title: Systems approaches and algorithms for discovery of combinatorial therapies.
abstract: Effective therapy of complex diseases requires control of highly nonlinear complex networks that remain incompletely characterized. In particular, drug intervention can be seen as control of cellular network activity. Identification of control parameters presents an extreme challenge due to the combinatorial explosion of control possibilities in combination therapy and to the incomplete knowledge of the systems biology of cells. In this review paper, we describe the main current and proposed approaches to the design of combinatorial therapies, including the heuristic methods used now by clinicians and alternative approaches suggested recently by several authors. New approaches for designing combinations arising from systems biology are described. We discuss in special detail the design of algorithms that identify optimal control parameters in cellular networks based on a quantitative characterization of control landscapes, maximizing utilization of incomplete knowledge of the state and structure of intracellular networks. The use of new technology for high-throughput measurements is key to these new approaches to combination therapy and essential for the characterization of control landscapes and implementation of the algorithms. Combinatorial optimization in medical therapy is also compared with the combinatorial optimization of engineering and materials science and similarities and differences are delineated.
authors.affiliation: Burnham Institute for Medical Research, San Diego, CA, USA.
authors.forename: Jacob D
authors.initials: JD
authors.lastname: Feala
authors.affiliation: Department of Mechanical and Aerospace Engineering, University of California, San Diego, CA, USA.
authors.forename: Jorge
authors.initials: J
authors.lastname: Cortes
authors.affiliation: Department of Physics and Astronomy, Michigan State University, East Lansing, MI, USA.
authors.forename: Phillip M
authors.initials: PM
authors.lastname: Duxbury
authors.affiliation: Department of Physics and Astronomy, Michigan State University, East Lansing, MI, USA.
authors.forename: Carlo
authors.initials: C
authors.lastname: Piermarocchi
authors.affiliation: Department of Bioengineering, University of California, San Diego, CA, USA.
authors.forename: Andrew D
authors.initials: AD
authors.lastname: McCulloch
authors.affiliation: Burnham Institute for Medical Research, San Diego, CA, USA.
authors.forename: Giovanni
authors.initials: G
authors.lastname: Paternostro
mesh_terms: D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D003131:Combined Modality Therapy; D006801:Humans; D049490:Systems Biology / Q000379:methods*