In the biotech game, New York City doesn't hold a candle to Boston or San Francisco. But if anyone can change that perception, perhaps it's Eric Schadt, the chief scientist of Pacific Biosciences ($PACB) who is helming the Mount Sinai Institute for Genomics and Multiscale Biology. Schadt, who is an expert in the use of computational biology in genomics, talked to Xconomy about his new roles at Mount Sinai, where he's also a professor of genomics and chair of the department of genetics and genomics sciences.
"I think Mount Sinai is a good example of an institution pushing hard to transform its research programs to better use all of the cutting-edge technologies, high-performance computing and information sciences to get at truly predictive models of disease," Schadt told the online news network. His efforts at the major research hospital will involve the use of sequencing technologies, including PacBio's recently introduced SMRT sequencer, to create the disease models.
Schadt, whose appointment at Mount Sinai began Aug. 1, is likely to be a big draw for researchers from multiple disciplines that want to pioneer the integration of data from sequencing machines, clinical research and other sources to advance better treatments for patients. The institute he's heading is expected to get $100 million in funding over the next 5 years. And he's already made a big name for himself among computational biologists and genomics researchers through his efforts at PacBio and previously as a founder of Sage Bionetworks and a genomics leader at Rosetta Inpharmatics. His name also appears on multiple scientific advisory board rosters in the biotech IT arena.
He told Xconomy what to expect from his new institute at Mount Sinai in its early days and in the future.
"The short-term priorities are to get the institute going, which involves very intense planning, recruiting and infrastructure-building," he said in the interview. "The mission of the institute is to become the main data-interpretation hub at Mount Sinai, collaborating deeply with 12 disease-oriented institutes so that we can better understand how to diagnose and treat disease. To pull this off we need a multidisciplinary team, comprised of computer engineers and scientists, data modelers to build predictive models, data analysts to recognize patterns and biological data miners and experimentalists to generate and validate hypotheses about common human diseases and drug response."
- read the interview in Xconomy