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

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Summary

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.

Introduction

Advances in treatments and technologies have notably improved care for people with diabetes. However, a substantial proportion of people with diabetes are still unable to reach the recommended treatment targets and frequently experience hypoglycaemia and hyperglycaemia, reducing their day-to-day function and exposing them to future medical and psychological complications. Automated insulin delivery (AID) systems, also called closed-loop or artificial pancreas systems, automatically adjust some aspects of insulin dosing by use of an algorithm in response to continuous data from a glucose sensor, data from an insulin pump along with additional information.1 These systems are safe and effective in increasing time in range (TIR), minimising variability in glucose concentrations detected by continuous glucose monitoring (CGM) sensors and hypoglycaemia in people with diabetes of various ages under many conditions.2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12

Despite the notable research and commercial drives, given the lengthy and complex development and approval processes, few AID systems have been approved by regulators. These commercial systems are constrained by device ecosystem options and are not universally available, as approval, access, regulatory, and reimbursement policies for diabetes technologies vary considerably between countries.

Given these limitations, open-source automated insulin delivery (ie, open-source AID) systems have been co-created and supported by online communities who are directly affected by diabetes. Open-source refers to freely available software code. Although some people describe these systems as do-it-yourself, we prefer the term open-source, given the collaborative effort.

These communities have created accessible resources that provide detailed instructions for set-up and use. We estimate that over 10 000 individuals worldwide are using open-source AID systems, and uptake continues to increase globally.13 Despite their increasing use, there is no professional guidance available for health-care professionals to support their use in clinical settings.14 Although no evidence exists from randomised control trials (RCTs), real-world observational outcomes indicate effectiveness and safety for these systems,15, 16, 17, 18, 19, 20, 21 with improved quality of life and sleep quality in people who use open-source AID systems.18, 22, 23, 24, 25, 26 Nevertheless, there are limitations in the evidence, with potential for selection bias, as detailed in this manuscript.

As with commercial systems, the control strategies that are used by open-source algorithms vary. Open-source AID systems are designed for considerable user customisation, making a direct comparison of the available systems challenging. Additionally, experts, patient organisations, and diabetes charity position statements from different regions provide variable opinions on the legal position of open-source AID systems for health-care professionals.27, 28, 29, 30, 31, 32 As a result, many health-care teams worldwide are uncertain how to best support people with diabetes who are using open-source AID systems in clinical care.

This international consensus statement and practical guidance review provides detailed recommendations for health-care professionals caring for individuals with diabetes who are using open-source AID systems. We consider evidence on effectiveness of AID systems, user-reported outcomes and lived experiences, safety aspects, potential limitations, and challenges that are associated with open-source AID systems; ethical and legal factors; and hands-on advice on how to provide support to health-care professionals in clinical practice. Although we do not universally recommend the use of open-source over commercial AID systems, we propose that the best interest of the individual should be balanced against the risks of using open-source AID systems.19, 23, 33, 34, 35, 36, 37, 38, 39

Section snippets

Methods

KB, RAL, and SH formed a steering and writing committee of health-care professionals (ie, endocrinologists, educators, exercise physiologists, and psychologists with clinical experience in open-source AID systems or publication track record on this topic) in February, 2020, to develop best practice guidance and statements that are up to date. An international group of 44 health-care professionals and four legal experts with clinical experience and expertise on the topic of open-source AID

Overview of open-source AID systems

Several open-source AID algorithms exist: oref0/oref1 and the Loop algorithm. OpenAPS implements oref0/oref1 in a program that runs on a Linux-based mini-computer (appendix p 5), whereas AndroidAPS executes oref0/oref1 on an Android app (appendix p 6) and FreeAPS X implements oref0/oref1 on an iPhone. The Loop algorithm is implemented in the iOS app Loop (appendix p 7, table).

The development of the first open-source AID system, OpenAPS, proceeded from the acquisition of CGM data (initially

Summary of existing evidence

The current scientific literature on open-source AID systems is mainly based on evidence in the real world, which might include different software versions running on a variety of hardware.40 In addition to glycaemic improvements, there is preliminary evidence that open-source AID systems can have a positive effect on quality of life, sleep quality, fear of hypoglycaemia, and on other aspects of everyday life.18, 22, 23, 24, 25, 26 A multinational survey assessing motivations for building an

Technicalities of open-source and commercial AID systems

Since the launch of Medtronic's 670G system in 2016, further commercial AID systems have been approved in selected countries (table). Having one company responsible for the creation of the CGM device, insulin pump, and algorithm is a challenging and expensive endeavour. Thus, the FDA has defined three interoperable components: integrated CGM (iCGM) device, alternate controller enabled (ACE) insulin pump, and interoperable automated glycaemic controller (iAGC) to accelerate the development

