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Recruitment platform


People with type 2 diabetes mellitus (T2DM) have insulin resistance and relative insulin deficiency. Therefore, the management of this condition involves both reducing insulin resistance and promoting insulin secretion.

T2DM naturally progresses towards an increasingly marked insulin deficiency, which leads to the need for the pancreas to supplement insulin.

Artificial intelligence using a self-learning algorithm can be used to automatise and personalise insulin administration. These “closed loop” systems improve glycaemic control, reduce the number of hypo- and hyperglycaemias, as well as the mental burden associated with the disease, thereby improving the quality of life of affected individuals. To date, these “closed loops” are only available for people with type 1 diabetes. The considerable benefits of these systems for T1DM suggest that similar benefits could occur for T2DM treated with basal-bolus insulin regimens. This study is part of a project to develop a specific algorithm that addresses the specific characteristics of T2DM.



Project coordination


Type of study

Interventional / Clinical investigation in the home

Single-centre protocol

Grenoble University Hospital

Sample size

35 participants

Study design

Prospective observational data collection study.

The aim of this study is to record changes in blood glucose levels in people with T2DM during different daily life situations: physical activity, meal-times, sleep etc. The data will be used to develop a bench test for the evaluation of insulin delivery algorithms to treat people with insulin-dependent diabetes using a closed-loop system.

IC@dom has been commissioned to provide comprehensive support for Diabeloop at every stage of the clinical investigation:

règle juxtaposée d'un crayon

Project design and management

tableur avec checklist

Drafting the protocol

liste de tableur

Drafting the CRF (case report form)


Home-intervention by a team of diabetes nurse specialists

maison et loupe juxtaposée

Inclusion and follow-up of participants


Provision of actimeters and data analysis


Blood glucose data were collected over 7 consecutive days and compared with data collected during daily life situations (physical activity, meal-times, sleep, etc.) to model an algorithm test bed for the development of the first closed-loop treatment for people with T2DM


This initial study led to a second feasibility trial, in which people with T2DM underwent closed-loop treatment as part of the trial.

graph result


feasibility study


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