Outpatient glycemic control with a bionic pancreas in type 1 diabetes

Improving Diabetes Care with Technology and Information Management

Patients and physicians in the 21^st century require new tools to manage the growing burden of chronic illness. For providers responsible for the care of diabetic patients, developments in information management, real-time health education and feedback, and new approaches to self-monitoring and insulin delivery hold great promise to improve the quality and safety of diabetes care. This article will briefly highlight some of the major developments in the field, and the ways these technologies can be integrated into a typical practice.

Stimuli-Responsive Delivery of Therapeutics for Diabetes Treatment

Diabetic therapeutics, including insulin and glucagon-like peptide 1 (GLP-1), are essential for diabetic patients to regulate blood glucose levels. However, conventional treatments that are based on subcutaneous injections are often associated with poor glucose control and a lack of patient compliance. In this review, we focus on the different stimuli-responsive systems to deliver therapeutics for diabetes treatment to improve patient comfort and prevent complications. Specifically, the pH-responsive systems for oral drug delivery are introduced first. Then, the closed-loop glucose-responsive systems are summarized based on different glucose-responsive moieties, including glucose oxidase (GOx), glucose binding protein (GBP), and phenylboronic acid (PBA). Finally, the on-demand delivery systems activated by external remote triggers are also discussed. We conclude by discussing advantages and limitations of current strategies, as well as future opportunities and challenges in this area.

Periodic zone-MPC with asymmetric costs for outpatient-ready safety of an artificial pancreas to treat type 1 diabetes. AUTOMATICA : THE JOURNAL OF IFAC, THE INTERNATIONAL FEDERATION OF AUTOMATIC CONTROL 2016;71:237-246. [PMID: 27695131 PMCID: PMC5040369 DOI: 10.1016/j.automatica.2016.04.015]

A novel Model Predictive Control (MPC) law for an Artificial Pancreas (AP) to automatically deliver insulin to people with type 1 diabetes is proposed. The MPC law is an enhancement of the authors' zone-MPC approach that has successfully been trialled in-clinic, and targets the safe outpatient deployment of an AP. The MPC law controls blood-glucose levels to a diurnally time-dependent zone, and enforces diurnal, hard input constraints. The main algorithmic novelty is the use of asymmetric input costs in the MPC problem's objective function. This improves safety by facilitating the independent design of the controller's responses to hyperglycemia and hypoglycemia. The proposed controller performs predictive pump-suspension in the face of impending hypoglycemia, and subsequent predictive pump-resumption, based only on clinical needs and feedback. The proposed MPC strategy's benefits are demonstrated by in-silico studies as well as highlights from a US Food and Drug Administration approved clinical trial in which 32 subjects each completed two 25 hour closed-loop sessions employing the proposed MPC law.

Coming of age: the artificial pancreas for type 1 diabetes

The artificial pancreas (closed-loop system) addresses the unmet clinical need for improved glucose control whilst reducing the burden of diabetes self-care in type 1 diabetes. Glucose-responsive insulin delivery above and below a preset insulin amount informed by sensor glucose readings differentiates closed-loop systems from conventional, threshold-suspend and predictive-suspend insulin pump therapy. Insulin requirements in type 1 diabetes can vary between one-third-threefold on a daily basis. Closed-loop systems accommodate these variations and mitigate the risk of hypoglycaemia associated with tight glucose control. In this review we focus on the progress being made in the development and evaluation of closed-loop systems in outpatient settings. Randomised transitional studies have shown feasibility and efficacy of closed-loop systems under supervision or remote monitoring. Closed-loop application during free-living, unsupervised conditions by children, adolescents and adults compared with sensor-augmented pumps have shown improved glucose outcomes, reduced hypoglycaemia and positive user acceptance. Innovative approaches to enhance closed-loop performance are discussed and we also present the outlook and strategies used to ease clinical adoption of closed-loop systems.

Nonadjunctive Use of Continuous Glucose Monitoring for Diabetes Treatment Decisions

While self-monitoring of blood glucose (SMBG) is the current standard used by people with diabetes to manage glucose levels, recent improvements in accuracy of continuous glucose monitoring (CGM) technology are making it very likely that diabetes-related treatment decisions will soon be made based on CGM values alone. Nonadjunctive use of CGM will lead to a paradigm shift in how patients manage their glucose levels and will require substantial changes in how care providers educate their patients, monitor their progress, and provide feedback to help them manage their diabetes. The approval to use CGM nonadjunctively is also a critical step in the pathway toward FDA approval of an artificial pancreas system, which is further expected to transform diabetes care for people with type 1 diabetes. In this article, we discuss how nonadjunctive CGM is expected to soon replace routine SMBG and how this new usage scenario is expected to transform health outcomes and patient care.

Non-insulin drugs to treat hyperglycaemia in type 1 diabetes mellitus

Insulin treatment of individuals with type 1 diabetes has shortcomings and many patients do not achieve glycaemic and metabolic targets. Consequently, the focus is on novel non-insulin therapeutic approaches that reduce hyperglycaemia and improve metabolic variables without increasing the risk of hypoglycaemia or other adverse events. Several therapies given in conjunction with insulin have been investigated in clinical trials, including pramlintide, glucagon-like peptide-1 receptor agonists, dipeptidyl peptidase-4 inhibitors, sodium-glucose co-transporter inhibitors, metformin, sulfonylureas, and thiazolidinediones. These drugs have pleiotropic effects on glucose metabolism and different actions complementary to those of insulin-this Review reports the effects of these drugs on glycaemic control, glucose variability, hypoglycaemia, insulin requirements, and bodyweight. Existing studies are of short duration with few participants; evidence for the efficacy of concomitant treatments is scarce and largely clinically insignificant. A subgroup of patients with type 1 diabetes for whom non-insulin antidiabetic drugs could significantly benefit glycaemic control cannot yet be defined, but we suggest that obese patients prone to hypoglycaemia and patients with residual β-cell function are populations of interest for future trials.

Closed-Loop Insulin Delivery during Pregnancy in Women with Type 1 Diabetes

BACKGROUND

In patients with type 1 diabetes who are not pregnant, closed-loop (automated) insulin delivery can provide better glycemic control than sensor-augmented pump therapy, but data are lacking on the efficacy, safety, and feasibility of closed-loop therapy during pregnancy.

METHODS

We performed an open-label, randomized, crossover study comparing overnight closed-loop therapy with sensor-augmented pump therapy, followed by a continuation phase in which the closed-loop system was used day and night. Sixteen pregnant women with type 1 diabetes completed 4 weeks of closed-loop pump therapy (intervention) and sensor-augmented pump therapy (control) in random order. During the continuation phase, 14 of the participants used the closed-loop system day and night until delivery. The primary outcome was the percentage of time that overnight glucose levels were within the target range (63 to 140 mg per deciliter [3.5 to 7.8 mmol per liter]).

