Do-It-Yourself Artificial Pancreas Systems: A Review of the Emerging Evidence and Insights for Healthcare Professionals

Automating insulin delivery through pump and continuous glucose monitoring connectivity: Maximizing opportunities to improve outcomes

The development of automated insulin delivery (AID) systems, which connect continuous glucose monitoring (CGM) systems with algorithmic insulin delivery from an insulin pump (continuous subcutaneous insulin infusion, [CSII]), has led to improved glycaemia and quality of life benefits in those with insulin-treated diabetes. This review summarizes the benefits gained by the connectivity between insulin pumps and CGM devices. It details the technical requirements and advances that have enabled this, and highlights the clinical and user benefits of such systems. Clinical trials and real-world outcomes from the use of AID systems in people with type 1 diabetes (T1D) will be the focus of this article; outcomes in people with type 2 diabetes (T2D) and other diabetes subtypes will also be discussed. We also detail the limitations of current technological approaches for connectivity between insulin pumps and CGM devices. While recognizing the barriers, we discuss opportunities for the future.

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.

Psychosocial Outcomes Among Users and Nonusers of Open-Source Automated Insulin Delivery Systems: Multinational Survey of Adults With Type 1 Diabetes

BACKGROUND

Emerging research suggests that open-source automated insulin delivery (AID) may reduce diabetes burden and improve sleep quality and quality of life (QoL). However, the evidence is mostly qualitative or uses unvalidated, study-specific, single items. Validated person-reported outcome measures (PROMs) have demonstrated the benefits of other diabetes technologies. The relative lack of research investigating open-source AID using PROMs has been considered a missed opportunity.

OBJECTIVE

This study aimed to examine the psychosocial outcomes of adults with type 1 diabetes using and not using open-source AID systems using a comprehensive set of validated PROMs in a real-world, multinational, cross-sectional study.

METHODS

Adults with type 1 diabetes completed 8 validated measures of general emotional well-being (5-item World Health Organization Well-Being Index), sleep quality (Pittsburgh Sleep Quality Index), diabetes-specific QoL (modified DAWN Impact of Diabetes Profile), diabetes-specific positive well-being (4-item subscale of the 28-item Well-Being Questionnaire), diabetes treatment satisfaction (Diabetes Treatment Satisfaction Questionnaire), diabetes distress (20-item Problem Areas in Diabetes scale), fear of hypoglycemia (short form of the Hypoglycemia Fear Survey II), and a measure of the impact of COVID-19 on QoL. Independent groups 2-tailed t tests and Mann-Whitney U tests compared PROM scores between adults with type 1 diabetes using and not using open-source AID. An analysis of covariance was used to adjust for potentially confounding variables, including all sociodemographic and clinical characteristics that differed by use of open-source AID.

RESULTS

In total, 592 participants were eligible (attempting at least 1 questionnaire), including 451 using open-source AID (mean age 43, SD 13 years; n=189, 41.9% women) and 141 nonusers (mean age 40, SD 13 years; n=90, 63.8% women). Adults using open-source AID reported significantly better general emotional well-being and subjective sleep quality, as well as better diabetes-specific QoL, positive well-being, and treatment satisfaction. They also reported significantly less diabetes distress, fear of hypoglycemia, and perceived less impact of the COVID-19 pandemic on their QoL. All were medium-to-large effects (Cohen d=0.5-1.5). The differences between groups remained significant after adjusting for sociodemographic and clinical characteristics.

CONCLUSIONS

Adults with type 1 diabetes using open-source AID report significantly better psychosocial outcomes than those not using these systems, after adjusting for sociodemographic and clinical characteristics. Using validated, quantitative measures, this real-world study corroborates the beneficial psychosocial outcomes described previously in qualitative studies or using unvalidated study-specific items.

Open-source automated insulin delivery systems and formal healthcare: A qualitative study of challenges in the interaction between service-users with type 1 diabetes and healthcare professionals

OBJECTIVES

To explore the challenges that open-source automated insulin delivery systems pose to the encounter between service-users and healthcare professionals and how these challenges might be addressed in the future.

METHODS

Five adult service-users and six healthcare professionals participated in semi-structured interviews. A six-step thematic analysis was conducted, the focus being on challenges and needs for improvement of the interactions.

RESULTS

The analysis revealed three overarching challenges and wishes: (1) Lack of exchange of experiences. Service-users are reticent about disclosing their use of the systems to healthcare professionals. (2) Unclear ethical responsibility. Service-users are aware of their responsibility and guidelines can help to alleviate healthcare professional's legal responsibility; however, ambiguities around ethical responsibility for healthcare professionals remain an impediment to meaningful clinical interactions. (3) Unresolved individual and mutual expectations. Service-users expect better access to technology and focus on psychosocial aspects. In contrast, healthcare professionals fear the burden associated with the rising technical expectations.

CONCLUSION

Transparency and openness towards open-source systems need to be part of service-user and healthcare professionals interaction. Requirements for future care include improved knowledge about the systems, an openminded approach towards user-driven initiatives among healthcare professionals, and a focus on psychosocial aspects in the interaction.

The Effect of Do-It-Yourself Real-Time Continuous Glucose Monitoring on Glycemic Variables and Participant-Reported Outcomes in Adults With Type 1 Diabetes: A Randomized Crossover Trial

AIM

Real-time continuous glucose monitoring (rtCGM) has several advantages over intermittently scanned continuous glucose monitoring (isCGM) but generally comes at a higher cost. Do-it-yourself rtCGM (DIY-rtCGM) potentially has benefits similar to those of rtCGM. This study compared outcomes in adults with type 1 diabetes using DIY-rtCGM versus isCGM.

METHODS

In this crossover trial, adults with type 1 diabetes were randomized to use isCGM or DIY-rtCGM for eight weeks before crossover to use the other device for eight weeks, after a four-week washout period where participants reverted back to isCGM. The primary endpoint was time in range (TIR; 3.9-10 mmol/L). Secondary endpoints included other glycemic control measures, psychosocial outcomes, and sleep quality.

