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Automated insulin delivery system

An automated insulin delivery (AID) system, also known as a closed-loop or artificial pancreas system, is a medical technology that combines a (CGM), an , and a control to automatically calculate and deliver insulin doses in based on interstitial glucose readings, primarily to manage . These systems aim to mimic the function of a healthy by dynamically adjusting basal insulin rates while often requiring user-initiated boluses for meals in hybrid configurations. The core components of an AID system include the CGM, which measures glucose levels every few minutes via a subcutaneous ; the , which infuses rapid-acting insulin through a ; and the algorithm, typically running on the pump or a connected device, that processes glucose data to modulate delivery and predict risks like . Most commercially available systems are hybrid closed-loop (HCL) designs, automating basal insulin but relying on manual carbohydrate counting and bolus dosing for postprandial control, though advancements toward fully automated systems with meal detection are underway. This integration reduces the cognitive burden of compared to traditional multiple daily injections or sensor-augmented pumps. Clinical evidence demonstrates significant benefits of AID systems, particularly in improving glycemic outcomes for children, adolescents, and adults with . A 2025 systematic review and of randomized controlled trials found that AID systems increased time in range (70–180 mg/dL) by 11.5% overall and 19.7% at night compared to standard care, while reducing HbA1c by 0.41% and minimizing exposure. These improvements are associated with enhanced , including better sleep, reduced diabetes-related anxiety, and lower treatment burden, without increasing severe adverse events in most studies. The development of AID systems traces back to the with early intravenous prototypes, evolving through the Biostator device to subcutaneous systems in the , with the first FDA-approved commercial HCL system, MiniMed 670G, launched in 2016. As of 2025, several FDA-approved systems are available, including the MiniMed 780G with 4 sensor, t:slim X2 with Control-IQ technology, and Insulet Omnipod 5, alongside updates like the Simplera Sync CGM integration. In 2025, systems like the MiniMed 780G and Control-IQ received FDA approval for adults with . These interoperable devices support personalized glycemic targets and have expanded access through regulatory clearances for broader age groups and settings. Despite these advances, challenges persist, including technological issues like sensor inaccuracies, set failures, and cybersecurity risks, as well as barriers to equitable due to high costs and socioeconomic disparities. Recommendations from expert consensus emphasize structured , improved monitoring, and efforts to enhance affordability and for diverse populations. Ongoing focuses on bihormonal systems incorporating and for fully automated meal insulin delivery.

Overview

Definition and principles

Automated insulin delivery (AID) systems represent an integrated technology that combines real-time continuous glucose monitoring (CGM), automated insulin dosing via an , and user oversight to maintain euglycemia—blood glucose levels within the normal range of approximately 70-180 mg/dL—in individuals with . These systems function as a partial artificial by continuously sensing interstitial glucose levels and adjusting insulin delivery to mimic the body's natural beta-cell response, thereby reducing the manual burden of . User oversight remains essential, particularly for administering bolus insulin with meals and monitoring system performance to ensure safety and efficacy. The core principles of AID systems rely on bidirectional communication between the CGM and insulin pump, facilitated by a control algorithm that processes glucose data to dynamically adjust basal insulin rates based on current levels and trends. Common algorithms include proportional-integral-derivative (PID) control, which responds to the magnitude, duration, and rate of change of glucose deviations from a target, and (MPC), which forecasts future glucose excursions over 2-3 hours using patient-specific models to optimize insulin delivery and avoid extremes. These principles enable proactive modulation of insulin to prevent hypo- and while accounting for factors like insulin-on-board and individual sensitivity. The basic workflow of an AID system begins with the CGM providing real-time glucose readings every 5 minutes, which serve as input to the control for computation of the required insulin adjustment. The then directs the to deliver microboluses or suspend delivery as needed, creating a closed feedback loop that iteratively refines dosing. A foundational example is the , expressed as: u(t) = K_p e(t) + K_i \int_0^t e(\tau) \, d\tau + K_d \frac{de(t)}{dt} where u(t) is the insulin output rate, e(t) is the (difference between sensed glucose and ), and K_p, K_i, K_d are tunable gains for proportional, , and terms, respectively; this formulation ensures responsive yet stable by addressing immediate errors, accumulated deviations, and trends. Target benefits of AID systems include reduced events of (time below range <70 mg/dL) and hyperglycemia (time above range >250 mg/dL), with clinical evidence showing increases in time in range by 9-16% and HbA1c reductions of 0.3-0.7% without elevating risk. These improvements enhance overall glycemic and for users. Prerequisites for AID use typically involve individuals requiring intensive insulin therapy, such as multiple daily injections or pump therapy for , along with proficiency in carbohydrate counting, device troubleshooting, and access to healthcare support for training and monitoring.

Historical development

The development of automated insulin delivery (AID) systems traces its origins to the early 1960s, when Arnold Kadish designed the first prototype of a closed-loop insulin delivery device, an external pump that used intravenous sampling to monitor glucose and adjust insulin and infusions based on . This wearable system, roughly the size of a , represented an initial attempt to automate glycemic control but remained experimental due to limitations in sensor accuracy and invasiveness. In the 1970s, advancements built on these foundations with the creation of the Biostator, a bedside closed-loop system developed by Ernst F. Pfeiffer and colleagues at , which employed intravenous glucose clamps and a proportional-integral-derivative algorithm to deliver insulin and glucose in real time. Approved by the FDA and commercialized by in 1977, the Biostator facilitated but was impractical for outpatient use owing to its large size and need for venous access. These early experiments established the core principle of feedback-controlled insulin delivery, shifting focus toward more portable technologies. The 1980s and 1990s saw the transition to subcutaneous insulin infusion with the introduction of external open-loop pumps, such as the Mill Hill Infuser in 1976 and commercial models like the Auto-Syringe AS 6C in 1983, which allowed programmable basal rates without automation. Rudimentary glucose sensors emerged during this period, but reliable continuous monitoring awaited later breakthroughs; the first real-time (CGM) for personal use, Medtronic's Guardian REAL-Time system, received FDA approval in 2006, enabling sensor-augmented pump () therapy by integrating glucose data with manual insulin adjustments. A pivotal catalyst was the Juvenile Diabetes Research Foundation's (JDRF) launch of the Artificial Pancreas Project in 2006, which funded collaborative research among academia, industry, and regulators to accelerate closed-loop development through clinical trials and standardization efforts. This initiative spurred progress from open-loop systems to automated features, including the 2013 FDA approval of Medtronic's MiniMed 530G, the first with threshold suspend automation that halted insulin delivery upon detecting low glucose levels. By 2015, predictive capabilities advanced with the MiniMed 640G system's SmartGuard technology, which suspended insulin proactively if was forecasted within 30 minutes. The 2010s marked a surge in community-driven innovation, exemplified by the 2013 emergence of the do-it-yourself (DIY) Open Artificial Pancreas System (OpenAPS) community, founded by Dana Lewis and Scott Leibrand, which adapted off-the-shelf pumps and CGMs into open-source closed-loop algorithms shared transparently online. This grassroots movement demonstrated real-world efficacy and pressured commercial development, culminating in the 2016 FDA approval of Medtronic's MiniMed 670G as the first hybrid closed-loop (HCL) system, automating basal insulin adjustments while requiring user input for boluses. Entering the 2020s, AID systems expanded accessibility and automation; Insulet's Omnipod 5, a tubeless HCL system, received FDA clearance in 2022 for individuals aged 6 and older with . By 2023, the Beta Bionics iLet Bionic became the first fully closed-loop device approved by the FDA, automating both basal and bolus insulin without meal announcements. Expansions to followed, with the FDA clearing Omnipod 5 for adults with type 2 in 2024 and Tandem's Control-IQ+ technology for the same population in 2025. Integration of longer-wear CGMs, such as Senseonics' Eversense 365 approved in 2024 for up to one year of implantation, further enhanced system usability and reduced maintenance. Open-source communities like OpenAPS continued to influence commercial acceleration by validating algorithms and advocating for standards.

Core components

Continuous glucose monitors

Continuous glucose monitors (CGMs) serve as the primary sensing component in automated insulin delivery (AID) systems, providing real-time measurements of glucose levels to inform insulin dosing decisions. These devices measure glucose concentrations in the fluid surrounding cells every 5 minutes, offering a continuous stream of data that captures trends and alerts users to hypo- or without the need for frequent fingerstick tests. In AID systems, CGM data is essential for enabling closed-loop functionality, where glucose readings are fed directly into algorithms to automate insulin adjustments. While most modern CGMs are factory-calibrated and do not require routine blood glucose verification for accuracy, some models still benefit from occasional to maintain precision over their wear period. The core technology behind most CGMs involves enzymatic electrochemical sensors that utilize to detect glucose in fluid. A thin filament coated with the is inserted subcutaneously, typically in the or upper , where it reacts with glucose to produce an electrical signal proportional to glucose concentration. This signal is processed by an onboard transmitter and sent wirelessly via to a receiver, app, or , enabling seamless integration with AID systems. Subcutaneous placement allows for minimally invasive monitoring but introduces a physiological lag, as glucose levels trail blood glucose by 5-10 minutes due to the time required for glucose across walls. CGM performance is evaluated primarily through the mean absolute relative difference (MARD), which quantifies accuracy by comparing sensor readings to reference blood glucose values; typical MARD values range from 8% to 12% across devices, with lower values indicating higher reliability for therapeutic decisions. Wear duration varies by model, influencing user convenience and cost in applications—for instance, the G7 sensor lasts up to 15 days with a MARD of 8.0% as of 2025, while the FreeStyle Libre 3 Plus provides 15 days of wear at a MARD of 7.9%. In contexts, this data input supports predictive algorithms, though the 5-10 minute lag must be accounted for to avoid delayed responses to rapid glucose changes. Common CGM models integrated with AID systems include the G6 and G7, which offer high accuracy and compatibility with multiple pumps; the FreeStyle Libre 3 Plus, noted for its compact design and minute-by-minute readings; and the Guardian 4 sensor, which pairs natively with Medtronic pumps with no routine calibrations required. By 2025, advancements have expanded access, with over-the-counter availability for non-insulin-using individuals with through devices like the FreeStyle Libre Rio, alongside broader approvals for management in prescription models. The Eversense system stands out with implantable sensors lasting up to 180 days (or 365 days in the Eversense 365 model), achieving a MARD of 8.5% and reducing replacement frequency. Despite these benefits, CGMs face limitations that can affect their utility in AID systems, including sensor drift where readings gradually deviate from true values over time, necessitating replacements or recalibrations in some cases. Skin irritation or allergic reactions at the insertion site occur in up to 10% of users, potentially leading to early sensor removal. Additionally, while factory-calibrated models like the minimize user burden, calibration-dependent systems such as earlier models require fingerstick confirmations to mitigate inaccuracies from or environmental factors.
ModelWear DurationMARD (%)Key Features in AID
Dexcom G715 days8.0Factory-calibrated, 5-min readings, to pumps
FreeStyle Libre 3 Plus15 days7.9No calibration, compact , type 2 compatible
Medtronic Guardian 47 days8.7No routine , integrated with AID
Eversense E3Up to 180 days8.5Implantable, vibration alerts, long-term wear

Insulin delivery devices

Insulin delivery devices in automated insulin delivery () systems are specialized designed to administer insulin subcutaneously with high precision, enabling both continuous basal and on-demand bolus doses to manage blood glucose levels. These devices integrate seamlessly with continuous glucose monitors (CGMs) and control algorithms to automate dosing adjustments based on real-time glucose data. Tubed insulin pumps, which are tethered to an external set via flexible tubing, allow for remote placement of the pump unit while delivering insulin through a inserted under the skin. In contrast, patch pumps are tubeless and wearable, adhering directly to the body with an integrated and , offering greater discretion and reduced risk of tubing-related issues. The core mechanisms of these devices typically involve either peristaltic drivers, which use rotating rollers to compress flexible tubing and propel insulin in pulsatile increments, or syringe drivers that advance a within a to dispense insulin more linearly. These mechanisms support basal delivery at rates as low as 0.025 units per hour (U/h) to mimic physiological insulin secretion, with programmable variations throughout the day, and bolus delivery up to a maximum of 75 units to cover meals or correct . Reservoir capacities generally range from 200 to 300 units of U-100 insulin, sufficient for several days of use depending on individual needs, and are often disposable cartridges that users fill and insert. features include advanced detection, which monitors delivery pressure to alert users of blockages in the path within minutes, preventing insulin underdelivery, as well as wireless or radio-frequency connectivity to CGMs and controllers for automated data exchange and dosing commands. By 2025, industry standards emphasize durability and user convenience, with most devices achieving an IP28 waterproof rating for submersion up to 8 feet (2.4 meters) for two hours, enabling activities like without removal. Smartphone app control has become ubiquitous, allowing remote programming of basal rates, bolus delivery, and system monitoring via or interfaces, often with over-the-air software updates. Compatibility with rapid-acting insulins, such as Fiasp ( with faster onset), is now standard, supporting its use in both basal and bolus modes without increased risk of infusion set occlusion. Safety features are integral, including audible and vibratory low reservoir alerts that notify users when insulin levels drop below a customizable (e.g., 10-20 units remaining), and programmable site change reminders to prompt cannula replacement every 2-3 days to minimize or issues. The evolution of these devices reflects decades of miniaturization and refinement, originating from bulky 1970s prototypes roughly the size of a and weighing several pounds, which relied on rudimentary mechanical delivery. Advances in materials, , and battery efficiency have transformed them into compact 2025 designs weighing under 50 grams, such as lightweight patch pumps at approximately 26 grams, enhancing portability and comfort for continuous wear.

Control algorithms

Control algorithms in automated insulin delivery (AID) systems form the software core that interprets real-time glucose data from continuous glucose monitors (CGMs) to compute and adjust insulin doses, aiming to maintain glucose levels within a safe target range. These algorithms integrate physiological models of glucose-insulin dynamics with optimization techniques to automate basal insulin delivery and, in advanced forms, correction boluses, reducing the burden on users with . The primary control strategies include algorithms for reactive adjustments and for predictive modeling using glucose forecasts. PID algorithms respond to current glucose deviations from a target (typically 120 mg/dL) by calculating microbolus doses based on proportional error, integral accumulation of past errors, and derivative anticipation of rate changes, with inputs like glucose values every 5 minutes and insulin sensitivity factors. In contrast, MPC algorithms employ dynamic models to predict future glucose trajectories over 30-60 minutes, optimizing insulin delivery to minimize deviations while respecting physiological constraints. MPC operates by solving an at each interval, typically every 5-15 minutes, to determine the insulin sequence that best achieves glycemic goals. The objective function minimizes the squared errors between predicted glucose levels and the , penalized by changes in insulin to avoid excessive dosing: \min \sum_{k=1}^{N} \left( G(k) - G_{\text{[target](/page/Target)}} \right)^2 + \lambda \sum_{k=1}^{M} \Delta u(k)^2 subject to pump constraints on maximum insulin rates and glucose bounds, where G(k) is the predicted glucose at step k, N is the prediction horizon (e.g., 30-60 minutes), u(k) is the insulin input, M is the control horizon, and \lambda is a balancing glucose and insulin smoothness. Inputs to these algorithms include glucose trends from CGM, insulin-on-board (IOB) to account for active insulin, and user-entered carbohydrate intake for meal compensation; outputs consist of adjusted basal rates or automated correction boluses to correct excursions. Safety layers are integral to prevent or overdose, incorporating upper and lower glucose thresholds—such as suspending insulin delivery if glucose falls below 70 mg/dL—and limits on adjustments, such as capping auto-basal rates at up to 400-500% of programmed values in advanced systems to balance efficacy and . These constraints ensure the system reverts to manual mode if anomalies occur, such as . As of 2025, advancements include adaptive tuning that personalizes parameters based on individual user patterns, such as varying insulin sensitivity over time, and integration of for automated meal detection to estimate intake without user input, enhancing fully closed-loop performance. Validation of these algorithms emphasizes time-in-range (TIR), targeting at least 70% of time spent between 70-180 mg/dL to assess glycemic control and safety in clinical trials.

