Do-It-Yourself Artificial Pancreas System and the OpenAPS Movement

Glycemic Variability Assessment in Newly Treated Exocrine Pancreatic Insufficiency With Type 1 Diabetes

BACKGROUND

Thirty-nine percent of people with type 1 diabetes may have lowered pancreatic elastase levels, correlated with exocrine pancreatic insufficiency (EPI or PEI). EPI is treated with oral supplementation of pancreatic enzymes. Little is known about the glycemic impact of pancreatic enzyme replacement therapy (PERT) in people with diabetes. This article demonstrates a method of assessing glycemic variability (GV), glycemic outcomes, and other changes in an individual with type 1 diabetes using open-source automated insulin delivery (AID).

METHOD

Macronutrient, PERT intake, and EPI-related symptoms were self-tracked; diabetes data were collected automatically via an open-source AID system. Diabetes data were uploaded via Nightscout to Open Humans and downloaded for analysis alongside self-tracked data (food, PERT). Glycemic outcomes, macronutrients, PERT dosing, and a variety of GV metrics following meals were evaluated for one month before and one month after PERT commencement. Breakfast was assessed independently across both time periods.

RESULTS

In an n = 1 individual using an open-source AID, time in range was already above goal and improved further after PERT commencement. Glucose rate of change and excursions >180 mg/dL were reduced; mean high blood glucose index was reduced overall and more so specifically at breakfast following PERT commencement.

CONCLUSIONS

GV can aid in assessing response to new-onset medications, as was demonstrated in this article for n = 1 individual with type 1 diabetes (using an open-source AID) after commencing PERT for newly identified EPI. GV may be useful for evaluating the efficacy of new-onset medications for people with insulin-requiring diabetes.

New advances in type 1 diabetes

Type 1 diabetes is an autoimmune condition resulting in insulin deficiency and eventual loss of pancreatic β cell function requiring lifelong insulin therapy. Since the discovery of insulin more than 100 years ago, vast advances in treatments have improved care for many people with type 1 diabetes. Ongoing research on the genetics and immunology of type 1 diabetes and on interventions to modify disease course and preserve β cell function have expanded our broad understanding of this condition. Biomarkers of type 1 diabetes are detectable months to years before development of overt disease, and three stages of diabetes are now recognized. The advent of continuous glucose monitoring and the newer automated insulin delivery systems have changed the landscape of type 1 diabetes management and are associated with improved glycated hemoglobin and decreased hypoglycemia. Adjunctive therapies such as sodium glucose cotransporter-1 inhibitors and glucagon-like peptide 1 receptor agonists may find use in management in the future. Despite these rapid advances in the field, people living in under-resourced parts of the world struggle to obtain necessities such as insulin, syringes, and blood glucose monitoring essential for managing this condition. This review covers recent developments in diagnosis and treatment and future directions in the broad field of type 1 diabetes.

From digital health to learning health systems: four approaches to using data for digital health design

Digital health technologies, powered by digital data, provide an opportunity to improve the efficacy and efficiency of health systems at large. However, little is known about different approaches to the use of data for digital health design, or about their possible relations to system-level dynamics. In this contribution, we identify four existing approaches to the use of data for digital health design, namely the silent, the overt, the data-enabled, and the convergent. After characterising the approaches, we provide real-life examples of each. Furthermore, we compare the approaches in terms of selected desirable characteristics of the design process, highlighting relative advantages and disadvantages. Finally, we reflect on the system-level relevance of the differentiation between the approaches and point towards future research directions. Overall, the contribution provides researchers and practitioners with a broad conceptual framework to examine data-related challenges and opportunities in digital health design.

Variability of Glycemic Outcomes and Insulin Requirements Throughout the Menstrual Cycle: A Qualitative Study on Women With Type 1 Diabetes Using an Open-Source Automated Insulin Delivery System

BACKGROUND

The impact of hormone dynamics throughout the menstrual cycle on insulin sensitivity represents a currently under-researched area. Despite therapeutic and technological advances, self-managing insulin therapy remains challenging for women with type 1 diabetes (T1D).

METHODS

To investigate perceived changes in glycemic levels and insulin requirements throughout the menstrual cycle and different phases of life, we performed semi-structured interviews with 12 women with T1D who are using personalized open-source automated insulin delivery (AID) systems. Transcripts were analyzed using thematic analysis with an inductive, hypothesis-generating approach.

