100 Clinical Trials for Various Conditions
The goal of this clinical trial is to obtain safety data and exploratory glycemic control data from use of an at-home closed loop control (CLC) system (t:slim X2 with Control-IQ Technology) with periodic parameter adjustments driven by an AI-based Advisor system in young children with Type 1 Diabetes. The main endpoints this study aims to answer is the safety and efficacy of the use of the AI-driven pump parameters. Participants will use the study system (pump and Continuous Glucose Monitor) in closed-loop mode for eight weeks.
This study is intended to assess a Neural-net Artificial Pancreas (NAP) implementation of an established AP controller - the University of Virginia Model Predictive Control Algorithm (UMPC). The health outcomes achieved on NAP will be compared to the health outcomes achieved on UMPC in a randomized crossover design. The investigators will consent up to 20 participants, ages ≥18.0, with a goal of completing 15 participants.
This study will examine the potential cardiovascular effect(s) of artificial pancreas (AP) technology in patients with type 1 diabetes. AP technology is a system of devices that closely mimics the glucose-regulating function of a healthy human pancreas. It includes an insulin pump and a continuous glucose monitor (CGM). In this study, the investigators will research whether improvements in blood glucose levels and blood glucose variability will in turn decrease biomarkers of inflammation and endothelial dysfunction while improving cardiovascular function.
The objective of this proposal is to demonstrate a viable, functionally integrated multivariable artificial pancreas (mvAP) that will address meal, physical activity (PA) and acute psychological stress (APS) challenges without any manual inputs to better regulate glucose levels of people with diabetes. Acute psychological stress and many other forms of PA besides planned exercise can affect blood glucose levels and cause challenges to maintaining euglycemia for people with type 1 diabetes mellitus (T1DM). Various PA and APS affect the metabolism and sensitivity to insulin in different ways. Hence, their types, intensities and durations, and their individual and concurrent presence must be detected in order to determine the optimal insulin administration. The mvAP approach provides a well-integrated and user-friendly technology with minimal burden on the user and mitigates the effects of unexpected PA and APS inducements. Twenty subjects with type 1 diabetes (ages 18-60) who use insulin pumps enrolled in this study. The study will take place at the UIC-College of Nursing Diabetes and Exercise Laboratory. The protocol will include 1 screening visit and 5 sessions at the laboratory. The primary activities at each meeting will include: (1) screening; (2) measurement of peak exercise capacity; (3) estimation of maximal strength from submaximal strength tests; (4) Trier Social Stress Test; (5) submaximal bouts of aerobic and resistance exercise, and activities of daily living with and without stress (e.g., mental calculations, video games). These activities will be included visit 3, 4 and 5 as appropriate. In addition, subjects will perform activities at home include: housekeeping chores, stationary bike (if available); treadmill (if available); walking; and light weights (if available). Periodically, the research assistant will call the subject during these times and ask them to perform stress-inducing activities while performing the activity. The stress inducing activities will include mental challenges such as a mathematical computation while performing the activity. The subjects will be called at home 3-5 times during the study. The fully automated algorithm will be tested in a home setting, however, the methodology will be developed and approved for testing later in the study.
The purpose of this study is to learn whether an investigational automated insulin delivery system ("study system") for young children (2 yo to less than 6 yo) with type 1 diabetes can safely improve blood glucose (sometimes called blood sugar) control.
This study designed to assess changes in control of Type 1 Diabetes in pubertal adolescents over a two year period. There are two arms/substudies, the first being a longitudinal randomized controlled trial and the second an observational study.
This feasibility study is a randomized crossover trial that will compare the efficacy and safety of an automated insulin delivery (AID) system in patients with type 1 diabetes using a Model Predictive Control (MPC) algorithm versus sensor augmented pump therapy (SAP)/Predictive Low Glucose Suspend (PLGS), and will include different stress induction and assessments over a 4 week period.
A single-arm, multi-center, clinical study to assess the safety profile of the Tandem t:slim X2 with Control-IQ system in children with T1D aged 2-6 years old under free living condition
This is a randomized crossover trial with 1:1 randomization to the admission sequence of using the Control AP system (rMPC - Naïve Model Predictive Control) vs. Experimental AP system (EnMPC - Ensemble Model Predictive Control) over approximately 4 months. Eligible participants will proceed to the Data Collection Phase for approximately 28 days, during which they will participate in regimented exercise activities. If the participant collected adequate data during the Data Collection Phase, they will be randomized and undergo the study admissions in the assigned sequence. Each admission is approximately 36 hours in length and will consist of one afternoon of exercise and one without.
