I am studying the impact that the performance of the continuous glucose monitor (CGM) has on the blood glucose control provided for people with type 1 diabetes by the Artificial Pancreas. While the CGM provides valuable information to the controller, there are many factors that can cause error in the sensor measurements. My current focus is on using computational modeling to characterize implantable glucose sensors and insulin pumps. I use these models to develop control algorithms that will work with a novel fully implantable artificial pancreas.
In addition, I developed and maintain the AP Clinical Trial Database, which contains information on over 74 published clinical trials of the artificial pancreas.
B.S., Chemical Engineering, Lafayette College, 2011
L.M. Huyett, R. Mittal, H.C. Zisser, E.S. Luxon, A. Yee, E. Dassau, F.J. Doyle III, D.R. Burnett. J Diabetes Sci Technol. 2016. doi:10.1177/1932296816640542
J.E. Pinsker, J.B. Lee, E. Dassau, D.E. Seborg, P.K. Bradley, R. Gondhalekar, W.C. Bevier, L. Huyett, H.C. Zisser, F.J. Doyle III. Diabetes Care, 39(7): 1135-42, 2016. doi: 10.2337/dc15-2344.
F.J. Doyle III, L. M. Huyett, J. B. Lee, H. C. Zisser, E. Dassau , “Closed- Loop Artificial Pancreas Systems: Engineering the Algorithms,” Diabetes Care, May 2014. [DOI]
D.R. Burnett, L.M. Huyett, H.C. Zisser, F.J. Doyle III, B.D. Mensh, “Glucose sensing in the peritoneal space offers faster kinetics than sensing in the subcutaneous space,” Diabetes, vol. 63, no. 7, pp. 2498-505,Jul 2014. [DOI]
T.H. Nguyen, N. Easter, L. Gutierrez, L. Huyett, E. Defnet, S.E. Mylon, J.K. Ferri, N.A. Viet, “The RNA core weakly influences the interactions of the bacteriophage MS2 at key environmental interfaces,” Soft Matter, vol. 7, no. 21, pp. 10449, 2011. [DOI]