Classification of systems

Threshold and predictive suspend systems

Threshold suspend systems represent an early advancement in automated insulin delivery (AID), designed to automatically halt basal insulin infusion when continuous glucose monitoring (CGM) detects a low sensor glucose value, thereby preventing or mitigating without requiring user intervention. These systems activate upon reaching a user-defined , typically set at 70-80 mg/dL, and remain suspended until the glucose level rises above the or the user manually resumes delivery. The MiniMed 530G system, approved by the FDA in September 2013, was the first commercial implementation of this technology, classified as an artificial pancreas device system with suspend automation for individuals aged 16 and older with . In clinical trials such as the ASPIRE study, suspend reduced the area under the curve for nocturnal by 37.5% and the frequency of such events by 31.8% compared to sensor-augmented pump therapy alone, without increasing HbA1c levels. Building on threshold suspend, predictive low glucose suspend (PLGS) systems incorporate forecasting algorithms to preemptively pause insulin delivery before hypoglycemia occurs, using trends in CGM data to predict future glucose levels. In the MiniMed 640G/630G system with SmartGuard technology, approved by the FDA in September 2016, the algorithm analyzes the most recent four sensor glucose values to forecast the glucose level 30 minutes ahead; insulin is automatically suspended if the prediction falls to 70 mg/dL or below, with resumption occurring when the predicted value exceeds 80 mg/dL. This predictive capability allows suspensions to begin 5 to 30 minutes prior to an anticipated low, based on a rate of glucose change exceeding a threshold such as -2 mg/dL/min, and can last up to 2 hours if needed. Clinical evidence demonstrates the efficacy of PLGS in reducing across age groups. The SMILE in children and adolescents showed that PLGS decreased hypoglycemic events below 65 mg/dL by approximately 40% (from 7.4 to 4.4 events over 14 days), with significant reductions both daytime and nighttime, while increasing time spent above 140 mg/dL without severe adverse events. Similarly, the trial in a mixed-age reported a 31% reduction in time spent below 70 mg/dL (from 3.6% to 2.6% of the day) compared to standard sensor-augmented therapy. Real-world analyses have indicated up to 69% fewer glucose values at or below 50 mg/dL when the feature is active. These systems offer key advantages in prevention, particularly for nocturnal lows, where severe events can be reduced by 30-70% depending on the metric and population studied, providing a safety net for users at risk of impaired . However, limitations include the lack of automated insulin resumption in initial versions, reliance on user intervention for management post-suspension, and potential for rebound due to prolonged pauses, which may slightly elevate mean glucose levels. As a transitional from basic sensor-augmented pumps, and PLGS systems paved the way for more advanced by demonstrating safe automation of basal insulin adjustments, with FDA approvals between 2013 and 2016 marking regulatory milestones in device innovation.

Hybrid closed-loop systems

Hybrid closed-loop (HCL) systems represent a significant advancement in automated insulin delivery, where the system automatically adjusts basal insulin rates in response to continuous glucose monitoring (CGM) data while requiring users to manually administer bolus doses for meals. These systems use an algorithm to increase or decrease basal insulin delivery every few minutes to maintain glucose levels within a predefined target range, typically aiming for 120 mg/dL in early models like the MiniMed 670G, which was the first FDA-approved HCL system in 2016 for individuals aged 7 and older. Advanced hybrid closed-loop (AHCL) systems build on this foundation with more responsive features, including automatic correction boluses for and broader target ranges such as 100-180 mg/dL to enhance time in range (TIR). For instance, the MiniMed 780G, approved in 2020 and updated through , incorporates auto-correction boluses up to every 5 minutes and adjustable targets as low as 100 mg/dL, leading to TIR improvements of up to 60% in real-world use compared to prior sensor-augmented pump therapy. At the core of HCL and AHCL systems is a control , often based on (MPC), which forecasts future glucose levels and optimizes insulin delivery while accounting for insulin on board (IOB) to prevent stacking. The suspends or reduces basal insulin to mitigate when glucose approaches low thresholds and ramps up delivery to address , integrating CGM inputs with user-provided data like intake for boluses. Users retain an active role in HCL systems by announcing carbohydrate intake and delivering manual meal boluses, though the automation of basal adjustments reduces the overall frequency of interventions. Emerging features as of 2025 include integration with activity trackers for exercise detection, allowing the algorithm to preemptively adjust insulin during to minimize glycemic excursions. Pivotal clinical trials have demonstrated the efficacy of HCL systems, with reductions in HbA1c of 10-15% relative to baseline in adolescents and adults, alongside increased TIR without elevated risk. For example, trials of systems like the MiniMed 670G showed HbA1c decreases from approximately 7.7% to 7.1%, while AHCL trials in younger children reported similar proportional improvements and approvals extended to ages 2 and older for select systems.

Fully closed-loop systems

Fully closed-loop systems represent the most advanced form of automated insulin delivery (AID), providing end-to-end automation of insulin dosing without any requirement for user input, such as meal announcements or carbohydrate counting. These systems integrate continuous glucose monitoring (CGM) data with sophisticated control algorithms to detect and respond to glucose excursions autonomously, mimicking the function of a healthy . Meals are identified indirectly through rises in glucose levels or rates of change, enabling the system to adjust basal and bolus insulin delivery in real time. Algorithms employed include advanced (MPC), which forecasts future glucose trajectories based on personalized models, and emerging (RL) approaches that optimize insulin decisions through iterative learning from glucose patterns. Key features of fully closed-loop systems emphasize user independence and glycemic targets typically set between 70-180 mg/dL (3.9-10.0 mmol/L), with some aiming for tighter ranges like 70-140 mg/dL (3.9-7.8 mmol/L) to minimize variability. By eliminating manual bolusing, these systems reduce cognitive burden and improve time in range (TIR), with 2025 clinical trials reporting TIR levels ranging from 66% to 89% depending on participant characteristics and study conditions. For instance, the CamAPS HX system, a fully closed-loop , achieved a TIR of 66.3% in an 8-week trial involving adults with , while a in a reported 89% TIR with no hypo- or hyperglycemic events. The CamAPS HX has received in Europe for use in as of 2024, with ongoing studies for . These outcomes highlight the potential for sustained glycemic control without user intervention, though results vary based on individual insulin sensitivity and activity levels. Despite these advances, fully closed-loop systems face significant challenges, particularly an over-reliance on accurate glucose predictions and limitations in postprandial control. Without direct meal information, algorithms must infer carbohydrate intake from glucose dynamics, which can lead to delayed or insufficient bolus responses, resulting in post-meal . Sensor lag and the pharmacokinetic profiles of current rapid-acting insulins exacerbate this issue, as insulin onset may not match the speed of glucose rises after eating. Clinical studies confirm that fully closed-loop performance lags behind systems in managing peak postprandial excursions, with exposure often 10-20% higher in unannounced meal scenarios. Ongoing refinements in robustness and accuracy are essential to address these gaps. Promising examples in trials include the CamAPS HX system, which is expanding through ongoing type 1 diabetes studies in the UK, demonstrating feasibility across diverse populations. Looking to the future, integration with ultra-rapid insulins, like ultra-rapid insulin lispro, holds substantial potential to enhance response times and postprandial control; a 2025 randomized crossover trial using CamAPS FX showed a trend toward 9.4% higher TIR (49.3% vs. 39.9%) and reduced compared to standard insulins in simulated missed-bolus scenarios. Such innovations could push TIR toward 80-90% consistently, further automating .

Commercial systems

Medtronic MiniMed 780G

The MiniMed 780G is an advanced hybrid closed-loop automated insulin delivery system approved by the (FDA) on April 21, 2023, for individuals aged 7 years and older with . It integrates the Guardian 4 (CGM), which provides real-time glucose readings without fingerstick calibration, with a tubed capable of delivering basal rates from 0 to 35 units per hour and bolus doses up to 25 units. In September 2025, the FDA expanded its indications to include adults aged 18 years and older with insulin-treated , making it one of the first such systems approved for this population. Key features of the MiniMed 780G include automated basal insulin adjustments every 5 minutes based on CGM data, along with auto-correction boluses delivered when sensor glucose exceeds the target level, typically set at 120 mg/dL but adjustable as low as 100 mg/dL. The system's Meal Detection technology identifies rapid rises in glucose indicative of unannounced intake and responds by delivering enhanced correction boluses without , helping to mitigate post-meal . This tubed pump design ensures precise subcutaneous insulin delivery via an infusion set, and the system is compatible with Bluetooth-enabled devices such as select and models for remote monitoring and data sharing. Clinical studies from 2024 and 2025 demonstrate strong performance, with real-world data showing time in range (TIR, 70-180 mg/dL) averaging around 75-80% in users with , and up to 84.9% in adults with after system initiation. time below 70 mg/dL remains low at approximately 1.4% or less, with no severe events reported in pediatric trials for children aged 2-6 years, where TIR improved by 9.9% compared to baseline. The initial cost of the system is approximately $8,000, with ongoing supplies such as sensors and infusion sets adding monthly expenses covered variably by insurance. User experiences highlight the benefits of simplified glucose management, including fewer manual interventions and improved , though some report the need for daily data uploads to the app for optimal tracking. Alert fatigue has been noted in reviews, with users occasionally finding the frequency of notifications excessive despite overall reductions in nighttime alerts by up to 45%. Clinicians emphasize the importance of initial training to set realistic expectations and minimize such issues.

Tandem t:slim X2 with Control-IQ

The Tandem t:slim X2 with Control-IQ technology received FDA clearance in December 2019 as an advanced hybrid closed-loop system for automated insulin delivery in individuals with aged 6 years and older. Subsequent updates expanded its indications; by 2024, it was cleared for use in those aged 2 years and older, with compatibility enhancements continuing into 2025 for broader pediatric application. The system integrates with continuous glucose monitors (CGMs) such as G6, G7, and, following a June 2025 software update, FreeStyle Libre 3 Plus, enabling real-time glucose data to inform insulin adjustments. Control-IQ features predictive algorithms that forecast glucose levels 30 minutes ahead and automatically adjust basal insulin delivery every 5 minutes, increasing rates up to twice the programmed basal or suspending delivery to mitigate hypoglycemia. Unique to this system are customizable modes for varying activities: standard mode targets 112.5–160 mg/dL, sleep mode narrows to 112.5–120 mg/dL for overnight control, and exercise mode raises targets to 140 or 160 mg/dL to prevent lows during physical activity. The built-in bolus calculator incorporates CGM data and activity mode settings to recommend precise meal boluses, while users must still manually initiate boluses and enter carbohydrate estimates. Clinical data from real-world studies and meta-analyses through 2025 demonstrate strong performance, with users achieving median time in range (TIR, 70–180 mg/dL) of 72–78%, including up to 90% overnight TIR in enhanced modes, alongside reduced hypoglycemic events due to predictive suspension technology. The pump's compact design measures 2 × 3.13 × 0.6 inches and weighs 3.95 ounces with a full 300-unit reservoir, facilitating discreet wear. is a key strength, as the February 2025 clearance of Control-IQ+ software version integrates Basal-IQ predictive suspend features across multiple CGMs without proprietary restrictions, and ongoing updates like version supporting Libre 3 Plus enhance flexibility. Without insurance, the t:slim X2 pump costs approximately $4,000, with monthly supplies averaging $300; however, strong coverage through most private insurers and plans typically reduces out-of-pocket costs to under $50 per month for eligible users. Tandem's financial assistance programs further support access for those facing barriers.

Insulet Omnipod 5

The Insulet Omnipod 5 is a tubeless automated insulin delivery system approved by the U.S. Food and Drug Administration (FDA) in January 2022 for individuals with aged 6 years and older, with an expansion in August 2022 to include children as young as 2 years old. In August 2024, the FDA further expanded its indication to adults aged 18 and older with , marking it as the first automated insulin delivery system cleared for this population. The system consists of a disposable, waterproof Pod that adheres directly to the skin and delivers insulin subcutaneously without tubing, paired with a compatible (CGM) such as Dexcom G6 or for glucose . Key features of the Omnipod 5 include its waterproof design, which allows continuous wear during activities like showering for up to 24 hours at a time, and a 72-hour operational duration per Pod, minimizing the frequency of device changes compared to daily injections. The system automates basal insulin delivery and provides correction boluses as needed, targeting a default glucose level of mg/dL to maintain stability, with users able to adjust targets between and 150 mg/dL via the companion app. Control is managed entirely through the Omnipod 5 on compatible or smartphones, enabling remote Pod activation, deactivation, bolus delivery, and glucose monitoring without a separate controller device. Its tubeless patch-pump design enhances discretion and mobility, as the Pod can be worn under clothing on the arm, , or back. Clinical performance data from 2025 real-world studies demonstrate the system's effectiveness, with users achieving an average time in range (TIR, 70-180 mg/dL) of approximately 69-75% when targeting 110 mg/dL, representing a significant improvement over prior therapies. The 72-hour Pod wear reduces infusion site changes to every three days, supporting better adherence, while the 200-unit insulin reservoir accommodates varying daily needs without frequent refills. These outcomes are supported by reduced (less than 1.2% of time below 70 mg/dL) and improved HbA1c levels by about 0.3-0.5%. By 2025, the Omnipod 5 received updates expanding CGM compatibility to include Abbott's FreeStyle Libre 2 Plus sensor alongside options, broadening integration choices for users. The indication, effective from late 2024, has seen rapid adoption, with about 30% of new U.S. users in 2025 having , facilitated by the system's basal-only suitable for basal insulin regimens. The absence of tubing further promotes discretion and ease during daily activities, distinguishing it as a convenient option for on-the-go management. User experiences highlight the Omnipod 5's suitability for active lifestyles, with features like automated adjustments during exercise reducing the burden of manual interventions and enabling participation in sports or outdoor pursuits without device interference. However, some users report challenges with Pod in hot or humid conditions, where sweat can compromise the , potentially leading to leaks or early detachment despite . Insulet provides guidance on skin preparation and overpatches to mitigate these issues, emphasizing thorough drying and avoidance of oils for optimal hold.

