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OpenAPS (oref0)

Open-source community (OpenAPS / #WeAreNotWaiting)

What it is

The original do-it-yourself closed-loop system, launched in 2015. Its oref0/oref1 reference algorithm is the open-source code that seeded much of the movement and powers AndroidAPS and Trio (with adaptations). Foundational and rigorously evidenced (the CREATE randomized trial used this algorithm), but the classic rig-based OpenAPS itself is now legacy-leaning — many users now run its descendants.

Editorial review: .

Source dates appear in the references where available; this record has no dated citation metadata.

Trial status, labels and access can change between reviews. How we review the evidence · How to read the evidence

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Available nowStrong evidenceopen-sourcediy

Evidence behind this assessment

Key evidence notes. Study results, product eligibility and access answer different questions.

Who was studied?
Study populations and analysis groups vary. Product age limits alone do not describe who was studied.See the linked studies and their populations →
Benefit or performance
Algorithm sophistication: The reference oref0/oref1 algorithm — prediction, autosensitivity, super-micro-bolus and unannounced-meal handling; proven in the CREATE randomized trial, though its descendants now extend it further.Read the supporting discussion; this assessment has no individually linked citation.
Important harms and treatment burden
Read the safety discussion and original sources. A missing summary does not establish safety.
Approval and country access
Country-specific approval and access are not summarized in this record.Approval, trial recruitment, local supply and funding are separate. Check the cited label or access source.
Follow-up and remaining uncertainty
Read the full discussion and original sources for follow-up duration and study limitations.
Editorial score: calculation and evidence

A weighted editorial judgment on a 0–100 scale, not a probability of success or a measured treatment effect. Higher criterion scores mean more favorable assessments.

Default calculation: 82 × 25 + 45 × 20 + 96 × 20 + 80 × 15 + 25 × 20 = 6570; divide by total weight 100. Unrounded weighted result: 65.7.

Algorithm sophistication82

The reference oref0/oref1 algorithm — prediction, autosensitivity, super-micro-bolus and unannounced-meal handling; proven in the CREATE randomized trial, though its descendants now extend it further.

Hardware support45

Tied to a narrow set of older Medtronic pumps and a Linux 'rig'; the original Intel Edison hardware is discontinued.

Customizability96

The defining open reference design — parameters, predictions and dosing decisions are inspectable and tunable in open source.

Community & docs80

Extensive ReadTheDocs documentation and a large founding #WeAreNotWaiting community.

Ease of setup25

Among the hardest to build: flashing a Linux single-board-computer rig, sourcing legacy hardware, and self-maintenance via the command line.

The full picture

OpenAPS — the Open Source Artificial Pancreas System — is the project that started DIY closed-looping. After building a personal system called #DIYPS, Dana Lewis and Scott Leibrand (with Ben West, who reverse-engineered communication with older Medtronic pumps) open-sourced their work as OpenAPS in February 2015, under the community banner #WeAreNotWaiting.1 Its purpose is "an open and transparent effort to make safe and effective basic Artificial Pancreas System (APS) technology widely available" to anyone willing to build their own.2

Platform. Classic OpenAPS is not a phone app. It runs on a small Linux "rig" — historically an Intel Edison + Explorer Board, or a Raspberry Pi — that sits between your pump and continuous glucose monitor (CGM) and adjusts insulin every five minutes.1 The Edison hardware is discontinued, which is a large part of why the project is now legacy-leaning.3

Algorithm lineage and sophistication. OpenAPS publishes the reference design and the oref0 / oref1 algorithm that much of the field builds on.4 It calculates insulin-on-board, predicts where glucose is heading, and sets temporary basal rates toward a target.4 oref1 added super-micro-boluses (SMB) for faster mealtime response and unannounced-meal (UAM) handling, plus autosensitivity that adapts to changing insulin needs.4 This code lineage powers AndroidAPS and Trio (with adaptations), so OpenAPS's importance far exceeds its current direct user base.5

Supported pumps and CGMs. Direct OpenAPS works only with specific older Medtronic MiniMed pumps (e.g. 515/715, 522/722, and 554/754 Veo on early firmware), because newer firmware blocks the remote commands looping needs.6 Supported CGMs include Dexcom G4/G5/G6 and Medtronic Enlite, with other sensors usable via Nightscout.7

Customizability. Because it is the open reference implementation, parameters and dosing decisions are inspectable and tunable in open source — the core promise of the movement.4

Community, docs, setup and legal status. Documentation is extensive (the OpenAPS ReadTheDocs), but building a rig is genuinely hard: flashing a single-board computer and maintaining it from the command line.1 Crucially, OpenAPS is not a regulated or commercial product — there is no company behind it, and the trademark is "not authorized for use by any commercial entity"; you build it and you are responsible for it.2

