Cellular Hedging and mathematical modeling
Abstract
Cells have evolved redundant strategies where the function of survival is through asmall dormant subpopulation of cells (sometimes called persistor cells) within a morerapidly proliferating population. It has been suggested that these cells are responsiblefor the persistence of chronic infections, as well as the recalcitrance of certaincancers. Acquisition of resistance to anticancer drugs is a major problem in cancertherapy and these cells could be viable targets for new therapies. Nevertheless, theirtransient nature and low abundance, has impeded experimental advancements. Novelways of thinking about these issues are needed. The Black Scholes Merton model is a stochastic mathematical model of a financial market containing derivative investment instruments. Using Hamilton Jacobi Bellman optimal control theory, a partial differential equation can be derived that estimates the price of an option. The key idea is to hedge the option by buying and selling the underlying asset to minimise risk. These ideas revolutionised the financial industry. The aim of this project is to bring these two areas together making significant contributions to Fundamental Laws of Biology, Synthetic Biology, and Stochastic Control. The underlying hypothesis is that some biological cells hedge by carrying additional regulatory and chemical machinery. This machinery may only function in response to periods of extreme stress. We will develop stochastic models driven by Wiener noise and Poisson jump noise (to account for behaviour under extreme stress) that capture the behaviour of this machinery.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jul 28, 2017
- Source ID
- FA23861714037
Entities
People
- Kevin Burrage
Organizations
- Air Force Office of Scientific Research
- Queensland University of Technology
- United States Air Force