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Preventable Vioxx Problems?

By John Russell

Feb 15, 2006 | Pathway analysis tools might have identified Vioxx’s problematic off-target activity much earlier, argue authors of a fascinating review article in Current Opinion in Chemical Biology [1].

“[M]uch of the relevant pathway regarding this COX-2 inhibitor (refecoxib) side effect was available at the time of the clinical trials in 1999... This is where modern pathway databases can help to organize the scattered but essential pieces of information to facilitate efficient look-up of drug targets involved in multiple critical pathways,” write Upinder Bhalla and colleagues from the National Centre for Biological Science, Tata Institute of Fundamental Research, Bangalore, India.

Bhalla and colleagues examine the progress of systems modeling, in which they include pathway assemblage and analysis. They cite 10 or so instances in which modeling has helped or is poised to help drug discovery. Among the several examples explored by the authors are: FGF-2 receptor signaling (angiogenesis); EGFR inhibitory agents (cancers); beta-adrenergic signaling network (congestive heart failure); and Asthma PhysioLab (from Entelos).

“The advent of combinatorial chemistry, structure-based design and genomics each marked shifts in the drug discovery paradigm. Can modeling and, specifically, the quantitative modeling of cell signaling pathways be the next milestone?” ask the authors. Their answer seems to be yes!

Wondering which modeling approach to use for your project? There’s another excellent COCB review article [2] that does a solid job surveying computational modeling approaches for proteomics networks. It’s written by Kevin Janes and Douglas Lauffenburger of MIT’s Biological Engineering Division and Cell Decision Processes Center.

“[W]e and others have argued against a consensus ‘one-size-fits-all’ philosophy, favoring instead a spectrum of computational techniques,” write Janes and Lauffenburger.

“If the choice of model is flexible but not arbitrary, then which modeling approaches are appropriate for which biological applications? [W]e attempt to answer this question through examples of recently published proteomic-network models.” Included is an informative figure with a decision-tree for selecting the various approaches (Bayesian, probabilistic, statistical, ODEs, etc.).

Part of what makes both reviews important is their reliance on specific examples. Systems biology, in all of its guises, has suffered from a “where’s the beef” syndrome. Here’s a little beef.

BP 2006: The Best Is Yet to Come

Bio•IT World is now soliciting entries to its fourth annual Best Practices Awards Contest. We’ve made a few small tweaks to the program based on our experience of processing roughly 150 entries, but the program’s goals remain unchanged: to showcase efforts by life science organizations developing and deploying innovative solutions for streamlining the drug development and clinical process.

One perennial issue has been grouping entries into proper categories. The overlap has often been substantial, and forced shuffling of entries after submission. So we’ve trimmed the number of categories to two: (1) Drug Discovery and Development and (2) Clinical Research and Trials.

The venue for the awards announcement and presentation has been moved to Philadelphia, to keep it close to DIA, which is being held there this year. As always, the winners and entrants will be featured in a Special Report published in Bio•IT World. All qualified entrants also receive a compendium of the entries — it’s our modest effort at creating peer-to-peer database for sharing ideas.

Last year, there were six prize winners (Pfizer, GSK, NCI, Harvard, the U.K., and TGen) and two Editors’ Choice awards (J. Craig Venter Institute and Broad Institute) representing submissions from industry, academia, and even one from the U.K. Trade and Investment agency. Showcased technologies ranged from clinical trial simulation to giant LIMS and automation projects. All of these projects advanced drug discovery and development in concrete ways and will continue to do so. 

Don’t miss this year’s chance to achieve recognition for yourself, your group, and your company. Visit


1 Rajasethupathy, P. et al. "Systems Modeling: a pathway to drug discovery." Curr Opin Chem Biol 9, 400-6; 2005.
2 Janes, K.A. and Douglas, A. "A biological approach to computational models of proteomic networks." Curr Opin Chem Biol online, Jan. 6, 2006.

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