Q: How is systems biology different from genomic and proteomic drug discovery?
A: It involves two ideas. One is you study elements not one at a time, but all at one time. The second is you have to do global analyses at many levels. Each data type gives you different and unique aspects of a system. Another objective is the visualization and mathematical modeling of those data sets. None of those elements are in genomic and proteomic drug approaches. The idea of a "systems" approach has been around a long time. It's what physiologists used 20 and 30 years ago. What has changed in last 10 years has been this explosion of high-throughput technology. ISB has uniquely fashioned the integration [aspect] of that [data]. We are the only location that is currently set up to do systems biology in this highly integrated manner.
Q: What do you mean by "systems"?
A: A system might be how galactose is metabolized in yeast. We look at that as one system and how it behaves. Ultimately you'd like to translate that visualization into mathematical modeling to predict the behavior of the system given a certain perturbation.
We try to use genomic and proteomic approaches to systematically study how the system functions.
Q: Is there any overarching technology that will compete with systems biology for the hearts and minds of the bioscience world?
A: My feeling is that in the end, people may use systems biology in different ways, but at the heart, they will be similar. All roads lead to these systems approaches.
Q: What are the tools you use to conduct systems biology?
A: [We need] a lot of high-throughput biological tools such as large-scale DNA sequencing, microarrays, and mass spectrometry for proteomic profiling, a technology we have advanced. Another tool for us is a multiparameter cell-sorting instrument so you can put bone marrow cells in one end and come out the other end with pure stem cells. On the other side is computational power for acquiring and modeling this high-throughput data.
Q: Do you still need supercomputers, or can off-the-shelf computers make sense of the data?
A: We will always need supercomputers to do really large-scale analysis, which requires intense algorithms. On the other hand, it's certainly true a good workstation can handle a good amount of the data. But the data and all the analysis involved are increasing exponentially. We have a [high-speed] connection to the Arctic Region Supercomputer Center in Fairbanks, Alaska.
Q: Will computers be able to keep up?
A: There could be a mismatch in the future as we have larger and larger data Q: What have been ISB's major accomplishments so far?
A: On the Institute side, we have created an infrastructure and hired a cross-disciplinary faculty. And we have 10 industrial partners helping us develop high-throughput technology. If you want some scientific bullets, we've used galactose in yeast to demonstrate the power of this integrated systems approach (see www.systemsbiology.org/ news/newsscience0504.html). We have used global technology approaches on macrophages by tickling their receptors. The end goal is to understand how the macrophages carry specific immunologic reactions.
On the computational side, we've done pioneering work on developing methodologies for bringing multiple data sets into a single database and then developing the algorithm for their integration and visualization.
Q: In what diseases will genomics and proteomics live up to their potential and produce a blockbuster cure?
A: My guess is it is going to happen in one of the common types of cancer. You are already starting to see that with microarrays stratifying certain kinds of breast and bone cell cancers. We're going to do the same sort of thing for prostate cancer. We can stratify the cancers, but we don't know about their different behaviors. A second area is using proteomic and genomic techniques to identify markers in cancer cells that can be targets for activation of the immune system.
A lot of the advances will be in the immune systems. One of the things we are beginning to ask is how the innate and adaptive immune systems communicate to create vaccine for infectious diseases. This could be an area where we could have some enormous advances.
Q: When will cures happen en masse?
A: My prediction is we'll be moving into predictive and then preventative medicine over next 20 years (as opposed to today's "reactive" medicine). Within the next five years, we will see very few advances because we have so much work to do. Right now, we have lots of genes and proteins, but they haven't been put in a real biological context. Understanding them is more difficult and complicated than saying you've identified all 40,000 genes. Studying single genes or a few at a time has not told us very much.
Q: What will be the long-term social impact of these cures when and if they do come to fruition?
A: We can extend the average lifespan by 20 to 30 years. People will be productive and competent in the later stages of life, which creates a variety of social issues. We don't treat older people very well. How society deals with older productive people will be very interesting.
Q: What companies will be the big winners with the new technology?
A: The forté [of the big pharmas] is taking mature technologies and making them large scale. Most are not going to be able to do the systems biology I'm talking about. The biotechs tend to specialize in their own high-throughput platform and are one-dimensional. They will kind of be at the mercy of large pharmas.
There is an enormous opportunity in systems biology for a company to put it all together. (ISB, he says, has already spun off three companies.) There are a couple of companies that claim to do it, but the jury is out on who the winners will be.