Beta Bionics iLet Bionic Pancreas

The Beta Bionics iLet Bionic Pancreas is a fully automated insulin delivery system cleared by the U.S. (FDA) in May 2023 for individuals aged 6 years and older with . It features a dual-chamber pump design capable of delivering insulin and , though currently approved and commercialized for insulin-only use with Fiasp or lispro insulin formulations; the bi-hormonal configuration incorporating dasiglucagon remains in development with ongoing clinical trials as of 2025. The system integrates with compatible continuous glucose monitors (CGMs) such as G6/G7 or FreeStyle Libre 3 Plus to enable closed-loop operation. A key distinguishing feature of the iLet is its simplified , which eliminates the need for counting, preset basal rates, insulin-to-carbohydrate ratios, or manual correction boluses. Initialization requires only the user's body weight and age to estimate starting insulin doses, with the system autonomously adjusting all basal and bolus insulin deliveries based on real-time CGM data. Users can announce meals by selecting from simplified categories (e.g., , , ; usual, less, or more amounts) without quantifying exact grams. The default target glucose is 120 mg/dL, adjustable to 110 or 130 mg/dL, promoting a conservative approach to glycemia. The pump's dual-chamber architecture supports future bi-hormonal operation, where would be delivered to prevent or treat through counter-regulatory effects, as demonstrated in home-use trials showing reduced time below 54 mg/dL (0.2% vs. 0.6% for insulin-only). Clinical performance data from the pivotal in 440 participants (219 adults and 165 youth aged 6-17) demonstrated superior glycemic outcomes compared to standard care, with the iLet achieving 65% time in (TIR; 70-180 mg/dL) versus 54% in the , representing an 11 improvement (95% , 9-13; P<0.001). remained low and noninferior, with median time below 54 mg/dL at 0.3% versus 0.2% in controls (P<0.001 for noninferiority). Real-world data from over 24,000 s as of mid-2025, including 2-year follow-up presented at the Scientific Sessions, indicate sustained TIR around 70% on average, with median time below 54 mg/dL at 0.28%—one-quarter of the American Diabetes Association's target—and consistent benefits across varying levels. In bi-hormonal configurations, TIR reached 79% with further hypo mitigation via automated dosing (mean 0.35 mg/day), highlighting the system's potential for enhanced counter-regulation once approved. The pump supports up to 7-day cartridge wear in trials, though current insulin pods require changes every 3 days. The iLet's proprietary algorithm employs adaptive, model-predictive control that initializes dosing from body weight and continuously learns individual physiological patterns—such as insulin sensitivity and meal responses—over the first few weeks of use to refine autonomous decisions. This approach reduces provider burden and user effort, with no warm-up period required. By late 2025, the system has seen expanded coverage, including benefits from major providers, improving . Initial costs average approximately $10,000 for the and initial supplies, with ongoing monthly expenses for insulin vials and consumables around $500, though coverage mitigates out-of-pocket expenses for many users.

twiist AID system with Eversense 365 integration

The twiist automated insulin delivery () system, developed by Sequel Med Tech in partnership with Senseonics, integrates with the Eversense 365 implantable (CGM), following their commercial development agreement announced on April 29, 2025. This collaboration aims to create the first AID system compatible with a one-year implantable CGM, streamlining for individuals with . The Eversense 365 CGM received FDA clearance as an integrated CGM (iCGM) in September 2024, and the twiist pump was cleared separately; the full integration was anticipated for commercial availability in the third quarter of 2025 for adults aged 18 years and older. The twiist system operates as a hybrid closed-loop using Tidepool's algorithm, automatically adjusting basal insulin rates and delivering correction boluses based on CGM data from the Eversense 365, while targeting a customizable glucose range such as 100-160 mg/dL to optimize time in range without excessive risk. Users announce meals via a smartphone app, and the Bluetooth-enabled setup allows remote monitoring through a connected , enhancing involvement and flexibility. The tubed supports U-100 rapid-acting insulins, broadening compatibility for personalized , and features iiSure technology for precise micro-dosing measurement. The Eversense 365 CGM requires surgical implantation and provides year-long glucose monitoring with minimal user intervention, including twice-daily calibrations for the first 21 days and weekly thereafter, reducing daily maintenance compared to shorter-wear sensors. As of November 2025, clinical data for the integrated system remains limited, with ongoing trials evaluating efficacy and safety; component studies for twiist and Eversense demonstrate stable glycemic control with low variability. The integration innovates by minimizing sensor replacement to once per year, addressing a major burden in traditional CGM use and improving adherence for active lifestyles. This long-duration design, combined with the discreet tubed worn for up to 72 hours, prioritizes user convenience and reduces interruptions. with U-100 insulins ensures broad accessibility without requiring specialized formulations. Priced at approximately $7,000 for the full system, the twiist with Eversense 365 emphasizes affordability through reimbursement pathways and financial assistance programs, with the goal of alleviating long-term user burden via its extended-wear components. This focus on durability and simplicity positions it as a forward-looking option in the hybrid closed-loop category, particularly for those seeking fewer interventions.

Open-source and DIY systems

OpenAPS

OpenAPS is a pioneering open-source automated insulin delivery (AID) system developed by a global community of individuals with type 1 diabetes and their supporters, with its origins tracing back to the fall of 2013 when Dana Lewis and Scott Leibrand created the first public do-it-yourself (DIY) closed-loop prototype known as #DIYPS. The project formally launched in February 2015 as an open reference design aimed at automating basal insulin delivery to improve glycemic control, building on early innovations like John Costik's cloud-based glucose prediction algorithm from 2013. It integrates with existing continuous glucose monitors (CGMs) such as Dexcom G4-G6 and compatible insulin pumps, primarily older Medtronic models, using low-cost hardware like a Raspberry Pi or Intel Edison computer to run the software. As free, open-source software, OpenAPS emphasizes accessibility and community-driven improvements, allowing users to customize settings without proprietary restrictions. A key unique feature of OpenAPS is its customizable oref0 algorithm, a heuristic-based system that forecasts blood glucose levels under various scenarios—such as full absorption or insulin changes—and automatically adjusts basal insulin rates without issuing boluses to prioritize safety. It supports automated basal rate modifications, temporary target glucose ranges (e.g., higher targets during exercise), and precise tracking of insulin on board (IOB) to prevent stacking, enabling users to fine-tune parameters like ratios and factors for personalized control. Later iterations, such as oref1 introduced in 2017, added super-microbolus () capabilities for more responsive corrections while maintaining the core focus on basal automation. Implementation involves assembling a "rig" with a small Linux-based computer connected to a USB radio (e.g., Carelink stick) to wirelessly communicate with the , retrieving CGM data via apps like xDrip or Share, and executing the algorithm every 5 minutes. Users typically do not need to flash pump , as the system operates externally, though some advanced setups use modified for reliability; the process is documented step-by-step in community resources to enable self-setup. As of 2024, the OpenAPS community reports over 3,262 individuals worldwide using various DIY closed-loop implementations, including OpenAPS and derivatives. Safety is ensured through community-validated, transparent code reviewed by hundreds of contributors, with built-in safeguards like maximum dose limits and deviation alerts to avoid over-delivery. Multiple studies demonstrate its efficacy, including a 2019 analysis of 80 users showing an estimated HbA1c of 6.4% and TIR of 77.5%, with a subcohort (n=34) demonstrating a 0.4% HbA1c reduction (from 6.6% to 6.2%) and TIR increase to 80.4% compared to sensor-augmented pump use, alongside fewer severe hypoglycemic events, without increased adverse outcomes. A 2023 retrospective study of 248 clients using supported open-source APS (SOSAPS, based on the OpenAPS algorithm) reported no diabetic ketoacidosis, 3 severe hypoglycemic events over 17 months, a 0.5% HbA1c reduction (from 7.2% to 6.7%), and improved quality of life including hypoglycemia awareness. These results are supported by real-world data shared voluntarily through platforms like the OpenAPS Data Commons. The OpenAPS community fosters collaboration via online forums, GitHub repositories, and tools like Nightscout, an open-source platform for real-time remote viewing of glucose data, pump status, and boluses on websites, apps, or smartwatches, enabling caregivers and users to monitor from afar. Emphasis on drives ongoing enhancements, with users contributing anonymized CGM records to repositories to validate outcomes and inform broader development.

Loop

Loop is an iOS-based open-source automated insulin delivery (AID) system designed specifically for users within the , providing a customizable alternative to commercial options for managing . Developed in 2015 by software engineer Nate Racklyeft and collaborators as the second major DIY AID project following OpenAPS, Loop integrates continuous glucose monitoring (CGM) data with commands through an app that extends functionality to the . The system supports compatible hardware including Omnipod Eros and DASH pumps, older models (such as 515/715, 522/722, and select Veo series), and certain Sooil Dana and Medtrum Nano pumps, enabling automated basal insulin adjustments and bolus recommendations based on real-time glucose readings. A key strength of Loop lies in its unique features tailored to iOS and wearable integration, facilitating seamless . The app executes looping calculations every 5 minutes, synchronized with standard CGM update intervals like those from , to predict glucose trajectories and adjust insulin delivery proactively. Apple Watch support includes haptic alerts for glucose thresholds, bolusing capabilities, and on-wrist glucose displays, allowing users to monitor and respond without constantly checking their phone. Additionally, Loop incorporates a carb model that tracks historical meal impacts on blood glucose patterns, refining future predictions by accounting for unentered or extended carbohydrate effects beyond initial bolus calculations—this "carb memory" helps mitigate post-meal without requiring exhaustive manual logging. Customization is central to Loop's design, with its freely available on under the LoopKit organization, enabling users and developers to modify algorithms, interfaces, and integrations as needed. As of 2025, updates in the latest releases (version 3.x) have expanded compatibility to include G7 CGM sensors natively, alongside enhancements for remote bolus and carb entries via or , improving usability for caregivers and active lifestyles. As of September 2025, version 3.8.0 supports 18 and additional pumps like Dana-i and DanaRS-v3. The open-source nature fosters a collaborative development model, where community contributions address evolving hardware like newer Omnipod iterations while maintaining core safety features such as suspension thresholds to prevent . Real-world user experiences highlight Loop's effectiveness, with surveys and prospective studies reporting median time in range (TIR, 70-180 mg/dL) of approximately 75-77% among adults and children, alongside low rates of severe hypoglycemia (around 19 events per 100 patient-years). Community-driven data from platforms like the "Looped" Facebook group, which has over 10,000 members, demonstrate sustained improvements in glycemic control and quality of life, though outcomes vary based on user adherence and settings optimization. Forums such as these serve as vital resources for troubleshooting, sharing configurations, and peer support, emphasizing the importance of ongoing education for safe implementation. While the software itself is free and open-source, adopting Loop requires technical proficiency to compile and install the app via or GitHub Actions, making it accessible primarily to tech-savvy individuals or those with community guidance. Hardware costs typically range from $150-200 for essential components like a RileyLink or OrangeLink radio bridge to connect the to non-Bluetooth pumps, though full starter including spares and accessories can approach $500 depending on pump compatibility needs. No formal regulatory approval exists for the DIY version, underscoring the need for users to consult healthcare providers and monitor closely during initial setup.

AndroidAPS

AndroidAPS is an open-source automated insulin delivery (AID) system designed specifically for smartphones, enabling users with insulin-dependent to automate basal insulin dosing and manage glucose levels through a hybrid closed-loop approach. Developed in 2016 by Miloš Kozák as an adaptation of the OpenAPS algorithms to overcome compatibility limitations with certain insulin pumps, it expands accessibility to a broader range of hardware while maintaining the core predictive low-glucose suspend and basal adjustment functionalities. The system integrates continuous glucose monitoring (CGM) data to calculate and deliver insulin doses via compatible pumps, prioritizing user-configurable safety parameters to prevent . Key features of AndroidAPS include its ability to operate offline without constant internet connectivity, relying on local processing for real-time looping decisions, which distinguishes it from cloud-dependent alternatives. It supports CGM integration through apps like xDrip+ for sensors such as Dexcom G6 or FreeStyle Libre, and is compatible with insulin pumps including Accu-Chek Combo, DanaR, and DanaS models. Safety mechanisms, such as maximum insulin on board (maxIOB) limits and basal rate caps, allow users to set conservative or aggressive profiles based on individual needs, while advanced options like super micro bolus (SMB) enable proactive insulin delivery for unannounced meals in supported configurations. The August 2025 release of version 3.3.2.1 further refined these with fixes for Omnipod Bluetooth connection on Android 16 and other enhancements, all built from the freely available GitHub repository. The AndroidAPS community comprises an international team of volunteer developers and contributors who maintain the project through open collaboration on , with documentation and app interfaces translated into over 20 languages to support global adoption. Approximately 10,000 users worldwide engage with the system, as of 2025, benefiting from rapid community support forums and shared best practices for customization. Clinical and real-world studies indicate that AndroidAPS achieves time in range (TIR, 70-180 mg/dL) outcomes comparable to systems, typically 75-85%, with significant reductions in events when used under medical supervision. For instance, a prospective comparison reported 78% TIR for AndroidAPS users versus 75-76% for closed-loop devices, alongside improved HbA1c without increased adverse events. Setup for AndroidAPS involves downloading and building the app from source via or obtaining pre-built APKs from trusted community releases, followed by pairing with a compatible CGM and pump through . Integration with Nightscout enables remote monitoring and with healthcare providers, while a guided "Objectives" ensures progressive activation from open-loop basal tuning to full closed-loop operation, emphasizing safety checks at each step. Users must consult healthcare professionals for personalized configuration, as the system is not FDA-approved and relies on user responsibility for hardware integrity.

Systems in development

Inreda Automated Insulin Delivery System

The Inreda Automated Insulin Delivery System, developed by the Inreda Diabetic B.V. in , , is a bi-hormonal wearable device that delivers both insulin and subcutaneously to manage . The system functions as a fully closed-loop artificial , integrating continuous glucose monitoring with automated infusion to mimic physiological glucose regulation. Clinical trials for the Inreda AP began in 2016 with the first home-based dual-hormone study, demonstrating improved time in range compared to conventional therapy. It received initial CE marking in 2020 under the Medical Device Regulation, with an updated MDR CE certificate issued in December 2023, confirming compliance for use in adults with in . Key features of the Inreda AP include its fully automated operation, requiring no user input for counting, meal bolusing, or exercise announcements, which distinguishes it from systems. The device is designed for continuous 24-hour wear on the body, typically secured via accessories like a hip bag or belt, with dual subcutaneous infusion sets for insulin and delivery. It employs two integrated glucose sensors for and reactive dosing to maintain stable glucose levels, prioritizing safety during daily activities such as or physical . The system targets euglycemia without a user-adjustable setpoint, focusing on minimizing hypo- and through bi-hormonal balance. Recent progress includes a one-year prospective single-arm involving 79 adults with , published in 2024, which reported a time in range (70-180 mg/dL) of 80%, time below range (<70 mg/dL) of 1.4%, and mean HbA1c of 6.9% during real-world use. A 2025 analysis of a similar with 78 adults confirmed sustained after one year of fully closed-loop , achieving 80% time in range with subcutaneous delivery and low severe rates. These results highlight the system's reliability in outpatient settings, with ongoing refinements to the AP6 model for enhanced performance. Challenges in the Inreda primarily revolve around glucagon formulation and delivery, including daily reservoir replacements due to instability, potential tube occlusions, and infusion site issues such as lumps or pain. These factors contribute to maintenance demands, though clinical data show overall safety and superior glucose control over sensor-augmented pumps. The system shows promise for broader application, with a dedicated trial evaluating its performance in adolescents and youth with to support potential expansion beyond adults. While U.S. market entry remains in early stages, including FDA interactions on device components, pediatric evaluations could pave the way for approvals targeting younger users in the coming years.