RESULTS

Participants reported significant differences between the follicular phase, ovulation, and luteal phase of the menstrual cycle and also during puberty, pregnancy, and menopause. All participants reported increased comfort and safety since using AID, but were still required to manually adjust their therapy according to their cycle. A lack of information and awareness and limited guidance by health care providers were frequently mentioned. Although individual adjustment strategies exist, achieving optimum outcomes was still perceived as challenging.

CONCLUSIONS

This study highlights that scientific evidence, therapeutic options, and professional guidance on female health-related aspects in T1D are insufficient to date. Further efforts are required to better inform people with T1D, as well as for health care professionals, researchers, medical device manufacturers, and regulatory bodies to better address female health needs in therapeutic advances.

Open-source automated insulin delivery systems (OS-AIDs) in a pediatric population with type 1 diabetes in a real-life setting: the AWeSoMe study group experience

PURPOSE

The use of open-source automated insulin delivery systems (OS-AIDs), for the management of type 1 diabetes (T1D), has increased over recent years in all age groups. Real-life data has demonstrated the safety and efficacy of these systems, however, studies in the pediatric population remain limited. In this study, we aimed to examine the effect of transition to an OS-AIDs on glycemic parameters, and on several aspects related to quality of life. In addition, we aimed to characterize the socioeconomic position of families who chose this treatment modality, assess their motivations to do so, and evaluate treatment satisfaction.

METHODS

In this multi-center observational real-life study from the AWeSoMe Group, we compared glycemic parameters of 52 individuals with T1D (56% males, mean diabetes duration 4.2 ± 3.9 years), from the last clinic visit prior to OS-AIDs initiation to the most recent clinic visit while using the system. Socioeconomic position (SEP) index was retrieved from the Israel Central Bureau of Statistics. Caregivers completed questionnaires assessing reasons for system initiation and treatment satisfaction.

RESULTS

Mean age at OS-AIDs initiation was 11.2 ± 4 years, range 3.3-20.7 years with a median usage duration of 11.1 months (range 3-45.7). Mean SEP Index was 1.033 ± 0.956 (value range: -2.797 to 2.590). Time in range (TIR) of 70 to 180 mg/dl increased from 69.0 ± 11.9 to 75.5 ± 11.7%, (P < 0.001), and HbA1c decreased from 6.9 ± 0.7 to 6.4 ± 0.6%, (P < 0.001). Time in tight range (TITR) of 70 to 140 mg/dl increased from 49.7 ± 12.9 to 58.8 ± 10.8% (P < 0.001). No episodes of severe hypoglycemia or DKA were reported. Reduction in diabetes burden and sleep quality improvement were the main reasons for OS-AID initiation.

CONCLUSIONS

In our cohort of youth with T1D, the transition to an OS-AID resulted in greater TIR and less severe hypoglycemia regardless of age, diabetes duration or SEP, which was found to be above average. The overall improvement in glycemic parameters in our study population with excellent baseline glycemic control, provides additional evidence of beneficence and efficacy of OS-AIDs in the pediatric population.

Emerging Diabetes Technologies: Continuous Glucose Monitors/Artificial Pancreases

Over the past decade there have been many advances in diabetes technologies, such as continuous glucose monitors (CGM s), insulin-delivery devices, and hybrid closed loop systems . Now most CGMs (Medtronic-Guardian, Dexcom-G6, and Abbott-Libre-2) have MARD values of < 10%, in contrast to two decades ago when the MARD used to be > 20%. In addition, the majority of the new CGMs do not require calibrations, and the latest CGMs last for 10-14 days. An implantable 6-months CGM by Eversense-3 is now approved in the USA and Europe. Recently, the FDA approved Libre 3 which provides real-time glucose values every minute. Even though it is approved as an iCGM it is not interoperable with automatic-insulin-delivery (AID) systems. The newer CGMs that are likely to be launched in the next few months in the USA include the 10-11 days Dexcom G7 (60% smaller than the existing G6), and the 7-days Medtronic Guardian 4. Most of the newer CGM have several features like automatic initialization, easy insertion, predictive alarms, and alerts. It has also been noticed that an arm insertion site might have better accuracy than abdomen or other sites, like the buttock for kids. Lag time between YSI and different sensors have been reported differently, sometimes it is down to 2-3 min; however, in many instances, it is still 15-20 min, especially when the rate of change of glucose is > 2 mg/min. We believe that in the next decade there will be a significant increase in the number of people who use CGM for their day-to-day diabetes care.