RESULTS

Sixty participants were recruited, and 52 (87%) completed follow-up. Glucose outcomes were similar in the DIY-rtCGM and isCGM groups, including TIR (53.1% vs 51.3%; mean difference -1.7% P = .593), glycosylated hemoglobin (57.0 ± 17.8 vs 61.4 ± 12.2 mmol/L; P = .593), and time in hypoglycemia <3.9 mmol/L (3.9 ± 3.8% vs 3.8 ± 4.0%; P = .947). Hypoglycemia Fear Survey total score (1.17 ± 0.52 vs 0.97 ± 0.54; P = .02) and fear of hypoglycemia score (1.18 ± 0.64 vs 0.97 ± 0.45; P = .02) were significantly higher during DIY-rtCGM versus isCGM. Diabetes Treatment Satisfaction Questionnaire status (DTSQS) score was also higher with DIY-rtCGM versus isCGM (28.7 ± 5.8 vs 26.0 ± 5.8; P = .04), whereas diabetes-related quality of life was slightly lower (DAWN2 Impact of Diabetes score: 3.11 ± 0.4 vs 3.32 ± 0.51; P = .045); sleep quality did not differ between the two groups.

CONCLUSION

Although the use of DIY-rtCGM did not improve glycemic outcomes compared with isCGM, it positively impacted several patient-reported psychosocial variables. DIY-rtCGM potentially provides an alternative, cost-effective rtCGM option.

The changing landscape of automated insulin delivery in the management of type 1 diabetes

Automated insulin delivery systems, also known as closed-loop or 'artificial pancreas' systems, are transforming the management of type 1 diabetes. These systems consist of an algorithm which responds to real-time glucose sensor levels by automatically modulating insulin delivery through an insulin pump. We review the rapidly changing landscape of automated insulin-delivery systems over recent decades, from initial prototypes to the different hybrid closed-loop systems commercially available today. We discuss the growing body of clinical trials and real-world evidence demonstrating their glycaemic and psychosocial benefits. We also address future directions in automated insulin delivery such as dual-hormone systems and adjunct therapy as well as the challenges around ensuring equitable access to closed-loop technology.

Objectives and outcomes of patient-driven innovations published in peer-reviewed journals: a qualitative analysis of publications included in a scoping review

OBJECTIVES

The aim of this study was to gain a deeper understanding of the objectives and outcomes of patient-driven innovations that have been published in the scientific literature, focusing on (A) the unmet needs that patient-driven innovations address and (B) the outcomes for patients and healthcare that have been reported.

METHODS

We performed an inductive qualitative content analysis of scientific publications that were included in a scoping review of patient-driven innovations, previously published by our research group. The review was limited to English language publications in peer-reviewed journals, published in the years 2008-2020.

RESULTS

In total, 83 publications covering 21 patient-driven innovations were included in the analysis. Most of the innovations were developed for use on an individual or community level without healthcare involvement. We created three categories of unmet needs that were addressed by these innovations: access to self-care support tools, open sharing of information and knowledge, and patient agency in self-care and healthcare decisions. Eighteen (22%) publications reported outcomes of patient-driven innovations. We created two categories of outcomes: impact on self-care, and impact on peer interaction and healthcare collaboration.

CONCLUSIONS

The patient-driven innovations illustrated a diversity of innovative approaches to facilitate patients' and informal caregivers' daily lives, interactions with peers and collaborations with healthcare. As our findings indicate, patients and informal caregivers are central stakeholders in driving healthcare development and research forward to meet the needs that matter to patients and informal caregivers. However, only few studies reported on outcomes of patient-driven innovations. To support wider implementation, more evaluation studies are needed, as well as research into regulatory approval processes, dissemination and governance of patient-driven innovations.

A Systematic Review of Commercial Hybrid Closed-Loop Automated Insulin Delivery Systems

INTRODUCTION

Several different forms of automated insulin delivery systems (AID systems) have recently been developed and are now licensed for type 1 diabetes (T1D). We undertook a systematic review of reported trials and real-world studies for commercial hybrid closed-loop (HCL) systems.

METHODS

Pivotal, phase III and real-world studies using commercial HCL systems that are currently approved for use in type 1 diabetes were reviewed with a devised protocol using the Medline database.

RESULTS

Fifty-nine studies were included in the systematic review (19 for 670G; 8 for 780G; 11 for Control-IQ; 14 for CamAPS FX; 4 for Diabeloop; and 3 for Omnipod 5). Twenty were real-world studies, and 39 were trials or sub-analyses. Twenty-three studies, including 17 additional studies, related to psychosocial outcomes and were analysed separately.

CONCLUSIONS

These studies highlighted that HCL systems improve time In range (TIR) and arouse minimal concerns around severe hypoglycaemia. HCL systems are an effective and safe option for improving diabetes care. Real-world comparisons between systems and their effects on psychological outcomes require further study.

Mapping the Landscape of Do-it-Yourself Medicine

The practice of medicine is typically conceptualized as remaining within the boundaries of a hospital or clinic. However, in recent years, patients have been able to gain access to information about medical research as it is ongoing. As a result, there has been a rise in do-it-yourself (DIY) medicine, where individuals treat themselves for medical conditions outside of clinical settings, often mimicking experimental therapies that remain inaccessible to the wider public. For example, in DIY brain stimulation, individuals suffering from depression build at-home electrical headsets using nine-volt batteries, mimicking an experimental neuroscience technique used in scientific laboratories. In DIY fecal transplantation, those with intestinal disorders like C. Difficile and inflammatory bowel disease transplant stool from donors into themselves with the aid of blenders and enemas. In the open Artificial Pancreas System movement, diabetes patients hacked together an artificial pancreas system from their glucose monitors and insulin pumps, years before such a system was approved by the United States Food and Drug Administration (US FDA). To date, scholarship on DIY medicine has largely been relegated to specific medical domains (e.g., neurology, gastroenterology, infectious disease). In this paper, however, I recognize DIY medicine as a cross-cutting phenomenon that has emerged independently across medical domains but shares common features. I map the varieties of DIY medicine across these domains and suggest that four key factors lead to their creation, growth, and uptake. In doing so, this essay sheds light on an understudied area of biomedical citizen science that is likely to grow substantially in the coming decades.

