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Prof. Ryan Zurakowski

“Cancer Dynamics: Opportunities for Control Theory in Treatment Design

By Prof. Zurakowski

This talk covers applications both old and new where the dynamics of interactions between the cancer necessitate time-varying treatment applications to obtain maximum effect. 


Prof. Zurakowski’s research is in the area of nonlinear control theory and applications, especially in the area of mathematical biology and medicine. Many biological systems are governed by dynamics that are inherently and irreducibly nonlinear. This gives rise to behaviors that are non-intuitive, and cannot be ascertained by simple network reasoning. Prof. Zurakowski and his collaborators are working to develop mathematical descriptions of disease systems in particular, and to analyze the dynamics using nonlinear control techniques in order to suggest novel therapeutic approaches. In this process, engineering informs biology, as many of the problems arising in biology are similar to ones with well-established solutions in Control Engineering. Likewise, the biology informs the engineering, as many of the biological systems exhibit unique dynamics which forces Control Theory to expand in order to accommodate them. Particular systems of interest are combination oncolytic virus therapy for cancer, treatment interruption scheduling for auto-immunization in early-stage HIV infection, optimal regimen switching to minimize viral resistance during virologic failure in HIV therapy, and bacteria/bacteriophage models for testing evolutionary hypotheses with significance to HIV treatment. Prof. Zurakowski is also involved in more traditional applications of control systems through collaboration with the Army Research Laboratories. Projects include the development of state estimators for self-guided munitions. Current collaborators include Dominik Wodarz at the University of California, Irvine and Eric Wommack at the University of Delaware. Prof. Zurakowski is also affiliated with the Delaware Biotechnology Institute. Current Projects: Optimal management of resistance during regimen switching in HIV therapy, Bacteria/bacteriophage models for testing of evolutionary hypotheses, Nonlinear state-estimators for self-guided munitions.