Open-source automated insulin delivery: international consensus statement and practical guidance for health-care professionals
Open accessAbstract
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.
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OS-AID algorithms provide precise code governing operation, allowing HCP and people with diabetes to understand risks and benefits.
“Open-source automated insulin dosing (OS-AID) algorithms provide the precise code that governs their operation, so health care professionals and people with diabetes can have a more complete understanding of risks and benefits (254).”
From 7. Diabetes Technology: Standards of Care in Diabetes—2025 (2025) · cites this paper as [254]
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References 90 · Cited by 130
Research works printed but not linked: 2
- [51]Bazdarska Y, Iotova V, Mladenov V, Advantages from ‘do-it-yourself’ loops among children and adolescents in Varna’s Diabetes Center. Scr Sci Med 2019; 51: 54– 61.
- [60]Lal R, Quinlan A, Desborough L, Nykaza E. Optimizing formulas for basal, carb ratio and sensitivity factor for predictive controllers: lessons learned from Loop. The Official Journal of Advanced Technologies & Treatments for Diabetes Conference; June 2–5, 2021 (abstr O008/#282).
- Authors
- Braune, K., Lal, R. A., Petruželková, L., Scheiner, G., Winterdijk, P., Schmidt, S., Raimond, L., Hood, K. K., Riddell, M. C., Skinner, T. C., Raile, K., & Hussain, S.
- Affiliations
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin (DE)
- Stanford Medicine (US)
- University Hospital in Motol (CZ)
- Steno Diabetes Center Copenhagen (DK)
- York University (CA)
- University of Copenhagen (DK)
- Charité – Universitätsmedizin Berlin (DE)
- St Thomas' Hospital (GB)
- Corresponding author
- Lal, Rayhan A
- Hussain, Sufyan
- Venue
- The Lancet Diabetes & Endocrinology
- Publisher
- Elsevier BV
- Published
- 2022-01
- Volume
- 10
- Issue
- 1
- Pages
- 58-74
- ISSN
- 2213-8587 (ISSN-L)
- PMC
- PMC8720075
- OpenAlex
- W3214498242
- Cited by
- 130
- References
- 90
- Citations by year
- 2026: 18 · 2025: 20 · 2024: 28 · 2023: 34 · 2022: 29 · 2021: 1
- FWCI
- 17.21
- Type
- journal article
- Language
- en
- Update notices
- erratum (2022-01-01)
- Open access
- Licence
- Locations
- The Lancet Diabetes & Endocrinology (publishedVersion)
- PubMed (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, cc-by-nc-nd)
- PubMed Central (acceptedVersion)
- Figshare (submittedVersion)
- Research Portal (King's College London) (submittedVersion)
- Funders
- Novo Nordisk Fonden
- Stiftung Charité
- Berlin Institute of Health
- Region Hovedstaden
- Horizon 2020
- National Institute of Diabetes and Digestive and Kidney Diseases
- Wellcome Trust
- Technology Agency of the Czech Republic (TJ02000342)
- Stanford Maternal and Child Health Research Institute
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
- Keywords
- type 1 diabetes, user innovation
- MeSH terms
- Diabetes Mellitus, Type 1, Health Personnel, Humans, Hypoglycemic Agents, Insulin, Insulin Infusion Systems
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