Do-It-Yourself and Commercial Automated Insulin Delivery Systems in Type 1 Diabetes: An Uncertain Area for Canadian Health-care Providers

In the past century, since the discovery of insulin, methods of insulin delivery and glucose monitoring have advanced technologically. In particular, the introduction of insulin pumps, providing continuous subcutaneous insulin infusion (CSII), and continuous glucose monitors (CGMs) have been revolutionary for people living with type 1 diabetes. In this review, we have focussed on automated insulin delivery (AID) systems and discuss the implications of both approved and off-label options for the user and health-care providers. By pairing insulin pumps with CGM, AID systems facilitate automated adjustment in insulin delivery based on CGM readings. A subset of these have been developed commercially and were granted regulatory approval. In contrast, unregulated do-it-yourself AID systems, designed and set up by people living with type 1 diabetes and their families, have advanced rapidly and are gaining popularity worldwide. These patient-driven technologies have demonstrated impressive user self-reported improvements in glycemic control and quality of life, but have not been evaluated in any formal randomized controlled trials or by regulators. This presents challenging uncertainty for health-care providers, in addition to ethical and legal implications in supporting people with diabetes who wish to use these technologies. The current knowledge, opinions and practices relating to the use of AID systems across Canada are unknown. Gathering this information will highlight current practice and areas of knowledge gaps and concern and will assist in focussed education. This understanding is crucial to ensure people with type 1 diabetes using these systems have access to optimal, consistent and safe patient-centred care.

Closed-loop insulin delivery: update on the state of the field and emerging technologies

INTRODUCTION

Over the last five years, closed-loop insulin delivery systems have transitioned from research-only to real-life use. A number of systems have been commercialized and are increasingly used in clinical practice. Given the rapidity of new developments in the field, understanding the capabilities and key similarities and differences of current systems can be challenging. This review aims to provide an update on the state of the field of closed-loop insulin delivery systems, including emerging technologies.

AREAS COVERED

We summarize key clinical safety and efficacy evidence of commercial and emerging insulin-only hybrid closed-loop systems for type 1 diabetes. A literature search was conducted and clinical trials using closed-loop systems during free-living conditions were identified to report on safety and efficacy data. We comment on emerging technologies and adjuncts for closed-loop systems, as well as non-technological priorities in closed-loop insulin delivery.

EXPERT OPINION

Commercial hybrid closed-loop insulin delivery systems are efficacious, consistently improving glycemic control when compared to standard therapy. Challenges remain in widespread adoption due to clinical inertia and the lack of resources to embrace technological developments by health care professionals.

Improved Glycemia and Quality of Life Among Loop Users: Analysis of Real-world Data From a Single Center

BACKGROUND

Despite do-it-yourself automated insulin delivery being an unapproved method of insulin delivery, an increasing number of people with type 1 diabetes (T1D) worldwide are choosing to use Loop, a do-it-yourself automated insulin delivery system.

OBJECTIVE

In this study, we aimed to assess glycemic outcomes, safety, and the perceived impact on quality of life (QOL) in a local Edmonton cohort of known Loop users.

METHODS

An observational study of adults with T1D who used Loop was performed. An assessment of glycemic and safety outcomes, HbA1c, time in range, hospital admissions, and time below range compared users most recent 6 months of Loop use, with their prior regulatory approved insulin delivery method. QOL outcomes were assessed using Insulin Dosing Systems: Perceptions, Ideas, Reflections, and Expectations, diabetes impact, and device satisfaction measures (with maximum scores of 100, 10, and 10, respectively) and semistructured interviews.

RESULTS

The 24 adults with T1D who took part in this study 16 (67%) were female, with a median age of 33 (IQR 28-45) years, median duration of diabetes of 22 (IQR 17-32) years, median pre-Loop HbA1c of 7.9% (IQR 7.6%-8.3%), and a median duration of Loop use of 18 (IQR 12-25) months. 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 range, which were a significant improvement from prior therapy (P=.001 and P=.005), with a nonsignificant reduction in time below range; 3.0 to 3.9 mmol/L (P=.17) and <3 mmol/L (P=.53). Overall, 2 episodes of diabetic ketoacidosis occurred in a total of 470 months of Loop use, and no severe hypoglycemia occurred. The positive impact of Loop use on QOL was explored in qualitative analysis and additionally demonstrated through a median Insulin Dosing Systems: Perceptions, Ideas, Reflections, and Expectations score of 86 (IQR 79-95), a median diabetes impact score of 2.8 (IQR 2.1-3.9), and a median device satisfaction score of 9 (IQR 8.2-9.4).

CONCLUSIONS

This local cohort of people with T1D demonstrated a beneficial effect of Loop use on both glycemic control and QOL, with no safety concerns being highlighted.

