Timing your insulin could change how your body stores fat
NCT ID NCT07172672
First seen Jun 25, 2026 · Last updated Jun 27, 2026 · Updated 1 time
Summary
This study looks at whether the timing of insulin doses with meals affects where fat is stored in the body for people with type 1 diabetes. Ten participants will drink a high-fat liquid meal and receive insulin at different times (before, during, after, or skipping the dose). Researchers will use PET scans to track fat storage in organs like the liver and muscles. The goal is to understand if delaying insulin leads to more unhealthy fat storage.
What this could mean
Our plain-language read of the trial. This is informational only, not medical advice or a prediction.
- Active substance
- meal insulin timing (timing of insulin bolus)
- What this could lead to
- If successful, this could help people with type 1 diabetes better manage fat storage and metabolic health by optimizing when they take insulin with meals.
- What could go wrong
- This is a very small (10 people), early-stage study that only looks at short-term fat storage after a single meal. Results may not apply to real-life eating patterns or long-term health.
This is an AI summary of the original study and may miss details. Read our disclaimer.
Study facts
What this study's own registry entry says, in plain language.
- Phase
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Not a phased trial
Phase numbers describe drug development. The registry uses this when they do not apply, as it does for trials of devices, procedures or behaviour changes, and for observational studies.
- Participants
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About 10 people
The number the study aims to enrol. It can still change while the study runs.
- Expected to start
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Nov 2025
An estimate. Start dates often move.
- Expected to finish
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Nov 2027
An estimate. End dates often move.
- Lead sponsor
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Other sponsor
The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.
Who can take part
This study's own entry requirements. Only the study team can say for certain whether you qualify.
- Ages
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18 to 65 years
- Sex
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Anyone
- Healthy volunteers
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Accepted
You do not need to have the condition being studied to take part.
Show the full entry requirements Hide the full entry requirements
Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.
Inclusion Criteria: * Type 1 diabetes duration \> 3 years or c-peptide negative * Written and informed consent Exclusion Criteria: * Medicine with an impact on blood glucose or blood pressure * Affected screening blood sample as evaluated by the clinical responsible investigator. * Alcohol or substance abuse * BMI \> 35 kg/m2 or \< 18.5 kg/m2 * Participation in other clinical trials involving ionized radiation within the last 6 months * Lactose intolerance * Doesn't speak and understand Danish. * Severe claustrophobia. * Commitment to special diets
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Conditions
The condition(s) this trial relates to.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.
How to take part
Only the study team decides who joins. These are the ways to reach them.
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The places running it
1 site. The list below names each one and where it is.
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The official record
ClinicalTrials.gov lists the study team's own contact details, including names and phone numbers. We don't republish those.
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A doctor treating you
A doctor who knows your case can contact a study site on your behalf, and can tell you whether this study is worth pursuing at all.
Contacts and locations
Locations
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Department of Nuclear Medicine & PET-Centre, AUH Palle Juul-Jensens Blvd. 165, 8200 Aarhus N, Denmark and Medical Research Laboratories/Steno Diabetes Center Aarhus, AUH Palle Juul-Jensens Blvd. 11, 8200 Aarhus N, Denmark
Aarhus, 8200, Denmark
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Other studies related to the condition(s) this trial covers.
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- Can a bedtime snack tame overnight blood sugar swings in kids with diabetes?
- Can Open-Source insulin systems match commercial ones without meal announcements?
- A glucose Monitor's second chance: can it tame type 1 diabetes in High-Risk teens?
- AI takes the wheel: could a smart algorithm optimize insulin pumps from home?