Luna Diabetes AID

The Luna Diabetes AID is an automated insulin delivery system in development, designed as a single-hormone, AI-enhanced primarily for nighttime use among people with who rely on insulin pens for multiple daily injections. Founded in 2020 by diabetes veterans, including executives from —which was acquired by in September 2023 for an undisclosed amount to advance connected solutions—the Luna system aims to simplify overnight glucose management by automating basal insulin delivery and micro-boluses without requiring a traditional or complex setup. Clinical trials for the system commenced in October 2024 as a pivotal, at-home study evaluating its closed-loop performance in adults aged 18 and older with , focusing on time in range (TIR) as the primary efficacy endpoint. The virtual trial assesses the device's ability to integrate with users' existing pen-based routines, with enrollment ongoing into 2025 to gather data on safety and glycemic outcomes. Early concept testing has demonstrated high user interest and potential for improved overnight control, though full pivotal results are pending. Key features of the Luna AID include its compact, semi-reusable patch pump design, which adheres to the skin and delivers automated insulin adjustments via a closed-loop capable of learning glucose patterns for personalized dosing during . The requires only a single basal dose input at bedtime, enabling seamless transition to daytime pen use, and emphasizes user-friendly operation to minimize alerts and interruptions. While integration with continuous glucose monitors like is anticipated for , specific details remain under development; voice command functionality has not been publicly detailed. As of August 2025, Luna Diabetes secured $23.6 million in Series A funding to support ongoing trials, manufacturing scale-up, and regulatory submissions, positioning the system for potential FDA clearance later that year. Preliminary data from feasibility studies suggest enhanced TIR around 75% overnight with fewer hypoglycemic events and reduced alert burden compared to manual pen dosing, though these metrics await confirmation from the . The system's innovation lies in its targeted approach to nighttime for the over 90% of insulin-dependent individuals using pens, prioritizing and ease for non-technical users through a discreet, low-maintenance that avoids the of full-day pumps. This focus on hybrid use could enable broader adoption, with potential for over-the-counter pathways to reduce . However, the incorporation of AI-driven pattern learning introduces challenges related to data privacy, particularly in ensuring secure handling of sensitive glucose and dosing across connected devices.

Emerging bi-hormonal and implantable systems

Emerging bi-hormonal automated insulin delivery (AID) systems are advancing beyond single-hormone approaches by incorporating adjunctive therapies like (GLP-1) receptor agonists or analogs to enhance glycemic control and mitigate postprandial excursions. A phase 2 (NCT06630585) evaluating GIP/GLP-1 receptor agonist () as an adjunct to AID in adults with is ongoing, involving 42 participants in a randomized, open-label design assessing three months of dual-hormone delivery. Similarly, co-delivery of insulin with pramlintide, a synthetic analog, has shown promise in suppressing , slowing gastric emptying, and promoting , thereby reducing meal-related glucose spikes in closed-loop systems; a using AI-based meal detection with insulin-pramlintide co-formulation achieved fully automated delivery with TIR exceeding 80% in pilot testing. Implantable technologies are progressing toward fully integrated AID platforms, combining long-term continuous glucose monitoring (CGM) with potential pump innovations to minimize external components. Med Tech and Senseonics announced a collaboration in 2025 to integrate the Eversense 365, a one-year implantable CGM, with 's twiist AID system, enabling automated insulin adjustments based on subcutaneous glucose sensing for up to 365 days without sensor replacement. This hybrid approach addresses user burden by reducing insertion frequency, though the pump remains external in current prototypes. Parallel efforts in beta-cell encapsulation aim to create bioartificial pancreases; (formerly ViaCyte) reported 2025 clinical trial updates on stem cell-derived beta cells encapsulated in immunoprotective devices, demonstrating sustained insulin production after one year in patients with through optimized designs to prevent immune rejection. These systems hold potential for superior outcomes, including TIR targets of 90% or higher with reduced maintenance, as projected in multihormone closed-loop simulations that automate handling without input. However, challenges persist, such as of sensors and pumps, which can impair long-term accuracy due to protein adsorption and cellular overgrowth, and the need for periodic refills of drug reservoirs, often requiring minimally invasive procedures every few months. Commercialization timelines for advanced bi-hormonal and fully implantable are anticipated post-2027, with Beta Bionics targeting FDA clearance for a bi-hormonal iLet patch pump by late 2027, pending clinical validation, including a planned feasibility initiating in Q4 2025.

Technological approaches

Algorithmic and control strategies

Automated insulin delivery (AID) systems employ advanced algorithmic strategies to optimize insulin dosing while accommodating variability in glucose dynamics. Zone model predictive (zone-MPC) is a prominent approach that defines multi-target glucose ranges rather than a single setpoint, allowing for more flexible that prioritizes and comfort. For instance, zone-MPC can target daytime ranges of 80-110 mg/dL and overnight ranges of 80-100 mg/dL, enabling assertive corrections for without excessive risk of . In simulated evaluations for pregnant individuals with , a pregnancy-tuned zone-MPC increased time in the 63-140 mg/dL target by 10.3% compared to baseline, while reducing time above range by 10.7%. Fuzzy logic control addresses uncertainties in inputs such as exercise or unannounced meals by using rule-based reasoning to mimic expert without relying on precise physiological models. This method evaluates glucose levels and trends through linguistic rules (e.g., "if glucose is high and rising, then increase insulin moderately"), providing adaptable dosing in dynamic scenarios. Clinical testing of a controller in a closed-loop system demonstrated 76% time in the 70-200 mg/dL target range during inpatient studies with unannounced meals, successfully avoiding severe . Enhancements to these strategies often incorporate to mitigate noise in continuous glucose monitoring (CGM) data, improving prediction accuracy for real-time decisions. The estimates true glucose states by balancing process and measurement noise covariances, effectively smoothing signals while handling sensor delays or dropouts. In predictive pump shutoff algorithms for nocturnal prevention, Kalman-filtered CGM data enabled earlier insulin suspensions, preventing 73% of hypoglycemic events in trials. Glucose predictions in AID frequently use simplified linear models incorporating current levels, trends, and insulin-on-board (IOB) effects, such as: \text{Predicted glucose}(t) = \text{Current glucose} + B \times \text{trend} + C \times \text{IOB} where B scales the momentum from recent CGM readings (e.g., over 15 minutes), and C accounts for insulin activity via the insulin sensitivity factor. This formulation supports by forecasting effects over short horizons, updated every 5 minutes. Hybrid approaches combine rule-based elements with optimization techniques, such as integrating rules into proportional-integral-derivative () frameworks for refined meal handling. For example, if-then rules can trigger adjustments for carbohydrate intake, while PID ensures steady-state . An optimal PID-fuzzy controller has been shown to enhance blood glucose regulation in by balancing responsiveness and precision. As of 2025, enables real-time processing of CGM and activity data directly on wearable devices, reducing latency in algorithms for faster alerts and predictions. This decentralized approach achieves high accuracy in glycemic state classification, with up to 80% overall performance in detecting hypo- and . Safety is further bolstered by model mismatch detection, where augmented Kalman estimators identify discrepancies between predicted and observed glucose (e.g., due to parameter variability up to 30%), dynamically adjusting insulin bounds to prevent excursions. In simulations accounting for intrapatient variability, such interval safety layers maintained 92.7% normoglycemia with zero . Comparisons highlight PID's simplicity for reactive against MPC's foresight in anticipating glucose trajectories, with MPC often yielding superior outcomes in clinical metrics. In a randomized crossover , personalized MPC increased time in 70-180 mg/dL range to 74.4% versus 63.7% for PID, while maintaining comparable rates below 70 mg/dL (4.6% vs. 2.9%, not significant). MPC's predictive nature thus provides proactive hypo mitigation in varied conditions.

Physiological and bi-hormonal modeling

Physiological modeling in automated insulin delivery (AID) systems relies on mathematical representations of glucose-insulin interactions to simulate human metabolic dynamics, enabling the prediction and testing of insulin dosing strategies without immediate clinical risk. A foundational approach is the Bergman minimal model, developed in 1979, which captures essential glucose-insulin kinetics using a simplified set of differential equations derived from intravenous glucose tolerance test data. This model quantifies glucose effectiveness and insulin sensitivity, providing a baseline for understanding how insulin action influences blood glucose levels in . The core equation for glucose dynamics in the Bergman minimal model is: \frac{dG}{dt} = -p_1 (G - G_b) - X G + R_a(t) where G is glucose concentration, G_b is basal glucose, p_1 represents glucose effectiveness independent of insulin, X denotes remote insulin action, and R_a(t) is the rate of glucose appearance from meals or endogenous sources. An accompanying models insulin as \frac{dX}{dt} = -p_2 X + p_3 (I - I_b), where I is insulin, I_b is basal insulin, and p_2, p_3 relate to insulin sensitivity. These equations account for physiological delays in insulin action, such as the 15-20 minute onset time for subcutaneous insulin , allowing simulations to replicate real-world lags in glucose response. Bi-hormonal modeling extends these frameworks by incorporating to mimic counter-regulatory mechanisms, addressing limitations in insulin-only systems during . For instance, composite models integrate glucagon-glucose dynamics, where glucagon infusion promotes hepatic glucose production to aid recovery from low blood glucose, simulated through dual-chamber representations that predict hypo- and hyperglycemic excursions. The Hovorka model, adapted for bi-hormonal , uses three compartments for glucose, insulin, and glucagon action, estimating insulin sensitivity every 30 minutes and triggering glucagon delivery when glucose nears 95 mg/dL to prevent instability. Such models generate virtual patient cohorts for AID algorithm testing, as seen in the /Padova Type 1 Diabetes Simulator, which includes 100 profiles across age groups and has been FDA-accepted since 2008 as a substitute for preclinical animal trials. The simulator's 2013 update adds nonlinear responses and kinetics, enabling validation of control strategies against clinical data from 96 post-meal profiles in adults with . These tools facilitate personalized tuning by adjusting parameters like insulin sensitivity to individual variability, though limitations persist due to inter-patient differences in metabolic responses that models may not fully capture. Advantages include safe pre-clinical evaluation of bi-hormonal recovery from , reducing reliance on invasive testing while highlighting the need for ongoing refinements to handle physiological heterogeneity.

Integration of AI and machine learning

The integration of (AI) and (ML) into automated insulin delivery (AID) systems enhances adaptive and personalized control by processing real-time physiological data to optimize insulin dosing beyond traditional rule-based algorithms. , for instance, enable automated meal detection by analyzing patterns in continuous glucose monitoring (CGM) data, such as glucose rate of change and insulin availability, without requiring user announcements. A multioutput with fully connected layers has demonstrated a sensitivity of 83.3% for meal detection and a mean detection time of 25.9 minutes, reducing time above target glucose range by 10.8% compared to approaches. Reinforcement learning (RL), particularly deep RL, further advances long-term optimization in by treating glucose regulation as a dynamic problem, where agents learn to maximize rewards based on time in range (TIR) while adapting to inter- and intra-patient variability. Deep Q-networks and actor-critic methods, trained on simulators like UVA/Padova, improve TIR from baseline hybrid closed-loop levels of 65-80% by handling insulin action delays and perturbations, with clinical feasibility shown in (T1D) management. These techniques support fully closed-loop systems that minimize manual interventions, such as bolus calculations for unannounced meals. AI applications extend to predictive analytics for lifestyle factors, where ML models forecast the impact of exercise on glucose levels by integrating wearable data like metabolic expenditure, enabling proactive insulin adjustments to prevent hypoglycemia. Cloud-based platforms leverage AI for personalization, synthesizing CGM, historical insulin, and activity data to tailor dosing protocols in real time, as seen in decision support systems that enhance TIR while reducing hyperglycemia excursions. Examples include open-source AID communities, such as enhancements to OpenAPS and AndroidAPS, where developers incorporate ML for automated features like anomaly detection in glucose patterns, potentially reducing user input for meal boluses and basal rates. In development systems like Luna Diabetes AID explore automated insulin delivery during sleep, though integration remains in early stages. Ethical considerations in AI for AID emphasize bias mitigation through diverse training datasets and fairness audits to prevent disparities in glucose prediction accuracy across demographics, as underrepresented groups in data may face poorer model performance. Explainable AI techniques, such as LLM-based controllers, provide interpretable rationales for dosing decisions, fostering user trust and clinical adoption. Looking ahead, enables collaborative model improvement across users without sharing sensitive , as demonstrated in multiobjective frameworks achieving 76.54% TIR while eliminating in simulations, preserving and scaling personalization for diverse T1D populations.

Global initiatives and challenges

Regulatory approvals and access

, automated insulin delivery (AID) systems are classified as Class III medical devices by the (FDA), subjecting them to the most stringent premarket approval requirements due to their high-risk nature involving life-sustaining functions. The FDA expanded approvals to include adults with on insulin therapy in 2024, clearing the Omnipod 5 AID system for this population in August. The FDA's Devices has facilitated expedited reviews for innovative AID technologies by providing prioritized interactions and streamlined requirements, enabling faster market entry for devices demonstrating substantial clinical benefits. In November 2025, the FDA cleared the Mobi pump for use with smartphones, expanding options for users aged 2 and older. In , AID systems obtain market access through CE marking under the Medical Device Regulation (MDR), which certifies compliance with safety, health, and environmental protection standards. The MDR underwent updates in 2025 that intensified cybersecurity requirements, mandating harmonized standards like EN 18031-1 effective August 1 to address vulnerabilities in connected medical devices, including AID systems with wireless integrations. For instance, in July 2025, received CE Mark expansion for the MiniMed 780G system, allowing use in children as young as two years, during , and for . Regulatory progress varies in other regions; China's (NMPA) approved Medtronic's MiniMed 670G hybrid closed-loop system in 2023, with subsequent advancements like the MiniMed 780G gaining traction by 2024 through innovative pathways for imported technologies. In contrast, India's Central Drugs Standard Control Organization (CDSCO) has not yet approved domestic manufacturing of systems as of 2025, relying instead on import licenses for established devices, which streamlines entry for foreign-approved products via online portals but limits local innovation. Access to systems globally hinges on prescription requirements from qualified healthcare providers and mandatory programs to ensure safe use, as emphasized in clinical practice guidelines. The World Health Organization's broader frameworks, updated through 2025, advocate for adaptable technologies in low-resource settings, promoting simplified protocols to overcome infrastructure barriers like unreliable or supply chains. considerations have driven pediatric expansions, with approvals now standardizing AID use for children aged 2 and older across major regulators, reducing age-based disparities in care.

