January 30, 2013 Read More →

Eyal Dassau, Ph.D.


Senior Research Fellow in Biomedical Engineering in the Harvard John A. Paulson School of Engineering and Applied Sciences

Senior Investigator and Diabetes Team Research Manager

Adjunct Faculty, Joslin Diabetes Center, Boston, MA

Adjunct Senior Investigator at Sansum Diabetes Research Institute (SDRI)

Education
  • BSc: 1999, ChE, Technion Israel Institute of Technology
  • MSc: 2002, ChE, Technion Israel Institute of Technology
  • PhD: 2006, ChE, Technion Israel Institute of Technology
Honors
  • 2008 Otis William Fellowship Grant
  • 2012 Champions of Health Care Award
  • 2012 Wyss IEEE Translational Research Finalist Award
  • 2012 Transactions on Biomedical Engineering Highlight Paper Finalist
Research
  • Biomedical design and control: the application of process system engineering principles to design and control of automated insulin delivery system (artificial pancreatic β-cell) to improve glycemic control in type 1 diabetes mellitus patients
  • Process and product design with emphasis on medical and biomedical applications
  • Systems theory, modeling, simulation, optimization and control to medical, biological, and other complex systems
Contact Information

Harvard John A. Paulson School of Engineering and Applied Sciences
29 Oxford St., Rm. 317
Cambridge, MA 02138

Tel. +1 (617) 496-0358
Fax +1 (617) 496-5264
Email: dassau (at) seas (dot) harvard (dot) edu

Selected Publications

For a full and up-to-date list of publications, please see: Dr. Eyal Dassau’s PubMed Profile

