How do you assess the impact of biocomputational models?
In this webinar, you will learn about general principles to evaluate the prospective economic and clinical benefits of simulation methods. We will show how this approach enables you to:
The webinar is targeted at biocomputational modellers and researchers as well as RTD funding agencies in the field of Virtual Physiological Human and Physiome.
Tuesday, March 27, 2012, 09:00 PDST/13:00 EST/18:00 CEST (UTC +02:00)
Duration: 60 minutes
To register for the event, visit: https://stanford.webex.com/stanford/onstage/g.php?d=925320571&t=a
Karl Stroetmann and Rainer Thiel, empirica Communication and Technology Research, Bonn, Germany
About this webinar
The economic assessment method described reflects the latest research from the NMS Physiome project, a cooperation of two of the largest global research projects focusing on predictive, personalised and integrative musculoskeletal medicine: the Osteoporotic Virtual Physiological Human (VPHOP) project supported by the European Commission, and the Center for Physics-based Simulation of Biological Structures (SIMBIOS) at Stanford University, funded by the US National Institutes of Health.
The Virtual Physiological Human (VPH) is a framework of methods and technologies that, once fully established, is expected to make possible the virtual investigation of the human body as a whole. Started in Europe in 2005, it has rapidly grown to become one of the research priorities of the Information and Communication Technologies Programme of the EU Seventh Framework Programme for Research and Technological Development, which runs from 2007 to 2013. In the US, VPH-type research is funded by all the federal agencies that participate in the Interagency Modeling and Analysis Group (IMAG), whose grantees are coordinated in the Multi-Scale Modeling (MSM) consortium.
NMS Physiome is an international project co-funded by the European Commission Seventh Framework Programme for Research and Technological Development. The Webinar is hosted by SIMBIOS, Stanford University.