RESULTS

The percentage of time that overnight glucose levels were in the target range was higher during closed-loop therapy than during control therapy (74.7% vs. 59.5%; absolute difference, 15.2 percentage points; 95% confidence interval, 6.1 to 24.2; P=0.002). The overnight mean glucose level was lower during closed-loop therapy than during control therapy (119 vs. 133 mg per deciliter [6.6 vs. 7.4 mmol per liter], P=0.009). There were no significant differences between closed-loop and control therapy in the percentage of time in which glucose levels were below the target range (1.3% and 1.9%, respectively; P=0.28), in insulin doses, or in adverse-event rates. During the continuation phase (up to 14.6 additional weeks, including antenatal hospitalizations, labor, and delivery), glucose levels were in the target range 68.7% of the time; the mean glucose level was 126 mg per deciliter (7.0 mmol per liter). No episodes of severe hypoglycemia requiring third-party assistance occurred during either phase.

CONCLUSIONS

Overnight closed-loop therapy resulted in better glucose control than sensor-augmented pump therapy in pregnant women with type 1 diabetes. Women receiving day-and-night closed-loop therapy maintained glycemic control during a high proportion of the time in a period that encompassed antenatal hospital admission, labor, and delivery. (Funded by the National Institute for Health Research and others; Current Controlled Trials number, ISRCTN71510001.).

A Simplified Semiquantitative Meal Bolus Strategy Combined with Single- and Dual-Hormone Closed-Loop Delivery in Patients with Type 1 Diabetes: A Pilot Study

BACKGROUND

Single- and dual-hormone closed-loop systems can improve glycemic control and have the potential to reduce carbohydrate-counting burden for patients with type 1 diabetes; however, simplification of meal insulin calculation should not compromise glycemic control.

METHODS

We compared in a randomized outpatient pilot trial: (1) a single-hormone closed-loop system accompanied with carbohydrate-content matched boluses versus accompanied with a simplified meal bolus strategy, and (2) a dual-hormone closed-loop system accompanied with carbohydrate-content matched boluses versus accompanied with a simplified meal bolus strategy. Carbohydrate-matched boluses were based on the participant's carbohydrate meal content estimation whereas the simplified strategy involved the selection, by participants, of a semi-quantitative meal carbohydrate-content size: snack, regular, large, or very large meal. Each participant also underwent sensor-augmented pump therapy. Basal insulin delivery was more aggressive with the simplified bolus. The primary outcome was mean sensor glucose level over a 15-h daytime period.

RESULTS

Twelve participants were recruited (48.2 ± 16.0 years old; HbA1c 7.4% ± 0.9%) to compare the two bolus strategies during single- and dual-hormone closed-loop delivery. A similar mean sensor glucose level (15 h) was achieved with the carbohydrate-matched boluses and simplified strategy using single-hormone (median [interquartile]: 7.6 [7.2-8.1] vs. 8.0 [7.0-8.6] mmol/L; P = 0.90) and dual-hormone closed-loop systems (7.6 [6.7-9.1] vs. 7.0 [6.4-8.2] mmol/L; P = 0.08). Exploratory analyses showed that, as compared with sensor-augmented pump therapy, there was an increased time spent in hypoglycemia with the simplified strategy but not with the carbohydrate-matched boluses.

CONCLUSIONS

Though the algorithm employed in this pilot study may lead to an increased risk for hypoglycemia, this strategy has the potential to reduce the carbohydrate-counting burden in patients with type 1 diabetes while generally maintaining adequate glucose control. Longer outpatient studies with an improved algorithm are needed.

Camp for Youth With Type 1 Diabetes

Camps for youth with type 1 diabetes (T1D) have grown in size and scope since they first emerged in the 1920s. Anecdotal evidence suggests that attending camp with other youth with T1D is beneficial, largely attributed to sharing fun, active experiences and removing the isolation of living with diabetes. However, few studies have evaluated the psychosocial and medical impacts of T1D camp attendance during and after camp sessions. In addition, T1D camps have been a setting for numerous studies on a variety of T1D-related research questions not related to camp itself, such as testing novel diabetes management technologies in an active, non-laboratory setting. This paper reviews the evidence of psychosocial and medical outcomes associated with T1D camp attendance across the globe, provides an overview of other research conducted at camp, and offers recommendations for future research conducted at T1D camp.

Smart approaches to glucose-responsive drug delivery

A grand challenge in the field of "smart" drug delivery has been the quest to create formulations that can sense glucose and respond by delivering an appropriate dose of insulin. This approach, referred to as the "fully synthetic pancreas", envisions closed-loop insulin therapy. The strategies for incorporating glucose sensing into formulations can be broadly categorized into three subsets: enzymatic sensing, natural glucose-binding proteins and synthetic molecular recognition. Here, we highlight some examples of each of these approaches. The challenges remaining en route to the realization of closed-loop insulin therapy are substantial, and include improved response time, more authentic fidelity in glycemic control, improved biocompatibility for delivery materials and assurance of both safety and efficacy. The ubiquitous existence of glucose, combined with the unstable and toxic properties of insulin, further compound efforts towards the generation of a fully synthetic pancreas. However, given the growing incidence of both type-1 and type-2 diabetes, there is significant potential impact from the realization of such an approach on improving therapeutic management of the disease.

Therapeutic potential of human embryonic stem cells in type 2 diabetes mellitus

AIM: To evaluate the safety and efficacy of human embryonic stem cells (hESCs) for the management of type 2 diabetes mellitus (T2DM).

METHODS: Patients with a previous history of diabetes and its associated complications were enrolled and injected with hESC lines as per the defined protocol. The patients were assessed using Nutech functional score (NFS), a numeric scoring scale to evaluate the patients for 11 diagnostic parameters. Patients were evaluated at baseline and at the end of treatment period 1 (T1). All the parameters were graded on the NFS scale from 1 to 5. Highest possible grade (HPG) of 5 was considered as the grade of best improvement.

RESULTS: Overall, 94.8% of the patients showed improvement by at least one grade of NFS at the end of T1. For all the 11 parameters evaluated, 54% of patients achieved HPG after treatment. The four essential parameters (improvement in glycated hemoglobin (HbA1c) and insulin level, and fall in number of other oral hypoglycemic drugs with and without insulin) are presented in detail. For HbA1c, 72.6% of patients at the end of T1 met the World Health Organization cut off value, i.e., 6.5% of HbA1c. For insulin level, 65.9% of patients at the end of T1 were able to achieve HPG. After treatment, the improvement was seen in 16.3% of patients who required no more than two medications along with insulin. Similarly, 21.5% of patients were improved as their dosage regimen for using oral drugs was reduced to 1-2 from 5.