Cost, reimbursement, and equity issues

Automated insulin delivery (AID) systems represent a significant financial investment for users, with initial costs for devices such as the t:slim X2 or MiniMed 780G typically ranging from $4,000 to $10,000 in the as of 2025, depending on the model and without insurance coverage. Annual supplies, including infusion sets, reservoirs, and sensors, add $5,000 to $15,000, driven by ongoing consumable needs for hybrid closed-loop functionality. Emerging bi-hormonal systems in development may incur higher expenses due to glucagon costs, estimated at over $3.50 per mg based on 2015 data, potentially pushing annual costs 20-50% above insulin-only options. Reimbursement for AID varies by payer in the , where and cover approximately 80% of costs for individuals with meeting eligibility criteria, including external insulin pumps under Part B and related supplies. Private insurers provide more variable coverage, often requiring and limiting access to specific FDA-approved systems, though the (IRA) caps out-of-pocket insulin costs at $35 per month for Part D enrollees, a policy in effect since 2023. These policies aim to reduce financial barriers, yet gaps persist for non-insulin components like pumps, leading to average annual out-of-pocket expenses of $2,000-$5,000 even with coverage. Equity issues exacerbate access disparities, with low-income and rural populations in the experiencing AID adoption rates below 20%, compared to over 50% in urban, higher-income areas, as of 2022. In the global south, reliance on generic insulin analogs limits AID integration, as advanced systems remain unaffordable and unavailable in low-income countries where prevalence is rising but access to advanced technologies like AID remains very low, often under 5% based on insulin access proxies. Clinical trials for AID often underrepresent women, older adults, and racial minorities, perpetuating biases in system design and outcomes data. Initiatives to address these challenges include subsidies from non-profits like the T1D Exchange, which collaborates on access programs to provide financial aid for technology uptake among underserved patients. Manufacturing scale-ups in 2025 have begun reducing component costs by 10-15% through increased production of sensors and pumps, potentially broadening availability. However, high out-of-pocket expenses contribute to discontinuation rates of around 30% within the first year for AID users facing financial strain, underscoring the need for sustained policy reforms.

Clinical outcomes and future directions

Clinical outcomes from recent meta-analyses demonstrate the efficacy of automated insulin delivery () systems in improving glycemic control for individuals with . A 2025 network of outpatient randomized controlled trials reported HbA1c reductions of approximately 0.4-0.6% with advanced closed-loop systems compared to conventional sensor-augmented , alongside time in (TIR, 70-180 mg/dL) improvements of 20-25%. These systems also reduced time below (TBR <70 mg/dL) by about 3.5%, representing a relative risk reduction exceeding 50% in high-risk populations. Compared to manual insulin , achieves TIR levels of 70-75% versus 50-60%, establishing substantial clinical benefits in reducing and severe hypoglycemic events. In pediatric and adult populations with , AID systems show superior performance, with a 2025 systematic review and of randomized trials indicating consistent TIR gains and HbA1c improvements across age groups without increased risk. For , emerging evidence from insulin-treated outpatients highlights benefits, including TIR increases of about 9% and HbA1c reductions of 0.6% in randomized trials, though impacts remain neutral. These outcomes underscore AID's role in enhancing metabolic control, particularly for those with intensive insulin needs. Future directions in AID focus on achieving fully closed-loop systems by 2027, which would eliminate user inputs for meals and boluses through advanced algorithms. Innovations include ultra-long-acting insulin formulations to improve basal delivery stability and potential integration with stem cell-derived beta cells for near-curative effects in management. Key research gaps persist, including long-term data beyond five years to assess sustained and , as well as trials in diverse ethnic populations to address variability in glucose responses. Priorities for 2025 emphasize AI ethics in AID, such as mitigating and ensuring data privacy, alongside considerations for device manufacturing and energy use. Projections indicate widespread adoption, with the insulin pump market—encompassing systems—expected to reach $8.53 billion in the U.S. by 2030, reflecting over 50% penetration among patients due to proven outcomes and technological maturation. Cost reductions are anticipated through , potentially lowering initial system prices to around $2,000 as competition and manufacturing efficiencies advance.

