Open Source Biology Deserves a Shot

4/11/11Follow @xconomy

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the benefits of openness, Friend says. And patient advocacy groups, including the Genetic Alliance and the CHDI Foundation, have championed the cause.

One of Friend’s next steps, once there’s enough data in the Sage Commons, is creating a free online scientific journal with the ability to visually display network models of disease that connect the dots between genes, proteins, and clinical manifestations of disease in ways that today’s journals aren’t equipped to handle.

At this point, Friend said, there are “kernels” of useful data in the Sage Commons. “Have we got it all built? No,” he says.

That’s where you come in. The only way a movement like this can work, Friend says, is if a wide array of “communities of interest”—drugmakers, academic scientists, doctors, regulators, insurers, patients—grab this platform and run with it on their own.

“We’ll make it or not depending on whether our community of interest goes viral,” Friend says. “You look at Twitter, and it has 42 employees [in its early days---it's now 200. --Eds.]. It’s not about what they are doing. It’s about creating a community of interest who will build this.”

If this thing goes viral throughout biomedicine, it will change the way we think about healthcare. If it doesn’t go viral, it will probably fade into irrelevance.

One key step forward for Sage is coming up this Friday and Saturday at its second annual Sage Commons Congress. It will bring together more than 200 people from various fields to work together on this project at UC San Francisco’s Mission Bay campus. I’ll be there listening, interviewing, reporting, writing, and Tweeting under the conference hashtag, #sagecon. For those who want to participate but can’t be there in person, Sage is providing a webcast. I’ll be watching closely to see how the 200 people inside that room work together. But I’m even more curious to see if biologists outside that room will heed Friend’s call.

Anyone who cares about the future of medicine ought to.

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  • Dylan

    Great article, the potential that exists in “open source biology” is hard to even comprehend. Databases linking SNPs to disease to treatments to outcome…all of which can then be used for future drug development. As time goes on the volume and usefulness of the data will expand exponentially. If scientists and institutions don’t want to open up their databases straight away, perhaps some sort of common ground can be found. Let us hope!

  • http://mylocalhealthguide.com Michael McCarthy

    There’s R&D, there’s r&D, and there’s R&d –

    In his book “Science Business”, Harvard Business School professor Gary Pisano makes a great argument for far more collaboration between biotechnology researchers and businesses such as being attempted by Sage.

    In the book, Pisano argues that the biotechnology industry has been organized on the “one patent, one company” high-tech model in which one organization tries to go it alone to create the blockbuster drug.

    The problem is that with an electronic widget the challenge is primarily development not research. The basic science is usually known. The specs–the required input and output–for the device are known. Little research is needed; the work is development. Pisano refers to this as little “r”, big “D” — as in r&D.

    But in biotechnology there are just to many possible complications, too many unknowns, so the task of product development remains research heavy: “R&d”.

    Furthermore with a widget you know relatively quickly if it’s going to work. If things don’t look promising, you can quit while you’re ahead. A promising biotech product, on the other hand, can fail in a phase III clinical trials after decades of work.

    Pisano concludes that what biotechnology companies, investors and academic researchers need to do is find a way to breakdown the silos so they can share the costs and risks of the research phase of biotech R&D.

    It’s a good read: recommended.

  • http://www.xconomy.com/author/ltimmerman/ Luke Timmerman

    Dylan—thanks for the comment. One thing Stephen mentioned which I didn’t include in the article is how he foresees the Sage Commons being used to create “dynamic drug labels.” The idea is to put all the data in a public commons on how a patient responds (or doesn’t), and the kind of adverse events he or she experiences. It would create a much deeper body of knowledge about a new pharmaceutical that could be continuously updated in real-time, instead of waiting years for a pattern to emerge like the ones that led to the downfall of Vioxx and Avandia.

    Michael–good comment as well on Pisano’s book. Few in biotech have taken his point to heart. Collaborations between pharma/biotech/academia are still happening the old way—they take months, if not years, to set up and get thoroughly lawyered on things like IP ownership. The model is nowhere near what most people would consider an efficient way of sharing cost and risk. Given how poor the drug development model works today, I think the industry owes it to itself to seriously consider what Sage and others are doing to change things.

  • http://austinpreclinical.com Eric Austin

    I have always supported the idea of an open network for sharing all the vast amounts of biologic data that has been collected since the early days of microarrays and genomic sequencing. It is frustrating that there have been so many groups that have developed proprietary platforms that have high barriers to entry (primarily cost) or are closed networks (much of big pharma) and I think Stephen is going in the right direction by trying to open this all up.

    The value for users is to increase the “connectivity” of the data so that new therapeutic approaches can be developed and the costs can be greatly lowered for people and organizations to find new methods to treat disease. You can still derive a proprietary approach to drug development from this sort of data so the incentives will still remain for investors and no one can complain that it will devalue IP because the sheer volume of information will be so enormous that there will be plenty to go around. Just the ability to take all the disparate data out there and present it in a digestible and useful fashion would lead to explosive growth in drug development in my opinion.

  • http://www.ai-one.com Tom Marsh

    This was covered as well in Wikinomics by Don Tapscott. He refers to this as Precompetitive Knowledge Commons and specifically cites the case for this approach to drug development.

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  • - t swell -

    Nice to have the financial links in the story. Why is there no clear link to Sage?

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