CONCLUSION: hESC therapy is beneficial in patients with diabetes and helps in reducing their dependence on insulin and other medicines.

Model-Free Machine Learning in Biomedicine: Feasibility Study in Type 1 Diabetes

Although reinforcement learning (RL) is suitable for highly uncertain systems, the applicability of this class of algorithms to medical treatment may be limited by the patient variability which dictates individualised tuning for their usually multiple algorithmic parameters. This study explores the feasibility of RL in the framework of artificial pancreas development for type 1 diabetes (T1D). In this approach, an Actor-Critic (AC) learning algorithm is designed and developed for the optimisation of insulin infusion for personalised glucose regulation. AC optimises the daily basal insulin rate and insulin:carbohydrate ratio for each patient, on the basis of his/her measured glucose profile. Automatic, personalised tuning of AC is based on the estimation of information transfer (IT) from insulin to glucose signals. Insulin-to-glucose IT is linked to patient-specific characteristics related to total daily insulin needs and insulin sensitivity (SI). The AC algorithm is evaluated using an FDA-accepted T1D simulator on a large patient database under a complex meal protocol, meal uncertainty and diurnal SI variation. The results showed that 95.66% of time was spent in normoglycaemia in the presence of meal uncertainty and 93.02% when meal uncertainty and SI variation were simultaneously considered. The time spent in hypoglycaemia was 0.27% in both cases. The novel tuning method reduced the risk of severe hypoglycaemia, especially in patients with low SI.

Day-and-Night Closed-Loop Glucose Control in Patients With Type 1 Diabetes Under Free-Living Conditions: Results of a Single-Arm 1-Month Experience Compared With a Previously Reported Feasibility Study of Evening and Night at Home

OBJECTIVE

After testing of a wearable artificial pancreas (AP) during evening and night (E/N-AP) under free-living conditions in patients with type 1 diabetes (T1D), we investigated AP during day and night (D/N-AP) for 1 month.

RESEARCH DESIGN AND METHODS

Twenty adult patients with T1D who completed a previous randomized crossover study comparing 2-month E/N-AP versus 2-month sensor augmented pump (SAP) volunteered for 1-month D/N-AP nonrandomized extension. AP was executed by a model predictive control algorithm run by a modified smartphone wirelessly connected to a continuous glucose monitor (CGM) and insulin pump. CGM data were analyzed by intention-to-treat with percentage time-in-target (3.9-10 mmol/L) over 24 h as the primary end point.

RESULTS

Time-in-target (mean ± SD, %) was similar over 24 h with D/N-AP versus E/N-AP: 64.7 ± 7.6 vs. 63.6 ± 9.9 (P = 0.79), and both were higher than with SAP: 59.7 ± 9.6 (P = 0.01 and P = 0.06, respectively). Time below 3.9 mmol/L was similarly and significantly reduced by D/N-AP and E/N-AP versus SAP (both P < 0.001). SD of blood glucose concentration (mmol/L) was lower with D/N-AP versus E/N-AP during whole daytime: 3.2 ± 0.6 vs. 3.4 ± 0.7 (P = 0.003), morning: 2.7 ± 0.5 vs. 3.1 ± 0.5 (P = 0.02), and afternoon: 3.3 ± 0.6 vs. 3.5 ± 0.8 (P = 0.07), and was lower with D/N-AP versus SAP over 24 h: 3.1 ± 0.5 vs. 3.3 ± 0.6 (P = 0.049). Insulin delivery (IU) over 24 h was higher with D/N-AP and SAP than with E/N-AP: 40.6 ± 15.5 and 42.3 ± 15.5 vs. 36.6 ± 11.6 (P = 0.03 and P = 0.0004, respectively).

CONCLUSIONS

D/N-AP and E/N-AP both achieved better glucose control than SAP under free-living conditions. Although time in the different glycemic ranges was similar between D/N-AP and E/N-AP, D/N-AP further reduces glucose variability.

Day-and-Night Hybrid Closed-Loop Insulin Delivery in Adolescents With Type 1 Diabetes: A Free-Living, Randomized Clinical Trial

OBJECTIVE

To evaluate feasibility, safety, and efficacy of day-and-night hybrid closed-loop insulin delivery in adolescents with type 1 diabetes under free-living conditions without remote monitoring or supervision.

RESEARCH DESIGN AND METHODS

In an open-label, randomized, free-living, crossover study design, 12 adolescents receiving insulin pump therapy (mean [±SD] age 15.4 ± 2.6 years; HbA1c 8.3 ± 0.9%; duration of diabetes 8.2 ± 3.4 years) underwent two 7-day periods of sensor-augmented insulin pump therapy or hybrid closed-loop insulin delivery without supervision or remote monitoring. During the closed-loop insulin delivery, a model predictive algorithm automatically directed insulin delivery between meals and overnight; prandial boluses were administered by participants using a bolus calculator.

RESULTS

The proportion of time when the sensor glucose level was in the target range (3.9-10 mmol/L) was increased during closed-loop insulin delivery compared with sensor-augmented pump therapy (72 vs. 53%, P < 0.001; primary end point), the mean glucose concentration was lowered (8.7 vs. 10.1 mmol/L, P = 0.028), and the time spent above the target level was reduced (P = 0.005) without changing the total daily insulin amount (P = 0.55). The time spent in the hypoglycemic range was low and comparable between interventions.

CONCLUSIONS

Unsupervised day-and-night hybrid closed-loop insulin delivery at home is feasible and safe in young people with type 1 diabetes. Compared with sensor-augmented insulin pump therapy, closed-loop insulin delivery may improve glucose control without increasing the risk of hypoglycemia in adolescents with suboptimally controlled type 1 diabetes.

Performance and safety of an integrated bihormonal artificial pancreas for fully automated glucose control at home

AIMS

To assess the performance and safety of an integrated bihormonal artificial pancreas system consisting of one wearable device and two wireless glucose sensor transmitters during short-term daily use at home.

METHODS

Adult patients with type 1 diabetes using an insulin pump were invited to enrol in this randomized crossover study. Treatment with the artificial pancreas started with a day and night in the clinical research centre, followed by 3 days at home. The control period consisted of 4 days of insulin pump therapy at home with blinded continuous glucose monitoring for data collection. Days 2-4 were predefined as the analysis period, with median glucose as the primary outcome.

