MODELING AND CONTROL OF BIOLOGICAL SYSTEMS

Lecture

1 - Recap from “Sistemi e Modelli”
2 - Parameter estimation: Bayes
3 - Fundamentals on glucose metabolism
4 - Models of glucose kinetics
5 - Models of insulin control from IVGTT data
6 - Models of glucose kinetics in muscle and brain from PET Imaging
7 - A cellular stochastic model of insulin secretion
8 - From a cellular to a whole-body model of insulin secretion during IVGTT
9 - From minimal to maximal models of glucose metabolism: the FDA accepted Type 1 diabetes Ssmulator
10 - Pharma and biotech applications of the Type 1 diabetes simulator: new insulin molecules and glucose sensors
11 - Type 1 diabetes: from open- to closed- loop (artificial pancreas) glucose control
12 - Model predictive control of glucose
13- In silico clinical trials with the Type 1 diabetes simulator for robust design of control algorithms and regulatory purposes
14 – Survey of artificial pancreas clinical trials both inpatient and outpatient

Laboratory
1. Linear least squares identification
2. Nonlinear least squares identification
3. Identification in presence of a-priori information using maximum a posteriori
4. Compartmental models
5. Identification with relative weights
6. Use of forcing function
7. Simulink and proportional-integrative-derivative (PID) control
8. Application of PID control on the type 1 diabetes simulator
9. Model identification for new insulin molecules