Computational Modeling for Bedside Application - 22/08/11
, Sanjiv M. Narayan, MD, FACC b, Jeffrey H. Omens, PhD a, Lawrence J. Mulligan, PhD c, Andrew D. McCulloch, PhD a
Corresponding author. Department of Bioengineering, The Whitaker Institute for Biomedical Engineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0412.Abstract |
Advances in computer power, novel diagnostic and therapeutic medical technologies, and an increasing knowledge of pathophysiology from gene to organ systems make it increasingly feasible to apply multiscale patient-specific modeling based on proven disease mechanisms. Such models may guide and predict the response to therapy in many areas of medicine. This is an exciting and relatively new approach, for which efficient methods and computational tools are of the utmost importance. Investigators have designed patient-specific models in almost all areas of human physiology. Not only will these models be useful in clinical settings to predict and optimize the outcome from surgery and non-interventional therapy, but they will also provide pathophysiologic insights from the cellular level to the organ system level. Models, therefore, will provide insight as to why specific interventions succeed or fail.
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| This work was supported by Medtronic Inc., UC Discovery Grant ITL06-10159 (to A.D.M.), a grant from the UCSD von Liebig Center for Entrepreneurship and Technology Advancement (to A.D.M.), the National Biomedical Computation Resource (NIH grant P41 RR08605) (to A.D.M), the National Science Foundation (BES-0506252) (to A.D.M), NIH grant HL83359 and a grant from the Doris Duke Clinical Foundation (to S.M.N), NIH grant HL32583 (to J.H.O.). This investigation was conducted in part using a facility constructed with support from Research Facilities Improvement Program Grant Number C06 RR-017588-01 from the National Center for Research Resources, National Institutes of Health. |
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| Andrew McCulloch and Jeffrey Omens are cofounders of and consultants to Insilicomed Inc., a licensee of UCSD-owned software used in this research. Insilicomed was not involved in this research. Lawrence Mulligan is an employee of Medtronic. |
Vol 4 - N° 3
P. 371-378 - juillet 2008 Retour au numéro
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