References

  1. [1]
    The changing landscape of automated insulin delivery in the ... - NIH
    Automated insulin delivery systems, also known as closed-loop or 'artificial pancreas' systems, are transforming the management of type 1 diabetes.<|control11|><|separator|>
  2. [2]
    A Clinical Overview of Insulin Pump Therapy for the Management of ...
    An automated insulin delivery system consists of an insulin pump, a CGM device, and a control algorithm that calculates and dynamically adjusts insulin delivery ...
  3. [3]
    Automated insulin delivery: benefits, challenges, and ...
    Oct 6, 2022 · We provide a review of the current landscape of AID systems, with a particular focus on their safety. We conclude with a series of recommended targeted actions.
  4. [4]
    Automated Insulin Delivery Systems and Glucose Management in ...
    Sep 8, 2025 · This systematic review and meta-analysis investigates if, compared with standard care, automated insulin delivery systems used in an outpatient ...
  5. [5]
    Premarket Approval (PMA) - FDA
    Oct 27, 2025 · Premarket Approval (PMA) ; Guardian 4 Sensor · Sensor, Glucose, Invasive, Component of automated insulin delivery system · Medtronic MiniMed Inc.
  6. [6]
    FDA Roundup: February 28, 2025
    Feb 28, 2025 · On Monday, the FDA cleared Tandem Diabetes Care, Inc.'s Control-IQ+ technology, an interoperable automated glycemic controller (iAGC) that is a ...
  7. [7]
    [PDF] SUMMARY OF SAFETY AND EFFECTIVENESS DATA (SSED)
    PMA panel track supplement P160017/S118 was approved on April 18, 2025 and added compatibility to the Simplera Sync CGM as an alternative CGM component for the ...
  8. [8]
    [PDF] September 24, 2025 Tandem Diabetes Care, Inc. Miriam Chan ...
    Sep 24, 2025 · The t:slim X2 pump can be used for basal and bolus insulin delivery with or without a CGM or with any compatible interoperable automated dosing ...
  9. [9]
    Algorithms for Automated Insulin Delivery: An Overview - PMC - NIH
    With AID systems the insulin delivery approach is somewhat different, the insulin pump is activated multiple times to apply the insulin dose calculated on a “ ...
  10. [10]
    Consensus Recommendations for the Use of Automated Insulin ...
    AID systems utilize a sophisticated controller algorithm that continuously adjusts insulin delivery in response to real-time sensor glucose levels, residual ...
  11. [11]
    Closed-Loop Insulin Delivery Systems: Past, Present, and Future ...
    Jun 6, 2022 · The first closed-loop insulin delivery system was developed by Arnold Kadish in the early 1960s. Kadish's invention, which he termed a “ ...
  12. [12]
    Dr. Arnold Kadish: Insulin pump inventor and “Diabetes Dad”
    Jul 17, 2025 · Dr. Kadish's device was not only the first insulin pump prototype; it was also the first prototype of a closed-loop insulin delivery system.
  13. [13]
    Insulin pumps: from inception to the present and toward the future
    Mar 5, 2010 · Greater attention was directed to the first computer-controlled closed-loop insulin pump, named Biostator which was developed in 1974 (24–26) ( ...
  14. [14]
    Closed-Loop Artificial Pancreas Using Subcutaneous Glucose ...
    Indeed, an artificial pancreas (Biostator™) was developed in the early 1970s, approved by the Food and Drug Administration (FDA), and marketed by Miles Labs ( ...
  15. [15]
    Past, Present, and Future of Insulin Pump Therapy - NIH
    Dawn of Pump Therapy. Continuous subcutaneous insulin infusion (CSII) pump therapy was introduced to treat patients with type 1 diabetes in the late 1970's (1,2) ...
  16. [16]
    Medtronic, Inc. Receives FDA Approval For Guardian(R) REAL-Time ...
    Jul 17, 2006 · Medtronic, Inc. Receives FDA Approval For Guardian(R) REAL-Time Continuous Glucose Monitoring System. July 17, 2006 |. 4 min ...
  17. [17]
    Artificial Pancreas: Past, Present, Future | Diabetes
    Oct 17, 2011 · The artificial pancreas (AP), known as closed-loop control of blood glucose in diabetes, is a system combining a glucose sensor, a control algorithm, and an ...
  18. [18]
    Medtronic Gains Approval of First Artificial Pancreas Device System ...
    Sep 27, 2013 · Threshold Suspend automation automatically stops the delivery of insulin if glucose levels reach a threshold, which can be set by a healthcare ...
  19. [19]
    Medtronic launches MiniMed 640G, gets closer to artificial pancreas +
    Jan 22, 2015 · The system both automatically suspends insulin delivery when sensor glucose levels are predicted to approach a low limit and resume insulin ...<|control11|><|separator|>
  20. [20]
    OpenAPS Overview and Project History - Read the Docs
    The first public example of this was the #DIYPS closed loop system, created in their spare time by @DanaMLewis and @ScottLeibrand in the fall of 2013 based on ...Missing: launch | Show results with:launch
  21. [21]
    Medtronic Receives FDA Approval for World's First Hybrid Closed ...
    Sep 28, 2016 · The system is approved for the treatment of people with type 1 diabetes fourteen years of age and older with ongoing studies to expand the ...
  22. [22]
    Insulet's Omnipod 5 Cleared by FDA - AJMC
    Jan 31, 2022 · Insulet's Omnipod 5 Cleared by FDA ... The FDA has cleared the first tubeless automated insulin delivery system with a smartphone app control.
  23. [23]
    [PDF] Automated Insulin Delivery Systems
    Jun 10, 2025 · In August 2024, the FDA extended the Omnipod 5 system's approval for adults with type 2 diabetes, following its 2022 clearance for children and ...
  24. [24]
    FDA Clears First Device to Enable Automated Insulin Dosing for ...
    Aug 26, 2024 · The US Food and Drug Administration expanded the indications of the Insulet SmartAdjust technology, an interoperable automated glycemic controller.Missing: 2023 2025
  25. [25]
    Tandem Diabetes Care Announces FDA Clearance of Control-IQ+ ...
    Feb 25, 2025 · Feb 25, 2025. Tandem Diabetes Care Announces FDA Clearance of Control-IQ+ Automated Insulin Delivery Technology for People with Type 2 Diabetes.
  26. [26]
    FDA Approves Year-Long Continuous Glucose Monitoring Sensor
    Sep 19, 2024 · The US Food and Drug Administration (FDA) has approved Eversense 365, the first and only continuous glucose monitoring (CGM) system designed to function for an ...
  27. [27]
    OpenAPS DIY Automated Insulin Delivery Users Report 81% Time ...
    OpenAPS, the do-it-yourself (DIY) automated insulin delivery system created by Ben West, Dana Lewis, and Scott Leibrand, now has over 87 users worldwide and ...Missing: launch | Show results with:launch
  28. [28]
    Insulin pumps: MedlinePlus Medical Encyclopedia
    Jul 21, 2024 · Patch pumps are worn directly on the body with the reservoir and tubes inside a small case. A separate wireless device programs insulin ...
  29. [29]
    Patch Pumps: Are They All the Same? - PMC - NIH
    Aug 22, 2018 · In general, patch pumps are smaller, more discrete, easier to use, and often cheaper than conventional insulin pumps.
  30. [30]
    A Comparative Pulse Accuracy Study of Two Commercially ... - NIH
    Unlike durable pumps, patch pumps are free of infusion sets as the cannula and delivery system are built into the device. They are worn directly on the body and ...
  31. [31]
    Evolution of Insulin Delivery Devices: From Syringes, Pens, and ...
    May 14, 2020 · This review discusses the evolution of syringes, disposable, durable pens and connected pens, needles, tethered and patch insulin pumps, bionic pancreas.
  32. [32]
    Advancements in Insulin Pumps: A Comprehensive Exploration of ...
    This research explores the progression of insulin pumps, following their advancement from initial ideas to advanced contemporary systems.
  33. [33]
    Water-Resistance Rating on the Tandem Mobi System
    The Tandem Mobi insulin pump is water-resistant to a depth of 8 feet (2.4 meters) for up to two hours (IP28 rating) when the cartridge is loaded.
  34. [34]
    What is Omnipod? | Tubeless Insulin Pump Therapy
    *The Pod has an IP28 rating for up to 25 feet for 60 minutes. The Personal Diabetes Manager and Controller are not waterproof.
  35. [35]
    Can Fiasp (insulin aspart) be used in an insulin pump? - Dr.Oracle
    May 2, 2025 · A study published in 2018 found that Fiasp was safe and effective for use in insulin pumps, with no cases of infusion set plugging reported 3. A ...Missing: waterproofing IP28 smartphone<|separator|>
  36. [36]
    Evolution of Diabetes Insulin Delivery Devices - PMC - NIH
    The first manufactured insulin pump was introduced in the 1970s, while the first manufactured insulin pen, the NovoPen® (Novo Nordisk), was introduced in 1985.
  37. [37]
    The development and evolution of insulin pumps - PubMed
    May 25, 2023 · This review presents a synopsis of the development and evolution of insulin pumps, starting with the earliest technologies available.<|control11|><|separator|>
  38. [38]
    [PDF] Insulin Pump Comparison Table - Offspring Health
    Weight. 95.7g. 112g. 83g. 26g. Tubing. 45cm-110cm. 60-110cm. 45cm-110cm. Tube Free. Cannula. 6mm-17mm. 6mm-13mm. 6mm-9mm. 9mm with 6.5mm under the skin at 50 ...
  39. [39]
    Automated Insulin Delivery Algorithms | Diabetes Spectrum
    Aug 1, 2019 · Randomized crossover comparison of personalized MPC and PID control algorithms for the artificial pancreas . Diabetes Care. 2016. ;. 39. : 1135.
  40. [40]
    Randomized Crossover Comparison of Personalized MPC and PID ...
    We conclude that the MPC controller matched or outperformed the PID controller on all clinical metrics of glucose control in this study, although both ...Missing: papers | Show results with:papers
  41. [41]
    Effectiveness and safety of a model predictive control (MPC ...
    Dec 9, 2022 · The purpose of this study was to assess the effectiveness and safety of a model predictive control (MPC) algorithm for an artificial pancreas system in ...
  42. [42]
    Consensus Recommendations for the Use of Automated Insulin ...
    Consider recommending appropriate AID systems to people with other types of diabetes treated with intensive insulin therapy (multiple daily injections or pump ...Missing: prerequisites | Show results with:prerequisites
  43. [43]
    Low Settings - MiniMed™ 770G System Support - Medtronic Diabetes
    Note, insulin delivery will not be suspended if you are more than 70 mg/dL above your low limit. After a Suspend before low event occurs, there is a period ...Missing: 200%
  44. [44]
    [PDF] SYSTEM USER GUIDE - Medtronic Diabetes
    The Max basal rate is the maximum amount of basal insulin that the pump can deliver per hour. Set the Max basal rate as indicated by a healthcare professional.
  45. [45]
    New UVA Clinical Trial Explores AI-Powered Insulin Delivery for ...
    Feb 5, 2025 · A new clinical trial at UVA is aiming to simplify diabetes management by testing an innovative AI-powered device designed to improve automated insulin delivery.
  46. [46]
    Enabling fully automated insulin delivery through meal detection ...
    Mar 13, 2023 · The RAP system includes a neural network model to automatically detect meals and deliver a recommended meal insulin dose. The meal detection ...
  47. [47]
    CGM & Time in Range - American Diabetes Association
    What is time in range? Time in range is the amount of time you spend in the target blood glucose (blood sugar) range—between 70 and 180 mg/dL for most people.Missing: automated | Show results with:automated
  48. [48]
    Premarket Approval (PMA) - FDA
    THE MINIMED 530G SYSTEM CAN BE PROGRAMMED TO AUTOMATICALLY SUSPEND DELIVERY OF INSULIN WHEN THE SENSOR GLUCOSE VALUE FALLS BELOW A PREDEFINED THRESHOLD VALUE.
  49. [49]
    Threshold-based insulin-pump interruption for reduction ... - PubMed
    Jul 18, 2013 · This study showed that over a 3-month period the use of sensor-augmented insulin-pump therapy with the threshold-suspend feature reduced ...
  50. [50]
    Predictive Low-Glucose Suspend Reduces Hypoglycemia in Adults ...
    Oct 1, 2018 · Threshold suspend technology allows for automated suspension of insulin delivery when the sensor glucose falls below a predefined lower limit.
  51. [51]
    Prevention of Hypoglycemia With Predictive Low Glucose Insulin ...
    Mar 28, 2017 · To investigate whether predictive low glucose management (PLGM) of the MiniMed 640G system significantly reduces the rate of hypoglycemia ...
  52. [52]
    Retrospective Analysis of the Real-World Use of the Threshold ...
    May 1, 2015 · Patient-days in which the TS feature was enabled, compared with patient-days in which it was not, had 69% fewer SG values ≤50 mg/dL (0.64% vs.<|control11|><|separator|>
  53. [53]
    MiniMed 780G System | Medtronic (CA)
    The MiniMed™ 780G system lets you select your glucose target (5.5, 6.1, or 6.7 mmol/L). Self-adjusts insulin and corrects highs every 5 minutes* to help keep ...
  54. [54]
    MiniMed 780G™ advanced hybrid closed-loop system performance ...
    Oct 17, 2023 · MiniMed™ 780G system performance among different age groups​​ TIR 70–180 mg/dL was increased in all age groups post-AHCL compared with pre-AHCL. ...
  55. [55]
    A Closed-Loop Artificial Pancreas Using Model Predictive Control ...
    The MPC was integrated with the IOB algorithm to adjust control outputs based on insulin on board.
  56. [56]
    Zone-MPC Automated Insulin Delivery Algorithm Tuned ... - Frontiers
    Zone-MPC is an optimization-based algorithm that uses model predictions to optimize insulin injections in a way that blood glucose levels are kept within a ...
  57. [57]
    7. Diabetes Technology: Standards of Care in Diabetes—2025
    Dec 9, 2024 · Diabetes technology now includes automated insulin delivery (AID) systems that use CGM-informed algorithms to modulate insulin delivery. It also ...
  58. [58]
    ATTD 2025 Top 10 Hits - The Glucose Never Lies®
    Top hits at ATTD 2025 included Control-IQ+ for type 2 diabetes, fully closed-loop systems, early AID initiation, and CGM-guided exercise.
  59. [59]
    Glucose Outcomes with the In-Home Use of a Hybrid Closed-Loop ...
    Table 2 also shows that HbA1c levels fell from a mean of 7.7% ± 0.8% at baseline to 7.1% ± 0.6% at the end of the study phase, for adolescents (P < 0.001) and ...<|control11|><|separator|>
  60. [60]
    Trial of Hybrid Closed-Loop Control in Young Children with Type 1 ...
    Mar 15, 2023 · Closed-loop control systems of insulin delivery may improve glycemic outcomes in young children with type 1 diabetes.
  61. [61]
    FDA OKs automated insulin device for young children | AAP News
    Sep 4, 2020 · Medtronic's MiniMed 770G System is a hybrid closed loop diabetes ... It will be available for patients ages 2 years and older and is the first of ...
  62. [62]
    Closed-Loop Insulin Delivery Systems: Past, Present, and Future ...
    Jun 5, 2022 · The first closed-loop insulin delivery system was developed by Arnold Kadish in the early 1960s. Kadish's invention, which he termed a “ ...
  63. [63]
    Fully Closed Loop: Automated Insulin Delivery Takes the Next Step
    Jan 27, 2025 · Fully closed loop AID systems aim to simplify diabetes management by eliminating the need to announce meals, carb count, and manually bolus insulin.
  64. [64]
    Deep Reinforcement Learning for Automated Insulin Delivery Systems
    While model predictive control provides a flexible framework for developing AIDs control algorithms, models that capture inter- and intra-patient variability ...1. Introduction · 2. Overview Of Drl · 4. Challenges To Be...
  65. [65]
    Role of automated insulin delivery in managing insulin-treated ... - NIH
    Oct 15, 2025 · AID systems benefit people with type 1 diabetes (T1D), demonstrating increased time spent in the target glucose range, reduced HbA1c levels, ...
  66. [66]
    Successful use of a fully closed-loop insulin delivery system in an ...
    Jun 30, 2025 · 2, Table 1). The CamAPS HX FCL maintained glucose levels in the target range 89% of the time, with no hypo- or hyperglycemic episodes. The time ...
  67. [67]
    The challenges of Achieving Postprandial Glucose Control using ...
    The greatest challenges remain in regards to the pharmacokinetic and –dynamic profiles of available rapid insulins as well as sensor accuracy and lag-time. New ...
  68. [68]
    Diabetes Technology Updates – Fall 2024 - Diabetotech
    Nov 21, 2024 · Hardware Updates. Upcoming Insulin Pumps: 8-Series Pump: Smaller, tubed pump controllable via new Android and iOS apps.Missing: waterproofing IP28
  69. [69]
    Fully closed-loop control with ultra-rapid versus standard insulin lispro
    Aug 15, 2025 · URIL in a fully closed-loop setting showed a clinically meaningful trend towards improved TIR and reduced hyperglycaemia compared to IL.
  70. [70]
    ViCentra to Bring Smartphone-Based Closed Loop Therapy to ...
    Aug 12, 2025 · Kaleido patch pump system with Diabeloop's DBLG2 algorithm and Dexcom G7 CGM to launch in Germany and the Netherlands in early 2026, ...
  71. [71]
    MiniMed 780G System – P160017/S091 - FDA
    May 17, 2023 · Approval Date: April 21, 2023. Approval Letter: Approval Order. What is it? The Medtronic MiniMed 780G System is an automated insulin delivery ...
  72. [72]
    MiniMed™ 780G Insulin Pump System - Medtronic Diabetes
    The pump dimensions in inches are approximately 2.1 width x 3.78 length x 0.96 depth. The weight of the pump is approximately 3 ounces. Warranty. Insulin pump: ...Compare insulin pumps · El Sistema de Bomba MiniMed... · Infusion SetsMissing: 50g | Show results with:50g
  73. [73]
    FDA approves hybrid closed-loop system for type 2 diabetes - Healio
    Sep 2, 2025 · The FDA approved an expanded indication for the MiniMed 780G (Medtronic), allowing the system to be used by adults aged 18 years and older ...
  74. [74]
    Studies show promising results for individuals with type 2 diabetes ...
    Jun 20, 2025 · Results showed those using the MiniMed™ 780G system with SmartGuard™ achieved a 0.6% lower HbA1C and 9.9% higher Time in Range when compared to ...Missing: 2024 | Show results with:2024
  75. [75]
    Medtronic 780G - DiabetesWise Pro
    Widely covered for insulin-dependent type 1 and type 2. Pump can be provided by pharmacy or DME. Price range; $0-$8,574 to start and $0-$300/Month. Price range ...
  76. [76]
    Real-World User and Clinician Perspective and Experience with ...
    Jun 6, 2023 · Studies conducted on users of the MiniMed™ 780G system have demonstrated improved outcomes, such as a reduction in the glucose management ...
  77. [77]