In-silico evaluation of an artificial pancreas achieving automatic glycemic control in patients with type 1 diabetes

Artificial pancreas (AP) is a useful tool for maintaining the blood glucose (BG) of patients with type 1 diabetes (T1D) within the euglycemic range. An intelligent controller has been developed based on general predictive control (GPC) for AP. This controller exhibits good performance with the UVA/Padova T1D mellitus simulator approved by the US Food and Drug Administration. In this work, the GPC controller was further evaluated under strict conditions, including a pump with noise and error, a CGM sensor with noise and error, a high carbohydrate intake, and a large population of 100 in-silico subjects. Test results showed that the subjects are in high risk for hypoglycemia. Thus, an insulin on board (IOB) calculator, as well as an adaptive control weighting parameter (AW) strategy, was introduced. The percentage of time spent in euglycemic range of the in-silico subjects was 86.0% ± 5.8%, and the patient group had a low risk of hypoglycemia with the GPC+IOB+AW controller. Moreover, the proposed AW strategy is more effective in hypoglycemia prevention and does not require any personalized data compared with the IOB calculator. Thus, the proposed controller realized an automatic control of the BG of patients with T1D without meal announcements and complex user interaction.

Open-Source Automated Insulin Delivery in Type 1 Diabetes

BACKGROUND

Open-source automated insulin delivery (AID) systems are used by many patients with type 1 diabetes. Data are needed on the efficacy and safety of an open-source AID system.

METHODS

In this multicenter, open-label, randomized, controlled trial, we assigned patients with type 1 diabetes in a 1:1 ratio to use an open-source AID system or a sensor-augmented insulin pump (control). The patients included both children (defined as 7 to 15 years of age) and adults (defined as 16 to 70 years of age). The AID system was a modified version of AndroidAPS 2.8 (with a standard OpenAPS 0.7.0 algorithm) paired with a preproduction DANA-i insulin pump and Dexcom G6 CGM, which has an Android smartphone application as the user interface. The primary outcome was the percentage of time in the target glucose range of 70 to 180 mg per deciliter (3.9 to 10.0 mmol per liter) between days 155 and 168 (the final 2 weeks of the trial).

RESULTS

A total of 97 patients (48 children and 49 adults) underwent randomization (44 to open-source AID and 53 to the control group). At 24 weeks, the mean (±SD) time in the target range increased from 61.2±12.3% to 71.2±12.1% in the AID group and decreased from 57.7±14.3% to 54.5±16.0% in the control group (adjusted difference, 14 percentage points; 95% confidence interval, 9.2 to 18.8; P<0.001), with no treatment effect according to age (P = 0.56). Patients in the AID group spent 3 hours 21 minutes more in the target range per day than those in the control group. No severe hypoglycemia or diabetic ketoacidosis occurred in either group. Two patients in the AID group withdrew from the trial owing to connectivity issues.

CONCLUSIONS

In children and adults with type 1 diabetes, the use of an open-source AID system resulted in a significantly higher percentage of time in the target glucose range than the use of a sensor-augmented insulin pump at 24 weeks. (Supported by the Health Research Council of New Zealand; Australian New Zealand Clinical Trials Registry number, ACTRN12620000034932.).

Understanding the needs of people aging with type 1 diabetes: a user-focused research study with prototype diabetes advance directive and setting the stage for future research

Purpose

People living with Type 1 diabetes (T1D) are living longer than ever and facing the new "luxury" of the challenges of aging. While research is slowly expanding and addressing T1D physiology with regards to aging, there is little research addressing specific challenges and barriers to optimal care by those aging with T1D. To address this gap, this study employed human-centered design research to explore the gaps and barriers to care faced by people aging with T1D.

Methods

Researchers employed human-centered design methods of needfinding and user interviews and facilitated participatory workshops. In total, 27 people with T1D (PWT1D), 5 loved ones (partners of PWT1D), and 7 healthcare providers (HCPs) were engaged.

