SystemsX: The Final Frontier for Biotechnology?

Although difficult to conceive, the 21st century may see the boundaries of biological knowledge completely defined. While the notion that we could understand everything there is to know about living systems is hard to grasp from a philosophical point of view, it has profound implications for the commercial sector of biotechnology. A new project called “Systems X,” now underway in Switzerland, may provide answers to fundamental questions of medical science and supply the direction for development of a new generation of therapies.

The project-driven by a consortium of universities and private companies in Zurich, Lausanne, and Basel-grew out of the realization that complex biological states and organizational structures cannot be understood as a series of linear, cause-and-effect relationships. In the 19th century, health challenges such as major infectious diseases could be seen as a simple presence or absence of a pathogen, and in the 20th century fundamental molecular processes were reduced to simple mechanistic models (i.e., genes are composed of DNA; the genetic code is a triplet; RNA exists in three forms). In the 21st century, however, the questions faced by basic scientists and entrepreneurs are more complex by orders of magnitude. For example, major diseases such as cancer and cardiovascular diseases do not have simple, unitary causes, but rather arise from the interaction of many contributing genetic and environmental factors. Sorting out these various components requires highly complex models that can integrate many input variables in a multidimensional fashion. Systems biology seeks to map out these networks and model complex assemblies that will allow predictions and eventually control and management of biological processes.

According to the SystemsX web site, the field is still attempting to define itself. It is described, rather than defined, as an interdisciplinary approach to the investigation of all the components and networks contributing to a system. Using large data sets and computer modeling, it will generate iterative cycles of predictions and experimentation, based on paradigms from physics and chemistry (1). The level of complexity requires the collaboration of investigators from many disciplines, including biology, physics, mathematics, information science, chemistry, and nanotechnology. Its proponents anticipate revolutionary discoveries and with them, novel applications such as the manipulation of biological molecules and the development of biochips and miniature sensors for rapid diagnosis and measurement of regulatory parameters. This vision explains the vast scope of the project, which will extend over many years, and the difficulty of more modest programs to attack systems biology in a meaningful fashion.

The chair of the SystemsX executive committee, Professor Rűdi Aebersold, director of the Institute for Molecular Systems Biology at the Swiss Federal Institute of Technology Zurich (www.ethz.ch) explains the basis of the program using language as an analogy. Aebersold says that although the genomes of many organisms have been completely sequenced at this time, and thus the words of the language are known, the syntax is still a mystery. And that syntax, he says, is critical for an understanding of complex biological phenomena.

New science requires new organization
The founders of SystemsX believe that systems biology requires not only new science, but new organization as well. The program is a joint effort of a consortium of universities and private companies, and is centered at the Swiss Federal Institute of Technology Zurich (www.ethz.ch), EPF Lausanne (the Federal Polytechnic Institute of Lausanne, www.epfl.ch), the University of Zurich (www.unibas.ch), and the University of Basel (www.unizh.ch). The program will operate as a network of “scientific nodes”-each rooted at one of the participating institutions-and a series of “glue projects,” which, as the name implies, tie the institutes together with overreaching joint research goals. The structure of SystemsX is designed to minimize traditional rivalries that have bedeviled large collaborative scientific projects in the past.

Thus, SystemsX will comprise an interdisciplinary program spread over the entire country and beyond the borders of Switzerland. It will focus on new approaches, technologies within a new framework and with a new educational program. While the timeline is somewhat speculative at present, it clearly will extend for a decade or more.

Why systems biology?
If the concept is not yet clearly defined, and no therapies or treatments of disease have emanated from it, one might question why a Manhattan Project-size effort to elaborate systems biology would be justified at this time. Perhaps the best explanation can be couched in a consideration of the vast failures of conventional inductive biology to solve the major health issues of the second half of the 20th century. Between 1945 and 1995 virtually no progress was made in lowering death rates in cancer victims (2).

Groopman discussed these trends in an acerbic and skeptical analysis in The New Yorker (3) in which he described cycles of euphoria and despair as new cancer treatments were introduced in the 1970s, 80s, and 90s with great fanfare, only to be found wanting. Recent American Cancer Society statistics (1995–2002) show dramatic improvement in cancer survival rates, although much of this is the result of smoking cessation, and it is too early to measure the long-term benefits of new therapies such as anticancer monoclonal antibodies.

