Life Sciences in San Diego Gets Analytical: A Chat with Paul A. Rejto, Head of Computational Biology at Pfizer Oncology

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sufficiently productive to sustain the current pharmaceutical enterprise. The past ten years have been characterized by a series of business-driven efforts to incrementally improve productivity and profitability, such as outsourcing and the many mergers and acquisitions, but these have not fundamentally addressed the grand challenge we face.

Many of us are optimistic that the insight afforded by molecular profiling approaches will enable pursuit of targeted therapy more rapidly, effectively and efficiently. In addition to historical examples such as the Estrogen Receptor, HER2, and EGFR, there are many exciting trials of targeted agents in targeted populations currently underway at Pfizer and elsewhere.

I believe that the biggest outstanding challenges are not primarily technical, but rather cultural (e.g. while we are making progress, we need to dramatically increase communication and collaboration between preclinical and clinical scientists) and logistic (e.g. we need to accelerate the routine collection and broad access to consented tumor samples). Given that programs entering clinical trials have success rates under 10 percent, we may want to think more systematically about how to best leverage the information generated from the many trails that do not lead to successful registrations.

X: What is the role of the San Diego innovation community in advancing this technology? Besides fostering drug research and development, can the technology provide jobs and economic growth?

PR: San Diego is a hub of biotechnology, pharmaceutical research, diagnostics and information technology. Coupled with strong universities and research institutes, San Diego is well-positioned to play a significant role. Without question, the environment is far more challenging than when I started working here in the early 1990s. Successful companies today, be they small start-ups or major pharmaceutical giants, need to be smart, focused and lean. Those that are not are quickly punished.

Several of the recent hires performing lab work in the Oncology Research Unit have significant computational expertise, particularly in the area of statistics and scripting. Likewise, we look to hire computational biologists with experience and understanding of cancer biology. My recommendation to young scientists is that they combine deep computational expertise with real biological insight.

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Denise Gellene is a former Los Angeles Times science writer and regular contributor to Xconomy. You can reach her at Follow @

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