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AIMS: To evaluate an algorithm with glucose prediction capacity and continuous adaptation of patient parameters-a model predictive control (MPC) algorithm-to control blood glucose concentration during fasting conditions in patients with Type 1 diabetes. In the subcutaneous (sc) route within a closed loop system. METHODS: Paired experiments were performed in six patients. Over 8 h the MPC algorithm was used to control glucose with s.c. insulin administration and two different glucose monitoring protocols: first, the algorithm was provided with intravenous (i.v.) glucose values for insulin dosage calculation directly (i.v.-s.c. route). Then, in the second experiment, i.v. glucose values were fed to the MPC with a delay of 30 min to simulate s.c. glucose measurements ('s.c.'-s.c. route). In both experiments plasma glucose, insulin dosage, and serum insulin levels were analysed. RESULTS: Glucose concentration was brought from hyper- to normoglycaemia and kept in the physiological range (6-7 mmol/l) with both routes in all subjects. Mean glucose concentration reached the threshold of 7 mmol/l approximately 2 (i.v.-s.c. route) and 3 ('s.c.'-s.c. route) hours after the start of glucose control with the MPC. During the last 2 h of automated glucose control, mean glucose concentration was 6.3 +/- 0.2 mmol/l and 6.6 +/- 0.3 mmol/l for i.v.-s.c. and 's.c.'-s.c. route, respectively. Glucose concentration, insulin doses, and serum insulin levels did not differ significantly between routes (P > 0.05). CONCLUSIONS: The MPC algorithm is suitable for glucose control during fasting within an extracorporeal artificial beta-cell in the subcutaneous route Type 1 diabetic patients.

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BACKGROUND AND MOTIVATION: INCA (Intelligent Control Assistant for Diabetes) is a project funded by the EU with the objective to improve diabetes therapy by creating a personal control loop interacting with telemedical remote control. Development of telemedical systems generally is a complex task especially in international projects where engineering and user groups with different social and cultural background have to be included into the system development process. OBJECTIVES: To explore if and how sophisticated information system modelling and simulation techniques can improve the development of telemedical systems. METHODS: For system analysis and design the MOSAIK-M approach was chosen. MOSAIK-M means "Modelling, simulation, and animation of information and communication systems in medicine". It includes a generic process scheme, a meta model and a tool environment. The generic process scheme guides modelling projects to produce models of high quality in terms of correctness, completeness and validity. The meta model defines the modelling language.In INCA MOSAIK-M is used for analysis of the problem domain, specification of the telemedical system and cost/benefit-analysis. RESULTS: The MOSAIK-M approach was used to create two models: an "As Is"-model of the problem domain and a "To Be"-model of the INCA system. The "As Is"-model of conventional insulin pump based diabetes care comprises submodels of diabetes management, ambulatory and clinical care. The "To Be"-model describes a patient's diabetes management using a smart phone that controls an insulin pump based on continuously measured interstitial glucose. It also describes telemedical care of a patient by diabetologists and a call centre. Both models can be simulated enhanced by visualisation capabilities to explore specific cases or scenarios. This feature proved valuable for the evaluation of both models through domain experts. The "To Be" model is used to guide the implementation of the system. Both models are being augmented by cost structures to support cost/benefit-analysis. CONCLUSIONS: Even a complex telemedical system like the INCA system can be successfully specified using sophisticated modelling and simulation based approaches like MOSAIK-M. The resulting specification is a result of its own and ensures a lasting effect of the definitions and specifications produced during the project. International cooperation and evaluation of the system design prior to its implementation profit from simulation and visualisation capabilities of MOSAIK-M.

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We developed a new system to monitor glucose continuously in vivo. The miniaturised system is very easy to handle and was optimised to a resource-saving working modus. Sampling was performed by means of a biocompatible microdialysis needle probe inserted into the subcutaneous tissue. During glucose tolerance tests the results of our monitoring system were correlated with the glucose level of the venous blood stream. A comparison according to the procedure known as 'error grid analysis' provided an excellent correlation between the two completely independent analyses systems with the reference determination results. All values obtained with our systems were clinically correct or at least clinically acceptable.

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