Title :
Synthesizing combination therapies for evolutionary dynamics of disease for nonlinear pharmacodynamics
Author :
Jonsson, Vanessa ; Matni, Nikolai ; Murray, Richard M.
Author_Institution :
Dept. of Control & Dynamical Syst., California Inst. of Technol., Pasadena, CA, USA
Abstract :
Our previous results proposed an iterative scalable algorithm for the systematic design of sparse, small gain feedback strategies that stabilize the evolutionary dynamics of a generic disease model with linear pharmacodynamics. In this manuscript, we use piecewise linear approximations to model nonlinear drug effects. We leverage results from optimal controller synthesis for positive systems to formulate the feedback synthesis problem as an optimization problem that sequentially explores piecewise linear subsystems corresponding to higher and higher treatment dosages.
Keywords :
control system synthesis; diseases; drugs; evolutionary computation; feedback; iterative methods; medical control systems; optimal control; optimisation; piecewise linear techniques; combination therapies synthesis; disease; evolutionary dynamics; feedback synthesis problem; generic disease model; iterative scalable algorithm; linear pharmacodynamics; nonlinear drug effects; nonlinear pharmacodynamics; optimal controller synthesis; optimization problem; piecewise linear subsystems; positive systems; small gain feedback strategies; systematic design; treatment dosages; Drugs; Heuristic algorithms; Human immunodeficiency virus; Mathematical model; Piecewise linear approximation; Robustness;
Conference_Titel :
Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-1-4799-7746-8
DOI :
10.1109/CDC.2014.7039747
