loop insulin delivery compared with conventional continuous subcutaneous insulin infusion (CSII) in two distinct age groups with type 1 diabetes mellitus (T1DM), young people aged 5 to 18 years and adults, combining data of previously published randomized studies.

METHODS

We evaluated four randomized crossover studies in 17 children and adolescents [13.4 ± 3.6 years; mean ± standard deviation (SD)] and 24 adults (37.5 ± 9.1 years) on 45 closed-loop (intervention) and 45 CSII (control) visits. Each subject attended for two overnight study visits, using either closed-loop or conventional pump therapy, in random order. In each age group, studies were designed to mimic realistic likely scenarios. In the children and adolescent studies, closed loop was used following a standard evening meal and following 40 min of moderate-intensity exercise. In the adult studies, closed loop was commenced following a 60 g carbohydrate meal or a 100 g carbohydrate meal accompanied by alcohol. The primary outcome measure was time for which plasma glucose was within target range (3.91-8.0 mmol/liter).

RESULTS

Overnight closed loop increased the time in target plasma glucose in both young (from 40% to 60%, p = .002) and adults (from 50% to 76%, p < .001) compared with conventional CSII. Combined analysis showed an increase from 43% to 71% with closed loop (p < .001). Additionally, closed loop reduced the time spent below 3.91 mmol/liter and above 8.0 mmol/liter, from 4.1% to 2.1% (p = .01) and 33% to 20% (p = .03), respectively. Glycemic variability, as measured by the SD of plasma glucose, was lower during closed loop compared with CSII (1.5 versus 2.1 mmol/liter, p = .007).

CONCLUSIONS

Overnight closed loop may improve glycemic control and reduce nocturnal hypoglycemia in both young people and adults with T1DM.

Evolution of devices in diabetes management

Recent technological advancements in insulin administration and glucose monitoring have allowed patients with diabetes to become increasingly involved in their own care. Devices replacing the traditional vial and syringe, such as insulin pens, are gaining popularity and offer simple and convenient insulin administration. Pen devices are associated with improved dose accuracy, reducing the risk of hypo- or hyperglycemia, and are continually being updated with new safety features in order to optimize their performance. In patients for whom glucose variability remains a problem, continuous subcutaneous insulin infusion via an implanted canula or continuous intraperitoneal insulin infusion via an implanted pump is safe and effective when used correctly, although cost can be a limitation. More accurate retrospective and real-time continuous monitoring devices, which can better detect blood glucose excursions, have become standard components of modern-day diabetes management. The most recent devices have sensor-signaling capabilities with wireless data transmission, leading to reduced time delay and more accurate alerts. Ultimately, though, while self-management remains a critical factor in improving glycemic control at present, human error may undermine even the most accurate treatment interventions. A key long-term goal in diabetes management is, therefore, to develop an automated and accurate closed-loop system for blood glucose monitoring and insulin delivery to better reflect the physiological mechanisms of glucose homeostasis and remove the "human" element. This "artificial pancreas" would offer the most innovative intervention for diabetes management and has the potential to considerably reduce the patient's burden of self-care.

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.

Role of chronic and acute hyperglycemia in the development of diabetes complications

Chronic hyperglycemia, as assessed by hemoglobin A1c (HbA1c) levels, has been associated with the development of microvascular and macrovascular complications of diabetes. Several studies have shown that acute hyperglycemia can add to the effect of chronic hyperglycemia in inducing tissue damage. Acute hyperglycemia can activate the same metabolic and hemodynamic pathways as chronic hyperglycemia. In particular, it is associated with increased mitochondrial production of reactive oxidant species, which have been suggested as the link between hyperglycemia and the activation of downstream pathways, mediating tissue damage. Studies performed in subjects with diabetes have shown that there is a positive association between HbA1c and both fasting and postprandial glucose levels. However, it appears that the contribution of these two parameters to the total HbA1c concentrations varies according to the degree of metabolic control. Postprandial glucose excursions are predominant in patients with a good or mild glycemic control, whereas the contribution of fasting hyperglycemia is stronger as glycemic control worsens. Glucose variability, like the intra-day glucose fluctuations from peaks to nadirs, is another important parameter, which, mainly in subjects with type 2 diabetes, has emerged as an HbA1c-independent risk factor for the development of vascular complications. Based on the current knowledge on the association not only of HbA1c, but also of fasting and postprandial glucose, with diabetes complications, it is paramount that antidiabetes strategies are directed at improving all these components in order to reduce the burden associated with diabetes.

A closed-loop artificial pancreas based on risk management

BACKGROUND

Control algorithms that regulate blood glucose (BG) levels in individuals with type 1 diabetes mellitus face several fundamental challenges. Two of these are the asymmetric risk of clinical complications associated with low and high glucose levels and the irreversibility of insulin action when using only insulin. Both of these nonlinearities force a controller to be more conservative when uncertainties are high. We developed a novel extended model predictive controller (EMPC) that explicitly addresses these two challenges.

METHOD

Our extensions to model predictive control (MPC) operate in three ways. First, they explicitly minimize the combined risk of hypoglycemia and hyperglycemia. Second, they integrate the effect of prediction uncertainties into the risk. Third, they understand that future control actions will vary if measurements fall above or below predictions. Using the University of Virginia/Padova Simulator, we compared our novel controller (EMPC) against optimized versions of a proportional-integral-derivative (PID) controller, a traditional MPC, and a basal/bolus (BB) controller, as well as against published results of an independent MPC (IMPC). The BB controller was optimized retrospectively to serve as a bound on the possible performance.