An Intelligent Model-Based Effective Approach for Glycemic Control in Type-1 Diabetes

Type-1 diabetes mellitus (T1DM) is a challenging disorder which essentially involves regulation of the glucose levels to avoid hyperglycemia as well as hypoglycemia. For this purpose, this research paper proposes and develops control algorithms using an intelligent predictive control model, which is based on a UVA/Padova metabolic simulator. The primary objective of the designed control laws is to provide an automatic blood glucose control in insulin-dependent patients so as to improve their life quality and to reduce the need of an extremely demanding self-management plan. Various linear and nonlinear control algorithms have been explored and implemented on the estimated model. Linear techniques include the Proportional Integral Derivative (PID) and Linear Quadratic Regulator (LQR), and nonlinear control strategy includes the Sliding Mode Control (SMC), which are implemented in this research work for continuous monitoring of glucose levels. Performance comparison based on simulation results demonstrated that SMC proved to be most efficient in terms of regulating glucose profile to a reference level of 70 mg/dL compared to the classical linear techniques. A brief comparison is presented between the linear techniques (PID and LQR), and nonlinear technique (SMC) for analysis purposes proving the efficacy of the design.

Practical Guidance on Open Source and Commercial Automated Insulin Delivery Systems: A Guide for Healthcare Professionals Supporting People with Insulin-Requiring Diabetes

As increasing numbers of people with insulin-managed diabetes use automated insulin delivery (AID) systems or seek such technologies, healthcare providers are faced with a steep learning curve. Healthcare providers need to understand how to support these technologies to help inform shared decision making, discussing available options, implementing them in the clinical setting, and guiding users in special situations. At the same time, there is a growing diversity of commercial and open source automated insulin delivery systems that are evolving at a rapid pace. This practical guide seeks to provide a conversational framework for healthcare providers to first understand and then jointly assess AID system options with users and caregivers. Using this framework will help HCPs in learning how to evaluate potential new commercial or open source AID systems, while also providing a guide for conversations to help HCPs to assess the readiness and understanding of users for AID systems. The choice of an AID system is not as simple as whether the system is open source or commercially developed, and indeed there are multiple criteria to assess when choosing an AID system. Most importantly, the choices and preferences of the person living with diabetes should be at the center of any decision around the ideal automated insulin delivery system or any other diabetes technology. This framework highlights issues with AID use that may lead to burnout or perceived failures or may otherwise cause users to abandon the use of AID. It discusses the troubleshooting of basic AID system operation and discusses more advanced topics regarding how to maximize the time spent on AID systems, including how to optimize settings and behaviors for the best possible outcomes with AID technology for people with insulin-requiring diabetes. This practical approach article demonstrates how healthcare providers will benefit from assessing and better understanding all available AID system options to enable them to best support each individual.

Meal and Physical Activity Detection from Free-Living Data for Discovering Disturbance Patterns of Glucose Levels in People with Diabetes

Objective: The interpretation of time series data collected in free-living has gained importance in chronic disease management. Some data are collected objectively from sensors and some are estimated and entered by the individual. In type 1 diabetes (T1D), blood glucose concentration (BGC) data measured by continuous glucose monitoring (CGM) systems and insulin doses administered can be used to detect the occurrences of meals and physical activities and generate the personal daily living patterns for use in automated insulin delivery (AID). Methods: Two challenges in time-series data collected in daily living are addressed: data quality improvement and the detection of unannounced disturbances of BGC. CGM data have missing values for varying periods of time and outliers. People may neglect reporting their meal and physical activity information. In this work, novel methods for preprocessing real-world data collected from people with T1D and the detection of meal and exercise events are presented. Four recurrent neural network (RNN) models are investigated to detect the occurrences of meals and physical activities disjointly or concurrently. Results: RNNs with long short-term memory (LSTM) with 1D convolution layers and bidirectional LSTM with 1D convolution layers have average accuracy scores of 92.32% and 92.29%, and outperform other RNN models. The F1 scores for each individual range from 96.06% to 91.41% for these two RNNs. Conclusions: RNNs with LSTM and 1D convolution layers and bidirectional LSTM with 1D convolution layers provide accurate personalized information about the daily routines of individuals. Significance: Capturing daily behavior patterns enables more accurate future BGC predictions in AID systems and improves BGC regulation.

Real-world evidence on clinical outcomes of people with type 1 diabetes using open-source and commercial automated insulin dosing systems: A systematic review

AIMS

Several commercial and open-source automated insulin dosing (AID) systems have recently been developed and are now used by an increasing number of people with diabetes (PwD). This systematic review explored the current status of real-world evidence on the latest available AID systems in helping to understand their safety and effectiveness.

METHODS

A systematic review of real-world studies on the effect of commercial and open-source AID system use on clinical outcomes was conducted employing a devised protocol (PROSPERO ID 257354).

RESULTS

Of 441 initially identified studies, 21 published 2018-2021 were included: 12 for Medtronic 670G; one for Tandem Control-IQ; one for Diabeloop DBLG1; two for AndroidAPS; one for OpenAPS; one for Loop; three comparing various types of AID systems. These studies found that several types of AID systems improve Time-in-Range and haemoglobin A_1c (HbA_1c ) with minimal concerns around severe hypoglycaemia. These improvements were observed in open-source and commercially developed AID systems alike.

CONCLUSIONS

Commercially developed and open-source AID systems represent effective and safe treatment options for PwD of several age groups and genders. Alongside evidence from randomized clinical trials, real-world studies on AID systems and their effects on glycaemic outcomes are a helpful method for evaluating their safety and effectiveness.

#WeAreNotWaiting DIY artificial pancreas systems and challenges for the law

Commercial hybrid closed-loop systems are becoming more readily available, yet the number of DIY artificial pancreas system (DIY APS) users continues to rise. These DIY systems have not gone through the usual regulatory approvals processes, and, thus, present a number of legal difficulties for a number of actors, including clinicians, parents who build DIY APS for their children, and users themselves. These issues have so far received insufficient attention. Due to the complex constellation of actors involved in both development of DIY APSs and in its deployment, it is not currently clear who, and to what extent, different parties might (successfully) be held liable if something goes wrong. Despite this uncertainty, unless and until clearer guidance is issued by relevant bodies, or a case appears before the courts which clarifies the situation, existing legal principles apply. In this article, we examine some of these to shed light on how the law would likely be applied if harm were to result from the use of a DIY APS.

