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Oct 1, 2011 (Vol. 31, No. 17)

Biological Complexity Under Attack

A Personal View of Systems Biology and the Coming of "Big" Science

  • P4 Medicine

    Data-driven, information-based, proactive P4 medicine is a systems approach to disease that focuses on understanding the dynamics of disease-perturbed networks in the disease-relevant organ(s).19-24 These insights provide powerful new approaches for understanding disease mechanisms, pioneering new diagnostics techniques, and rethinking how drug targets should be chosen.

    The vision is that in 10 years each patient will be surrounded by a virtual cloud of billions of data points and that we will have the information technology to reduce this enormous data dimensionality to simple hypotheses about health and disease. The ultimate outcome is to create for the individual patient disease models that are predictive and actionable. P4 medicine is a major scientific thrust at ISB.

  • Key Challenge

    The challenge for all scientific and engineering disciplines in the 21st century is complexity. Biology has uniquely powerful systems approaches, emerging technologies, and new analytical tools for deciphering this complexity. Each scientific discipline has its own types of complexity although there are certainly unifying principles that interconnect them.

    There are four fundamental pillars for dealing with biology’s complexity:

    1.  Biology is an informational science. This view is essential to deconvolutioning biological complexity.
    2.  A systems approach to dealing with complex biological systems needs to be holistic rather than atomistic.
    3. Evolving and emerging technologies must let new dimensions of an organism’s (and patient’s) data space be explored—in a holistic, high-throughput, integrative, and ultimately, quantitative manner.
    4. New analytic tools, both mathematical and computational, can capture, validate, store, mine, integrate, and, ultimately, model various types of biological data.

    With these four pillars, biology is in a position to attack some of society’s most fundamental (or big) problems—healthcare, global health, agriculture, nutrition, environment, bioenergy, animal health, etc. We have had a glimpse at how these principles might be applied to healthcare and what we have learned about how to effectively attack the medical challenges can readily be extended to the other biological areas.

    Systems approaches are also being used to attack fundamental problems in many other areas, including economics, sociology, and even politics. Certain types of big science will be essential for solving these societal problems. 

  • Big and Small Science

    Since the inception of the Human Genome Project, there has been a conflict in the minds’ of biologists between big and small science. In the mid 1980s, it was clear that most biologists and the NIH were opposed to the big science of the Human Genome Project. They viewed big science as wasteful and inefficient, as centered on a problem that was trivial (most of the genome was “junk”). They considered it an endeavor that could be done by technicians and that real biologists would not find interesting.

    The fear also was that big science would take away financial support from small science—the single investigator-initiated science focused on very discrete hypotheses and biological problems.

    Instead, the Human Genome Project, the discovery form of big science, has transformed the field of biology and medicine and brought with it new resources.

    There is, however, a natural synergy between big and small science. Big science can lay out the general context of the challenges, whereas small labs are wonderful at attacking and deciphering the more subtle details.

    The cry against big science continues today and is exacerbated each time research funding becomes compromised. Indeed, small science can potentially get easily lost in the maize of Darwinian complexity, and big science can provide powerful roadmaps for the most fruitful directions forward.

    A critical point is that these big problems can most effectively be attacked by several forms of big science including the type we have developed at ISB.

  • Types of Big Science

    There are many types of big science and they each can be useful for different types of problems.

    First, the focused, systems-driven, cross-disciplinary, milestone-driven, and integrative systems biology of ISB has been quite effective in attacking both complex biological and medical problems such as P4 medicine.

    Second, the Human Genome Project represents a wonderful example of discovery-based big science where the objective is to define all of the elements in a biological object (the human genome) without consideration of hypothesis-driven questions.

    Third, another type of big science is a loose federation of scientists that cluster around a central problem such as breast cancer. These groups often do not have sharply focused objectives, are not cross disciplinary, and usually are not integrative.

    A fourth approach is that of a single large laboratory that is directed by one individual and often focused on one or more big problems. These efforts can be very productive but are often not systems-driven, cross-disciplinary, nor integrative.

    Finally, the DOE National Laboratories represent another type of big science that has access to incredible technologies and computational and mathematical resources. Clearly different types of big science can be used to approach different types of big problems. 

  • The type of big science that is most effectively poised to attack many large problems of society is the focused, milestone-driven, cross disciplinary, systems-driven, and integrative biology approach. The key to this type of big science is that it is embedded in a cross-disciplinary environment that allows scientists to learn the languages of the other disciplines and permits them to operate in teams to attack the technical and analytical challenges of big problems.

    Moreover, the cross-disciplinary infrastructure is readily accessible to individual scientists to do small science when necessary and appropriate. Fundamental to this type of big science is the creation of milestones to drive the process. Leadership that is organized is also important.

