Active Participants:
David Cai
Howard J. Chizeck
James Glazier
Dan Haworth
George Karniadakis
Wilfred Li
Ching-Long Lin
Michela Taufer
Observers:
Roger Armen
Victor Barocas
Jim Brasseur
Dennis Chao
Steven Dong
Bill Hazelton
Eric Hoffman
Andre Kerstens
Gregor Kovacic
Georg Luebeck
Andrew McCulloch
Igor Pivkin
Peter Richarsdon
Pat Teller
Kurt Anderson
Active participants:
Active Participants:
Daniel Beard, Medical College of Wisconsin
Gerald Saidel, Case Western Reserve University
Nicola Lai, Case Western Reserve University
Ranjan Dash, Medical College of Wisconsin
James Bassingthwaighte, University of Washington
Wilfred Li, San Diego Supercomputer Center
Andrew McCulloch, University of California, San Diego
Nicholas Smith, University of Auckland
Observers:
Howard Chizeck, University of Washington, Seattle
The main goal of this project is to develop a software based on a novel mathematical framework that uses individual COVID-19 patient data to obtain accurate personalized treatment strategies. We aim to achieve this goal using an extensive pharmacokinetic model building, an optimal control approach for parameter estimation, and tools from statistical sensitivity analysis to devise new and efficient treatment strategies. Our proposed framework will be highly beneficial for health professionals to make fast and accurate decisions about treatment strategies, without the need for numerous clinical trials, thereby assisting the world in its fight against COVID-19.
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Note: Because of Covid-19, the training workshops will not be held in person. Instead, we will use a combination of Zoom, YouTube and other remote access tools. We will keep attendees informed as the details are finalized.
Veterans Health Administration (VHA) Innovation Ecosystem launched the COVID-19 Risk Factor Modeling Challenge.
