The CLINICIP partners followed a two-step approach:

In a first step, a decision support system for tight glycaemic control was developed combining automated insulin delivery with an intelligent algorithm. The algorithm combines automatically recorded data about carbohydrate intake and current glucose levels measured by the nursing staff to calculate how much insulin is needed.

The decision support system has been successfully developed within the CLINICIP project, resulting in a functional prototype that could be tested effectively within clinical trials.

The second step was designed to establish a complete glycaemic control system, “closing the loop” between glucose monitoring and insulin delivery. It involved the development of a body interface to provide access to the body fluid compartments and sensors to provide reliable glucose and other metabolite readings. With this in mind, three different glucose sensor types – an infrared spectroscopic, a fibre-optical and an amperometric sensor – and a vascular body interface based on a novel microdialysis membrane were developed. The spectroscopic sensor and the body interface were integrated into a fully automated metabolic control system, which was successfully tested in a proof of concept study in a clinical setting.

Research work within the CLINICIP project also included the integration of data management and physiology research on the applicability of glucose monitoring from subcutaneous adipose tissue.