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 […]
A Personalized Week-to-Week Updating Algorithm to Improve Continuous Glucose Monitoring Performance
Stamatina Zavitsanou, Joon Bok Lee, Jordan E. Pinsker, Mei Mei Church, Francis J. Doyle III, Eyal Dassau, A Personalized Week-to-Week Updating Algorithm to Improve Continuous Glucose Monitoring Performance, Journal of Diabetes Science and Technology, Accepted
Event-Triggered Model Predictive Control For Embedded Artificial Pancreas Systems
A. Chakrabarty, S. Zavitsanou, F. J. Doyle III, E. Dassau, “Event-Triggered Model Predictive Control For Embedded Artificial Pancreas Systems.” Preprint available, IEEE Trans. Biomedical Engineering, May 2017.
Embedded Control in Wearable Medical Devices: Application to the Artificial Pancreas
S. Zavitsanou, A. Chakrabarty, E. Dassau, and F.J. Doyle III. “Embedded Control in Wearable Medical Devices: Application to the Artificial Pancreas.” Processes 4(4), 35, 2016. doi:10.3390/pr4040035
Periodic zone-MPC with asymmetric costs for outpatient-ready safety of an artificial pancreas to treat type 1 diabetes.
R. Gondhalekar, E. Dassau, and F.J. Doyle III. “Periodic zone-MPC with asymmetric costs for outpatient-ready safety of an artificial pancreas to treat type 1 diabetes.” Automatica 71: 237-246, 2016. doi:10.1016/j.automatica.2016.04.015
Outcome Measures for Artificial Pancreas Clinical Trials: A Consensus Report.
D.M. Maahs, B.A. Buckingham, J.R. Castle, A. Cinar, E.R. Damiano, E. Dassau, J.H. DeVries, F.J. Doyle III, S.C. Griffen, A. Haidar, L. Heinemann, R. Hovorka, T.W. Jones, C. Kollman, B. Kovatchev, B.L. Levy, R. Nimri, D.N. O’Neal, M. Philip, E. Renard, S.J. Russell, S.A. Weinzimer, H. Zisser, J.W. Lum. Diabetes Care. 39(7):1175-9, 2016. doi: 10.2337/dc15-2716. […]
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.
Adjustment of open-loop settings to improve closed-loop results in type 1 diabetes: a multicenter randomized trial
E. Dassau, S.A. Brown, A. Basu, J.E. Pinsker, Y.C. Kudva, R. Gondhalekar, S. Patek, D. Lv, M. Schiavon, J.B. Lee, C.D. Man, L. Hinshaw, K. Castorino, A. Mallad, V. Dadlani, S.K. McCrady-Spitzer, M. McElwee-Malloy, C.A. Wakeman, W.C. Bevier, P.K. Bradley, B. Kovatchev, C. Cobelli, H.C. Zisser, F.J. Doyle III, “Adjustment of open-loop settings to improve […]
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]
Novel insulin delivery profiles for mixed meals for sensor-augmented pump and closed-loop artificial pancreas therapy for type 1 diabetes mellitus
A. Srinivasan, J.B. Lee, E. Dassau, F.J. Doyle III, “Novel insulin delivery profiles for mixed meals for sensor-augmented pump and closed-loop artificial pancreas therapy for type 1 diabetes mellitus,” Journal of Diabetes Science and Technology, vol. 8, no. 5, pp. 957-68,Sep 2014. [DOI]
Model-Based Personalization Scheme of an Artificial Pancreas for Type 1 Diabetes Applications
J. B. Lee, E. Dassau, D. Seborg, F.J. Doyle III, “Model-Based Personalization Scheme of an Artificial Pancreas for Type 1 Diabetes Applications,” Proceedings of the American Controls Conference 2013.
Clinical evaluation of a personalized artificial pancreas
E. Dassau, H. Zisser, R.A. Harvey, M.W. Percival, B. Grosman, W. Bevier, E. Atlas, S. Miller, R. Nimri, L. Jovanovic, F.J. Doyle III “Clinical evaluation of a personalized artificial pancreas,” Diabetes Care, vol. 36, no. 4, pp. 801-9, Apr 2013. [DOI]
In silico evaluation of an artificial pancreas combining exogenous ultrafast-acting technosphere insulin with zone model predictive control
J.J. Lee, E. Dassau, H. Zisser, R.A. Harvey, L. Jovanovič, F.J. Doyle III “In silico evaluation of an artificial pancreas combining exogenous ultrafast-acting technosphere insulin with zone model predictive control,” Journal of Diabetes Science and Technology, vol. 7, no. 1, pp. 215-26, January 2013. [PMID]
Design of the health monitoring system for the artificial pancreas: low glucose prediction module
R.A. Harvey, E. Dassau, H. Zisser, D.E. Seborg, L. Jovanovič, F.J. Doyle III “Design of the health monitoring system for the artificial pancreas: low glucose prediction module,” Journal of Diabetes Science and Technology, vol. 6, no. 6, pp. 1345-54, November 2012. [PMID]
Fully integrated artificial pancreas in type 1 diabetes: modular closed-loop glucose control maintains near normoglycemia
M. Breton, A. Farret, D. Bruttomesso, S. Anderson, L. Magni, S. Patek, C. Dalla Man, J. Place, S. Demartini, S. Del Favero, C. Toffanin, C. Hughes-Karvetski, E. Dassau, H. Zisser, F.J. Doyle III, G. De Nicolao, A. Avogaro, C. Cobelli, E. Renard, B. Kovatchev, International Artificial Pancreas Study Group, “Fully integrated artificial pancreas in type […]
Pilot studies of wearable outpatient artificial pancreas in type 1 diabetes
