Roadmap to Fully Closing the Loop to Optimize Health in Type 1 Diabetes

Objective: Current commercially available automated insulin delivery systems require meal and exercise announcements for optimal function, placing them in the hybrid closed loop category. Ongoing advancements aim to establish fully closed loop (FCL) systems as the next-generation standard for type 1 diabetes (T1D) management, eliminating the need for such inputs. We sought to develop a shared definition of FCL so that emerging technologies, including those using artificial intelligence, multi-hormone delivery, multi-analyte sensing, and/or adjunctive therapies, are held to uniform performance standards. Methods: A group of invited experts, including clinicians, researchers, and people with lived experience convened to propose an outcome-driven definition of FCL systems. Results: FCL systems are defined by three core domains centered on meeting intensive glycemic targets while reducing self-management burden and improving lived experience: Time in Tight Range (TITR) 70–140 mg/dL (3.9–7.8 mmol/L), Time Below Range (TBR) <54 mg/dL (<3.0 mmol/L), and person-reported outcomes (PROs) measured with validated T1D-specific assessments. This definition rests on a three-tiered classification in which all FCL systems improve lived experience and attain >50% TITR and <1% TBR without mandatory meal or activity announcements. Class 3 systems must attain >50% TITR; Class 2, >70%; and Class 1, >90%—while simultaneously demonstrating improved quality of life and reduced treatment burden per validated PROs. Given the elevated hypoglycemia risk from insulin-on-board during exercise, Class 1a requires >90% TITR with demonstrable hypoglycemia prevention during standardized exercise testing (0% TBR). Conclusion: This framework provides a uniform benchmark for evaluating future FCL technologies. Taken together, this person-centered, outcome-driven framework holds that FCL systems should (1) autonomously attain near-normoglycemia, (2) meaningfully improve lived experience across the lifespan and clinical contexts, and (3) prevent exercise-related hypoglycemia.

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Journal
Diabetes Technology & Therapeutics
Published
2026-10-09
DOI
https://doi.org/10.1177/15209156261496643
Primary Topic
Diabetes Management and Research
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article
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article

Roadmap to Fully Closing the Loop to Optimize Health in Type 1 Diabetes

Molly L. Tanenbaum, Marisa E. Hilliard, Marjana Marinac, Othmar Moser et al.
Diabetes Technology & Therapeutics
Diabetes Management and Research
article

Roadmap to Fully Closing the Loop to Optimize Health in Type 1 Diabetes

Molly L. Tanenbaum, Marisa E. Hilliard, Marjana Marinac, Othmar Moser, ABDULMOHSEN M.K. BAKHSH, Courtney A. Ackeifi, Brynn E. Marks, Aaron J. Kowalski, Tadej Battelino, Anastasia Albanese-O’Neill, Julie Heverly, David Norman O'Neal, Chantal Mathieu, Gregory P. Forlenza, Kelly L. Close, David T. Ahn, Michael Charles Riddell, Jennifer L. Sherr, Michael Roehrhoff Rickels, Catarina Limbert, Ramzi A Ajjan, Jonathan Rosen, Moshe Phillip, Viral N Shah, Satish Garg, Chengyuan Press, David M. Maahs, Julia K. Mader, Monica Oxenreiter, Boris Kovatchev, Thomas Danne, Pratik Choudhary, Benjamin J. Wheeler, Banshi Saboo, Klemen Dovc, Elizabeth A. Davis, Rimei Nishimura, Revital Nimri, Sanjoy Dutta
article en

Abstract

Objective: Current commercially available automated insulin delivery systems require meal and exercise announcements for optimal function, placing them in the hybrid closed loop category. Ongoing advancements aim to establish fully closed loop (FCL) systems as the next-generation standard for type 1 diabetes (T1D) management, eliminating the need for such inputs. We sought to develop a shared definition of FCL so that emerging technologies, including those using artificial intelligence, multi-hormone delivery, multi-analyte sensing, and/or adjunctive therapies, are held to uniform performance standards. Methods: A group of invited experts, including clinicians, researchers, and people with lived experience convened to propose an outcome-driven definition of FCL systems. Results: FCL systems are defined by three core domains centered on meeting intensive glycemic targets while reducing self-management burden and improving lived experience: Time in Tight Range (TITR) 70–140 mg/dL (3.9–7.8 mmol/L), Time Below Range (TBR) <54 mg/dL (<3.0 mmol/L), and person-reported outcomes (PROs) measured with validated T1D-specific assessments. This definition rests on a three-tiered classification in which all FCL systems improve lived experience and attain >50% TITR and <1% TBR without mandatory meal or activity announcements. Class 3 systems must attain >50% TITR; Class 2, >70%; and Class 1, >90%—while simultaneously demonstrating improved quality of life and reduced treatment burden per validated PROs. Given the elevated hypoglycemia risk from insulin-on-board during exercise, Class 1a requires >90% TITR with demonstrable hypoglycemia prevention during standardized exercise testing (0% TBR). Conclusion: This framework provides a uniform benchmark for evaluating future FCL technologies. Taken together, this person-centered, outcome-driven framework holds that FCL systems should (1) autonomously attain near-normoglycemia, (2) meaningfully improve lived experience across the lifespan and clinical contexts, and (3) prevent exercise-related hypoglycemia.

Diabetes Technology & Therapeutics
Jikei University School of Medicine (JP), Hoag Memorial Hospital Presbyterian (US), University of Leeds (GB), Alfaisal University (SA), University of Leicester (GB), University of Ljubljana (SI), York University (CA), Medical University of Graz (AT), Universitair Ziekenhuis Leuven (BE), Princess Margaret Hospital for Children (AU), King Faisal Specialist Hospital & Research Centre (SA), Ljubljana University Medical Centre (SI), Yale University (US), St Vincent's Hospital Melbourne (AU), Breakthrough T1D (US), Schneider Children's Medical Center (IL), Diabetes Care & Hormone Clinic (IN), Close Concerns (United States) (US), Stanford Medicine (US), Texas Children's Hospital (US), Indiana University Indianapolis (US), Indiana University School of Medicine, Comprehensive Health Research Centre (PT), University of Virginia (US), University of Pennsylvania (US), University of Otago (NZ), Universidade Nova de Lisboa (PT), University of Colorado Denver (US), Stanford University (US)
Openalex Percentile: Top 11%
Diabetes Management and Research
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