Daniel Baugh Institute

The major long-range goal of the Physiome Project is to quantitatively describe the human organism based upon an understanding of human physiology and pathophysiology, and to use this understanding to improve human health. Models of human physiology integrate knowledge at increasing levels of biological organization from genomics, molecular biology and the environment; to cells, tissues and organs; ultimately to integrated systems. Top-down modeling of particular systems has already proven its value in new drug design. These models can be broadly based and well validated against large amounts of experimental evidence, yet they do not predict a new drug's side effects outside the particular system modeled. Genotype-to-phenotype statistical relationships represent the result of the combination of genetic, developmental and environmental influences. Large-scale high-level models of the cardiovascular/respiratory/transport system for solute exchange, however, can be predictive. These models are hierarchical, with representation at different levels including, for example, 1) regulation of transcription and protein metabolism; 2) processes in cells and tissues, and 3) organ and system level interactions. One example is our work in modeling respiratory gas and solute exchanges. We developed transport models (in JSim, a Java-based simulation system) using one-dimensional partial differential equations of solute absorbance profiles along airways and extraction or reaction along capillaries. Spatial profiles of tissue concentration are determined by rates of permeation, binding or transformation in each tissue cell type. Metabolic models must necessarily include the transport processes if physiological parameterization is the goal. One of the several difficulties with multiscale modular modeling is that using reduced form models to gain computational speed sacrifices robustness and breadth of applicability (Supported by NIH grants R01-HL073598-01, R01-EB001973-24 to develop JSim and to distribute it for free at http://www.physiome.org, and DARPA X81XWH-04).

David Samuels, PhD

David Samuels is an assistant professor at the Virginia Bioinformatics Institute at Virginia Tech, where his group works on computational biomedical research, mainly in the area of mitochondrial medicine. Dr. Samuels' PhD is in Physics, from the University of Oregon. He was a postdoctoral fellow at Stanford, NASA, and at Emory University. Later, he was Reader in Applied Mathematics at the University of Newcastle upon Tyne in the UK. At Newcastle, David began to work with members of the Neurology department in the medical school. In 2002 David moved to the new bioinformatics research institute at Virginia Tech to devote his research to biomedical work, in collaboration with several clinical and lab researchers.