RESULTS

We tuned each controller, where possible, to minimize a published blood glucose risk index (BGRI). The simulated controllers (PID/MPC/EMPC/BB) provided BGRI values of 2.99/3.05/2.51/1.27 as compared to the published IMPC BGRI value of 4.10. These correspond to 73/79/84/92% of BG values lying in the euglycemic range (70-180 mg/dl), respectively, with mean BG levels of 151/156/147/140 mg/dl.

CONCLUSION

The EMPC strategy extends MPC to explicitly address the issues of asymmetric glycemic risk and irreversible insulin action using estimated prediction uncertainties and an explicit risk function. This controller reduces the avoidable BGRI by 56% (p < .05) relative to a published MPC algorithm studied on a similar population.

Closed-loop insulin delivery: from bench to clinical practice

Automated closed-loop insulin delivery, also referred to as the 'artificial pancreas', has been an important but elusive goal of diabetes treatment for many decades. Research milestones include the conception of continuous glucose monitoring in the early 1960s, followed by the production of the first commercial hospital-based artificial pancreas in the late 1970s that combined intravenous glucose sensing and insulin delivery. In the past 10 years, research into the artificial pancreas has gained substantial momentum and focused on the subcutaneous route for glucose measurement and insulin delivery, which reflects technological advances in interstitial glucose monitoring and the increasing use of the continuous subcutaneous insulin infusion. This Review discusses the design of an artificial pancreas, its components and clinical results, as well as the advantages and disadvantages of different types of automated closed-loop systems and potential future advances. The introduction of the artificial pancreas into clinical practice will probably occur gradually, starting with simpler approaches, such as overnight control of blood glucose concentration and temporary pump shut-off, that are adapted to more complex situations, such as glycemic control during meals and exercise.

Use of sensors in the treatment and follow-up of patients with diabetes mellitus

Glucose control is the cornerstone of Diabetes Mellitus (DM) treatment. Although self-regulation using capillary glycemia (SRCG) still remains the best procedure in clinical practice, continuous glucose monitoring systems (CGM) offer the possibility of continuous and dynamic assessment of interstitial glucose concentration. CGM systems have the potential to improve glycemic control while decreasing the incidence of hypoglycemia but the efficiency, compared with SRCG, is still debated. CGM systems have the greatest potential value in patients with hypoglycemic unawareness and in controlling daily fluctuations in blood glucose. The implementation of continuous monitoring in the standard clinical setting has not yet been established but a new generation of open and close loop subcutaneous insulin infusion devices are emerging making insulin treatment and glycemic control more reliable.

Systems engineering medicine: engineering the inflammation response to infectious and traumatic challenges

The complexity of the systemic inflammatory response and the lack of a treatment breakthrough in the treatment of pathogenic infection demand that advanced tools be brought to bear in the treatment of severe sepsis and trauma. Systems medicine, the translational science counterpart to basic science's systems biology, is the interface at which these tools may be constructed. Rapid initial strides in improving sepsis treatment are possible through the use of phenomenological modelling and optimization tools for process understanding and device design. Higher impact, and more generalizable, treatment designs are based on mechanistic understanding developed through the use of physiologically based models, characterization of population variability, and the use of control-theoretic systems engineering concepts. In this review we introduce acute inflammation and sepsis as an example of just one area that is currently underserved by the systems medicine community, and, therefore, an area in which contributions of all types can be made.

Insulin patch pumps: their development and future in closed-loop systems

Steady progress is being made toward the development of a so-called "artificial pancreas," which may ultimately be a fully automated, closed-loop, glucose control system comprising a continuous glucose monitor, an insulin pump, and a controller. The controller will use individualized algorithms to direct delivery of insulin without user input. A major factor propelling artificial pancreas development is the substantial incidence of-and attendant patient, parental, and physician concerns about-hypoglycemia and extreme hyperglycemia associated with current means of insulin delivery for type 1 diabetes mellitus (T1DM). A successful fully automated artificial pancreas would likely reduce the frequency of and anxiety about hypoglycemia and marked hyperglycemia. Patch-pump systems ("patch pumps") are likely to be used increasingly in the control of T1DM and may be incorporated into the artificial pancreas systems of tomorrow. Patch pumps are free of tubing, small, lightweight, and unobtrusive. This article describes features of patch pumps that have been approved for U.S. marketing or are under development. Included in the review is an introduction to control algorithms driving insulin delivery, particularly the two major types: proportional integrative derivative and model predictive control. The use of advanced algorithms in the clinical development of closed-loop systems is reviewed along with projected next steps in artificial pancreas development.

Continuous glucose monitoring: real-time algorithms for calibration, filtering, and alarms

Algorithms for real-time use in continuous glucose monitors are reviewed, including calibration, filtering of noisy signals, glucose predictions for hypoglycemic and hyperglycemic alarms, compensation for capillary blood glucose to sensor time lags, and fault detection for sensor degradation and dropouts. A tutorial on Kalman filtering for real-time estimation, prediction, and lag compensation is presented and demonstrated via simulation examples. A limited number of fault detection methods for signal degradation and dropout have been published, making that an important area for future work.