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

fYear

2014

fDate

15-17 Dec. 2014

Firstpage

2352

Lastpage

2358

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on

Conference_Location

Los Angeles, CA

Print_ISBN

978-1-4799-7746-8

Type

conf

DOI

10.1109/CDC.2014.7039747

Filename

7039747