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Fully closed-loop systems: can people with type 1 diabetes just do it? Insights from open-source systems
Rayhan Lal1,2, Katarina Braune3,4, Dana M Lewis5
1Departments of Medicine & Pediatrics, Division of Endocrinology, Stanford University, Stanford, CA, USA.
Diabetologia
|January 19, 2026
Summary
Open-source automated insulin delivery (OS-AID) systems show promise for diabetes management without meal announcements. These systems offer comparable glucose control to commercial options, potentially reducing user burden but requiring expert configuration.
Area of Science:
- Endocrinology
- Biomedical Engineering
- Diabetes Technology
Background:
- Automated insulin delivery (AID) systems have advanced diabetes care, reducing user interaction for glucose management.
- Commercial hybrid closed-loop (HCL) systems require manual meal announcements, limiting real-world automation.
- Open-source AID (OS-AID) systems, developed by the diabetes community, offer potential for operation without meal announcements.
Purpose of the Study:
- To review the current status and future prospects of AID systems that do not require meal announcements.
- To focus on real-world insights from OS-AID technologies.
- To evaluate the potential for reduced user management burden with OS-AID.
Main Methods:
- Review of current literature and clinical trials on AID systems without meal announcement.
- Synthesis of user and healthcare professional experiences with OS-AID.
- Analysis of emerging clinical evidence regarding OS-AID performance.
Main Results:
- OS-AID systems demonstrate effective glucose management comparable to HCL systems, without requiring meal announcements.
- Clinical trials suggest OS-AID can achieve similar glycaemic outcomes with potentially less user burden.
- Challenges include the need for expert configuration and managing rapid physiological changes (e.g., exercise).
Conclusions:
- Successful implementation of AID without meal announcement necessitates advanced algorithms, personalization, and clinician involvement.
- Future advancements may include adjunctive therapies, AI, and enhanced physiological modeling for improved performance.
- The goal is to achieve wider adoption and 'set-and-forget' functionality in diabetes management.
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