    There are serious societal problems that could benefit from big science. How to realize P4 medicine is one such problem because the challenge of delineating dynamically changing disease-perturbed networks to provide insights into fundamental disease mechanisms, as well as new approaches to diagnosis, therapy, and, ultimately, prevention, must be addressed.

    Moreover, P4 medicine requires the development of many new clinical assays for exploring new dimensions of data space. It also requires new approaches to analyzing data—that capacity to handle billions of data points for the individual patient will require novel computational and mathematical approaches.

  • The Future

    For NIH, a balanced portfolio between big and small science is essential (and I would say the same for the other federal research funding agencies). At least 10–20% of the NIH research dollars should go into big science initially. The capacity to attack big science problems will be fundamental to our future national and international competitiveness.

    In addition, for academia, there is an opportunity to make investments in the cross-disciplinary infrastructure that will make it possible for scientists to attack the big problems of society as well as the small problems of individual investigator-initiated efforts. The U.S. must seriously consider what is key for staying competitive at a national level and in the world forum of science.

  • References

    References:

    1 Hood L, Gray WR, Sanders BG, Dreyer WJ. (1967) Light Chain Evolution. Cold Spring Harbor Symposia on Quantitative Biology 32:133-146.

    2 Dreyer WJ, Gray WR, Hood LE. (1967) The Genetic, Molecular, and Cellular Basis of Antibody Formation: Some Facts and a Unifying Hypothesis. Cold Spring Harbor Symposia on Quantitative Biology 32:353-367.

    3 Steinmetz M, Frelinger JG, Fisher D, Hunkapiller T, Pereira D, Weissman SM, Uehara H, Nathenson S, Hood L. (1981). Cell 24:125-134.

    4 Steinmetz MA, Winoto K, Minard, Hood L. (1982). Cell 28:489-498.

    5 Clark SP, Yoshikai Y, Taylor S, Siu G, Hood L, Mak TW. (1984). Nature 311:387-389.

    6 Kuhn T. (1962) The Philosophy of Science, the Nature and Necessity of Scientific Revolutions, 148-158. MIT Press.

    7 Hood, L. (2002) My Life and Adventures Integrating Biology and Technology. A Commemorative Lecture for the 2002 Kyoto Prize in Advanced Technologies. 2002 Kyoto Prizes and Inamori Grants, 111-165

    8 Hood L. (2008) A personal journey of discovery: developing technology and changing biology. Annu Rev Anal Chem (Palo Alto Calif)1:1-43

    9 Hood, L. Acceptance Remarks for Fritz J. and Delores H. Russ Prize, NAE Journal The Bridge, Summer 2011, 41:(2):46-49.

    10 Hood L. (2002). Journal of Proteome Research 1:399-409.

    11 Rowen L, Koop BF, Hood L. (1996). Science 272:1755-1762.

    12 Lander ES, et al. (2001). Nature 409:860-921.

    13 Lander ES, et al. (2004). Nature 431:931-945.

    14 Zody MC, et al. (2006). Nature 440:671-675.

    15 Heilig R, et al. (2003). Nature 421:601-607.

    16 Smith LM, Sanders JZ, Kaiser RJ, Hughes P, Dodd C, Connell CR, Heiner C, Kent SBH, Hood LE. (1986). Nature 321:674-679.

    17 Hood L, Rowen L, Galas DJ, Aitchison JD. (2008). Briefings in Functional Genomics and Proteomics Jul:7(4):239-48.

    18 Weston AD, Hood L. (2004). Journal of Proteome Research 3:179-196.

    19 Hood L, Heath JR, Phelps ME, Lin B. (2004). Science 306:640-643.

    20 Hood L, (2008) A Systems Approach to Medicine Will Transform Healthcare”, In Physical Biology: From Atoms to Medicine Ahmed H. Zewail (ed.) p. 337, Imperial College Press, London.

    21 Hood LE, Galas D (2009). IBC 2009, vol. 1, no. 2, article no. 6, pp. 1-4.

    22 Hwang D, Lee IY, Yoo H, Gehlenborg N, Cho J-H, Petritis B, Baxter D, Pitstick R, Young R, Spicer D, Price ND, Hohmann JG, Stephen J, DeArmond SJ, Carlson GA, Hood LE. (2009). Molecular Systems Biology 5:252.

    23 Price ND, Edelman LB, Lee I, Yoo H, Hwang D, Carlson G, Galas DJ,Heath JR and Hood L. (2009) Systems Biology and the Emergence of Systems Medicine. Genomic and Personalized Medicine: From Principles to Practice (Ginsburg G and Willard H eds.) Vol.1, pp. 131-141, Elsevier.

    24 Hood L, Friend SH. (2011). Nat Rev Clin Oncol. Mar;8(3):184-7.


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