Results

Design artifacts were developed, including user personas that help visually articulate the different experiences of PWT1D and their unique needs as they age, as well as a prototype diabetes-specific advance directive that could be further refined to specifically aid those with Type 1 diabetes who are aging and requiring more interactions with the healthcare system. Initial user testing with people with T1D as well as healthcare providers demonstrated the need for such a diabetes advance directive tool or document.

Conclusion

This work supports the conclusion that additional focus and scientific enquiry should be given to the needs of people aging with Type 1 diabetes, with a goal of improving the experience of all people with T1D when interacting with their care providers or with the healthcare system as a whole.

Large-Scale Data Analysis for Glucose Variability Outcomes with Open-Source Automated Insulin Delivery Systems

Open-source automated insulin delivery (AID) technologies use the latest continuous glucose monitors (CGM), insulin pumps, and algorithms to automate insulin delivery for effective diabetes management. Early community-wide adoption of open-source AID, such as OpenAPS, has motivated clinical and research communities to understand and evaluate glucose-related outcomes of such user-driven innovation. Initial OpenAPS studies include retrospective studies assessing high-level outcomes of average glucose levels and HbA1c, without in-depth analysis of glucose variability (GV). The OpenAPS Data Commons dataset, donated to by open-source AID users with insulin-requiring diabetes, is the largest freely available diabetes-related dataset with over 46,070 days’ worth of data and over 10 million CGM data points, alongside insulin dosing and algorithmic decision data. This paper first reviews the development toward the latest open-source AID and the performance of clinically approved GV metrics. We evaluate the GV outcomes using large-scale data analytics for the n = 122 version of the OpenAPS Data Commons. We describe the data cleaning processes, methods for measuring GV, and the results of data analysis based on individual self-reported demographics. Furthermore, we highlight the lessons learned from the GV outcomes and the analysis of a rich and complex diabetes dataset and additional research questions that emerged from this work to guide future research. This paper affirms previous studies’ findings of the efficacy of open-source AID.

User and Healthcare Professional Perspectives on Do-It-Yourself Artificial Pancreas Systems: A Need for Guidelines

A growing number of individuals with type 1 diabetes are choosing to use "do-it-yourself" artificial pancreas systems (DIY APS) to support their diabetes self-management. Observational and self-report data of glycemic benefits of DIY APS are promising; however, without rigorous clinical trials or regulation from governing bodies, liability and user safety continue to be central concerns for stakeholders. Despite DIY APS having been used for several years now, there are no guidelines to assist users and healthcare professionals in addressing DIY APS use in routine clinical care. This commentary reports key stakeholders' perspectives presented at the annual Advanced Technologies and Treatments in Diabetes conference in February 2020. Important considerations to inform the development of clinical care guidelines are also presented to generate further debate.

Youth and parent preferences for an ideal AP system: It is all about reducing burden

BACKGROUND

As new diabetes technologies improve to better manage glucose levels, users' priorities for future technologies may shift to prioritize burden reduction and ease of use. We used qualitative methods to explore youth and parent desired features of an "ideal" artificial pancreas (AP) system.

METHODS

We conducted semi-structured interviews with 39 youth, ages 10-25 years, and 44 parents. Interviews were audio-recorded, transcribed, and coded using thematic analysis.

RESULTS

Youth (79% female, 82% non-Hispanic white) were (M ± SD) ages 17.0 ± 4.7 years, with diabetes for 9.4 ± 4.9 years, and HbA1c of 8.4 ± 1.1%; 79% were pump-treated and 82% used CGM. Of parents, 91% were mothers and 86% were non-Hispanic white. Participants suggested various ways in which an ideal AP system could reduce physical and emotional burdens of diabetes. Physical burdens could be reduced by lessening user responsibilities to manage glucose for food and exercise, and wear or carry devices. Emotional burden could be reduced by mitigating negative emotional reactions to sound and frequency of alerts, while increasing feelings of normalcy. Youth and parents differed in their suggestions to reduce emotional burden. Participants suggested features that would improve glycemia, but nearly always in the context of how the feature would directly reduce their diabetes-specific burden.