RESULTS

A total of 10 patients completed the study. The median [interquartile range (IQR)] glucose level was similar for the two treatments [7.3 (7.0-7.6) mmol/l for the artificial pancreas vs. 7.7 (7.0-9.0) mmol/l for the control; p = 0.123]. The median (IQR) percentage of time spent in euglycaemia (3.9-10 mmol/l) was longer during use of the artificial pancreas [84.7 (82.2-87.8)% for the artificial pancreas vs. 68.5 (57.9-83.6)% for the control; p = 0.007]. Time in hypoglycaemia was 1.3 (0.2-3.2)% for the artificial pancreas and 2.4 (0.4-10.3)% for the control treatment (p = 0.139). Separate analysis of daytime and night-time showed that the improvements were mainly achieved during the night.

CONCLUSIONS

The results of this pilot study suggest that our integrated artificial pancreas provides better glucose control than insulin pump therapy in patients with type 1 diabetes at home and that the treatment is safe.

Progress and challenges for treating Type 1 diabetes

It has been more than 30 years since the initial trials of Cyclosporin A to treat patients with new onset Type 1 diabetes (T1D). Since that time, there have been insights into genetic predisposition to the disease, the failures of immune tolerance, and mechanisms that cause the immune mediated β cell destruction. The genetic loci associated affect lymphocyte development and tolerance mechanisms. Discoveries related to the roles of specific immune responses gene such as the major histocompatibility complex, PTPN22, CTLA-4, IL-2RA, as well as the mechanisms of antigen presentation in the thymus have suggested ways in which autoreactivity may follow changes in the functions of these genes that are associated with risk. Antigens that are recognized by the immune system in patients with T1D have been identified. With this information, insights into the novel cellular mechanisms leading to the initiation and orchestration of β cell killing have been developed such as the presentation of unique antigens within the islets. Clinical trials have been performed, some of which have shown efficacy in improving β cell function but none have been able to permanently prevent loss of insulin secretion. The reasons for the lack of long term success are not clear but may include the heterogeneity of the immune response and in individual responses to immune therapies, recurrence of autoimmunity after the initial effects of the therapies, or even intrinsic mechanisms of β cell death that proceeds independently of immune attack after initiation of the disease. In this review, we cover developments that have led to new therapeutics and characteristics of patients who may show the most benefits from therapies. We also identify areas of incomplete understanding that might be addressed to develop more effective therapeutic strategies.

Randomized Crossover Comparison of Personalized MPC and PID Control Algorithms for the Artificial Pancreas

OBJECTIVE

To evaluate two widely used control algorithms for an artificial pancreas (AP) under nonideal but comparable clinical conditions.

RESEARCH DESIGN AND METHODS

After a pilot safety and feasibility study (n = 10), closed-loop control (CLC) was evaluated in a randomized, crossover trial of 20 additional adults with type 1 diabetes. Personalized model predictive control (MPC) and proportional integral derivative (PID) algorithms were compared in supervised 27.5-h CLC sessions. Challenges included overnight control after a 65-g dinner, response to a 50-g breakfast, and response to an unannounced 65-g lunch. Boluses of announced dinner and breakfast meals were given at mealtime. The primary outcome was time in glucose range 70-180 mg/dL.

RESULTS

Mean time in range 70-180 mg/dL was greater for MPC than for PID (74.4 vs. 63.7%, P = 0.020). Mean glucose was also lower for MPC than PID during the entire trial duration (138 vs. 160 mg/dL, P = 0.012) and 5 h after the unannounced 65-g meal (181 vs. 220 mg/dL, P = 0.019). There was no significant difference in time with glucose <70 mg/dL throughout the trial period.

CONCLUSIONS

This first comprehensive study to compare MPC and PID control for the AP indicates that MPC performed particularly well, achieving nearly 75% time in the target range, including the unannounced meal. Although both forms of CLC provided safe and effective glucose management, MPC performed as well or better than PID in all metrics.

Psychosocial Impact of the Bionic Pancreas During Summer Camp

BACKGROUND

The psychosocial impact of the bionic pancreas (BP) was assessed among children attending diabetes camp.

METHODS

Nineteen children were randomly assigned for 5 days to the BP condition and 5 days to the control condition in a crossover design.

RESULTS

Significant reductions in hypoglycemic fear and regimen burden were found. Children felt less burdened or worried about diabetes and felt freer to do things they enjoyed while using the BP. Children wished the BP responded to out of range numbers faster and expressed annoyance about carrying around the necessary equipment.

CONCLUSIONS

Children may experience improved psychosocial outcomes following use of BP while expressing key areas of user concern. Future studies in less controlled environments with larger sample sizes can determine if these findings are generalizable to other groups.

A Review of Safety and Design Requirements of the Artificial Pancreas

As clinical studies with artificial pancreas systems for automated blood glucose control in patients with type 1 diabetes move to unsupervised real-life settings, product development will be a focus of companies over the coming years. Directions or requirements regarding safety in the design of an artificial pancreas are, however, lacking. This review aims to provide an overview and discussion of safety and design requirements of the artificial pancreas. We performed a structured literature search based on three search components—type 1 diabetes, artificial pancreas, and safety or design—and extended the discussion with our own experiences in developing artificial pancreas systems. The main hazards of the artificial pancreas are over- and under-dosing of insulin and, in case of a bi-hormonal system, of glucagon or other hormones. For each component of an artificial pancreas and for the complete system we identified safety issues related to these hazards and proposed control measures. Prerequisites that enable the control algorithms to provide safe closed-loop control are accurate and reliable input of glucose values, assured hormone delivery and an efficient user interface. In addition, the system configuration has important implications for safety, as close cooperation and data exchange between the different components is essential.

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.

Psychological Reactions Associated With Continuous Glucose Monitoring in Youth

Glucose monitoring is prerequisite to all other diabetes self-care behaviors and helps patients to reduce their risk for diabetes-related complications due to elevated glycemia. Because of the amount of information available and the ability to deliver glucose results in real-time, continuous glucose monitoring (CGM) has the ability to improve on self-monitoring blood glucose. However, epidemiologic data demonstrate slow uptake of CGM by patients, especially among youth. Several new diabetes therapies rely on CGM for feedback on patients' glucose levels to optimize treatment (eg, the low-glucose suspend insulin pump) and there are new technologies currently in development that will also need this information to work (eg, the artificial pancreas). To help patients to realize the potential benefits of these new treatments, it is essential to explore patients' psychological and behavioral reactions to CGM and then target device enhancements and/or the development of behavioral therapies to minimize negative reactions and to improve patients' CGM adoption rates. Limited research is available examining the psychological and behavioral reactions of CGM use in youth exclusively, but there are more studies examining these reactions in mixed samples of youth, parents, and adults. The purpose of this review is to summarize the available literature examining psychological and behavioral reactions to CGM use in young people with diabetes and to highlight how the results of past and future studies can inform device updates and/or behavioral intervention development to minimize barriers.

