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December 16 2013

Four short links: 17 December 2013

  1. WebGraph a framework for graph compression aimed at studying web graphs. It provides simple ways to manage very large graphs, exploiting modern compression techniques. (via Ben Lorica)
  2. Learn to Program with Minecraft PluginsYou’ll need to add features to the game itself: learn how to build plugins for your own Minecraft server using the Java programming language. You don’t need to know anything about programming to get started—-this book will teach you everything you need to know! Shameless Christmas stocking bait! (via Greg Borenstein)
  3. In Search of Perfection, Young Adults Turn to Adderall at Work (Al Jazeera) — “Adderall is just the tip of the iceberg,” Essig said. “There are lots more drugs coming down the pike. The way we set up our cultural model for dealing with psychologically performance-enhancing drugs is a real serious question.”
  4. Explain Shell — uses parsed manpages to explain a shell commandline. (via Tracy K Teal)

December 04 2013

Four short links: 4 December 2013

  1. Skyjack — drone that takes over other drones. Welcome to the Malware of Things.
  2. Bootstrap Worlda curricular module for students ages 12-16, which teaches algebraic and geometric concepts through computer programming. (via Esther Wojicki)
  3. Harvestopen source BSD-licensed toolkit for building web applications for integrating, discovering, and reporting data. Designed for biomedical data first. (via Mozilla Science Lab)
  4. Project ILIAD — crowdsourced antibiotic discovery.

September 29 2013

Médicaments : le gouvernement met en ligne une base de données_publique

#Médicaments : le gouvernement met en ligne une base de #données_publique
http://lemonde.fr/sante/article/2013/09/29/medicaments-le-gouvernement-met-en-ligne-une-base-de-donnees-publique_348672

Une base de données sur les médicaments, accessible librement et gratuitement sur le site du ministère de la santé, a été mise en place par un décret paru dimanche 29 septembre au Journal officiel. Elle sera accessible dès le 1er octobre sur le site
#pharma
www.medicaments.gouv.fr, déclare le ministère de la santé sur son site.

http://www.sante.gouv.fr/medicaments,1969.html#panel-1
http://www.sante.gouv.fr/local/cache-vignettes/L580xH500/Schema-Medicament-033-a7dcd.png

August 23 2013

Financial Conflicts in Medicine*, Joseph Engelberg , Christopher A. Parsons , Nathan Teff

Financial Conflicts in Medicine*, Joseph Engelberg , Christopher A. Parsons , Nathan Teff
http://rady.ucsd.edu/faculty/directory/engelberg/pub/portfolios/DOCTORS.pdf

Si une firme #pharma donne de l’argent à un médecin, quelle est la probabilité qu’il augmente sa prescription de médicaments ?

#recherche #corruption #santé

July 28 2013

Bill Gates, Big Pharma, Bogus Philanthropy | NEWS JUNKIE POST

Bill Gates, Big Pharma, Bogus Philanthropy | NEWS JUNKIE POST
http://newsjunkiepost.com/2013/06/07/bill-gates-big-pharma-bogus-philanthropy

there has been a systematic historical tendency to use the less developed continents (especially Africa) for non-consensual research to pioneer money-making techniques disguised as development, and that Bill Gates could be a part of this. After all, Big Pharma is one of the most profitable industries on the planet, and it strongly relies on the enforcement of patent extensions and intellectual rights for which Bill Gates is notorious from his work in Microsoft. Africa has been the place most severely affected by the strict patent rights enforced by transnational corporations with support from the International Monetary Fund – World Bank – World Trade Organization (IMF-WB-WTO) cartel.

There is also a huge body of documented evidence that the pharmaceutical industry has, for a long time and repeatedly, used vulnerable populations in the developed and developing world as guinea pigs to study disease and test new drugs (e.g. the Tuskegee Experiment, among many others). This is not limited to Big Pharma but applies to nearly every sector of the industrial capitalist economy which, by definition, is based on the exploitation of an underclass.

Having established these premises (I invite you to challenge them), let us analyze the facts:

#paludisme #polio #santé #bill_gates #GSK #pharma

July 14 2013

Breeding Bacteria on Factory Farms - NYTimes.com

Breeding Bacteria on Factory Farms - NYTimes.com
http://opinionator.blogs.nytimes.com/2013/07/09/breeding-bacteria-on-factory-farms/?smid=tw-bittman

La dernière étude en date montrant la dangerosité de l’antibiothérapie préventive dans l’élevage « industriel »

The latest study concerning antibiotic resistance was published last week in the journal PLoS One. It looked at livestock workers in North Carolina (the nation’s second biggest hog-producing state, after Iowa), including those in what the study’s authors called “industrial” livestock production and those on farms where the animals were raised without antibiotics and grown on pasture. In this study, the S. aureus bacteria with genetic markers most closely linked to livestock were found in far greater numbers in workers on the industrial farms.

La FDA traîne les pieds pour remédier à cette situation..

The F.D.A., which is under court order to do something about the routine use of antibiotics, has come up with a lame voluntary reduction scheme — “Guidance 213,” it’s called — acting as if it will save its real regulatory muscle for after this scheme flops. (Which it will — flop, that is.) Worse, despite repeated promises that the voluntary guidelines were imminent, they haven’t issued even those. And now, “Guidance 213 is currently in the clearance process, but we cannot predict a timeline on its release,” an agency spokeswoman wrote me in an e-mail. Period.

