January 30, 2013 Read More →

Lauren M. Huyett

5th Year PhD Candidate
Department of Chemical Engineering, UCSB
Schlinger Fellow (2015)
NSF Graduate Research Fellow

Research

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.

Education

B.S., Chemical Engineering, Lafayette College, 2011

Links

AP Clinical Trial Database
Google Scholar Profile
LinkedIn

Publications
12-Week 24/7 Ambulatory Artificial Pancreas With Weekly Adaptation of Insulin Delivery Settings: Effect on Hemoglobin A1c and Hypoglycemia
Eyal Dassau, Jordan E. Pinsker, Yogish C. Kudva, Sue A. Brown, Ravi Gondhalekar, Chiara Dalla Man, Steve Patek, Michele Schiavon, Vikash Dadlani, Isuru Dasanayake, Mei Mei Church, Rickey E. Carter, Wendy C. Bevier, Lauren M. Huyett, Jonathan Hughes, Stacey Anderson, Dayu Lv, Elaine Schertz, Emma Emory, Shelly K. McCrady-Spitzer, Tyler Jean, Paige K. Bradley, Ling […]
Intraperitoneal Insulin Delivery Provides Superior Glycemic Regulation to Subcutaneous Insulin Delivery in Model Predictive Control‐based Fully‐automated Artificial Pancreas in Patients with Type 1 Diabetes: A Pilot Study
Dassau, E., Renard, E., Place, J., Farret, A., Pelletier, M.J., Lee, J., Huyett, L.M., Chakrabarty, A., Doyle III, F.J. and Zisser, H.C. “Intraperitoneal Insulin Delivery Provides Superior Glycemic Regulation to Subcutaneous Insulin Delivery in Model Predictive Control‐based Fully‐automated Artificial Pancreas in Patients with Type 1 Diabetes: A Pilot Study.” Diabetes, Obesity and Metabolism, 2017. doi: […]
Preliminary Evaluation of a Long-Term Intraperitoneal Glucose Sensor With Flushing Mechanism.
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
Randomized Crossover Comparison of Personalized MPC and PID Control Algorithms for the Artificial Pancreas.
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.
Closed-loop artificial pancreas systems: engineering the algorithms
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]
Glucose sensing in the peritoneal space offers faster kinetics than sensing in the subcutaneous space
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]
The RNA core weakly influences the interactions of the bacteriophage MS2 at key environmental interfaces
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]