Dr. Michelson heads Entelos' in silico research and development efforts and manages the scientific teams that develop the PhysioLab™ biosimulation systems. Previously, he was the Vice President of Information Sciences at VistaGen, Inc. He spent 13 years at Roche Biosciences as Director of Scientific Support Services and, prior to its acquisition by Roche, headed the Department of Biomathematics at Syntex Discovery Research. He also held a research faculty position in the Department of Radiation Medicine at Brown University and has been a guest lecturer at the Soviet Academy of Sciences and at Beijing Medical University. Dr. Michelson received an M.A. in applied mathematics from the University of California at Berkeley, and an M.S. and Ph.D. in biomathematics from the University of California, Los Angeles.
Despite the advent of high throughput technologies, only ten percent of compounds entering human clinical studies go on to become medicines. The problem is clearly not a lack of data, but rather our ability to efficiently extract the appropriate information from it. By understanding a disease at its most fundamental levels, one can aid decision making across the entire development pipeline. Mechanism-based predictive biosimulation has emerged as a technology that:
Establishes, explicitly, what is known, unknown (termed a knowledge gap), and suspected (hypotheticals) about disease advent and progression Quantifies the dynamics surrounding those physiological processes Explicitly tests those assumptions Characterizes the impact of any given knowledge gap on the overall disease process.
Biosimulation allows the research scientist to test, in silico, the hypotheses he/she would entertain to fill the most important gaps. We will present an overview of predictive biosimulation and discuss illustrative case studies in this talk.
