Big Data, Big Biology, and the ‘Tipping Point’ in Quantified Health: Takeaways from Xconomy’s On-the-Record Dinner
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overcome to realize this vision, including:
—Scalability. Smarr sees a challenge in developing a bioinformatics network that could expand from a pilot project to serve the health needs of a population as big as San Diego.
—Trustability. As a founding member of Google Health, which operated from 2008 to 2011, Missy Krasner said one issue that became a problem was who owns the data—and who would be the trusted custodian of the data? Krasner, who is now an entrepreneur-in-residence at Morgenthaler Ventures in Mountain View, CA, also asked why anyone would want to participate. “What are the incentives that get the average consumer and the average provider at Sharp or Scripps or anywhere else to actually want to receive that data and do something with it?”
—Profitability. “How do you make money?” asked Lisa Suennen, a co-founder and managing member of the Psilos Group, a healthcare-focused venture capital firm in Corte Madera, CA. “If there’s not a clear path to that, it’s a barrier.”
—Engagability. Generating meaningful feedback for patients will be a challenge, said Ernesto Ramirez, who is working at UCSD’s Center for Wireless and Population Health Systems on a doctorate in health behavior. “To me the issue is not the statistical methods that tell me whether I’m going to have a heart attack. It’s the layering on of all the behavioral methods, the visualization, and all the other ways that you can help me understand the data.”
Despite the thicket of difficulties, though, there are still some things that could be done—which was another recurring theme of the discussion.
“You just start,” said Mark Stevenson, the president and chief operating officer of Life Technologies (NASDAQ: LIFE), the global biotechnology company based in Carlsbad, CA. If Larry Smarr’s 10-year experiment in quantified health represents what Stevenson calls an “n of 1”—a single case study—then it’s simply a matter of trying to extrapolate the technology from there to get to an “n of 300,” or an “n of 3 million.”
Rather than trying to … Next Page »