CONCLUSIONS

Although participants expressed interest in improving glucose levels, the pervasive desire among suggested features of an ideal AP system was to minimize the burden of diabetes. Understanding and addressing users' priorities to reduce physical and emotional burden will be necessary to enhance uptake and maintain use of future AP systems.

School Nurse Perspectives on Do-It-Yourself Automated Pancreas Systems in the School Setting

Do-it-yourself (DIY) artificial pancreas systems (APSs) are gaining popularity among children with type 1 diabetes. Little is known about how school systems provide care for children who use DIY APSs, and available guidance for schools is limited. This study explored school staff perspectives on DIY APSs through a national survey of school nurses about their current practices, beliefs, and attitudes toward DIY APSs. Although one-quarter (23%) of school nurses reported experience with DIY APSs in school, nearly half (46%) had no prior knowledge of this new technology. The majority (82%) reported that children should be allowed to use DIY APSs in school, although there was less consensus about school nurse responsibilities with these devices. Qualitative responses added context regarding potential barriers, including the need for more informed guidelines and training and fears of liability. Future development of school guidelines for DIY APSs is necessary and should incorporate stakeholder perspectives.

The Do-It-Yourself Artificial Pancreas

A growing number of people with diabetes are turning to self-built systems to dose and deliver insulin. These do-it-yourself artificial pancreas systems (DIY-APS) use commercially available insulin pumps and continuous glucose monitors and add an algorithm that independently modulates insulin dosing. Frustrated by the pace of diabetes technology development, a group of patients and diabetes advocates developed this technology without formal safety studies and without approval by the US Food and Drug Administration (FDA). Loop, OpenAPS, and AndroidAPS are the three available platforms, and patients worldwide are choosing them over other options. Patients generally report positive outcomes, but in May 2019, the FDA publicly warned against the use of such systems. Endocrinology providers are, therefore, faced with a difficult decision of whether to support patients interested in using a DIY-APS. This article describes the current state of DIY-APS, regulatory considerations, and our recommendations for endocrinology providers regarding this technology. [Pediatr Ann. 2021;50(7):e304-e307.].

Review of the Omnipod® 5 Automated Glucose Control System Powered by Horizon™ for the treatment of Type 1 diabetes

Type 1 diabetes (T1D) is a medical condition that requires constant management, including monitoring of blood glucose levels and administration of insulin. Advancements in diabetes technology have offered methods to reduce the burden on people with T1D. Several hybrid closed-loop systems are commercially available or in clinical trials, each with unique features to improve care for patients with T1D. This article reviews the Omnipod® 5 Automated Glucose Control System Powered by Horizon™ and the safety and efficacy data to support its use in the management of T1D.

The Do-It-Yourself Artificial Pancreas: A Comprehensive Review

Diabetes technology (DT) has accomplished tremendous progress in the past decades, aiming to convert these technologies as viable treatment options for the benefit of patients with diabetes (PWD). Despite the advances, PWD face multiple challenges with the efficient management of type 1 diabetes. Most of the promising and innovative technological developments are not accessible to a larger proportion of PWD. The slow pace of development and commercialization, overpricing, and lack of peer support are few such factors leading to inequitable access to the innovations in DT. Highly motivated and tech-savvy members of the diabetes community have therefore come up with the #WeAreNotWaiting movement and started developing their own do-it-yourself artificial pancreas systems (DIYAPS) integrating continuous glucose monitoring (CGM), insulin pumps, and smartphone technology to run openly shared algorithms to achieve appreciable glycemic control and quality of life (QoL). These systems use tailor-made interventions to achieve automated insulin delivery (AID) and are not commercialized or regulated. Online social network megatrends such as GitHub, CGM in the Cloud, and Twitter have been providing platforms to share these open source technologies and user experiences. Observational studies, anecdotal evidence, and real-world patient stories revealed significant improvements in time in range (TIR), time in hypoglycemia (TIHypo), HbA1c levels, and QoL after the initiation of DIYAPS. But this unregulated do-it-yourself (DIY) approach is perceived with great circumspection by healthcare professionals (HCP), regulatory bodies, and device manufacturers, making users the ultimate risk-bearers. The use of the regularized CGM and insulin pump with unauthorized algorithms makes them off-label and has been a matter of great concern. Besides these, lack of safety data, funding or insurance coverage, ethical, and legal issues are roadblocks to the unanimous acceptance of these systems among patients with type 1 diabetes (T1D). A multi-agency approach is necessary to evaluate the risks, and to delineate the incumbency and liability of clinicians, regulatory bodies, and manufacturers associated with the use of DIYAPS. Understanding the potential of DIYAPS as the need of the present time, many regional and international agencies have come with strategies to appraise its safety as well as to support education and training on its use. Here we provide a comprehensive description of the DIYAPS-including their origin, existing literature, advantages, and disadvantages that can help the industry leaders, clinicians, and PWD to make the best use of these systems.