Recent advances in closed-loop insulin delivery

Since the discovery of insulin 100 years ago, we have seen considerable advances across diabetes therapies. The more recent advent of glucose-responsive automated insulin delivery has started to revolutionise the management of type 1 diabetes in children and adults. Evolution of closed-loop insulin delivery from research to clinical practice has been rapid, and multiple systems are now commercially available. In this review, we summarise key evidence on currently available closed-loop systems and those in development. We comment on dual-hormone and do-it-yourself systems, as well as reviewing clinical evidence in special populations such as very young children, older adults and in pregnancy. We identify future directions for research and barriers to closed-loop adoption, including how these might be addressed to ensure equitable access to this novel therapy.

Association of British Clinical Diabetologists, Diabetes Technology Network UK and Association of Children's Diabetes Clinicians Survey of UK Healthcare Professional Attitudes Towards Open-Source Automated Insulin Delivery Systems

INTRODUCTION

Automated insulin delivery (AID) systems can enable improved glycaemic outcomes with reduced mental burden. Open-source AID (OS-AID) systems overcome some of the developmental and access barriers enabling a wider use of these systems. Limited data are available on healthcare professional (HCP) opinions and current practice regarding these systems. The aim of this survey was to gain insight into HCP perceptions and practices around OS-AID.

METHODS

This survey was developed collaboratively with OS-AID users and distributed to adult and children's teams, using an online survey tool. Results were received between February and April 2019. Responses were assessed using simple descriptive statistics with analyses stratified by respondent characteristics.

RESULTS

317 responses were obtained from a range of HCPs in both adult and paediatric services. Key results include: HCP perception of OS-AID as "risky in the wrong hands" (43%); 91% felt uncomfortable initiating discussions around OS-AID because of lack of regulation (67%) and/or their own lack of knowledge (63%). Half of HCPs (47%) reported that they would choose OS-AID if they themselves had type 1 diabetes.

CONCLUSIONS

HCPs are generally supportive of OS-AID users but many feel uncomfortable with the technicalities of the systems given the lack of approval. Knowledge around the use of these systems was limited. Re-assessment of HCP perceptions should be performed in the future given the evolving landscape of diabetes technology, recent consensus statements and emerging ethical and legal perspectives.

Patient-driven innovations reported in peer-reviewed journals: a scoping review

BACKGROUND

Awareness of patients' innovative capabilities is increasing, but there is limited knowledge regarding the extent and nature of patient-driven innovations in the peer-reviewed literature.

OBJECTIVES

The objective of the review was to answer the question: what is the nature and extent of patient-driven innovations published in peer-reviewed scientific journals?

ELIGIBILITY CRITERIA

We used a broad definition of innovation to allow for a comprehensive review of different types of innovations and a narrow definition of 'patient driven' to focus on the role of patients and/or family caregivers. The search was limited to years 2008-2020.

SOURCES OF EVIDENCE

Four electronic databases (Medline (Ovid), Web of Science Core Collection, PsycINFO (Ovid) and Cinahl (Ebsco)) were searched in December 2020 for publications describing patient-driven innovations and complemented with snowball strategies.

CHARTING METHODS

Data from the included articles were extracted and categorised inductively.

RESULTS

A total of 96 articles on 20 patient-driven innovations were included. The number of publications increased over time, with 69% of the articles published between 2016 and 2020. Author affiliations were exclusively in high income countries with 56% of first authors in North America and 36% in European countries. Among the 20 innovations reported, 'Do-It-Yourself Artificial Pancreas System' and the online health network 'PatientsLikeMe', were the subject of half of the articles.

CONCLUSIONS

Peer-reviewed publications on patient-driven innovations are increasing and we see an important opportunity for researchers and clinicians to support patient innovators' research while being mindful of taking over the work of the innovators themselves.

Efficient Closed Loop Simulation of Do-It-Yourself Artificial Pancreas Systems

BACKGROUND

Numerical simulations, also referred to as in silico trials, are nowadays the first step toward approval of new artificial pancreas (AP) systems. One suitable tool to run such simulations is the UVA/Padova Type 1 Diabetes Metabolic Simulator (T1DMS). It was used by Toffanin et al. to provide data about safety and efficacy of AndroidAPS, one of the most wide-spread do-it-yourself AP systems. However, the setup suffered from slow simulation speed. The objective of this work is to speed up simulation by implementing the algorithm directly in MATLAB^®/Simulink^®.

METHOD

Firstly, AndroidAPS is re-implemented in MATLAB^® and verified. Then, the function is incorporated into T1DMS. To evaluate the new setup, a scenario covering 2 days in real time is run for 30 virtual patients. The results are compared to those presented in the literature.

RESULTS

Unit tests and integration tests proved the equivalence of the new implementation and the original AndroidAPS code. Simulation of the scenario required approximately 15 minutes, corresponding to a speed-up factor of roughly 1000 with respect to real time. The results closely resemble those presented by Toffanin et al. Discrepancies were to be expected because a different virtual population was considered. Also, some parameters could not be extracted from and harmonized with the original setup.

CONCLUSIONS

The new implementation facilitates extensive in silico trials of AndroidAPS due to the significant reduction of runtime. This provides a cheap and fast means to test new versions of the algorithm before they are shared with the community.

Closed-Loop Insulin Delivery Systems: Past, Present, and Future Directions

Closed-loop (artificial pancreas) systems for automated insulin delivery have been likened to the holy grail of diabetes management. The first iterations of glucose-responsive insulin delivery were pioneered in the 1960s and 1970s, with the development of systems that used venous glucose measurements to dictate intravenous infusions of insulin and dextrose in order to maintain normoglycemia. Only recently have these bulky, bedside technologies progressed to miniaturized, wearable devices. These modern closed-loop systems use interstitial glucose sensing, subcutaneous insulin pumps, and increasingly sophisticated algorithms. As the number of commercially available hybrid closed-loop systems has grown, so too has the evidence supporting their efficacy. Future challenges in closed-loop technology include the development of fully closed-loop systems that do not require user input for meal announcements or carbohydrate counting. Another evolving avenue in research is the addition of glucagon to mitigate the risk of hypoglycemia and allow more aggressive insulin dosing.