C. Cobelli, E. Renard, B.P. Kovatchev, P. Keith-Hynes, N. Ben Brahim, J. Place, S. Del Favero, M. Breton, A. Farret, D. Bruttomesso, E. Dassau, H. Zisser, F.J. Doyle III, S.D. Patek, A. Avogaro, “Pilot studies of wearable outpatient artificial pancreas in type 1 diabetes,” Diabetes Care, vol. 35, no. 9, pp. e65-7, Sep 2012. [DOI]
Clinically relevant hypoglycemia prediction metrics for event mitigation
R.A. Harvey, E. Dassau, H.C. Zisser, W. Bevier, D.E. Seborg, L. Jovanovič, F.J. Doyle III “Clinically relevant hypoglycemia prediction metrics for event mitigation,” Diabetes Technology & Therapeutics, vol. 14, no. 8, pp. 719-27, Aug 2012. [DOI]
Control-relevant models for glucose control using a priori patient characteristics
K. van Heusden, E. Dassau, H.C. Zisser, D.E. Seborg, F.J. Doyle III, “Control-relevant models for glucose control using a priori patient characteristics,” IEEE Transactions on Bio-medical Engineering, vol. 59, no. 7, pp. 1839-49, Jul 2012. [DOI]
Predicting subcutaneous glucose concentration using a latent-variable-based statistical method for type 1 diabetes mellitus
C. Zhao, E. Dassau, L. Jovanovič, H.C. Zisser, F.J. Doyle III, D.E. Seborg, “Predicting subcutaneous glucose concentration using a latent-variable-based statistical method for type 1 diabetes mellitus,” Journal of Diabetes Science and Technology, vol. 6, no. 3, pp. 617-33, May 2012. [PMID]
Development of a multi-parametric model predictive control algorithm for insulin delivery in type 1 diabetes mellitus using clinical parameters
M.W. Percival, Y. Wang, B. Grosman, E. Dassau, H. Zisser, L. Jovanovič, F.J. Doyle III, “Development of a multi-parametric model predictive control algorithm for insulin delivery in type 1 diabetes mellitus using clinical parameters,” Journal of Process Control, vol. 21, no. 3, pp. 391-404, Mar 2011. [DOI]
Closing the loop
E. Dassau, E. Atlas, M. Phillip, “Closing the loop,” International Journal of Clinical Practice. Supplement, no. 170, pp. 20-5, Feb 2011. [DOI]
Automatic bolus and adaptive basal algorithm for the artificial pancreatic β-cell
Y. Wang, E. Dassau, H. Zisser, L. Jovanovič, F.J. Doyle III, “Automatic bolus and adaptive basal algorithm for the artificial pancreatic β-cell,” Diabetes Technology & Therapeutics, vol. 12, no. 11, pp. 879-87, Nov 2010. [DOI]
Quest for the artificial pancreas: combining technology with treatment
R.A. Harvey, Y. Wang, B. Grosman, M.W. Percival, W. Bevier, D.A. Finan, H. Zisser, D.E. Seborg, L. Jovanovic, F.J. Doyle III, E. Dassau “Quest for the artificial pancreas: combining technology with treatment,” IEEE Engineering in Medicine and Biology Magazine : The Quarterly Magazine of the Engineering in Medicine & Biology Society, vol. 29, no. 2, […]
Zone-Model Predictive Control: A Strategy to Minimize Hyper- and Hypo-glycemic Events
B. Grosman, E. Dassau, H. Zisser, L. Jovanovic, F.J. Doyle III, “Zone-Model Predictive Control: A Strategy to Minimize Hyper- and Hypo-glycemic Events,” J Diabetes Sci Technol, vol. 4, no. 4, pp. 961–975, July 2010. [DOI]
An advisory protocol for rapid- and slow-acting insulin therapy based on a run-to-run methodology
F. Campos-Cornejo, D.U. Campos-Delgado, D. Espinoza-Trejo, H. Zisser, L. Jovanovic, F.J. Doyle III, E. Dassau, “An advisory protocol for rapid- and slow-acting insulin therapy based on a run-to-run methodology,” Diabetes Technology & Therapeutics, vol. 12, no. 7, pp. 555-65, Jul 2010. [DOI]
Zone model predictive control: a strategy to minimize hyper- and hypoglycemic events
B. Grosman, E. Dassau, H.C. Zisser, L. Jovanovic, F.J. Doyle III, “Zone model predictive control: a strategy to minimize hyper- and hypoglycemic events,” Journal of Diabetes Science and Technology, vol. 4, no. 4, pp. 961-75, Jul 2010. [PMID]
Proposed clinical application for tuning fuzzy logic controller of artificial pancreas utilizing a personalization factor
R. Mauseth, Y. Wang, E. Dassau, R. Kircher Jr, D. Matheson, H. Zisser, L. Jovanovic, F.J. Doyle III, “Proposed clinical application for tuning fuzzy logic controller of artificial pancreas utilizing a personalization factor,” Journal of Diabetes Science and Technology, vol. 4, no. 4, pp. 913-22, Jul 2010. [PMID]
Real-Time Hypoglycemia Prediction Suite Using Continuous Glucose Monitoring: A safety net for the artificial pancreas
E. Dassau, F. Cameron, H. Lee, B.W. Bequette, H. Zisser, L. Jovanovic, H.P. Chase, D.M. Wilson, B.A. Buckingham, F.J. Doyle III, “Real-Time Hypoglycemia Prediction Suite Using Continuous Glucose Monitoring: A safety net for the artificial pancreas,” Diabetes Care, vol. 33, no. 6, pp. 1013–1017, June 2010. [DOI]
Model Predictive Control with Learning-Type Set-point:Application to Artificial Pancreatic β-Cell