The purpose of this proposed study is to assess the use of a new feature of the Control-IQ system, MyTDI.
The objective of this randomized crossover clinical trial is to 1) assess the efficacy and safety of an automated insulin delivery (AID) system using a Model Predictive Control (MPC) algorithm versus sensor augmented pump therapy (SAP)/Predictive Low Glucose Suspend (PLGS) in people with type 1 diabetes, and 2) assess the impact of different meal macronutrient content on glucose control when using AID and SAP.
This is a 3-month extension study (DCLP3 Extension) following a primary trial (DCLP3 or NCT03563313) to assess efficacy and safety of a closed loop system (t:slim X2 with Control-IQ Technology) in a large randomized controlled trial. Upon completion of the NIH 3-month extension study, subjects will be invited to participate in a continued use phase with Control-IQ Technology, funded by Tandem Diabetes Care, until the equipment has received FDA approval for commercial use.
The objective of the study is to assess efficacy and safety of a closed loop system (t:slim X2 with Control-IQ Technology) in a large randomized controlled trial.
The objective of this study is to test two different operating modes of the latest version of the Dose Safety artificial pancreas system (APS), the Dose Safety Controller (DSC version 2.3), in a population of subjects with type 1 diabetes (TID) in a hospital CRC setting. The first mode is the Fully Automated Closed Loop (FACL) mode, in which all insulin delivery is directed by the controller and the second mode is the Hybrid Closed Loop (HCL) mode, in which insulin delivery is a hybrid between controller directed delivery and user directed insulin delivery. There will be two study arms: HCL and FACL. No comparisons will be made between the two arms.
An early feasibility study that will test the efficacy of the Tandem t:slim X2 with Control-IQ and Dexcom Continuous Glucose System G6 in a winter/ski camp environment.
To demonstrate that a new insulin pump system can prevent low glucose episodes and improve brain function in aged Type 1 diabetes mellitus subjects.
Subjects will undergo a 7±1 day outpatient, standard therapy phase during which sensor and insulin data will be collected. Subjects or their caregivers will manage their diabetes at home per their usual routine using the study CGM and remain on current MDI or pump therapy. This will be followed by a 5-day/4-night or from approximately 48 to 72 hours for children ages 2.0-5.9 years, hybrid closed-loop phase conducted in a supervised hotel/rental house setting.
The purpose of this pilot study is to establish that closed-loop insulin delivery with a target enchanted model predictive control (eMPC)/Health Monitoring System (HMS) algorithms with a trust index of the predicted glucose value is safe and effective, to analyze and learn to improve upon the accuracy of the predicted glucose values, and to collect efficacy data to inform a future larger study.
To assess the safety and performance of the Insulet AP (artificial pancreas) system, using the Omnipod® insulin management system, Dexcom G4 Share® AP System and personalized model predictive control algorithm in adults with type 1 diabetes consuming high fat meals and undertaking moderate intensity exercise.
The purpose is to perform an early investigation on the safety and performance of an Automated Glucose Control (AGC) algorithm using the OmniPod® Insulin Management System and gather clinical data that will be used to make improvements or modifications to the algorithm for subsequent studies in adults, adolescents and children with type 1 diabetes.
The objectives of this outpatient research study are (1) to assess the ability of this automated system to be operated by a subject with limited professional oversight; (2) to assess whether the new devices (Dexcom Gen 4 sensors, Motorola ES400 smart phone, iDex pump controller) will reduce the frequency of hardware and data communication lapses seen in the previous system; and (3) to measure the degree of glucose control achievable with this automated system. The system will adjust blood glucose by administering insulin and glucagon. Insulin is a hormone that lowers blood glucose and will be given nearly continuously during this study. Glucagon raises blood glucose and will be automatically administered during hypoglycemia. Both are natural hormones made by people without diabetes. Each subject will have four devices placed on his abdomen: two Omnipod insulin pumps, one for delivering insulin and one for delivering glucagon, and two Dexcom G4 glucose sensors for measuring glucose. The two sensors will feed glucose data into Motorola smart phone master controller, which will calculate the correct amount of insulin or glucagon to deliver. The system will then send the command to the correct Omnipod through the iDex pod controller. In this new system, the research subject will be able to monitor the progress of the study by use of the smart phone graphical user interface. The subject will have a companion with him/her during the entire study for safety purposes. Both the subject and companion will complete a training course on how to treat diabetic emergencies and how to operate the system. A study physician and technician will be in the hotel during each study and will be monitoring the study via a cloud-based data communication system. These studies will be carried out in a hotel setting.
