A Scalable Formulation for Engineering Combination Therapies for Evolutionary Dynamics of Disease
Vanessa Jonsson and Richard M. Murray
Submitted, 2014 American Control Conference (ACC)
It has been shown that optimal controller synthesis for positive systems can be formulated as a linear program. Leveraging these results, we propose a scalable iterative algo- rithm for the systematic design of sparse, small gain feedback strategies that stabilize the evolutionary dynamics of a generic disease model. We achieve the desired feedback structure by augmenting the optimization problems with `1 and `2 regular- ization terms, and illustrate our method on an example inspired by an experimental study aimed at finding appropriate HIV neutralizing antibody therapy combinations in the presence of escape mutants.
- Conference Paper: http://www.cds.caltech.edu/~murray/preprints/jm14-acc_s.pdf