Reducing Glucose Variability Due to Meals and Postprandial Exercise in T1DM Using Switched LPV Control: In Silico Studies

BACKGROUND

Time-varying dynamics is one of the main issues for achieving safe blood glucose control in type 1 diabetes mellitus (T1DM) patients. In addition, the typical disturbances considered for controller design are meals, which increase the glucose level, and physical activity (PA), which increases the subject's sensitivity to insulin. In previous works the authors have applied a linear parameter-varying (LPV) control technique to manage unannounced meals.

METHODS

A switched LPV controller that switches between 3 LPV controllers, each with a different level of aggressiveness, is designed to further cope with both unannounced meals and postprandial PA. Thus, the proposed control strategy has a "standard" mode, an "aggressive" mode, and a "conservative" mode. The "standard" mode is designed to be applied most of the time, while the "aggressive" mode is designed to deal only with hyperglycemia situations. On the other hand, the "conservative" mode is focused on postprandial PA control.

RESULTS

An ad hoc simulator has been developed to test the proposed controller. This simulator is based on the distribution version of the UVA/Padova model and includes the effect of PA based on Schiavon.(1) The test results obtained when using this simulator indicate that the proposed control law substantially reduces the risk of hypoglycemia with the conservative strategy, while the risk of hyperglycemia is scarcely affected.

CONCLUSIONS

It is demonstrated that the announcement, or anticipation, of exercise is indispensable for letting a mono-hormonal artificial pancreas deal with the consequences of postprandial PA. In view of this the proposed controller allows switching into a conservative mode when notified of PA by the user.

Artificial Pancreas Device Systems for the Closed-Loop Control of Type 1 Diabetes: What Systems Are in Development?

BACKGROUND

Closed-loop artificial pancreas device (APD) systems are externally worn medical devices that are being developed to enable people with type 1 diabetes to regulate their blood glucose levels in a more automated way. The innovative concept of this emerging technology is that hands-free, continuous, glycemic control can be achieved by using digital communication technology and advanced computer algorithms.

METHODS

A horizon scanning review of this field was conducted using online sources of intelligence to identify systems in development. The systems were classified into subtypes according to their level of automation, the hormonal and glycemic control approaches used, and their research setting.

RESULTS

Eighteen closed-loop APD systems were identified. All were being tested in clinical trials prior to potential commercialization. Six were being studied in the home setting, 5 in outpatient settings, and 7 in inpatient settings. It is estimated that 2 systems may become commercially available in the EU by the end of 2016, 1 during 2017, and 2 more in 2018.

CONCLUSIONS

There are around 18 closed-loop APD systems progressing through early stages of clinical development. Only a few of these are currently in phase 3 trials and in settings that replicate real life.

Development of a Microsphere-Based System to Facilitate Real-Time Insulin Monitoring

BACKGROUND

The speed of insulin absorption after subcutaneous delivery is highly variable. Incorrect assumptions about insulin pharmacokinetics compromise effective glycemic regulation. Our ultimate goal is to develop a system to monitor insulin levels in vivo continuously, allowing pharmacokinetic parameters to be calculated in real time. We hypothesize that a bead-based detection system can be run on a flow-through microfluidic platform to measure insulin in subcutaneous fluid sampled via microdialysis. As a first step in development, we focused on microsphere-based measurement of insulin.

METHODS

Polystyrene microspheres coated with an anti-insulin monoclonal antibody were exposed to insulin-containing solutions, and after addition of a fluorescently labeled anti-insulin monoclonal antibody with a distinct epitope, bead-associated fluorescence was detected by fluorescence microscopy in 96-well plates or in a flow-through, microfluidic platform.

RESULTS

The bead detection system in plates had a linear range in buffer for regular human insulin (RHI), insulin lispro, and insulin aspart of 15-1115 µIU/ml, 14-976 µIU/ml, and 25-836 µIU/ml, respectively. Measurement on plasma samples demonstrated proportionality between basal and peak insulin levels similar to the laboratory reference method. Preliminary results in a polydimethylsiloxane-based, flow-through, microfluidic platform showed a strong signal at peak insulin levels.

CONCLUSIONS

We have developed a microsphere-based system to rapidly measure levels of insulin and insulin analogs. We have further demonstrated proof of concept that this bead detection system can be implemented in a lab-on-a-chip format, which will be further developed and combined with microdialysis for real-time monitoring of insulin in vivo.

Hybrid Closed-Loop Insulin Delivery in Type 1 Diabetes During Supervised Outpatient Conditions

BACKGROUND

Efficacy and safety of the Medtronic Hybrid Closed-Loop (HCL) system were tested in subjects with type 1 diabetes in a supervised outpatient setting.

METHODS

The HCL system is a prototype research platform that includes a sensor-augmented insulin pump in communication with a control algorithm housed on an Android-based cellular device. Nine subjects with type 1 diabetes (5 female, mean age 53.3 years, mean A1C 7.2%) underwent 9 studies totaling 571 hours of closed-loop control using either default or personalized parameters. The system required meal announcements with estimates of carbohydrate (CHO) intake that were based on metabolic kitchen quantification (MK), dietician estimates (D), or subject estimates (Control). Postprandial glycemia was compared for MK, D, and Control meals.

RESULTS

The overall sensor glucose mean was 145 ± 43, the overall percentage time in the range 70-180 mg/dL was 80%, the overall percentage time <70 mg/dL was 0.79%. Compared to intervals of default parameter use (225 hours), intervals of personalized parameter use (346 hours), sensor glucose mean was 158 ± 49 and 137 ± 37 mg/dL (P < .001), respectively, and included more time in range (87% vs 68%) and less time below range (0.54% vs 1.18%). Most subjects underestimated the CHO content of meals, but postprandial glycemia was not significantly different between MK and matched Control meals (P = .16) or between D and matched Control meals (P = .76). There were no episodes of severe hypoglycemia.

CONCLUSIONS

The HCL system was efficacious and safe during this study. Personally adapted HCL parameters were associated with more time in range and less time below range than default parameters. Accurate estimates of meal CHO did not contribute to improved postprandial glycemia.

Day and night glycaemic control with a bionic pancreas versus conventional insulin pump therapy in preadolescent children with type 1 diabetes: a randomised crossover trial

BACKGROUND

The safety and efficacy of continuous, multiday, automated glycaemic management has not been tested in outpatient studies of preadolescent children with type 1 diabetes. We aimed to compare the safety and efficacy of a bihormonal bionic pancreas versus conventional insulin pump therapy in this population of patients in an outpatient setting.