The purpose of this study is to verify an automated system of blood glucose control in Type I Diabetics. The automated system consists of the investigational Artificial Pancreas Control software (APC), two blood glucose sensors, and two hormone pumps, one for delivering insulin to lower blood sugar, and the second for delivering glucagon to raise blood sugar. The blood glucose sensors relays information to the Artificial Pancreas software, which uses the Adaptive Proportional Device algorithm to determine the rate of insulin and glucagon infusion by the hormone pumps. In prior studies, the Adaptive Proportional Device algorithm has been verified, but required manual input into the computer and hormone pumps. This study differs in that it uses a fully automated system under the control of the Artificial Pancreas Control software. The importance of this change is that it is the next step to enable outpatient use of automated, closed loop blood glucose control.
The investigators hypothesize that our closed-loop glucose-control system can provide BG control in subjects with type 1 diabetes using the estimated BG signal from a CGM as the input signal to the controller.
Objective: to gain experience in children and younger adolescents with in-home use of an algorithm that will dose insulin to minimize projected hyperglycemia overnight in addition to suspending the pump if hypoglycemia is projected overnight and to obtain feasibility, safety, and initial efficacy data Study Design: randomized controlled trial, with randomization on a night level within subject Patient Population: Youth 6.0 - \<15 years old with type 1 diabetes treated with daily insulin therapy for at least one year and an insulin infusion pump for at least 6 months who have HbA1c \< 10.0%. Sample Size: 30 subjects Study Duration and Visit Schedule: duration approximately 3 months, with preliminary run-in activities followed by up to 90 days spent in clinical trial phase of study; clinic visits at enrollment, following CGM and system assessment run-in phases, at start of clinical trial phase, at 21-day point of clinical trial phase, and after 42 nights of successful system use Major Efficacy Outcomes: * Primary: time in range (70-180 mg/dl, 3.9-10.0 mmol/L) overnight. * Secondary: time spent in hypoglycemia (\<70 mg/dl, 3.9 mmol/L) and time spent in hyperglycemia (\>180 mg/dl, 10.0 mmol/L) overnight. Major Safety Outcomes: CGM measures of hypo- and hyperglycemia, including morning blood glucose and mean overnight sensor glucose; adverse events including severe hypoglycemia and diabetic ketoacidosis
This is a proof of concept safety study of an artificial intelligence based closed loop glucose control system designed for use in the intensive care unit setting. The type 1 and type 2 diabetic subjects in this study will have their glucose controlled to a range of 100-140 mg/dL by a novel artificial intelligence based closed loop glucose control system for a period of 24 hours. The subjects will consume three standardized meals during the 24 hour study period.
This study is intended to test a Web-based Information Tool (WIT) software providing additional information regarding time in range, GMI, hypo- and hyperglycemia risks, variability tracker, daily glycemic profiles, and potential changes of insulin pump parameters, to users of a commercially available Closed-Loop Control (CLC) System (Control-IQ Technology).
The purpose of this study is to understand the impact of the automated priming boluses on the safety and feasibility of a new fully automated AP controller.
This is a proof of concept safety study of an artificial intelligence based closed loop glucose control system designed for use in the intensive care unit setting. The type 2 diabetic subjects in this study will have their glucose controlled to a range of 100-140 mg/dL by a novel artificial intelligence based closed loop glucose control system for a period of 24 hours. The subjects will consume three standardized meals during the 24 hour study period.
The purpose of this pilot study is to test the safety and feasibility of using two or three research modules in conjunction with an automated insulin delivery device (AID).
The objective of this research is to determine the most informative variables for detecting exercise, acute stress and sleep, identify select sensors that report these variables, and develop the algorithms to detect the occurrence of exercise, stress and sleep, to discriminate them and to determine their characteristics. Research is needed to identify which wearable devices report the most informative and predictive variables of exercise, acute stress and sleep with desired precision and accuracy, determine the best location to wear them for collecting reliable and informative data, and to distill accurate knowledge from data reported by wearable sensors. Data and their interpretation should be informative for various types of physical activities, stages of sleep, and types and intensities of acute stress, and concurrent occurrence of these factors. The investigators will use several devices (chest band, wristband and skin patches) to collect data and evaluate their information content and contribution to improvement of glucose concentration prediction, best locations for collecting accurate and reliable information by conducting clinical and free-living experiments at-home to assess the contributions of the wearable device in improving the accuracy of glucose concentration prediction and the performance of the multivariable artificial pancreas.