Evidence mapPaperPMID 40590459Full record

ReviewJournal of diabetes science and technology2025

Metabolic Models, in Silico Trials, and Algorithms.

Ali Cinar, Ananda Basu, B Wayne Bequette, Marc D Breton, Bruce Buckingham, Eda Cengiz, Claudio Cobelli, Eyal Dassau, Francis J Doyle, Chiara Fabris and 8 more

Abstract readReview
In one paragraph

Review in Journal of diabetes science and technology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Artificial Pancreas: The First 20 Years.Journal of diabetes science and technology · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Ali CinarDepartment of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL, USA.ORCID 0000-0002-1607-9943
Ananda BasuThe University of Alabama at Birmingham, Birmingham, AL, USA.
B Wayne BequetteRensselaer Polytechnic Institute, Troy, NY, USA.ORCID 0000-0002-6472-1902
Marc D BretonUniversity of Virginia, Charlottesville, VA, USA.ORCID 0000-0001-7645-2693
Bruce BuckinghamStanford University, Stanford, CA, USA.
Eda CengizUniversity of California, San Francisco, San Francisco, CA, USA.ORCID 0000-0001-7992-9506
Claudio CobelliUniversity of Padova, Padova, Italy.ORCID 0000-0002-0169-6682
Eyal DassauHarvard University, Boston, MA, USA.ORCID 0000-0001-5333-6892
Francis J DoyleBrown University, Providence, RI, USA.
Chiara FabrisUniversity of Virginia, Charlottesville, VA, USA.ORCID 0000-0001-7575-4622
Andrea FacchinettiUniversity of Padova, Padova, Italy.ORCID 0000-0001-8041-2280
Irl HirschUniversity of Washington, Seattle, WA, USA.ORCID 0000-0003-1675-8417
Roman HovorkaUniversity of Cambridge, Cambridge, UK.
Peter G JacobsOregon Health and Science University, Portland, OR, USA.ORCID 0000-0001-9897-4783
Boris P KovatchevUniversity of Virginia, Charlottesville, VA, USA.
Chiara Dalla ManUniversity of Padova, Padova, Italy.ORCID 0000-0002-4908-0596
Laurie QuinnUniversity of Illinois Chicago, Chicago, IL, USA.
Jay SkylerUniversity of Miami Diabetes Research Institute, Miami, FL, USA.

Funding

UAB Diabetes Research CenterP30DK079626 · UNIVERSITY OF ALABAMA AT BIRMINGHAM · 2025 to 2025
$1.3M
NIDDK NIH HHS P30 DK079626
6 · The paper itself

Abstract

Artificial pancreas (AP) systems, also called automated insulin delivery systems, have improved the time in range of glucose levels, reduced the daily burden of the user for glucose regulation, and improved their quality of life. Several commercially available AP systems operate in hybrid closed-loop mode that requires manual information from the user for meals and exercise. This article summarizes the progress on mathematical models of glucose-insulin dynamics, continuous glucose monitoring systems, and insulin pumps that form the building blocks of AP systems, the shift from animal studies to in silico clinical trials that accelerated the rate of progress in AP technologies and the efforts for developing the next-generation AP systems, and the fully automated AP that eliminates manual inputs and mitigates the effects of disturbances to glucose homeostasis-meals, physical activities, acute stress, and variations in sleep characteristics. A section is devoted to discuss the unique glycemic management challenges faced by women with diabetes across the lifespan (menstrual cycle, menopause, pregnancy) and summarize progress made to reduce their impact on glycemic management.

Indexed as

AlgorithmsBlood GlucoseInsulin Infusion SystemsModels, BiologicalPancreas, ArtificialAnimalsBlood Glucose Self-MonitoringComputer SimulationFemaleHumansHypoglycemic AgentsInsulinBlood GlucoseHypoglycemic AgentsInsulinartificial pancreasdigital twinsglucose control algorithmsmathematical modelssimulators for in silico clinical trialswomen with diabetes

Identifiers

PMID40590459
PMCPMC12213549

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.