Open-source automated insulin delivery: international consensus statement and practical guidance for health-care professionals

Open-source automated insulin delivery systems, commonly referred to as do-it-yourself automated insulin delivery systems, are examples of user-driven innovations that were co-created and supported by an online community who were directly affected by diabetes. Their uptake continues to increase globally, with current estimates suggesting several thousand active users worldwide. Real-world user-driven evidence is growing and provides insights into safety and effectiveness of these systems. The aim of this consensus statement is two-fold. Firstly, it provides a review of the current evidence, description of the technologies, and discusses the ethics and legal considerations for these systems from an international perspective. Secondly, it provides a much-needed international health-care consensus supporting the implementation of open-source systems in clinical settings, with detailed clinical guidance. This consensus also provides important recommendations for key stakeholders that are involved in diabetes technologies, including developers, regulators, and industry, and provides medico-legal and ethical support for patient-driven, open-source innovations.

Use of automated insulin delivery systems in people with type 1 diabetes fasting during Ramadan: An observational study

Fasting among people with type 1 diabetes imposes the risk of metabolic decompensation. Automated insulin dosing systems can allow better glycemic control without safety concerns. The utility in prolonged and repetitive fasting has not been studied. In this observational study, validated glycemic data were reviewed and analyzed from people with type 1 diabetes who observed fasting during Ramadan in 2019 and 2020 using automated insulin dosing systems. Six profiles met the inclusion criteria. The average age was 33.7 ± 4.8 years, diabetes duration was 23.5 ± 7.9 years, body mass index 23.6 ± 1.9 kg/m² and glycated hemoglobin was 6.3 ± 0.2% (45 ± 5 mmol/mol). The average glucose during Ramadan was 7.0 ± 0.5 mmol/L (126 ± 9 mg/dL), coefficient of variation 28.5%, percentage of time in range 3.9–10 mmol/L (70–180 mg/dL) 88.8 ± 7.3% and percentage time <3.9 mmol/L (<70.0 mg/dL) 2.5 ± 1.3%. The number of fasting days was 27.3 ± 3.3, and the number of days where fasting was broken due diabetes was 1 ± 1.5/participant. No significant differences in glycemic outcomes were noted between Ramadan and non‐Ramadan periods. In this first clinically validated study, automated insulin dosing systems showed a safe and effective management strategy to support prolonged and consecutive fasting in people with type 1 diabetes.

The Evolution of Insulin Administration in Type 1 Diabetes

Insulin has been utilized in the treatment of type 1 diabetes (T1D) for 100 years. While there is still no cure for T1D, insulin administration has undergone a remarkable evolution which has contributed to improvements in quality of life and life expectancy in individuals with T1D. The advent of faster-acting and longer-acting insulins allowed for the implementation of insulin regimens more closely resembling normal insulin physiology. These improvements afforded better glycemic control, which is crucial for limiting microvascular complications and improving T1D outcomes. Suspension of insulin delivery in response to actual and forecasted hypoglycemia has improved quality of life and mitigated hypoglycemia without compromising glycemic control. Advances in continuous glucose monitoring (CGM) and insulin pumps, efforts to model glucose and insulin kinetics, and the application of control theory to T1D have made the automation of insulin delivery a reality. This review will summarize the past, present, and future of insulin administration in T1D.

Current Advances of Artificial Pancreas Systems: A Comprehensive Review of the Clinical Evidence

Since Banting and Best isolated insulin in the 1920s, dramatic progress has been made in the treatment of type 1 diabetes mellitus (T1DM). However, dose titration and timely injection to maintain optimal glycemic control are often challenging for T1DM patients and their families because they require frequent blood glucose checks. In recent years, technological advances in insulin pumps and continuous glucose monitoring systems have created paradigm shifts in T1DM care that are being extended to develop artificial pancreas systems (APSs). Numerous studies that demonstrate the superiority of glycemic control offered by APSs over those offered by conventional treatment are still being published, and rapid commercialization and use in actual practice have already begun. Given this rapid development, keeping up with the latest knowledge in an organized way is confusing for both patients and medical staff. Herein, we explore the history, clinical evidence, and current state of APSs, focusing on various development groups and the commercialization status. We also discuss APS development in groups outside the usual T1DM patients and the administration of adjunct agents, such as amylin analogues, in APSs.

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.

Good enough? Parental decisions to use DIY looping technology to manage type 1 diabetes in children

People are using innovative internet of things technologies to gain individualised management of their type 1 diabetes. The #WeAreNotWaiting movement supports them to build their own hybrid closed loop systems and access their real time blood sugar data via any web connected device. A small number of parents in Australia use such DIY looping systems to manage their child's type 1 diabetes, but these systems have not been approved by the Therapeutic Goods Administration in Australia, creating ethical dilemmas for clinicians about how to respond to the use of medical devices that are not registered on the Australian Register of Therapeutic Goods. This article considers whether the use of DIY looping is in the best interests of the child and, if not, whether intervention in parental decision making is justified to prevent harm to the child. It addresses the ongoing duty of healthcare professionals to provide care to children who are 'looping.' Reference is made to findings from a study, Personalised Closed Loop Systems for Childhood Diabetes, to illustrate stakeholders' perceptions of benefits and harms of DIY looping systems. I conclude that the decision of parents to use DIY looping technology could be considered to be in a child's best interests, broadly defined, and falls within the Zone of Parental Discretion, however healthcare practitioners who support parents may have professional concerns in doing so.