    New MiniMed™ 780G system data demonstrates ability to address ...
    Jun 21, 2024 · New MiniMed™ 780G system data demonstrates ability to address persistent blood sugar challenges for people with type 1 diabetes ; 70-140 mg/dL.Missing: studies hypo
  78. [78]
    Tandem Diabetes Care Announces FDA Clearance of the t:slim X2 ...
    Dec 13, 2019 · The update is expected to be available by the end of January 2020 , and new pumps with Control-IQ technology will begin shipping to customers in ...
  79. [79]
    Tandem Control-IQ+: How It Works, Features, and Latest Updates
    Dec 3, 2024 · Sleep activity mode: Users can set programmed sleep schedules with a target range of 112.5–120 mg/dL (or you can enter this mode manually). The ...
  80. [80]
    Quarter 2 Diabetes Technology Update – August 2025 - Diabetotech
    Aug 22, 2025 · Here's how the available closed-loop systems might look in 3-5 years from now: While most closed-loop systems today still require tubing and ...
  81. [81]
    [PDF] Sleep Activity - Tandem Diabetes
    The t:slim X2 insulin pump with Control-IQ technology uses CGM values to predict glucose levels 30 minutes ahead and automati- cally adjust insulin every 5 ...
  82. [82]
    Insulin Pumps l t:slim X2 Control -IQ l danatech - adces
    The t:slim X2 uses Control-IQ to automatically adjust insulin based on glucose, has activity settings, automatic boluses, and a rechargeable battery.
  83. [83]
    Daytime and nighttime glycemic control with control-IQ technology ...
    Aug 12, 2025 · Our meta-analysis indicated that Control IQ favored Time above range TAR > 180 mg/dl outcome (MD -10.79%, CI 95% (-13.10 to -8.49), P < 0.00001) ...
  84. [84]
    t:slim X2 Insulin Pump With Control-IQ - ADA Consumer Guide
    Pump Size: 3.13 x 2 x 0.6 in. Pump Weight: 3.95 oz. with battery and full reservoir. Reservoir Size: 300-unit reservoir. Basal Range: From 0.1 to 15 units per ...Missing: 200-300 U occlusion detection wireless
  85. [85]
    Tandem t:slim X2: How It Works, Features, and the Latest Updates
    Jun 20, 2025 · Without insurance, the t:slim X2 costs $4,000. Tandem says the average customer with insurance pays less than $50 monthly, including supplies.
  86. [86]
    Insulin Pump Cost & Coverage | Tandem Diabetes Care
    This includes the cost of a t:slim X2 insulin pump or the cost of a Tandem Mobi system. Plus, Tandem pumps are covered through many Medicare Advantage plans.
  87. [87]
    Insulet Announces FDA Clearance of Omnipod® 5 for Children ...
    Aug 22, 2022 · Insulet Announces FDA Clearance of Omnipod® 5 for Children Aged Two Years and Older with Type 1 Diabetes. August 22, 2022. Download (opens in ...
  88. [88]
    [PDF] K203774.pdf - accessdata.fda.gov
    Jan 27, 2022 · The Omnipod 5 iAGC (SmartAdjust technology) is a software-only medical device intended for the management of type 1 diabetes mellitus. The ...
  89. [89]
    Omnipod® 5 Automated Insulin Delivery System is now FDA-cleared ...
    Aug 26, 2024 · Omnipod 5 is now indicated for use by people with type 2 diabetes (ages 18 years and older) in the US, making it the first and only AID system FDA-cleared.
  90. [90]
    Simplify Life with Omnipod® 5
    The Omnipod 5 Automated Insulin Delivery System is indicated for use by individuals with type 1 diabetes mellitus in persons 2 years of age and older and type 2 ...The Omnipod® 5 App · About Omnipod® 5 · CGM Sensor Integration
  91. [91]
    Insulin Pumps l Omnipod 5 l danatech - adces
    Each Pod lasts up to 3 days (72 hours) ... Changes target glucose to 150 mg/dL and reduces automated insulin delivery for duration specified, 1-24 hours.Missing: wear 110
  92. [92]
    Omnipod 5 - ADA Consumer Guide - American Diabetes Association
    The waterproof Pods can provide up to 72 hours of continuous insulin delivery. Features. Combo pump-CGM; No Tubing; Auto Basal Insulin Suspension; Auto Basal ...Missing: wear 110 mg/ dL app
  93. [93]
    Healthcare provider | Omnipod® 5 Real World Evidence
    The real-world evidence showed that Omnipod® 5 users achieved nearly 70% Time in Range with only 1.12% of time spent in hypoglycemia at an average target of 110 ...Highlights At A Glance · Adult Vs Pediatric Cohorts · Pediatric Cohort Results
  94. [94]
    The Omnipod® 5 App
    It sends commands to the Pod, displays glucose and insulin information from the Pod, and can be used to give meal and correction boluses.Missing: waterproof 72- hour 110
  95. [95]
    Omnipod 5: How It Works, Features, Latest Updates - diaTribe.org
    The Omnipod 5 automated insulin delivery system includes a tubeless insulin pump, Dexcom continuous glucose monitor, and an app that works on a controller or ...Missing: waterproof 72- hour wear
  96. [96]
    Impact of Omnipod 5 automated insulin delivery on continuous ...
    Sep 9, 2025 · Results: Omnipod 5 use was associated with improved TIR (+16%, p < 0.001) and a reduction in HbA1c (-3 mmol/mol, p < 0.001). The greatest ...Missing: performance | Show results with:performance
  97. [97]
    Real-World Evidence of Omnipod® 5 Automated Insulin Delivery ...
    Feb 16, 2024 · Median percentage of time in range (TIR; 70–180 mg/dL) was 68.8%, 61.3%, and 53.6% for users with average glucose targets of 110, 120, and 130– ...
  98. [98]
    Omnipod® 5 Clinical Outcomes
    Icon with an upwards arrow and the words "22% MORE TIR" inside in. Increased Time in Range by an average of 22% (over 5 hours per day). Lower A1C with a ...Omnipod® 5 Clinical... · 80% Time In Range · Omnipod 5 Secure-T2d TrialMissing: studies | Show results with:studies
  99. [99]
    Practical considerations for using the Omnipod® 5 Automated ...
    Apr 2, 2025 · Data from clinical trials and real world observational studies have shown that AID systems increase time in range (TIR), reduce time below range ...
  100. [100]
    Insulet Announces Omnipod® 5 System is Now Compatible with ...
    Nov 20, 2024 · The Omnipod 5 Automated Insulin Delivery (AID) System is now compatible with Abbott's FreeStyle Libre 2 Plus continuous glucose monitoring (CGM) sensor in the ...Missing: 2025 reservoir
  101. [101]
    The Most Exciting Diabetes Technology Updates: Summer 2025 ...
    Jul 3, 2025 · These innovations represent the cutting edge of diabetes technology, offering more personalized and user-friendly insulin delivery options.
  102. [102]
    Clinical Implementation of the Omnipod 5 Automated Insulin ... - NIH
    The Omnipod 5 System's Activity feature is intended to reduce the amount of insulin delivered during exercise or at other times when reduced insulin delivery ...
  103. [103]
    Adhesion Guide: Keeping your Pod in place - Omnipod
    Common challenges:​​ Damp skin: Dampness gets in the way of adhesion. Towel off and allow your site to air dry thoroughly; do not blow on it. Body hair: Body ...
  104. [104]
    https://www.omnipod.com/current-podders/resources/adhesion-guide
  105. [105]
    FDA Clears New Insulin Pump and Algorithm-Based Software to ...
    May 19, 2023 · The iLet Bionic Pancreas uses an adaptive closed-loop algorithm that is initialized only with a user's body weight and requires no additional ...
  106. [106]
    Beta Bionics Announces FDA Clearance and Commercialization of ...
    May 22, 2023 · Beta Bionics Announces FDA Clearance and Commercialization of the iLet Bionic Pancreas | Mon, 05/22/2023 - 08:00.
  107. [107]
    FDA Approves Beta Bionics' Insulin-Only Device. What about Dual ...
    Jun 4, 2023 · Last week, the FDA granted Beta Bionics approval to go to market with its “iLet® ACE Pump” and related dosing software.
  108. [108]
    Introducing the iLet Bionic Pancreas
    Apr 7, 2023 · The iLet Bionic Pancreas is an automated insulin delivery system that reduces the need to make decisions about your diabetes management.iLet for Adults · iLet for Children · iLet Reviews · Bionic Circle AppMissing: dual hormone glucagon
  109. [109]
    Multicenter, Randomized Trial of a Bionic Pancreas in Type 1 Diabetes
    Sep 28, 2022 · The difference in the percentage of time that the glucose level was in the target range of 70 to 180 mg per deciliter was 11 percentage points ...
  110. [110]
    iLet Bionic Pancreas - adces
    The iLet Bionic Pancreas System is a closed-loop system that delivers insulin based on input from an integrated continuous glucose monitor (iCGM)<|control11|><|separator|>
  111. [111]
    Performance of the Insulin-Only iLet Bionic Pancreas and the ... - NIH
    The iLet achieved a CGM capture rate of ≥80% during the insulin-only (90.7%) and bihormonal (88.7%) periods.
  112. [112]
    Real-world evidence from year one of iLet commercial availability
    Better Results – The iLet Bionic Pancreas System required much less effort from patients, with improved results consistent across high and low levels of patient ...Missing: performance | Show results with:performance
  113. [113]
    Beta Bionics Reports Third Quarter 2025 Financial Results and ...
    Oct 28, 2025 · On September 29, 2025, Beta Bionics received Special 510(k) clearance for iLet feature updates. ... The iLet Bionic Pancreas is the first FDA- ...
  114. [114]
    Sequel Med Tech and Senseonics Integrate Technologies to Create ...
    Apr 29, 2025 · Through this collaboration, the twiist™ Automated Insulin Delivery (AID) System will become the first AID system compatible with the Senseonics ...
  115. [115]
    Sequel Med Tech and Senseonics Integrate Technologies to
    Apr 29, 2025 · The agreement between Sequel and Senseonics will provide individuals with type 1 diabetes the option of a one-year CGM that integrates with the twiist AID ...
  116. [116]
    Sequel, Senseonics to integrate year-long CGM into AID system
    Apr 29, 2025 · The companies plan to integrate Sequel's twiist automated insulin delivery system with the Senseonics Eversense 365 continuous glucose monitor (CGM).
  117. [117]
    twiist: Home
    The twiist AID System offers 3 ways to control insulin delivery. Through your iPhone, your connected Apple watch or with the on-pump bolus button.Missing: Trio | Show results with:Trio
  118. [118]
    twiist - adces
    The twiist™ AID System is designed for individuals with type 1 diabetes ages 6 and older. It automates insulin delivery based on real-time continuous ...
  119. [119]
    Learn How To Calibrate Glucose Monitoring System for Accurate Data
    The Eversense E3 CGM system needs twice daily calibrations for the first 21 days, then primarily once a day using fingerstick readings. The system prompts the ...Missing: twiist TIR
  120. [120]
    Senseonics, Sequel partner to use 1-year CGM in automated insulin ...
    Apr 30, 2025 · The partnership extends the compatibility of Sequel's Twiist system to allow people with Type 1 diabetes to pair the device with Senseonics' Eversense 365 CGM.
  121. [121]
    Sequel and Senseonics Join Forces to Enhance Diabetes ...
    Apr 29, 2025 · Sequel Med Tech, LLC, and Senseonics Holdings, Inc., have announced a commercial development agreement to integrate advanced diabetes technologies.
  122. [122]
    Understanding CGM Cost: Insurance Coverage ... - Eversense
    Experience the Eversense 365 CGM system for as low as $199 for a full year. This includes the cost of both CGM sensor and transmitter.
  123. [123]
    FAQ - twiist
    The twiist AID System recently received FDA clearance. It's designed for people aged 6 and up with type 1 diabetes. To learn more, visit sequelmedtech.com and ...
  124. [124]
    Introducing the #OpenAPS project
    Feb 4, 2015 · The Open Artificial Pancreas System (#OpenAPS) is an open and transparent effort to make safe and effective basic Artificial Pancreas System ...Missing: launch | Show results with:launch
  125. [125]
    OpenAPS.org – #WeAreNotWaiting to reduce the burden of Type 1 ...
    There are features in the OpenAPS algorithm to help if BGs rise faster or drop faster than expected during or after a meal, but they don't replace a regular ...Open Artificial Pancreas... · Frequently Asked Questions · OpenAPS Outcomes
  126. [126]
    Welcome to OpenAPS's documentation! — OpenAPS 0.0.0 ...
    This documentation supports a self-driven Do-It-Yourself (DIY) implementation of an artificial pancreas based on the OpenAPS reference design.
  127. [127]
    OpenAPS Reference Design
    Sep 20, 2021 · The first such oref0 design constraint is that OpenAPS oref0 cannot issue insulin boluses. This is a key safety feature, because insulin pumps, ...Designing Openaps For... · Openaps Design Details · AlgorithmsMissing: MPC | Show results with:MPC
  128. [128]
    Introducing oref1 and super-microboluses (SMB) (and what it means ...
    Apr 30, 2017 · We have updated the OpenAPS Reference Design to reflect the differences between oref0 and the oref1 features. OpenAPS documentation about ...Missing: MPC | Show results with:MPC
  129. [129]
    Canadian experts speak out on DIY artificial pancreases
    Oct 10, 2023 · However, it is estimated that there are between 10,000 and 30,000 users worldwide, including around 2,500 Canadians, according to data collected ...
  130. [130]
    (PDF) Glycaemic control in individuals with type 1 diabetes using an ...
    May 25, 2025 · We analyzed continuous glucose monitoring (CGM) records of 80 OpenAPS users with type 1 diabetes (T1D). A total of 19 495 days (53.4 years) of ...<|separator|>
  131. [131]
    Open-source Artificial Pancreas Systems Are Safe and Effective ...
    Our aim in this study was to determine the safety, glycemia, and quality of life (QoL) associated with in-clinic installation and management of supported open- ...
  132. [132]
    Data Commons - OpenAPS.org
    Mar 27, 2023 · Use the Nightscout Data Transfer app to upload your Nightscout Data into Open Humans. (Nightscout URL is not stored in any way, so your ...
  133. [133]
    OpenAPS Data Commons - Open Humans
    The OpenAPS Data Commons was created to enable a simple way to share data sets from the community, both with traditional researchers who will create traditional ...
  134. [134]
    Open-source automated insulin delivery systems for the ... - NIH
    The three main open-source AID systems include openAPS, Loop and AndroidAPS. Loop is an iOS application that was developed in 2015 by Nate Racklyeft and others.
  135. [135]
    Compatible Pump - LoopDocs - GitHub Pages
    There are a number of Medtronic insulin pumps manufactured between 2006 – 2012 which are compatible with the Loop app.Compatible Pump · Pumps Compatible with the... · Omnipod PumpsMissing: AID | Show results with:AID
  136. [136]
    Meal Entries - LoopDocs - GitHub Pages
    Loop calculates how many carbs have been absorbed (regardless of how many you entered) based on your BG pattern and your settings. You can watch the progression ...Missing: AID | Show results with:AID
  137. [137]
    Quick Start Guide | Loop and Learn
    Quick Start Guide. This guide assumes that you're planning to Loop with a Dexcom G6, G7, ONE, or ONE+ and Omnipod DASH. When you complete this 8-day process ...
  138. [138]
    Dexcom CGM Options - Loop and Learn
    This page provides information on the four official Dexcom CGM options, as well as the Anubis transmitter which many Loopers use in place of the G6.
  139. [139]
    Improved Glycemia and Quality of Life Among Loop Users
    Oct 24, 2022 · During Loop use, the participants had median (IQR) values of 7.1% (6.5%-7.5%), 54 mmol (48-58) for HbA1c and 76.5% (64.6%-81.9%) for time in ...<|control11|><|separator|>
  140. [140]
    A Real-World Prospective Study of the Safety and Effectiveness of ...
    Objective: To evaluate the safety and effectiveness of the Loop Do-It-Yourself automated insulin delivery system. Research Design and Methods: A prospective ...
  141. [141]
    Qualitative Study of User Experiences with Loop, an Open-Source ...
    Loop is an open-source automated insulin delivery (AID) system, used by more than 9,000 people with type 1 diabetes. Understanding the pros and cons of Loop use ...
  142. [142]
    Riley Link
    GetRileyLink Order Site ; OrangeLink Pro. $185 Add to cart ; 850 mAh Polymer Lithium Ion Battery. $25 Add to cart ; RileyLink/OrangeLink Repair and Testing Service.RileyLink Compatible... · OrangeLink Pro · Donate to GetRileyLink.org · Contact Us<|control11|><|separator|>
  143. [143]
    Starting Loop: Cost | Loop and Learn
    The “Hard” Costs: Money, Required Expenses: A radio-link, Allows the phone and pump to communicate. Extremely Helpful Expenses: A computer.Missing: hardware | Show results with:hardware
  144. [144]
    Introduction to APS and AAPS — AndroidAPS 3.3 documentation
    Android APS (AAPS) is an open source app for people living with insulin-dependent diabetes. It is an artificial pancreas system (APS) which runs on Android ...
  145. [145]
    Release notes — AndroidAPS 3.3 documentation - Read the Docs
    Tip - if you do not want to lose your AAPS history ALWAYS do an UPDATE and NOT an UNINSTALL/INSTALL. As a precaution, back up your current AAPS settings and old ...
  146. [146]
    How to translate strings for the AAPS app or the documentation
    If you want to translate an individual file please search for the file via search dialog or tree structure and click on the filename to start the translation ...Missing: base | Show results with:base
  147. [147]
    Comparison of Control‐IQ and open‐source AndroidAPS automated ...
    Sep 25, 2023 · A real-world prospective study of the safety and effectiveness of the loop open source automated insulin delivery system. Diab Technol ...2 Research Design And... · 3 Results · 4 Discussion
  148. [148]
    Are all HCL systems the same? long term outcomes of three HCL ...
    Oct 15, 2023 · All of the systems met the recommended criteria for time in range (78% in AAPS, 76% in 780G, and 75% in Control-IQ users). CwD using AAPS spent ...
  149. [149]
    Safety and glycemic outcomes of do-it-yourself AndroidAPS hybrid ...
    Apr 5, 2021 · The secondary outcomes included: average sensor glycemia (SG), percentage of time in range (TIR) 70–180 mg/dl, 70–140 mg/dl, time below 70 mg/ ...
  150. [150]
    Discover the AP - Inreda Diabetic
    The Inreda AP is an automatic system (closed loop) and independently regulates the blood glucose level by administering insulin and glucagon.Missing: automated company mark 2022 US 2025
  151. [151]
    Ultrarapid Insulin Administered by a Bihormonal Closed Loop ...
    Inreda Diabetic B.V. (Goor, The Netherlands) developed a bi-hormonal reactive closed loop system to automate glucose regulation (artificial pancreas; AP) in ...Missing: 2025 | Show results with:2025
  152. [152]
    https://www.inredadiabetic.nl/en/discover-the-ap/