Access and availability

Open-source AID algorithms are available online and freely accessible on the software development platform GitHub. They can be set up on a variety of hardware that are available in a wide range of countries (table). Additional hardware might be needed depending on the particular set-up. A limitation of commercial systems is that their regulatory status and availability is limited to particular regions and groups. They may carry additional costs for the iAGC or require a pump upgrade. Hence,

Safety

Living with diabetes and self-managing insulin therapy inherently carries risk, with both underdelivery and overdelivery of insulin posing potentially substantial health consequences. Existing AID systems, including open-source systems, are developed for optimisation of safety, with the algorithms prioritising avoidance of hypoglycaemia. Any users having problems with an open-source system can report the issue to the development team or community for support. For issues requiring notable code

Potential limitations and challenges

No AID system is perfect. Commercial and open-source AID systems share many common limitations. Health-care providers might have specific concerns regarding open-source AID systems (panel 1). Health-care professionals' experience and ability to support users might be limited. Open-source AID systems do not have regulatory approval, official onboarding programmes (ie, educational programmes for users, which are often provided by the manufacturers of commercial AID systems), or a customer

Ethical considerations

Intensive insulin therapy and self-management are the basis of optimal glycaemic outcomes.61 The daily tasks that are required to reach these outcomes by people with diabetes or their caregivers can represent a substantial challenge. For many people, limiting access to treatments or constraining current treatments exacerbates this burden and adds unnecessary psychological distress.62, 63

One of the fundamental driving principles of diabetes care is respecting people with diabetes, and where

Legal challenges

Reverse engineering (eg, understanding how system components communicate65) is explicitly permitted in Europe.66 However, the use of open-source AID systems is not approved by regulatory bodies.36, 39 Substantial variation exists between different countries and regions in regulatory approval processes and potential legal consequences for health-care professionals supporting the use of unregulated systems. Regulatory approval does not preclude liability. Health-care professionals might be

Children and adolescents

At least 20% of users of open-source AID systems are children or adolescents (ie, aged 19 years or younger).13, 17, 25 Frequently changing insulin requirements, diurnal variability in counter-regulatory hormones (particularly during puberty), and unpredictable activity make children and adolescents ideal candidates for AID systems. The uptake of diabetes technology is particularly high among young children in countries where these treatment modalities are accessible.67 However, not all

Psychological aspects

Meeting glycaemic targets should always be balanced against treatment burden and its effect on emotional wellbeing. Extensive research and clinical experience show the bidirectional link between psychosocial functioning, defined as a person's thoughts, feelings, and behaviours, and diabetes management and outcomes. The need for attention to psychosocial functioning from the health-care professional is emphasised in therapy guidelines70, 71 and is also essential when considering support of

Recommendations for safe practice

The evidence for safety and effectiveness along with ethical considerations provide a rationale for health-care professionals to consider supporting the use of these systems in their clinical settings. We advocate the use of evidence-based ethical treatments, where they can be used within purview of local and federal regulations. We also advocate that device manufacturers should offer transparency on the functional aspects of their products. Building on previous statements from diabetes

Conclusion

Health-care professionals have an important role in facilitating and supporting people with diabetes to obtain beneficial outcomes from AID systems. Although we do not suggest that open-source AID systems be universally recommended over commercial options, strong ethical reasons support the use of open-source AID systems, with safety and effectiveness data derived from real-world evidence. This consensus guide (panel 6) provides an overview for health-care professionals to enable them to

Search strategy and selection criteria

We identified references for this consensus statement through searches of PubMed for articles published between Sept 30, 1993, and June 30, 2021, by use of the terms “automated insulin delivery”, “closed-loop insulin delivery”, “artificial pancreas”, “Do-it-Yourself artificial pancreas”, “open-source AID”, “OpenAPS”, and “AndroidAPS”. Additionally, we reviewed position statements and legal expert opinions regarding open-source automated insulin delivery systems or do-it-yourself artificial

Declaration of interests

In addition to their professional roles, KB, RAL, PW, MCR, KR, GS, KKH, and SH have personal experience of using open-source AID systems. KB received research grants from the European Commission's Horizon 2020 Research and Innovation programme, the Berlin Institute of Health Digital Clinician Scientist programme, and SPOKES Wellcome Trust; and has received grants from the Berlin Institute of Health Junior Clinician Scientist programme, Stiftung Charité, and the German Diabetes Association. KB

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