METHODS

In this randomised, open-label, crossover study, we enrolled preadolescent children (aged 6-11 years) with type 1 diabetes (diagnosed for ≥1 year) who were on insulin pump therapy, from two diabetes camps in the USA. With the use of sealed envelopes, participants were randomly assigned in blocks of two to either 5 days with the bionic pancreas or conventional insulin pump therapy (control) as the first intervention, followed by a 3 day washout period and then 5 days with the other intervention. Study allocation was not masked. The autonomously adaptive algorithm of the bionic pancreas received data from a continuous glucose monitoring (CGM) device to control subcutaneous delivery of insulin and glucagon. Conventional insulin pump therapy was administered by the camp physicians and other clinical staff in accordance with their established protocols; participants also wore a CGM device during the control period. The coprimary outcomes, analysed by intention to treat, were mean CGM-measured glucose concentration and the proportion of time with a CGM-measured glucose concentration below 3·3 mmol/L, on days 2-5. This study is registered with ClinicalTrials.gov, number NCT02105324.

FINDINGS

Between July 20, and Aug 19, 2014, 19 children with a mean age of 9·8 years (SD 1·6) participated in and completed the study. The bionic pancreas period was associated with a lower mean CGM-measured glucose concentration on days 2-5 than was the control period (7·6 mmol/L [SD 0·6] vs 9·3 mmol/L [1·7]; p=0·00037) and a lower proportion of time with a CGM-measured glucose concentration below 3·3 mmol/L on days 2-5 (1·2% [SD 1·1] vs 2·8% [1·2]; p<0·0001). The median number of carbohydrate interventions given per participant for hypoglycaemia on days 1-5 (ie, glucose <3·9 mmol/L) was lower during the bionic pancreas period than during the control period (three [range 0-8] vs five [0-14]; p=0·037). No episodes of severe hypoglycaemia were recorded. Medium-to-large concentrations of ketones (range 0·6-3·6 mmol/dL) were reported on seven occasions in five participants during the control period and on no occasion during the bionic pancreas period (p=0·063).

INTERPRETATION

The improved mean glycaemia and reduced hypoglycaemia with the bionic pancreas relative to insulin pump therapy in preadolescent children with type 1 diabetes in a diabetes camp setting is a promising finding. Studies of a longer duration during which children use the bionic pancreas during their normal routines at home and school should be done to investigate the potential for use of the bionic pancreas in real-world settings.

FUNDING

The Leona M and Harry B Helmsley Charitable Trust and the US National Institute of Diabetes and Digestive and Kidney Diseases.

Impact of Long-Term Poor and Good Glycemic Control on Metabolomics Alterations in Type 1 Diabetic People

CONTEXT

Poor glycemic control in individuals with type 1 diabetes (T1D) is associated with both micro- and macrovascular complications, but good glycemic control does not fully prevent the risk of these complications.

OBJECTIVE

The objective of the study was to determine whether T1D with good glycemic control have persistent abnormalities of metabolites and pathways that exist in T1D with poor glycemic control.

DESIGN

We compared plasma metabolites in T1D with poor (glycated hemoglobin ≥ 8.5%, T1D[-] and good (glycated hemoglobin < 6.5%, T1D[+]) glycemic control with nondiabetic controls (ND).

SETTING

The study was conducted at the clinical research unit.

PATIENTS OR OTHER PARTICIPANTS

T1D with poor (n = 14), T1D(-) and good, T1D(+) (n = 15) glycemic control and matched (for age, sex, and body mass index) ND participants were included in the study.

INTERVENTION(S)

There were no intervention.

MAIN OUTCOME MEASURE(S)

Comparison of qualitative and quantitative profiling of metabolome was performed.

RESULTS

In T1D(-), 347 known metabolites belonging to 38 metabolic pathways involved in cholesterol, vitamin D, tRNA, amino acids (AAs), bile acids, urea, tricarboxylic acid cycle, immune response, and eicosanoids were different from ND. In T1D(+),154 known metabolites belonging to 26 pathways including glycolysis, gluconeogenesis, bile acids, tRNA biosynthesis, AAs, branch-chain AAs, retinol, and vitamin D metabolism remained altered from ND. Targeted measurements of AA metabolites, trichloroacetic acid, and free fatty acids showed directional changes similar to the untargeted metabolomics approach.

CONCLUSIONS

Comprehensive metabolomic profiling identified extensive metabolomic abnormalities in T1D with poor glycemic control. Chronic good glycemic control failed to normalize many of these perturbations, suggesting a potential role for these persistent abnormalities in many complications in T1D.

Altered Skeletal Muscle Mitochondrial Proteome As the Basis of Disruption of Mitochondrial Function in Diabetic Mice

Insulin plays pivotal role in cellular fuel metabolism in skeletal muscle. Despite being the primary site of energy metabolism, the underlying mechanism on how insulin deficiency deranges skeletal muscle mitochondrial physiology remains to be fully understood. Here we report an important link between altered skeletal muscle proteome homeostasis and mitochondrial physiology during insulin deficiency. Deprivation of insulin in streptozotocin-induced diabetic mice decreased mitochondrial ATP production, reduced coupling and phosphorylation efficiency, and increased oxidant emission in skeletal muscle. Proteomic survey revealed that the mitochondrial derangements during insulin deficiency were related to increased mitochondrial protein degradation and decreased protein synthesis, resulting in reduced abundance of proteins involved in mitochondrial respiration and β-oxidation. However, a paradoxical upregulation of proteins involved in cellular uptake of fatty acids triggered an accumulation of incomplete fatty acid oxidation products in skeletal muscle. These data implicate a mismatch of β-oxidation and fatty acid uptake as a mechanism leading to increased oxidative stress in diabetes. This notion was supported by elevated oxidative stress in cultured myotubes exposed to palmitate in the presence of a β-oxidation inhibitor. Together, these results indicate that insulin deficiency alters the balance of proteins involved in fatty acid transport and oxidation in skeletal muscle, leading to impaired mitochondrial function and increased oxidative stress.

Recent advances in type 1 diabetes

Type 1 diabetes (T1D) is caused by an autoimmune attack on pancreatic beta cells that leads to insulin deficiency. The incidence of T1D in Australia has doubled over the past 20 years. T1D treatment focuses on physiological insulin replacement, aiming for near-normal blood glucose levels. Hypoglycaemia is a significant cause of morbidity and mortality in T1D. Optimal T1D management is complex, and is enhanced by empowering individuals in all aspects of managing diabetes. New technologies, including insulin pumps, continuous glucose monitors and sensor-augmented pumps, can assist people achieve better glycaemic control and reduce the risk of severe hypoglycaemia. Women with T1D can achieve significantly better outcomes during pregnancy and for their infants by planning for their pregnancy and by intensive glycaemic control. Several trials are underway that seek to identify the determinants of autoimmunity and to develop therapies that prevent T1D in at-risk individuals. Pancreatic and islet cell transplants are proven therapies, but are only offered to individuals with diabetes and renal failure (pancreas) or severe hypoglycaemia unawareness (islet cell transplants). Although T1D is still associated with considerable premature mortality, recent findings show that a significant improvement in life expectancy has occurred.