Cardiovascular diseases declined dramatically over the last half century, but much of the change was due to improved diet, smoking cessation, and lifestyle improvement and had nothing to do with the deepening understanding of the condition on a molecular level (4).  Ageing, mental disorders, and autoimmune dysfunction all seemed more intractable, even as the molecular twists and turns of these conditions became clearer and more defined.

It is emblematic of the shortcomings of the strict reductionist approach to complex diseases that so many drugs fail, even in late-phase clinical trials. Several companies developing antibodies to inflammatory factors saw their fortunes slide in the 1990s (5) and recently several anticancer antibodies failed in Phase 2 and 3 trials. So while therapies that narrowly focus on specific targets in cancer cells have recently produced encouraging results (6), there clearly is a pressing need for more encompassing approaches to complex diseases.

Many research groups and institutes throughout the world focus on systems biology. Most notable is The Institute for Systems Biology in Seattle, of which Leroy Hood is the director. This premier organization is on the forefront of systems biology investigation (7–12) and has strong ties to the SystemsX Project, as shown by the fact that Hood is a member of its scientific advisory board and Aebersold is a co-founder of the ISB.

There is an extensive literature of systems biology investigation (1,200 citations in Medline), and a number of private companies are venturing into the therapeutic arena. For example, Genstruct is developing complex models of diseases combining analysis of genes, proteins, and metabolic parameters. Entelos is evaluating mathematical modeling to study diseases. Merrimack Pharmaceutical is testing information on signaling networks in tumor cells to determine which drugs are effective. Avalon Pharmaceuticals is using gene expression technology to determine likely responders to therapies (13).

But what distinguishes the SystemsX Project is its ability to bring together investigators, disciplines, and resources in a fashion that has not yet been possible. “For us, what distinguishes SystemsX from other systems biology initiatives is its structure,” says Aebersold. “In a sense, we try to let ‘form follow function.’ We are attempting to study networks of interacting components and hence SystemsX is also structured as a network of interacting elements.”

While international in scope, SystemsX is centered in a part of world dense with biomedical talent. Hoffman La Roche and Novartis, with their headquarters in Basel, will provide support for the project as will other companies. The universities involved in the work are among the best on the planet. By pooling talent and resources, it should be possible to generate and manage in an unparalleled fashion the vast rivers of data that will flow into the project.

The progress of the SystemsX project in developing new therapeutics will be measured in years, not months, and venture capitalists and pharmaceutical executives may be looking at programs that will outlast their tenures. But the force of this approach is powerful enough to carry it along to a point at which treatments for the many intractable conditions that constitute the final frontier of clinical medicine begin to accrue.
 References

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2. American Cancer Society [Internet page]. Atlanta: American Cancer Society, 2007. Available from: www.cancer.org/downloads/STT/CAFF2006PWSecured.pdf).

3. Groopman, J. The thirty years’ war; have we been fighting cancer the wrong way? The New Yorker. 2001;(6-4):52–63.

4. Anonymous. Achievements in Public Health, 1900–1999: Decline in deaths from heart disease and stroke–United States, 1900­–1999. MMWR Weekly. 1999;48(30):649–656.

5. Morrow, KJ. Recent failures drive biotechnology firms to adopt novel strategies to combat sepsis. Gen Eng News. 1994;14(17):1–12.

6. Caponigro F, Milano A, Ottaiano A, Iaffaioli RV. Epidermal growth factor receptor as a major anticancer drug target. Expert Opin Ther Targets. 2006;10(6):877–88.

7. Bonneau R, et al. The Inferelator: an algorithm for learning parsimonious regulatory networks from systems-biology data sets de novo. Genome Biol 2006;7(5):R36.

8. Burrage K, Hood L, Ragan MA. Advanced computing for systems biology. Brief Bioinform. 2006 Sep 25;[Epub ahead of print].

9. Hwang D, et al. A data integration methodology for systems biology. Proc Natl Acad Sci USA 2005a;102(48):17296–301.

10. Hwang D, et al. A data integration methodology for systems biology: experimental verification. Proc Natl Acad Sci USA. 2005b;102(48):17302–7.

11. Stanford JL, et al. Prostate cancer and genetic susceptibility: a genome scan incorporating disease aggressiveness. Prostate. 2006;66(3):317–25.

12. True L, et al. A molecular correlate to the Gleason grading system for prostate adenocarcinoma. Proc Natl Acad Sci. USA 2006;103(29):10991–6.
 
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