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Joseph O. Deasy, PhD
Chair, Department of Medical Physics
Enid A. Haupt Endowed Chair in Medical Physics
Memorial Sloan Kettering Cancer Center
New York, New York
Seeking to develop new tools to interpret and understand large sets of scientific data.
Novel mathematical methods are applied to understand cancer growth, progression and response to therapy.
These efforts will inform novel treatment approaches that can be tested in the laboratory and ultimately in the clinic.
Certain characteristics of cancer are highly mathematical. For example, cancer growth itself can be modeled using relatively simple mathematical equations. Intracellular signaling is a very complicated phenomenon, but with mathematical models it can be understood as a network of connected nodes. The research led by Drs. Deasy, Tannenbaum, and Norton is applying an integrated mathematical approach to model cancer development and response to treatments.
Full Research Summary
Massive amounts of scientific data have been generated in cancer research over the last decade. The information that is buried in these data silos has the potential to both unlock new discoveries that will advance our knowledge of cancer initiation, treatment, and control, and to change the course of cancer care for millions of people around the globe. Appropriate mathematical models and tools need to be developed to shine a light on the inner principles driving cancer and treatment response.
This project headed by Drs. Deasy, Tannenbaum and Norton brings together mathematicians, biologists, oncologists and other scientists to develop new tools to interpret, model, and understand scientific data.
Novel mathematical methods will be used to focus on disease evolution, cancer treatment response, and variable patient risk of toxicity to advance precision medicine in cancer.
The researcher team has already assessed the impact of genes that are likely associated with individual drug response, successfully identifying very plausible biological processes associated with drug response across various cell lines and cell types.
In the coming year they will continue to refine their model to more accurately approximate what happens inside of a cell. They will test the effects of various treatments in their model of cancer cell function and then validate them in cell and biological systems.
The mathematical methods derived from these efforts will be used to predict novel treatment approaches that can be tested in the laboratory and ultimately in the clinic.
Dr. Joseph O. Deasy is Chair of the Department of Medical Physics, and holder of the Enid A. Haupt Endowed Chair in Medical Physics, at Memorial Sloan Kettering Cancer Center, New York.
Dr. Deasy is an attending physicist at Memorial Sloan Kettering Cancer Center (MSK). He received his PhD in Physics from the University of Kentucky in 1992. Thereafter he completed a NIH-funded post-doctoral fellowship at the University of Wisconsin-Madison, with mentors Rock Mackie and Jack Fowler. Before arriving at MSK in 2010, Dr. Deasy spent 11 years in the Department of Radiation Oncology, Washington University in St. Louis, first in the physics division under the direction of James Purdy, and later as the first Director of the Division of Bioinformatics and Outcomes Research. Dr. Deasy is the co-author of about 140 peer-reviewed publications and has been the principal investigator of several NIH grants. Dr. Deasy’s current interests are in applying mathematical modeling and machine learning to the analysis of imaging, genomic, and treatment datasets in order to understand the relationship between treatment, patient, and disease characteristics and the probability of disease progression and treatment response.