  153. [153]
    Artificial pancreas from Dutch Inreda Diabetic likely to be on the ...
    May 25, 2022 · Inreda obtained the CE marking in 2020, which in principle means that the company is already authorized to market the artificial pancreas.
  154. [154]
    MDR CE certificate for Inreda AP
    On the 16th of December 2023, Inreda Diabetic BV received a CE certificate for the Inreda AP® as evidence that it complies with the new European regulation ...Missing: 2022 | Show results with:2022
  155. [155]
    What we do - Inreda Diabetic
    Fully automatic. Our device regulates your glucose level completely automatically, without having to ask you to enter carbs values, calculating and ...Missing: features automated input target 110 mg/ dL
  156. [156]
    Closed-loop systems: recent advancements and lived experiences
    Oct 10, 2024 · In this review, we summarize the key clinical efficacy and safety evidence for hybrid closed-loop systems, and the lived experience of users with type 1 ...
  157. [157]
    Research Gaps, Challenges, and Opportunities in Automated Insulin ...
    Jul 1, 2025 · Significant challenges around the resources required for clinical implementation in this population exist. Fully automated closed loop: clinical ...
  158. [158]
    How to Design a Leak Test for a Complex Medical Assembly
    Oct 27, 2025 · The Inreda AP®6 bi-hormonal model is projected to be available to the public in Q3 2026. With their new scalable leak test solution, Inreda will ...
  159. [159]
    Fully Closed Loop Glucose Control With a Bihormonal Artificial ...
    Jan 4, 2021 · Although the use of glucagon is indispensable for this AP to achieve tight glucose control, it currently has several drawbacks. The glucagon had ...Research Design And Methods · Results · Conclusions
  160. [160]
    [PDF] Fully Closed Loop Glucose Control With a Bihormonal Artificial ...
    In conclusion, this trial demonstrates that the Inreda Diabetic AP provides su- perior glucose control compared with insulin pump therapy and is safe in adults.
  161. [161]
    Portable Artificial Pancreas Applied for Youth and Adolescents
    The purpose of this study is to determine the performance of a bi-hormonal reactive closed-loop system in adolscents with type 1 diabetes mellitus.
  162. [162]
    In the News.. FDA warns Dexcom, Inreda dual-chambered pump ...
    A warning letter posted Tuesday by the Food and Drug Administration revealed quality control issues with Dexcom's continuous glucose monitors.
  163. [163]
    Abbott to Acquire Bigfoot Biomedical, Furthering Efforts to Develop ...
    Sep 5, 2023 · That commitment to the diabetes community remains at the core of everything Bigfoot does. Learn more at www.bigfootbiomedical.com/ and by ...Missing: Luna trials
  164. [164]
    Luna Diabetes | Better Nights for Better Days
    Automated insulin delivery for insulin pen users. Sign Up for Updates ... Pioneers from Companion Medical, Bigfoot Biomedical, Timesulin, and Welldoc, Luna ...
  165. [165]
    Luna Health raises $23.6M for tiny insulin patch pump | MedTech Dive
    Aug 20, 2025 · CEO John Sjölund and CFO Jon Brilliant, both co-founders of the company, previously were executives at Bigfoot Biomedical, a company that ...Missing: AID trials
  166. [166]
    Luna Diabetes Announces Start of Pivotal Study to Bring Automated ...
    Oct 24, 2024 · Luna is the first automated insulin delivery solution intended for the >90% of all people with insulin-requiring diabetes who take their insulin ...<|control11|><|separator|>
  167. [167]
    New Type 1 Study Recruiting Injection Pen Users for Overnight ...
    Oct 30, 2024 · This virtual, at-home clinical trial will be testing the effectiveness of Luna, a new wearable insulin delivery patch to be worn during sleep.
  168. [168]
    Explore Luna: Automated Nighttime Insulin Therapy - Luna Diabetes
    Luna's cutting-edge technology automatically adjusts insulin dosing while your patients sleep, reducing their risk of nocturnal hyperglycemia. Ease of Use. Our ...
  169. [169]
    Luna Diabetes Secures $23.6M For Its Nighttime Insulin Patch Pump
    The Series A funding comes as Luna advances through pivotal trials. The ... Bigfoot Biomedical and Beta Bionics. Check out our full podcast interview ...Missing: acquisition 2023-2025
  170. [170]
    Luna Diabetes raises $23.6M for automated insulin patch pump
    Aug 18, 2025 · Sjölund previously co-founded and led Timesulin as CEO until its acquisition by Bigfoot Biomedical. After that, he served as VP of connected ...Missing: AID | Show results with:AID
  171. [171]
    Luna Diabetes trials automated wearable insulin pump
    Oct 24, 2024 · The Luna system was developed as a wearable insulin pump and alternative to insulin pen to automate the insulin delivery process. The device ...
  172. [172]
    NCT06630585 | GIP/GLP-1RA as Adjunctive to Automated Insulin ...
    This is a prospective, randomized, open-label design. The investigators will enroll 42 participants over 18 years of age with confirmed T1D diagnosis ≥6 months, ...
  173. [173]
    2012-LB: AI-Based Meal Detection Enables Fully-Automated ...
    Amylin, co-secreted with insulin by β-cells, suppresses glucagon, slows gastric emptying, and reduces post-meal glucose. Pramlintide is an FDA- ...
  174. [174]
    Simple meal announcements and pramlintide delivery versus ...
    We developed a novel insulin-and-pramlintide closed-loop system that replaces carbohydrate counting with simple meal announcements.
  175. [175]
    Stem cell-derived pancreatic beta cells: a step closer to functional ...
    Jul 16, 2025 · Stem cell encapsulation could reduce tissue immunogenicity and ... Stem cell therapy cost (2025 update). Cayman Islands: DVC Stem; 2025 ...
  176. [176]
    Encapsulated stem cell–derived β cells exert glucose control in ...
    Nov 27, 2023 · Here we report interim, 1-year outcomes in one study group that received 2–3-fold higher cell doses in devices with an optimized membrane perforation pattern.
  177. [177]
    Challenges for successful implantation of biofuel cells - ScienceDirect
    These problems include (i) the life-time of the enzymes and their low yield, (ii) biocompatibility of their components in the living body, and (iii) bio-fouling ...
  178. [178]
    Approaches and Challenges of Engineering Implantable ... - MDPI
    This review examines the challenges faced in implementing implantable MEMS drug delivery systems in vivo and the solutions available to overcome these ...2. Drug Reservoir Size And... · 5. Controllability · 6. Biocompatibility
  179. [179]
    S-1 - SEC.gov
    Jan 6, 2025 · Subject to receiving 510(k) clearance for our patch pump, we expect to launch our patch pump commercially by the end of 2027. Bihormonal iLet.
  180. [180]
    https://www.mdpi.com/2072-666X/3/4/615
  181. [181]
    https://www.sec.gov/Archives/edgar/data/1674632/000119312525002177/d880651ds1.htm
  182. [182]
    https://finance.yahoo.com/news/beta-bionics-reports-third-quarter-200200715.html
  183. [183]
    Glucose Prediction - LoopDocs - GitHub Pages
    Loop uses a model predictive control ( MPC ) algorithm to maintain glucose in a correction range by predicting the contributions from four individual effects.
  184. [184]
    https://doi.org/10.1089/dia.2013.0036
  185. [185]
    https://doi.org/10.1177/193229681200600519
  186. [186]
    https://loopkit.github.io/loopdocs/operation/algorithm/prediction/
  187. [187]
    Origins and History of the Minimal Model of Glucose Regulation - PMC
    Feb 15, 2021 · In 1979 Richard Bergman and Claudio Cobelli worked together to find a “minimal model” based upon experimental data from Bergman's laboratory.
  188. [188]
    A Composite Model of Glucagon–Glucose Dynamics for In Silico ...
    A novel glucagon–glucose composite model, which accounts for the effect of exogenous insulin and glucagon infusion on glucose dynamics, was successfully ...
  189. [189]
    Automated control of an adaptive bi-hormonal, dual-sensor artificial ...
    We discuss how we integrate a control algorithm with an adaptive expert system and a physiologic glucoregulatory model to enable automated bi-hormonal drug ...
  190. [190]
    The University of Virginia/Padova Type 1 Diabetes Simulator ...
    In 2008 we developed a T1DM simulator that has been accepted by the FDA as a substitute for preclinical animal trials for certain insulin treatments. The ...Missing: AID | Show results with:AID
  191. [191]
    An automatic deep reinforcement learning bolus calculator ... - Nature
    Jul 2, 2024 · This study exploits the deep reinforcement learning (DRL) algorithm to calculate insulin bolus for unannounced meals without utilizing the information on CHO ...Methodology · Pd Controller · The Drl Algorithm
  192. [192]
    Integrating metabolic expenditure information from wearable fitness ...
    Aug 3, 2023 · AIDs can integrate exercise data from smartwatches to inform insulin dosing and limit hypoglycaemia while improving glucose outcomes. Future ...
  193. [193]
    Revolutionizing Diabetes Care: The Impact of Artificial Intelligence in ...
    May 5, 2025 · In 2025, AI-driven platforms synthesize patient data in real time to recommend highly individualized care protocols. These platforms adjust ...
  194. [194]
    Welcome to the AAPS documentation — AndroidAPS 3.3 ...
    To use AAPS you need three compatible devices: (1) an Android phone, (2) a continuous glucose monitor (CGM), and (3) a FDA/CE approved insulin pump. Optionally ...Component Overview · Setup Wizard · Key AAPS features · Release notesMissing: outcomes | Show results with:outcomes
  195. [195]
    Luna Diabetes trials automated wearable insulin pump
    Oct 24, 2024 · The Luna system was developed as a wearable insulin pump and alternative to insulin pen to automate the insulin delivery process. The device ...
  196. [196]
    [PDF] Algorithmic Bias in AI-Based Diabetes Care - InfoScience Trends
    May 2, 2025 · Without systematic bias mitigation and equitable design, these tools risk exacerbating existing health disparities. Future research must pri-.
  197. [197]
    Artificial intelligence and diabetes: time for action and caution
    May 22, 2025 · The potential of AI in diabetes care extends far beyond current applications. In the near future, AI could enhance early diagnostics and ...
  198. [198]
    Explainable Insulin Pump Control with LLM Controllers for Type 1...
    Oct 5, 2025 · This hybrid system transforms a complex algorithm into an approachable "copilot," paving the way for safer, more understandable, and patient- ...
  199. [199]
    Privacy-Preserving Glycemic Management in Type 1 Diabetes
    Jul 4, 2025 · By leveraging federated RL, PRIMO-FRL enables a collaborative learning process where individual patient devices contribute to the improvement of ...
  200. [200]
    Breakthrough Devices Program | FDA
    The Breakthrough Devices Program is a voluntary program for certain medical devices and device-led combination products that provide for more effective ...Missing: AID | Show results with:AID
  201. [201]
    EU MDR Cybersecurity Requirements for Medical Device - I3CGlobal
    Jun 12, 2025 · The European Medical Device Regulation (MDR) started new, more demanding requirements for medical device cybersecurity, to ensure that medical device software ...
  202. [202]
    Medtronic secures CE Mark for MiniMed™ 780G System for insulin ...
    Jul 21, 2025 · NICE guidelines (TA943)(opens new window) recommend hybrid closed-loop systems for all children and adolescents with T1D. Recognizing the ...
  203. [203]
    Hybrid Closed Loop Insulin Delivery System approved for marketing
    Feb 27, 2023 · Recently, the innovative product Hybrid Closed Loop Insulin Delivery System ( MiniMed 670G BLE) of Medtronic MiniMed is approved by China NMPA.Missing: 2024 | Show results with:2024
  204. [204]
    Medical device & diagnostics - CDSCO
    Permission to import or manufacture new in vitro diagnostic medical device: The applicant shall make an application in MD-28 in sugam online portal for grant of ...
  205. [205]
    CDSCO simplifies online provision for import of medical devices ...
    Sep 18, 2025 · CDSCO simplifies online provision for import of medical devices & IVD already approved by CLA. Gireesh Babu, New Delhi
  206. [206]
    [PDF] Practice Considerations for Automated Insulin Delivery (AID)
    6. Decide the settings for the AID initiation. Each system is different. There are also resources provided by most AID manufacturers to guide.
  207. [207]
    WHO Guidelines - World Health Organization (WHO)
    A WHO guideline is defined broadly as any information product developed by WHO that contains recommendations for clinical practice or public health policy.
  208. [208]
    FDA Clears Tandem's Mobi Insulin Pump for Ages 2+
    Tandem's new Mobi automated insulin delivery system has received FDA clearance, making it the world's smallest insulin delivery system to be fully controllable ...
  209. [209]
    t:slim X2 Insulin Pump | Tandem Diabetes Care
    The t:slim X2 insulin pump is an all-in-one system that features a slim, sleek, user-friendly color touchscreen and multiple CGM options to fit your lifestyle.Free Virtual Pump Demo · Get Accessories · Mobile Apps · Glucose MonitoringMissing: 200-300 occlusion detection
  210. [210]
    Cost-Effectiveness of the MiniMed 780G System for Type 1 Diabetes
    Apr 10, 2025 · The MiniMed 780G insulin pump system is a cost-effective treatment option in the US for type 1 diabetes vs multiple daily injections with intermittently ...
  211. [211]
    How much is Omnipod without insurance? - SingleCare
    Jul 23, 2025 · The Omnipod 5 system, which connects to a continuous glucose monitor (CGM) for dynamic insulin delivery, costs $808 for a box of 10 pods. The ...Missing: annual | Show results with:annual
  212. [212]
    Glucagon in the Artificial Pancreas: Supply and Marketing Challenges
    Aug 19, 2014 · This would also mean that the daily cost of insulin and glucagon would be approximately $22/day or roughly $8000/year. Especially in regions ...Missing: Inreda $15000/
  213. [213]
    Medicare | Insulin Pump Therapy - Omnipod
    The Omnipod® 5 Automated Insulin Delivery System is indicated for use by individuals with type 1 diabetes mellitus in persons 2 years of age and older and ...
  214. [214]
    Insulin - Medicare
    Medicare covers insulin under Part B and Part D, with a $35 monthly limit. Part B covers insulin with pumps, while Part D may cover other injectable insulin. ...Missing: automated | Show results with:automated
  215. [215]
    Study finds disparities in access to insulin pumps among youth with ...
    Jun 14, 2022 · "Racial-ethnic minority groups and those of lower socioeconomic status still have unequal access to this very beneficial management tool.
  216. [216]
    Report: Low access to insulin in poor countries hinders diabetes care
    Oct 13, 2022 · Diabetes patients in low- and middle-income countries (LMICs) lack access to the insulin they need to manage their condition.
  217. [217]
    Disparities in Diabetes Technology Uptake in Youth and Young ...
    Although some of the differences in diabetes technology utilization in Latin America can be explained by social inequalities, economic and ethnic differences ...
  218. [218]
    [PDF] Technology and health inequities in diabetes care - T1D Exchange
    Jan 4, 2024 · All financial support from industry has been though his organization, T1D Exchange. David Kerr has received consultancy fees from Sanofi, Abbott ...
  219. [219]
    https://www.endocrine.org/news-and-advocacy/news-room/2022/study-finds-disparities-in-access-to-insulin-pumps-among-youth-with-type-1-diabetes
  220. [220]
    Unintended Consequences of Increased Out-of-Pocket Costs During ...
    Aug 11, 2023 · Increased OOP costs during Medicare coverage gap were associated with higher risk of DOAC discontinuation, which in turn was associated with higher risk of ...
  221. [221]
    Efficacy of automated insulin delivery systems in people with type 1 ...
    Apr 11, 2025 · The comparative efficacy of automated insulin delivery (AID) systems and other treatment options for type 1 diabetes, accounting for the certainty of evidence ...
  222. [222]
    Safety and Efficacy of Sustained Automated Insulin Delivery ...
    Sep 20, 2023 · In adults with T1D at high risk for hypoglycemia, AID reduced the risk for hypoglycemia more than twofold, as quantified by TBR, while improving TIR and ...
  223. [223]
    Efficacy and Safety of Automated Insulin Delivery Systems in Patients with Type 1 Diabetes Mellitus: A Systematic Review and Meta-Analysis
    ### Key Outcomes: TIR, GRI, HbA1c for AID vs Other Treatments
  224. [224]
    Automated Insulin Delivery Systems and Glucose Management in ...
    Sep 8, 2025 · This systematic review and meta-analysis investigates if, compared with standard care, automated insulin delivery systems used in an ...
  225. [225]
    The Future of Automated Insulin Delivery Systems - PubMed - NIH
    Jun 16, 2025 · This review examines key limitations of current AID systems and explores future directions, including fully closed-loop control, novel insulin formulations.
  226. [226]
    Research Gaps, Challenges, and Opportunities in Automated Insulin ...
    Jul 1, 2025 · Automated insulin delivery (AID) systems have enabled people living with T1D to safely manage their glucose, reduce their HbA1c, and improve their overall ...
  227. [227]
    Artificial intelligence for diabetes care: current and future prospects
    Artificial intelligence (AI) use in diabetes care is increasingly being explored to personalise care for people with diabetes and adapt treatments for ...
  228. [228]
    What Are Some Ethical Considerations of AI in Diabetes ...
    Aug 19, 2024 · The ethical use of AI in diabetes management requires careful consideration of data privacy, informed consent, algorithmic bias, and ...Data Privacy And Security · Algorithmic Bias And... · Transparency And...
  229. [229]
    U.S. Insulin Pump Market Size | Growth Analysis Report [2030]
    The U.S. insulin pump market size was valued at $2.58 billion in 2022 & is projected to grow from $2.98 billion in 2023 to $8.53 billion by 2030.
  230. [230]
    Insulin Delivery System Market to Boost USD 38.09 Bn by 2034
    Nov 20, 2024 · The global insulin delivery system market size is calculated at US$ 17.77 in 2024, grew to US$ 19.18 billion in 2025, and is projected to reach around US$ 38. ...Market Dynamics · Segmental Insights · Regional Insights<|separator|>