A real-world study of user characteristics, safety and efficacy of open-source closed-loop systems and Medtronic 670G

We report a real-world evaluation of the first commercially approved automated insulin delivery (AID) system, MiniMed 670G (670G), and open source-automated insulin delivery (OS-AID) systems. This was undertaken as a retrospective observational study in adults with type 1 diabetes using AID systems for 6 months or longer in a publicly funded health service using clinically validated data. Sixty-eight adults (38 670G, 30 OS-AID systems) were included. OS-AID system users were younger, had a shorter diabetes duration and a higher education status. OS-AID systems displayed a significantly better change in HbA1c (median -0.9% [-0.4%, -1.1%] vs. -0.1% [IQR -0.7%, 0.2%], P = .004) and time in range 3.9-10 mmol/L (mean 78.5%, SD ± 12.0% vs. 68.2% ± 14.7%, P = .024) compared with 670G. Both systems showed minimal hypoglycaemia, with OS-AID systems revealing significantly improved secondary outcomes of mean glucose and percentage of time more than 10 mmol/L, with a higher percentage of time of less than 3 mmol/L. OS-AID system users displayed improved glycaemic outcomes with no clinical safety concerns compared with 670G, although higher weight-adjusted insulin dose and weight gain were noted. The study highlights key differences in OS-AID system user characteristics that are important for interpreting real-world findings from recent OS-AID system studies.

How Adults with Type 1 Diabetes Are Navigating the Challenges of Open-Source Artificial Pancreas Systems: A Qualitative Study

Objective: An emerging group of people with type 1 diabetes are building and using their own artificial pancreas systems (APS). Currently, these "user-led," open-source systems are not endorsed by regulatory bodies. People face multiple challenges when building and using open-source APS (e.g., lacking required technical knowledge, difficulties sourcing hardware). We explored the experiences of adults with type 1 diabetes using open-source APS to understand how they are navigating these challenges. Research Design and Methods: We conducted semistructured telephone interviews (October 2018 to January 2019) with Australian adults about their experiences using an open-source APS. Interviews were recorded, transcribed, and analyzed thematically. Results: Participants included 23 adults with type 1 diabetes, aged 25-64 years, 10 (43%) women, with 1-34 months of experience of open-source APS. Participants used four key strategies to navigate challenges: (1) peer support, (2) self-sufficiency, (3) risk management, and (4) trade-offs. Participants relied on peer support and self-sufficiency to fill perceived gaps in professional and industry support. They felt that using an open-source solution was no riskier than previous management and demonstrated a conscious weighing-up of risks. Overall, participants felt that the experienced benefits for their physical health and quality of life outweighed the challenges and potential risks. Conclusions: Adults with type 1 diabetes are applying several interweaving psychosocial and practical strategies to navigate the challenges of building and using open-source APS. The findings highlight the importance of health professionals' showing support and understanding for those choosing to use an open-source APS.

Efficacy of advanced hybrid closed loop systems for the management of type 1 diabetes in children

Over the last years significant advances have been achieved in the development of technologies for diabetes management. Continuous subcutaneous insulin infusion (CSII), continuous glucose monitoring (CGM), predictive low glucose management (PLGM), hybrid closed loop (HCL) and advanced hybrid closed loop (AHCL) systems allow better diabetes management, thus reducing the burden of the disease and the risk of chronic complications. This review summarizes the main characteristics of the currently available HCL and AHCL systems and their primary effects in children and adolescents with type 1 diabetes (T1D). The findings of trials assessing the glucose control (time in range, HbA1c values, hypoglycemic events), the health-related quality of life and the existing limits of the use of these technologies are reported. The most recent data clearly confirm the ability of the HCL and AHCL insulin delivery systems to safely achieve a significant improvement of glucose control and quality of life in the pediatric population with T1D. Further studies are underway to overcame current barriers and future improvements in the usability of these technologies are awaited to facilitate their use in the routine clinical practice. The HCL and AHCL algorithms are the key features of today's insulin delivery systems that mark a crucial step towards fully automated closed loop systems.

Review of Self-Reported Data from UK Do-It-Yourself Artificial Pancreas System (DIYAPS) Users to Determine Whether Demographic of Population Affects Use or Outcomes

INTRODUCTION

This study investigates the use of do-it-yourself artificial pancreas systems (DIYAPS) in the UK, and whether self-reported outcomes associated with them are affected by the demographics of the user.

METHODS

An online survey was conducted to assess user demographic data and self-reported time-in-range (TIR) outcomes. Statistical analysis was undertaken to review the results and check whether there were major differences in change in TIR across age, gender and duration of diabetes.

RESULTS

Of 253 valid responses to the survey across a wide age range of users, 74.4% related to adult users and 25.6% related to under-16s. The majority (65.6%) used AndroidAPS, but there was greater use of Loop (43.1%) amongst under-16s than amongst adults (25.9%). Correspondingly, more under-16s (40.0%) than adults (24.3%) used Omnipod Eros. A 17.3% (± 13.7%) increase in time in range was reported across all participants, with no significant differences observed between age groups, genders or diabetes duration groups (p > 0.05).

CONCLUSIONS

The results show that these systems are being used by both genders, and that users cover a wide range of ages and diabetes durations. They also show that improvements in self-reported DIYAPS healthcare outcomes may not be specific to any particular age, gender or duration of diabetes, and the results may provide additional insights into the applicability of the algorithms by demographic. This study may also inform healthcare professionals about the use and effectiveness of DIYAPS solutions.