Continuous Glucose Monitoring, Future Products, and Update on Worldwide Artificial Pancreas Projects

The development of accurate and easy-to-use continuous glucose monitoring (CGM) improved diabetes treatment by providing additional temporal information on glycemia and glucose trends to patient and physician. Although CGM enables users to lower their average glucose level without an increased incidence of hypoglycemia, this comes at the price of additional patient effort. Automation of insulin administration, also known as closed-loop (CL) or artificial pancreas treatment, has the promise to reduce patient effort and improve glycemic control. CGM data serve as the conditional input for insulin automation devices. The first commercial product for partial automation of insulin administration used insulin delivery shutoff at a predefined glucose level. These systems showed a reduction in hypoglycemia. Insulin-only CL devices show increased time spent in euglycemia and a reduction of hypo- and hyperglycemia. Improved glycemic control, coinciding with a minor decrease in hemoglobin A1c level, was confirmed in recent long-term home studies investigating these devices, paving the way for pivotal studies for commercialization of the artificial pancreas. Although the first results from dual-hormone CL systems are promising, because of increased cost of consumables of these systems, long-term head-to-head studies will have to prove superiority over insulin-only approaches. Now CL glucose control for daily use might finally become reality. Improved continuous glucose sensing technology, miniaturization of electrical devices, and development of algorithms were key in making this possible. Clinical adoption challenges, including device usability and reimbursement, need to be addressed. Time will tell for which patient groups CL systems will be reimbursed and whether these devices can deliver the promise that they hold.

The artificial pancreas: evaluating risk of hypoglycaemia following errors that can be expected with prolonged at-home use

AIMS

Artificial pancreas systems show benefit in closely monitored at-home studies, but may not have sufficient power to assess safety during infrequent, but expected, system or user errors. The aim of this study was to assess the safety of an artificial pancreas system emulating the β-cell when the glucose value used for control is improperly calibrated and participants forget to administer pre-meal insulin boluses.

METHODS

Artificial pancreas control was performed in a clinic research centre on three separate occasions each lasting from 10 p.m. to 2 p.m. Sensor glucose values normally used for artificial pancreas control were replaced with scaled blood glucose values calculated to be 20% lower than, equal to or 33% higher than the true blood glucose. Safe control was defined as blood glucose between 3.9 and 8.3 mmol/l.

RESULTS

Artificial pancreas control resulted in fasting scaled blood glucose values not different from target (6.67 mmol/l) at any scaling factor. Meal control with scaled blood glucose 33% higher than blood glucose resulted in supplemental carbohydrate to prevent hypoglycaemia in four of six participants during breakfast, and one participant during the night. In all instances, scaled blood glucose reported blood glucose as safe.

CONCLUSIONS

Outpatient trials evaluating artificial pancreas performance based on sensor glucose may not detect hypoglycaemia when sensor glucose reads higher than blood glucose. Because these errors are expected to occur, in-hospital artificial pancreas studies using supplemental carbohydrate in anticipation of hypoglycaemia, which allow safety to be assessed in a controlled non-significant environment should be considered as an alternative. Inpatient studies provide a definitive alternative to model-based computer simulations and can be conducted in parallel with closely monitored outpatient artificial pancreas studies used to assess benefit.

Intravenous glucagon in a deliberate insulin overdose in an adolescent with type 1 diabetes mellitus

Massive insulin overdose may be associated with unpredictable and prolonged hypoglycemia. Concerns surrounding the potential provocation of insulin release from beta cells have previously prevented the use of intravenous glucagon as an adjunct to infusion of dextrose in this situation. We describe the case of a 15-yr-old boy with type 1 diabetes mellitus (T1DM) who presented with profound hypoglycemia following an overdose of an unknown quantity of premixed insulin. Owing to an increasing dextrose requirement and a dependence on hourly intramuscular glucagon injections, a continuous intravenous infusion of glucagon was commenced which successfully avoided the requirement for central venous access or concentrated dextrose infusion. Nausea was managed with anti-emetics. Intramuscular and subcutaneous glucagon is effective in the management of refractory and severe hypoglycemia in youth with both T1DM and hyperinsulinism. Concerns regarding the precipitation of rebound hypoglycemia with the use of intravenous glucagon do not relate to those with T1DM. This treatment option may be a useful adjunct in the management of insulin overdose in youth with T1DM and may avoid the requirement for invasive central venous access placement.

Continuous Glucose Monitoring: A Review of Successes, Challenges, and Opportunities

Continuous glucose monitoring (CGM) provides information unattainable by intermittent capillary blood glucose, including instantaneous real-time display of glucose level and rate of change of glucose, alerts and alarms for actual or impending hypo- and hyperglycemia, "24/7" coverage, and the ability to characterize glycemic variability. Progressively more accurate and precise, reasonably unobtrusive, small, comfortable, user-friendly devices connect to the Internet to share information and are sine qua non for a closed-loop artificial pancreas. CGM can inform, educate, motivate, and alert people with diabetes. CGM is medically indicated for patients with frequent, severe, or nocturnal hypoglycemia, especially in the presence of hypoglycemia unawareness. Surprisingly, despite tremendous advances, utilization of CGM has remained fairly limited to date. Barriers to use have included the following: (1) lack of Food and Drug Administration approval, to date, for insulin dosing ("nonadjuvant use") in the United States and for use in hospital and intensive care unit settings; (2) cost and variable reimbursement; (3) need for recalibrations; (4) periodic replacement of sensors; (5) day-to-day variability in glycemic patterns, which can limit the predictability of findings based on retrospective, masked "professional" use; (6) time, implicit costs, and inconvenience for uploading of data for retrospective analysis; (7) lack of fair and reasonable reimbursement for physician time; (8) inexperience and lack of training of physicians and other healthcare professionals regarding interpretation of CGM results; (9) lack of standardization of software methods for analysis of CGM data; and (10) need for professional medical organizations to develop and disseminate additional clinical practice guidelines regarding the role of CGM. Ongoing advances in technology and clinical research have addressed several of these barriers. Use of CGM in conjunction with an insulin pump with automated suspension of insulin infusion in response to actual observed or predicted hypoglycemia, as well as progressive refinement of closed-loop systems, is expected to dramatically enhance the clinical utility and utilization of CGM.