Y. Wang, H. Zisser, E. Dassau, L. Jovanovic, F.J. Doyle III, “Model Predictive Control with Learning-Type Set-point:Application to Artificial Pancreatic β-Cell ,” AIChE Journal, vol. 56, no. 6, pp. 1510–1518, June 2010.[DOI]
Prevention of Nocturnal Hypoglycemia Using Predictive Alarm Algorithms and Insulin Pump Suspension
B.A. Buckingham, H.P. Chase, E. Dassau, E. Corby, P. Clinton, V. Gage, K. Caswell, J. Wilkinson, F. Cameron, H. Lee, B.W. Bequette, F.J. Doyle III, “Prevention of Nocturnal Hypoglycemia Using Predictive Alarm Algorithms and Insulin Pump Suspension,” Diabetes Care, vol. 33, no. 5, pp. 1013–1017, May 2010.[DOI]
Closed-Loop Control of Artificial Pancreatic β-Cell in Type 1 Diabetes Mellitus Using Model Predictive Iterative Learning Control
Y. Wang, E. Dassau, F.J. Doyle III, “Closed-Loop Control of Artificial Pancreatic β-Cell in Type 1 Diabetes Mellitus Using Model Predictive Iterative Learning Control,” Biomedical Engineering, IEEE Transactions on, vol. 57, no. 2, pp. 211–219, February 2010.[DOI]
Enhanced 911/global position system wizard: a telemedicine application for the prevention of severe hypoglycemia–monitor, alert, and locate
E. Dassau, L. Jovanovic, F.J. Doyle III, H.C. Zisser, “Enhanced 911/global position system wizard: a telemedicine application for the prevention of severe hypoglycemia–monitor, alert, and locate,” Journal of Diabetes Science and Technology, vol. 3, no. 6, pp. 1501-6, Nov 2009. [PMID]
A Novel Adaptive Basal Therapy Based on the Value and Rate of Change of Blood Glucose
Y. Wang, M.W. Percival, E. Dassau, H.C. Zisser, L. Jovanovic, F.J. Doyle III, “A Novel Adaptive Basal Therapy Based on the Value and Rate of Change of Blood Glucose,” J Diabetes Sci Technol, vol. 3, pp. 1099–1108, September 2009.[DOI]
Safety constraints in an artificial pancreatic beta cell: an implementation of model predictive control with insulin on board
C. Ellingsen, E. Dassau, H. Zisser, B. Grosman, M.W. Percival, L. Jovanovic, F.J. Doyle III, “Safety constraints in an artificial pancreatic beta cell: an implementation of model predictive control with insulin on board,” Journal of Diabetes Science and Technology, vol. 3, no. 3, pp. 536-44, May 2009. [PMID]
Practical approach to design and implementation of a control algorithm in an artificial pancreatic β-cell
M. W. Percival, E. Dassau, H. Zisser, L. Jovanovic, and F. J. Doyle III, “Practical approach to design and implementation of a control algorithm in an artificial pancreatic β-cell,” Ind Eng Chem Res, vol. 48, pp. 6059–6067, April 2009.[DOI]
In silico evaluation platform for artificial pancreatic beta-cell development–a dynamic simulator for closed-loop control with hardware-in-the-loop
E. Dassau, C.C. Palerm, H. Zisser, B.A. Buckingham, L. Jovanovic, F.J. Doyle III, “In silico evaluation platform for artificial pancreatic beta-cell development–a dynamic simulator for closed-loop control with hardware-in-the-loop,” Diabetes Technology & Therapeutics, vol. 11, no. 3, pp. 187-94, Mar 2009. [DOI]
In silico preclinical trials: methodology and engineering guide to closed-loop control in type 1 diabetes mellitus
S.D. Patek, B.W. Bequette, M. Breton, B.A. Buckingham, E. Dassau, F.J. Doyle III, J. Lum, L. Magni, H. Zisser, “In silico preclinical trials: methodology and engineering guide to closed-loop control in type 1 diabetes mellitus,” Journal of Diabetes Science and Technology, vol. 3, no. 2, pp. 269-82, Mar 2009. [PMID]
Coordinated basal-bolus infusion for tighter postprandial glucose control in insulin pump therapy
J. Bondia, E. Dassau, H. Zisser, R. Calm, J. Vehí, L. Jovanovič, F.J. Doyle III “Coordinated basal-bolus infusion for tighter postprandial glucose control in insulin pump therapy,” Journal of Diabetes Science and Technology, vol. 3, no. 1, pp. 89-97, Jan 2009. [PMID]
Bolus calculator: a review of four “smart” insulin pumps
H. Zisser, L. Robinson, W. Bevier, E. Dassau, C. Ellingsen, F.J. Doyle III, L. Jovanovic, “Bolus calculator: a review of four “smart” insulin pumps,” Diabetes Technology & Therapeutics, vol. 10, no. 6, pp. 441-4, Dec 2008. [DOI]
Modular artificial beta-cell system: a prototype for clinical research
E. Dassau, H. Zisser, C. C Palerm, B. A Buckingham, L. Jovanovic, F. J Doyle III, “Modular artificial beta-cell system: a prototype for clinical research,” Journal of Diabetes Science and Technology, vol. 2, no. 5, pp. 863-72, Sep 2008. [PMID]
Detection of a Meal Using Continuous Glucose Monitoring: Implications for an artificial β-cell
E. Dassau, B. W. Bequette, B. A. Buckingham, and F. J. Doyle III, “Detection of a Meal Using Continuous Glucose Monitoring: Implications for an artificial β-cell,” Diabetes Care, vol. 31, pp. 295–300, February 2008.[DOI]

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