BACKGROUND: Glucose homeostasis is the result of complex interactions across different biological levels. This multilevel characteristic should be considered when analyzing and designing closed-loop glucose control algorithms. Classic control schemes use only a pharmacokinetic-pharmacodynamic (PKPD) perspective to describe the gluco-regulatory system. METHODS: A multilevel model combining a PKPD model with an insulin signaling model is proposed for patients with type 1 diabetes mellitus T1DM (T1DM). The PKPD Dalla Man model for T1DM is expanded to include an intracellular level involving insulin signaling to control glucose uptake through glucose transporter type 4 (GLUT4) translocation. A model-based controller is then designed and used as an example to illustrate the feasibility of the proposal. RESULTS: Two significant results were obtained for the controller explicitly utilizing multilevel information. No hypo-glycemic events were registered and an excellent performance for interpatient variability was achieved. Controller performance was evaluated using two indexes. The glucose was kept inside the range (70-180) mg/dl more than 99% of the time, and the intrapatient variability measured using control variability grid analysis was solid with 90% of the population inside the target zone. CONCLUSIONS: Multilevel models open new possibilities for designing glucose control algorithms. They allow controllers to take into account variables that have a strong influence on glucose homeostasis. A model-based controller was used for demonstrating how improved knowledge of the multilevel nature of diabetes increases the robustness and performance of glucose control algorithms. Using the proposed multi-level approach, a reduction of the hypoglycemic risk and robust behaviour for intrapatient variability was demonstrated.
BACKGROUND:Glucose homeostasis is the result of complex interactions across different biological levels. This multilevel characteristic should be considered when analyzing and designing closed-loop glucose control algorithms. Classic control schemes use only a pharmacokinetic-pharmacodynamic (PKPD) perspective to describe the gluco-regulatory system. METHODS: A multilevel model combining a PKPD model with an insulin signaling model is proposed for patients with type 1 diabetes mellitus T1DM (T1DM). The PKPD Dalla Man model for T1DM is expanded to include an intracellular level involving insulin signaling to control glucose uptake through glucose transporter type 4 (GLUT4) translocation. A model-based controller is then designed and used as an example to illustrate the feasibility of the proposal. RESULTS: Two significant results were obtained for the controller explicitly utilizing multilevel information. No hypo-glycemic events were registered and an excellent performance for interpatient variability was achieved. Controller performance was evaluated using two indexes. The glucose was kept inside the range (70-180) mg/dl more than 99% of the time, and the intrapatient variability measured using control variability grid analysis was solid with 90% of the population inside the target zone. CONCLUSIONS: Multilevel models open new possibilities for designing glucose control algorithms. They allow controllers to take into account variables that have a strong influence on glucose homeostasis. A model-based controller was used for demonstrating how improved knowledge of the multilevel nature of diabetes increases the robustness and performance of glucose control algorithms. Using the proposed multi-level approach, a reduction of the hypoglycemic risk and robust behaviour for intrapatient variability was demonstrated.
Authors: Daniela Bruttomesso; Anne Farret; Silvana Costa; Maria Cristina Marescotti; Monica Vettore; Angelo Avogaro; Antonio Tiengo; Chiara Dalla Man; Jerome Place; Andrea Facchinetti; Stefania Guerra; Lalo Magni; Giuseppe De Nicolao; Claudio Cobelli; Eric Renard; Alberto Maran Journal: J Diabetes Sci Technol Date: 2009-09-01
Authors: Elin Nyman; Cecilia Brännmark; Robert Palmér; Jan Brugård; Fredrik H Nyström; Peter Strålfors; Gunnar Cedersund Journal: J Biol Chem Date: 2011-05-13 Impact factor: 5.157
Authors: Roman Hovorka; Fariba Shojaee-Moradie; Paul V Carroll; Ludovic J Chassin; Ian J Gowrie; Nicola C Jackson; Romulus S Tudor; A Margot Umpleby; Richard H Jones Journal: Am J Physiol Endocrinol Metab Date: 2002-05 Impact factor: 4.310