Dr. Chiara Fabris is Assistant Professor at the University of Virginia School of Medicine and member of the faculty at the Center for Diabetes Technology. She holds a Master’s and a Doctoral Degree in Bioengineering from the University of Padova (Padova, Italy) and has significant experience in mathematical modeling and simulation – especially regarding the glucose/insulin regulation system – and algorithm development. Over the past four years, Dr. Fabris has been awarded an Advanced Postdoctoral Fellowship and a Career Development Award by the Juvenile Diabetes Research Foundation, which supported the development and clinical testing of decision support systems to help people with diabetes manage their disease. Dr. Fabris is involved in several projects focused on optimization of treatments for diabetes and diabetes data science. Dr. Boris Kovatchev is Professor at the University of Virginia School of Medicine and School of Engineering, and founding director of the Center for Diabetes Technology. He has a 30-year track record in mathematical modeling, biosimulation, and algorithm development. Currently, he is Principal Investigator of several projects dedicated to Diabetes Data Science and the development of artificial pancreas and decision support systems, including the large-scale NIH International Diabetes Closed-Loop Trial and the UVA Strategic Investment Fund project “Precision Individualized Medicine for Diabetes”. Dr. Kovatchev is author of over 200 peer-reviewed publications and holds 85 patents.

• SECTION 1: SELF-MONITORING BLOOD GLUCOSE DEVICES1. Introduction to SMBG2. Analytical performance of SMBG systems3. Clinical evaluation of SMBG systems4. Consequences of SMBG systems inaccuracy5. Modeling the SMBG measurement error SECTION 2: CONTINUOUS GLUCOSE MONITORING DEVICES6. CGM sensor technology7. Clinical impact of CGM use8. Accuracy of CGM systems9. Calibration of CGM systems10. CGM filtering and denoising techniques11. Retrofitting CGM traces12. Modeling the CGM measurement error SECTION 3: CLINICAL USE OF MONITORING DATA13. Low-glucose suspend systems14. Predictive low-glucose suspend systems15. Automated closed-loop insulin delivery: system components, performance, and limitations16. The dawn of automated insulin delivery: from promise to product