Goals Needs Approach Benefits Coopetition

Goals

The Center for Computational Biology advances the science and engineering of Symbolic Systems Biology and Synthetic Biology. Symbolic Systems Biology applies symbolic representation and reasoning tools to biological systems, providing biologists with predictive power tools. Synthetic Biology leverages parts from natural biological systems to intentionally construct physical systems on the molecular scale, and will enable the reengineering of the living world. The synergy of Symbolic Systems Biology and Synthetic Biology enables human understanding, informed design, and predictive control of biological systems. The Center for Computational Biology is intrinsically multi-disciplinary involving joint work with computer scientists, biologists, mathematicians, chemists, control theorists, and engineers. The Center fosters cross-disciplinary teaming with top research teams at universities and government laboratories.
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Needs

[graph of FDA drug approval rate] The dire potential for new society-threatening emerging diseases and other biological threats demands we rethink how we go about producing new treatments and otherwise defend ourselves. Exponentially increasing populations of senior citizens and people with chronic and urgent medical needs demand more cost-effective diagnosis and treatments. The synergy of symbolic systems biology and synthetic biology provides an approach to addressing this need. Population explosions in developing countries provide breeding grounds for virulent diseases, and increased access to worldwide transportation make worldwide outbreaks of new diseases a deadly certainty. New drug development costs are escalating exponentially, but the number of new drugs approved each year in the U.S. is dropping. Although the combined research budgets of the pharmaceutical industry exceeds 30 billion dollars a year, and federal spending on biological research exceeds 28 billion dollars a year by the National Institute of Health (NIH), the drug and treatment approval rate by the FDA has plummeted from over 50 to less than 20 per year since 1996. This is a disturbing trend for a growing world population under the threat of rapidly spreading infectious diseases, and an aging populations in many countries. From the pharmaceutical industry viewpoint, just as troubling as the diminishing number new drugs reaching the market is the fact that half of those drugs do not even return their inital investment.

[a graph of data growth] Fortunately, there has been explosive progress in biological data gathering. The exponential growth of available biological data and the exponential decrease in the cost of obtaining new data follow steeper trends than Moore's Law or Robert's Law driving the revolution in information technology. In order to effectively exploit the torrents of genomic, proteomic, and chemogenomic data coming available we must develop tools able to reason about biological systems at high levels of abstraction, but able to concretize results to real biological problems and solutions.

The motivation for the Center of Computational Biology is that two keys to accelerate biological and pharmaceutical research are:

  • the translation of data into knowlege
  • the translation of knowledge into architected biological processes.

The first transformation --from data to knowledge-- is achieved by applying the tools of modern computer science, including symbolic and hybrid symbolic/continuous reasoning tools, to problems of biological interest. This will provide biological researchers and decision makers with power tools, speeding up the human understanding of complex biological processes, and enabling more informed decisions.

The second transformation -- from knowledge to architected biology -- is achieved by bringing an engineering mindset to biology, leading to architected biological processes. New computational solutions to the analysis of biological data must be created. The existing computational solutions have not been sufficient in extracting critical knowledge from the data, which knowledge would accelerate and enhance biological and pharmaceutical research. Our solution is to create a synthesis of two cutting edge research: Symbolic Systems Biology and Synthetic Biology. This synthesis will be disruptive, both scientifically and commercially.

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Approach

The center has a multi-prongued approach of scientific and tool developments in Symbolic Systems Biology and Synthetic Biology. The programatic areas in the center are:

Programmatic Approaches
Symbolic Systems Biology Synthetic Biology
Pathway Logic Logical circuit design and implementation in biology (e.g., BioBricks)
Synthetic Biology: The biokleptic exploitation of natural parts, the engineering of new parts, and the systematic design and engineering of biological systems using those parts.
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Benefits

The Center for Comptutational Biology and collaborating research groups are at the forefront of a revolution in biological research. Applying the discipline of engineering to biology will revolutionize many aspects of life, from medical research to engineered construction materials to replacement body parts to as-yet-unimagined uses for engineered, reactive, self-sustaining colonies of living organisms. In the short-term, the Center for Comptuational Biology builds tools helping biologists understand complex biological systems, and small synthetic biology components.
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Partners

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Coopetition

Other groups are pursuing similar or complementary aims. Some of the key groups are listed. Only by appropriately building on each other's work will researchers be able to make advances in science and engineering at the pace required. The SRI Center for Comptuational Biology partners with several of these top research groups on problems and solutions of mutual interest. Please contact us if you would like to explore partnerships and joint projects.

Systems Biology

Synthetic Biology