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

Research output: Contribution to conferencePaper, not in proceeding

Abstract

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.

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Subject classification (UKÄ) – MANDATORY

  • Control Engineering
Original languageEnglish
Publication statusPublished - 2014
Publication categoryResearch
Peer-reviewedNo
EventAmerican Control Conference, 2014 - Portland, OR, United States
Duration: 2014 Jun 42014 Jun 6

Conference

ConferenceAmerican Control Conference, 2014
CountryUnited States
CityPortland, OR
Period2014/06/042014/06/06

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