Clinical evidence. This is where OpenAPS is unusually strong for a DIY tool. The CREATE randomized controlled trial tested the OpenAPS 0.7.0 algorithm (inside a modified AndroidAPS) against a sensor-augmented pump in 97 children and adults; time-in-range rose from 61% to 71% with the loop versus a fall in controls — about 3 hours 21 minutes more per day in range — with no severe hypoglycemia or ketoacidosis.5 Its 24-week continuation phase (about 48 weeks total use) confirmed a sustained ~12-point time-in-range benefit and a 0.5% HbA1c reduction.8 Observational and systematic-review data — including a pediatric survey and a systematic review of 730 participants — consistently show improved time-in-range, lower HbA1c and good quality of life, while noting most pre-RCT evidence was observational.910

What's coming. The future of this algorithm is largely its descendants: oref code lives on and evolves inside AndroidAPS and the newer Trio, where active development now concentrates.53 OpenAPS itself remains available and its reference design remains published, but the oref0 codebase has had no new release since 2022.3

The algorithm also remains a research substrate. A 2026 research letter in Diabetes Care from a Stanford group reports that pairing high-potency GLP-1 receptor agonists with the OpenAPS automated insulin dosing algorithm removed the need to announce meals in order to hit glycemic goals.11 Two caveats worth holding onto: this is a short letter rather than a full trial report — it carries no published abstract, so we can point to its conclusion but not to effect sizes, sample size or how durable the result is — and GLP-1 receptor agonists are not approved for type 1 diabetes. Treat it as an early and interesting signal about where unannounced-meal looping might go, not as a recipe to copy.

Sources

  1. [1]

    OpenAPS. Project History — DIYPS, founding by Dana Lewis, Scott Leibrand and Ben West, and the February 2015 open-source launch. OpenAPS ReadTheDocs (accessed 2026). https://openaps.readthedocs.io/en/latest/docs/Resources/history.html

  2. [2]

    OpenAPS. What is #OpenAPS? — mission statement, self-build/self-responsibility, and non-commercial trademark. OpenAPS.org (accessed 2026). https://openaps.org/what-is-openaps/

  3. [3]

    openaps/oref0 — releases and commit history. oref0 0.7.0 (10 Nov 2019) is the version tested in the CREATE trial; the head release tag is v0.7.1 (19 June 2022), and there has been no release since. GitHub (accessed July 2026). https://github.com/openaps/oref0/releases

  4. [4]

    OpenAPS. OpenAPS Reference Design — oref0/oref1 algorithm, IOB, prediction, temp-basal dosing and SMB (UAM and autosensitivity are documented in linked docs sub-pages). OpenAPS.org (accessed 2026). https://openaps.org/reference-design/

  5. [5]

    Burnside MJ, Lewis DM, Crocket HR, et al. Open-Source Automated Insulin Delivery in Type 1 Diabetes (CREATE trial; OpenAPS 0.7.0 algorithm). N Engl J Med 387:869-881 (2022). doi:10.1056/NEJMoa2203913. https://pubmed.ncbi.nlm.nih.gov/36069869/

  6. [6]

    OpenAPS. Compatible insulin pumps (older Medtronic models and firmware limits). OpenAPS ReadTheDocs (accessed 2026). https://openaps.readthedocs.io/en/latest/docs/Gear%20Up/pump.html

  7. [7]

    OpenAPS. Information about compatible CGMs (Dexcom G4/G5/G6, Medtronic Enlite, Nightscout). OpenAPS ReadTheDocs (accessed 2026). https://openaps.readthedocs.io/en/latest/docs/Gear%20Up/CGM.html

  8. [8]

    Burnside MJ, Lewis DM, Crocket HR, et al. Extended Use of an Open-Source Automated Insulin Delivery System: 24-Week Continuation Phase Following the CREATE RCT. Diabetes Technol Ther 25:250-259 (2023). doi:10.1089/dia.2022.0484. https://pubmed.ncbi.nlm.nih.gov/36763345/

  9. [9]

    Braune K, O'Donnell S, Cleal B, et al. Real-World Use of Do-It-Yourself Artificial Pancreas Systems in Children and Adolescents With Type 1 Diabetes: Online Survey and Self-Reported Outcomes. JMIR Mhealth Uhealth 7:e14087 (2019). doi:10.2196/14087. https://pubmed.ncbi.nlm.nih.gov/31364599/

  10. [10]

    Asarani NAM, Reynolds AN, Elbalshy M, et al. Efficacy, safety, and user experience of DIY or open-source artificial pancreas systems: a systematic review (730 participants). Acta Diabetol 58:539-547 (2021). doi:10.1007/s00592-020-01623-4. https://pubmed.ncbi.nlm.nih.gov/33128136/

  11. [11]

    Akcan T, Kingman RS, Morgan M, et al. Use of High-Potency GLP-1 Receptor Agonists With OpenAPS Automated Insulin Dosing Algorithm Eliminates Need for Meal Announcements to Achieve Glycemic Goals. Diabetes Care 49(3):e36-e37 (2026). doi:10.2337/dc25-2569. Research letter — no published abstract, so only the stated conclusion can be cited. https://pubmed.ncbi.nlm.nih.gov/41511751/