What's your view of the systems biology landscape?
We certainly see systems biology as covering all of the efforts designed to understand the behavior of biological systems, which for us typically means human or larger organism. So the technology people are using to approach this certainly includes a lot of the high-throughput biomarker discovery technologies, metabolomics, and proteomics. Those are very discovery-oriented technologies, you know, let's look at everything and see if we can't fit it together. So those are being applied for target selection, identification of lead targets, and helping to identify biomarkers.
Then there are the modeling approaches, where based on high-throughput data, they try to build predictive models and then test them. I think that has been most effective at the physiology scale. But the reality of drug discovery is that the computational approaches give you an idea of a clean drug and how it might act, but most drugs are dirty and you've got to know that you have to test the system someplace. I think the reality is the [modeling] application[s] for practical drug discovery are a long way away for those; those are more of an academic interest.
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