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A Scalable Formulation for Engineering Combination Therapies for Evolutionary Dynamics of Disease

På svenska

Author

Summary, in English

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 algorithm 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 l1 and l2 regularization 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.

Publishing year

2014

Language

English

Document type

Conference paper

Topic

  • Control Engineering

Conference name

American Control Conference, 2014

Conference date

2014-06-04 - 2014-06-06

Conference place

Portland, OR, United States

Status

Published

Project

  • LCCC

Research group

  • LCCC