Evolution of Insulin Delivery Devices: From Syringes, Pens, and Pumps to DIY Artificial Pancreas

The year 2021 will mark 100 years since the discovery of insulin. Insulin, the first medication to be discovered for diabetes, is still the safest and most potent glucose-lowering therapy. The major challenge of insulin despite its efficacy has been the occurrence of hypoglycemia, which has resulted in sub-optimal dosages being prescribed in the vast majority of patients. Popular devices used for insulin administration are syringes, pens, and pumps. An artificial pancreas (AP) with a closed-loop delivery system with > 95% time in range is believed to soon become a reality. The development of closed-loop delivery systems has gained momentum with recent advances in continuous glucose monitoring (CGM) and computer algorithms. This review discusses the evolution of syringes, disposable, durable pens and connected pens, needles, tethered and patch insulin pumps, bionic pancreas, alternate controller-enabled infusion (ACE) pumps, and do-it-yourself artificial pancreas systems (DIY-APS).

New technical approach to the diabetes therapy

Optimal glycemic control remains challenging in individuals with type 1 diabetes. With the comprehensive clinical evidence on safety and efficiency, the adoption of continuous glucose monitoring (CGM), insulin pumps, and control algorithms merging the two into closed-loop systems is rapidly increasing. Particularly the CGM and intermittently scanned CGM improved diabetes management outcomes in large populations. A meaningful translation from clinical trials in highly controlled settings to numerous evaluations of closed-loop technology in the unrestricted home environment ended with its commercialization and use in routine clinical practice. Although it is still not a cure, the closed-loop currently seems to be the most promising advancement in the treatment of diabetes, with promising results also reported from routine clinical practice in children and adults with type 1 diabetes. We summarize different aspects of a technological approach to diabetes care, list currently available devices and systems in the pipeline, and the key supporting clinical evidence for their use. We consider human factors associated with technology use and the importance of health economics to support implementation and reimbursement.

Use of a do-it-yourself artificial pancreas system is associated with better glucose management and higher quality of life among adults with type 1 diabetes

BACKGROUND

Previous studies show that the use of do-it-yourself artificial pancreas system (DIYAPS) may be associated with better glycemic control characterized by improved estimated hemoglobin A1c (eHbA1c) and time in range among adults with type 1 diabetes (T1D). However, few studies have demonstrated the changes in laboratory-measured HbA1c, which is a more accepted index for glycemic control, after using a DIYAPS.

METHODS

This is a retrospective before-after study approaching patients who reported self-use of AndroidAPS. The main inclusion criteria included: T1D; aged ⩾18 years; having complete record of ⩾3 months of continuous AndroidAPS use; with laboratory-measured HbA1c and quality of life scale data before and after 3 months of AndroidAPS use; and not pregnant. The primary outcome was the change in HbA1c between baseline and 3 months after initiation of AndroidAPS use.

RESULTS

Overall, 15 patients (10 females) were included; the median age was 32.2 years (range: 19.2-69.4), median diabetes duration was 9.7 years (range: 1.8-23.7) and median baseline HbA1c was 7.3% (range: 6.4-10.1). The 3 months of AndroidAPS use was associated with substantial reductions in HbA1c [6.79% (SD: 1.29) versus 7.63% (SD: 1.06), p = 0.002] and glycemic variability when compared with sensor-augmented pump therapy. A lower level of fear of hypoglycemia [22.13 points (SD: 6.87) versus 26.27 points (SD: 5.82), p = 0.010] was also observed after using AndroidAPS.

CONCLUSIONS

The 3 months of AndroidAPS use was associated with significant improvements in glucose management and quality of life among adults with T1D.