Current treatment options and challenges in patients with Type 1 diabetes: Pharmacological, technical advances and future perspectives

Type 1 diabetes mellitus imposes a significant burden of complications and mortality, despite important advances in treatment: subjects affected by this disease have also a worse quality of life-related to disease management. To overcome these challenges, different new approaches have been proposed, such as new insulin formulations or innovative devices. The introduction of insulin pumps allows a more physiological insulin administration with a reduction of HbA1c level and hypoglycemic risk. New continuous glucose monitoring systems with better accuracy have allowed, not only better glucose control, but also the improvement of the quality of life. Integration of these devices with control algorithms brought to the creation of the first artificial pancreas, able to independently gain metabolic control without the risk of hypo- and hyperglycemic crisis. This approach has revolutionized the management of diabetes both in terms of quality of life and glucose control. However, complete independence from exogenous insulin will be obtained only by biological approaches that foresee the replacement of functional beta cells obtained from stem cells: this will be a major challenge but the biggest hope for the subjects with type 1 diabetes. In this review, we will outline the current scenario of innovative diabetes management both from a technological and biological point of view, and we will also forecast some cutting-edge approaches to reduce the challenges that hamper the definitive cure of diabetes.

Diabetes technologies - what the general physician needs to know

Technology has revolutionised our society. From the creation of the internet to smartphones and applications (apps), technology has changed how we communicate with each other, undertake regular tasks in our lives and access information at our fingertips. Technology has also transformed how we deliver healthcare with electronic patient records, more sensitive imaging modalities and newer treatments that are less invasive yet more cost-effective. The management of diabetes mellitus is an area that has kept pace with this revolution. With the emergence of a range of widely used technological options that can improve quality of life and metabolic outcomes, general physicians need to be aware of their application in diabetes, as well as how to manage acute diabetes presentations in people using these devices. This article aims to improve the knowledge that general physicians may have with diabetes technologies and guide them on the acute management in people using these technologies.

Efficacy, safety, and user experience of DIY or open-source artificial pancreas systems: a systematic review

The do-it-yourself artificial pancreas system (DIYAPS) is a patient-driven initiative with the potential to revolutionise diabetes management, automating insulin delivery with existing pumps and CGM combined with open-source algorithms. Given the considerable interest in this topic within the diabetes community, we have conducted a systematic review of DIYAPS efficacy, safety, and user experience. Following recognised procedures and reporting standards, we identified 10 eligible publications of 730 participants within the peer-reviewed literature. Overall, studies reported improvements in time in range, HbA1c (glycated haemoglobin), reduced hypoglycaemia, and improved quality of life with DIYAPS use. While results were positive, the identified studies were small, and the majority were observational and at high risk of bias. Further research including well-designed randomised trials comparing DIYAPS with appropriate comparators is recommended.

Ramadan and Diabetes: A Narrative Review and Practice Update

Fasting in the Islamic month of Ramadan is obligatory for all sane, healthy adult Muslims. The length of the day varies significantly in temperate regions-typically lasting ≥ 18 h during peak summer in the UK. The synodic nature of the Islamic calendar means that Ramadan migrates across all four seasons over an approximately 33-year cycle. Despite valid exemptions, there is an intense desire to fast during this month, even among those who are considered to be at high risk, including many individuals with diabetes mellitus. In this review we explore the current scientific and clinical evidence on fasting in patients with diabetes mellitus, focussing on type 2 diabetes mellitus and type 1 diabetes mellitus, with brief reviews on pregnancy, pancreatic diabetes, bariatric surgery, the elderly population and current practice guidelines. We also make recommendations on the management of diabetes patients during the month of Ramadan. Many patients admit to a do-it-yourself approach to diabetes mellitus management during Ramadan, largely due to an under-appreciation of the risks and implications of the rigors of fasting on their health. Part of the issue may also lie with a healthcare professional's perceived inability to grasp the religious sensitivities of Muslims in relation to disease management. Thus, the pre-Ramadan assessment is crucial to ensure a safe Ramadan experience. Diabetes patients can be risk-stratified from low, medium to high or very high risk during the pre-Ramadan assessment and counselled accordingly. Those who are assessed to be at high to very high risk are advised not to fast. The current COVID-19 pandemic upgrades those in the high-risk category to very high risk; hence a significant number of diabetes patients may fall under the penumbra of the 'not to fast' advisory. We recognize that fasting is a personal choice and if a person chooses to fast despite advice to the contrary, he/she should be adequately supported and monitored closely during Ramadan and for a brief period thereafter. Current advancements in insulin delivery and glucose monitoring technologies are useful adjuncts to strategies for supporting type 1 diabetes patients considered to be high risk as well as 'high-risk' type 2 patients manage their diabetes during Ramadan. Although there is a lack of formal trial data, there is sufficient evidence across the different classes of therapeutic hypoglycaemic agents in terms of safety and efficacy to enable informed decision-making and provide a breadth of therapeutic options for the patient and the healthcare professional, even if the professional advice is to abstain. Thus, Ramadan provides an excellent opportunity for patient engagement to discuss important aspects of management, to improve control in the short term during Ramadan and to help the observants understand that the metabolic gains achieved during Ramadan are also sustainable in the other months of the year by maintaining a dietary and behavioural discipline. The application of this understanding can potentially prevent long-term complications.

Closed-loop control in insulin pumps for type-1 diabetes mellitus: safety and efficacy

INTRODUCTION

Type 1 diabetes is a lifelong disease with high management burden. The majority of people with type 1 diabetes fail to achieve glycemic targets. Algorithm-driven automated insulin delivery (closed-loop) systems aim to address these challenges. This review provides an overview of commercial and emerging closed-loop systems.

AREAS COVERED

We review safety and efficacy of commercial and emerging hybrid closed-loop systems. A literature search was conducted and clinical trials using day-and-night closed-loop systems during free-living conditions were used to report on safety data. We comment on efficacy where robust randomized controlled trial data for a particular system are available. We highlight similarities and differences between commercial systems.

EXPERT OPINION

Study data shows that hybrid closed-loop systems are safe and effective, consistently improving glycemic control when compared to standard therapy. While a fully closed-loop system with minimal burden remains the end-goal, these hybrid closed-loop systems have transformative potential in diabetes care.

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.