Pfizer seems to moving beyond the flirting stage with systems biology. Abouta year ago, it named a director of systems biology
(David de Graaf) with whomGomes works. After the panel, Gomes noted that internal demand is starting tooutstrip his small group’s ability to respond, based largely on the promisingresults from two projects that have excited Pfizer researcher interest.Undeniably, there is a new buzz around systems biology. Harvard Medical School, for example, nowhas a department of systems biology, and one of its professors, Walter Fontana,participated on the panel.“I represent the academic interest in systems biology,” Fontana said, “
I would like to takeissue with the notion that because we measure everything, we automatically knoweverything. That is far from being the case. So systems biology to me means twothings: first is the biology of systems, and that’s a truism, going fromindividual proteins to systems behavior. But the second target of systemsbiology is a systems technology.”Models should be collaborative learning devices, informed by both theory andexperiment, argued Fontana.Too often, he stressed, we think of models developed by theorists as differentfrom models developed by experimentalists. “We need to erase this distinction,”said Fontana.“When an experimentalist reasons about biological systems, he or she has amodel in her mind. What we need to do is to write down this model in order tomake the assumptions behind it explicit and enable that reasoning process to becomeassisted by machines. Biological knowledge is fragmented and open ended becausenew developments and technology give us new discovery. We need to have a systemin place for coping with open-ended knowledge, and modeling is one way ofcoping with that.”A few companies are trying to make a go of modeling, though virtually all ofthem use proprietary platforms. Panelist William Ladd, VP of discovery systems,Genstruct, noted they’ve had success generating hypotheses but agreed there wasmuch room for progress.In the end, Letovsky offered a sober caution. Yes, he said, we have madehuge progress in perturbing systems and generating rich data sets. There aretools to probe a wide variety of systems characteristics. But we’re still inthe early days for many of these technologies.“It’s also important to realize these things don’t work very well yet. RNAi,for example, is fraught with crosstalk issues that people are only beginning torealize,” cautioned Letovsky. “When we throw expression profiling at homogenatedtissue, we’re suppressing potential biological effects around the tissue’sheterogeneity.”“If stem cells are as important in cancer as people have started to thinkthey are, then we may be looking under lights instead of in the bushes wherewe’ve lost our keys when we homogenize our various cell lines or tissue sampleand do expression profiling that characterizes the mass of cells instead of therarer cells that we really should be looking at,” he said.Put another way, the Millennium researcher said we’ve learned to put pieceson the chessboard, and learned to assemble many combinations, but we stillhaven’t learned to play chess.