Type 1 Diabetes--Reaping the Rewards of a Targeted Research Investment

The Diabetes Control and Complications Trial (DCCT) precipitated a major research effort to develop new approaches to achieve near-normal glycemic control in real-world settings in people with type 1 diabetes. Toward that end, a unique funding stream from the U.S. Congress-the Special Statutory Funding Program for Type 1 Diabetes Research-has provided nearly $2.5 billion for research into the prevention, cure, and treatment of type 1 diabetes since 1998. This funding generated a targeted, sustained investment in type 1 diabetes research with six specific goals: identifying new therapeutic targets through the understanding of disease etiology and pathogenesis, preventing or reversing the disease, developing cell replacement therapy, improving management and care, preventing or reducing the complications, and attracting new talent and applying new technologies to type 1 diabetes research. This Perspective describes exciting results that have emerged from the investment and further advances on the horizon, including artificial pancreas technologies, new therapies for diabetic retinopathy, and breakthroughs in laboratory production of β-cells. The recent program extension enables us to build on this foundation and pursue key new initiatives to harness emerging technologies and develop the next generation of type 1 diabetes researchers.

Improved Accuracy of Continuous Glucose Monitoring Systems in Pediatric Patients with Diabetes Mellitus: Results from Two Studies

OBJECTIVE

This study was designed to evaluate accuracy, performance, and safety of the Dexcom (San Diego, CA) G4(®) Platinum continuous glucose monitoring (CGM) system (G4P) compared with the Dexcom G4 Platinum with Software 505 algorithm (SW505) when used as adjunctive management to blood glucose (BG) monitoring over a 7-day period in youth, 2-17 years of age, with diabetes.

RESEARCH DESIGN AND METHODS

Youth wore either one or two sensors placed on the abdomen or upper buttocks for 7 days, calibrating the device twice daily with a uniform BG meter. Participants had one in-clinic session on Day 1, 4, or 7, during which fingerstick BG measurements (self-monitoring of blood glucose [SMBG]) were obtained every 30 ± 5 min for comparison with CGM, and in youth 6-17 years of age, reference YSI glucose measurements were obtained from arterialized venous blood collected every 15 ± 5 min for comparison with CGM. The sensor was removed by the participant/family after 7 days.

RESULTS

In comparison of 2,922 temporally paired points of CGM with the reference YSI measurement for G4P and 2,262 paired points for SW505, the mean absolute relative difference (MARD) was 17% for G4P versus 10% for SW505 (P < 0.0001). In comparison of 16,318 temporally paired points of CGM with SMBG for G4P and 4,264 paired points for SW505, MARD was 15% for G4P versus 13% for SW505 (P < 0.0001). Similarly, error grid analyses indicated superior performance with SW505 compared with G4P in comparison of CGM with YSI and CGM with SMBG results, with greater percentages of SW505 results falling within error grid Zone A or the combined Zones A plus B. There were no serious adverse events or device-related serious adverse events for either the G4P or the SW505, and there was no sensor breakoff.

CONCLUSIONS

The updated algorithm offers substantial improvements in accuracy and performance in pediatric patients with diabetes. Use of CGM with improved performance has potential to increase glucose time in range and improve glycemic outcomes for youth.

An Overview of Insulin Pumps and Glucose Sensors for the Generalist

Continuous subcutaneous insulin, or the insulin pump, has gained popularity and sophistication as a near-physiologic programmable method of insulin delivery that is flexible and lifestyle-friendly. The introduction of continuous monitoring with glucose sensors provides unprecedented access to, and prediction of, a patient’s blood glucose levels. Efforts are underway to integrate the two technologies, from “sensor-augmented” and “sensor-driven” pumps to a fully-automated and independent sensing-and-delivery system. Implantable pumps and an early-phase “bionic pancreas” are also in active development. Fine-tuned “pancreas replacement” promises to be one of the many avenues that offers hope for individuals suffering from diabetes. Although endocrinologists and diabetes specialists will continue to maintain expertise in this field, it behooves the primary care physician to have a working knowledge of insulin pumps and sensors to ensure optimal clinical care and decision-making for their patients.

A Digital Ecosystem of Diabetes Data and Technology: Services, Systems, and Tools Enabled by Wearables, Sensors, and Apps

The management of type 1 diabetes (T1D) ideally involves regimented measurement of various health signals; constant interpretation of diverse kinds of data; and consistent cohesion between patients, caregivers, and health care professionals (HCPs). In the context of myriad factors that influence blood glucose dynamics for each individual patient (eg, medication, activity, diet, stress, sleep quality, hormones, environment), such coordination of self-management and clinical care is a great challenge, amplified by the routine unavailability of many types of data thought to be useful in diabetes decision-making. While much remains to be understood about the physiology of diabetes and blood glucose dynamics at the level of the individual, recent and emerging medical and consumer technologies are helping the diabetes community to take great strides toward truly personalized, real-time, data-driven management of this chronic disease. This review describes "connected" technologies--such as smartphone apps, and wearable devices and sensors--which comprise part of a new digital ecosystem of data-driven tools that can link patients and their care teams for precision management of diabetes. These connected technologies are rich sources of physiologic, behavioral, and contextual data that can be integrated and analyzed in "the cloud" for research into personal models of glycemic dynamics, and employed in a multitude of applications for mobile health (mHealth) and telemedicine in diabetes care.

Microfluidic Organ/Body-on-a-Chip Devices at the Convergence of Biology and Microengineering

Recent advances in biomedical technologies are mostly related to the convergence of biology with microengineering. For instance, microfluidic devices are now commonly found in most research centers, clinics and hospitals, contributing to more accurate studies and therapies as powerful tools for drug delivery, monitoring of specific analytes, and medical diagnostics. Most remarkably, integration of cellularized constructs within microengineered platforms has enabled the recapitulation of the physiological and pathological conditions of complex tissues and organs. The so-called “organ-on-a-chip” technology, which represents a new avenue in the field of advanced in vitro models, with the potential to revolutionize current approaches to drug screening and toxicology studies. This review aims to highlight recent advances of microfluidic-based devices towards a body-on-a-chip concept, exploring their technology and broad applications in the biomedical field.

Differentiation of human pluripotent stem cells into β-cells: Potential and challenges

Human embryonic stem cells (hESCs) and induced pluripotent stem cells (iPSCs) hold great potential as the basis for cell-based therapies of degenerative diseases, including diabetes. Current insulin-based therapies for diabetes do not prevent hyperglycaemia or the associated long-term organ damage. While transplantation of pancreatic islets can achieve insulin independence and improved glycemic control, it is limited by donor tissue scarcity, challenges of purifying islets from the pancreas, and the need for immunosuppression to prevent rejection of transplants. Large-scale production of β-cells from stem cells is a promising alternative. Recent years have seen considerable progress in the optimization of in vitro differentiation protocols to direct hESCs/iPSCs into mature insulin-secreting β-cells and clinical trials are now under way to test the safety and efficiency of hESC-derived pancreatic progenitor cells in patients with type 1 diabetes. Here, we discuss key milestones leading up to these trials in addition to recent developments and challenges for hESC/iPSC-based diabetes therapies and disease modeling.