San Diego’s role in computer analytics dates back to at least 1969, with the founding of Science Applications Inc., now SAIC, which used computer models to predict the effects of nuclear blasts for the Government. Today, a life sciences industry that didn’t exist in San Diego 40 years ago is embracing increasingly powerful computational tools to make sense of the massive amounts of data resulting from genetic discoveries and advances in molecular profiling.
Among the leaders in this emerging field is Paul A. Rejto, director of computational biology in oncology research at Pfizer in San Diego. A physical and theoretical chemist, Rejto started in 1994 at Agouron Pharmaceuticals, a San Diego biotech that became part of Pfizer in 2000. We caught up with Rejto by e-mail last week to find out more about the technology, its role in pharmaceutical research, and its importance to San Diego.
Xconomy: What is computational biology?
Paul Rejto: As with many interdisciplinary fields, there is no single well-established definition. Computational biology broadly refers to the application of computational and informatics approaches to address questions in biology. A number of other terms describe activities at this interface, with slightly different flavors. Bioinformatics is typically more focused on algorithms for sequence manipulation and analysis, and biomedical informatics is more focused on the acquisition and analysis of patient data and outcome.
X: What are some applications of computational biology?
PR: As you might imagine there are many applications. Here in the Pfizer Oncology Research Unit, we are applying computational approaches to support two major objectives: 1) identification and credentialing (or validation) of oncology targets, and 2) linking targets to patients using predictive markers of response. Our chief scientific officer, Neil Gibson, refers to these efforts as the bookends of the research portfolio – in other words, we support the selection of projects that are initiated within research and help to ensure a successful path for those projects moving forward out of research into the clinic.
To credential new targets, we use genomics and transcriptomics to assess targets and pathways in well-defined populations with unmet medical need, and look for evidence of functional activation. To accomplish this, we work closely with our commercial colleagues to ensure … Next Page »