Jorge Cortés


Systems approaches and algorithms for discovery of combinatorial therapeutics
J. Feala, J. Cortés, P. Duxbury, C. Piermarocchi, A. McCulloch, G. Paternostro
Wiley Interdisciplinary Reviews: Systems Biology 2 (2) (2010), 181-193


Effective therapy of complex diseases requires control of highly non-linear complex networks that remain incompletely characterized. In particular, drug intervention can be seen as control of signaling in cellular networks. 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 empirical 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. Combinatorial Biological Control is a growing field that is benefiting from advances in systems biology, targeted therapeutics, and high-throughput biological measurement technologies as well as from new and established approaches from mathematics, physics and engineering. The study of Combinatorial Therapies is the fastest expanding sub-discipline within this field, though therapeutic applications are not the only uses of the new principles and methods that are being discovered. Combinatorial approaches can also be used to optimize the survival and differentiation of cells in vitro, in synthetic genomics, to delay aging, and to improve physiological performance. Additionally, work in this field can help elucidate the strategies nature uses for combinatorial control and optimization at different scales, from evolution to organismal function. While until recently combinatorial therapies were based on largely empirical methods, new insights are arising from systems biology and from the integration of several biological and non- biological disciplines and are providing the prospect of more rational approaches to the therapy of complex diseases. In this review, we describe the state of the art of combinatorial optimization of medical therapy, starting with relevant contributions from systems biology. We then compare it with more established techniques of systematic optimization in engineering and material sciences.

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Mechanical and Aerospace Engineering, University of California, San Diego
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