Review: Commercially Developed, Open-Source AID Systems Deemed Safe and Effective

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Gleaning data from real-world studies, investigators determined that commercially developed and open-source automated insulin dosing systems are safe and effective.

A systematic review summarizing real-world evidence on available automated insulin dosing(AID) systems concluded that commercially developed and open-source AID systems are safe and effective treatment options for people with diabetes (PwD) across several age groups and genders.

To the best of the investigators’ knowledge, the current systematic review is the first to focus on real-world studies of several AID systems. Findings of the review were published in Diabetic Medicine.

In contrast with commercially developed systems, open-source AID systems are developed by a community of PwD who used freely available source codes and documentation found online.

It’s estimated over 10,000 patients currently use these systems—among them children and adolescents whose caretakers build the systems on their behalf, researchers explained. “None of the open-source AID systems have so far received regulatory approval; liability does not apply as in commercially developed medical devices,” they added.

Currently, no data from randomized controlled trials (RCT) on open-source AID systems exist, but one study is in progress.

To conduct the review, investigators gleaned data from 21 studies published between 2018 and 2021: 12 on Medtronic 670G; one on Tandem Control-IQ; 1 on Diabeloop DBLG1; 2 on AndrioidAPS; 1 on OpenAPS; 1 on Loop; and 3 comparing various types of AID systems.

Primary endpoints for this review included percentage time-in-range (TIR; 70–180 mg/dl, 3.9–10.0 mmol/L), change in TIR, and glycated hemoglobin (A1C).

Out of 12 studies evaluating the real-world use of the Medtronic 670G—the first AID system to gain US regulatory approval in 2016—10 studies found significant improvements in TIR, and 5 reported significant improvements in A1C.

In addition, real-world data collected over 7 weeks from 1435 US-based PwD using the Tandem Control IQ algorithm showed significant improvement in TIR after 3 weeks and at the end of the study, from 78.2% (70.2%–85.1%) to 79.2% (70.3%–86.2%; P< .001), without increasing time-below-range (TBR). The study participants presented relatively high TIR prior to using AID when compared with the general type 1 diabetes (T1D) population.

A study assessing the DBLGI system among 25 users aged >22 years demonstrated improvements in TIR from an average (SD) 53% (16.4%) to 69.7% (P < .0001) and a reduction in A1C from 63 (−14) to 54 mmol/mol (7.9 [0.9%] to 7.1% [P < .001]), with no serious adverse events.

Of 7 studies analyzing the 3 open-source AID systems, OpenAPS, AndroidAPS, and Loop, all demonstrated significantly decreased A1C levels and increased TIR. In all 4 studies that measured TBR, no increase in hypoglycemia was found.

A study evaluating device data of OpenAPS users found that the average TIR of the entire cohort of 80 individuals was 77.5 (10.5%) during the first 180 days with no further significant changes between days 1–60, 61–120 and 121–180.

A significant reduction in estimated A1C (eA1C) from 49 (14) to 44 (17) mmol/mol (6.6 [0.9%]–6.2 [0.6%]; P < .0001) and an increased TIR from 71.1 (13.5%) to 80.4 (8.3%) (P < .0001) with no significant change in TBR and a small decrease in hypoglycemic events were observed following evaluation of a subcohort of 34 patients before and after changing from sensor-augmented pump therapy to OpenAPS.

After taking glycemic measures of 558 Loop-users, the Loop Observational Study found that TIR significantly increased from 67 (16%) to 73.0 (13%) at 6 months, and A1C decreased from 51 (11) mmol/mol (6.8 [1%]) to 48 (9) mmol/mol (6.5 [0.8%]) at 6 months (P < .001).

Along with evidence from randomized clinical trials, real-world evidence on AID systems and their effect on glycemic outcomes are helpful for evaluating safety and efficacy, authors concluded.

Reference

Knoll C, Peacock S, Wäldchen M, et al. Real-world evidence on clinical outcomes of people with type 1 diabetes using open-source and commercial automated insulin dosing systems: a systematic review. Diabet Med. Published online November 12, 2021. doi:10.1111/dme.14741