.. et, quelques exceptions mises à part, l’Etat aussi

That’s simply insulting. Of course, almost no one is pushing the F.D.A. to do its job. There are a handful of people in Congress; certainly some well-meaning NGOs like Pew Charitable Trusts, Natural Resources Defense Council and others; and dedicated individuals like the lawyer Bill Marler. Against them are arrayed not only Big Pharma — which is providing four times as many antibiotics to animals as it is to humans — but industrial ag, which cares only about raising animals “efficiently” and profitably.

#santé #microbiologie #résistance_aux_antibiotiques #pharma #bigpharma #agroindustrie #lobbying

May 02 2012

Recombinant Research: Breaking open rewards and incentives

In the previous articles in this series I've looked at problems in current medical research, and at the legal and technical solutions proposed by Sage Bionetworks. Pilot projects have shown encouraging results but to move from a hothouse environment of experimentation to the mainstream of one of the world's most lucrative and tradition-bound industries, Sage Bionetworks must aim for its nucleus: rewards and incentives.

Previous article in the series: Sage Congress plans for patient engagement.

Think about the publication system, that wretchedly inadequate medium for transferring information about experiments. Getting the data on which a study was based is incredibly hard; getting the actual samples or access to patients is usually impossible. Just as boiling vegetables drains most of their nutrients into the water, publishing results of an experiment throws away what is most valuable.

But the publication system has been built into the foundation of employment and funding over the centuries. A massive industry provides distribution of published results to libraries and research institutions around the world, and maintains iron control over access to that network through peer review and editorial discretion. Even more important, funding grants require publication (but the data behind the study only very recently). And of course, advancement in one's field requires publication.

Lawrence Lessig, in his keynote, castigated for-profit journals for restricting access to knowledge in order to puff up profits. A chart in his talk showed skyrocketing prices for for-profit journals in comparison to non-profit journals. Lessig is not out on the radical fringe in this regard; Harvard Library is calling the current pricing situation "untenable" in a move toward open access echoed by many in academia.

Lawrence Lessig keynote at Sage Congress
Lawrence Lessig keynote at Sage Congress.

How do we open up this system that seemed to serve science so well for so long, but is now becoming a drag on it? One approach is to expand the notion of publication. This is what Sage Bionetworks is doing with Science Translational Medicine in publishing validated biological models, as mentioned in an earlier article. An even more extensive reset of the publication model is found in Open Network Biology (ONB), an online journal. The publishers require that an article be accompanied by the biological model, the data and code used to produce the model, a description of the algorithm, and a platform to aid in reproducing results.

But neither of these worthy projects changes the external conditions that prop up the current publication system.

When one tries to design a reward system that gives deserved credit to other things besides the final results of an experiment, as some participants did at Sage Congress, great unknowns loom up. Is normalizing and cleaning data an activity worth praise and recognition? How about combining data sets from many different projects, as a Synapse researcher did for the TCGA? How much credit do you assign researchers at each step of the necessary procedure for a successful experiment?

Let's turn to the case of free software to look at an example of success in open sharing. It's clear that free software has swept the computer world. Most web sites use free software ranging from the server on which they run to the language compilers that deliver their code. Everybody knows that the most popular mobile platform, Android, is based on Linux, although fewer realize that the next most popular mobile platforms, Apple's iPhones and iPads, run on a modified version of the open BSD operating system. We could go on and on citing ways in which free and open source software have changed the field.

The mechanism by which free and open source software staked out its dominance in so many areas has not been authoritatively established, but I think many programmers agree on a few key points:

  • Computer professionals encountered free software early in their careers, particularly as students or tinkerers, and brought their predilection for it into jobs they took at stodgier institutions such as banks and government agencies. Their managers deferred to them on choices for programming tools, and the rest is history.

  • Of course, computer professionals would not have chosen the free tools had they not been fit for the job (and often best for the job). Why is free software so good? Probably because the people creating it have complete jurisdiction over what to produce and how much time to spend producing it, unlike in commercial ventures with requirements established through marketing surveys and deadlines set unreasonably by management.

  • Different pieces of free software are easy to hook up, because one can alter their interfaces as necessary. Free software developers tend to look for other tools and platforms that could work with their own, and provide hooks into them (Apache, free database engines such as MySQL, and other such platforms are often accommodated.) Customers of proprietary software, in contrast, experience constant frustration when they try to introduce a new component or change components, because the software vendors are hostile to outside code (except when they are eager to fill a niche left by a competitor with market dominance). Formal standards cannot overcome vendor recalcitrance--a painful truth particularly obvious in health care with quasi-standards such as HL7.

  • Free software scales. Programmers work on it tirelessly until it's as efficient as it needs to be, and when one solution just can't scale any more, programmers can create new components such as Cassandra, CouchDB, or Redis that meet new needs.

Are there lessons we can take from this success story? Biological research doesn't fit the circumstances that made open source software a success. For instance, researchers start out low on the totem pole in very proprietary-minded institutions, and don't get to choose new ways of working. But the cleverer ones are beginning to break out and try more collaboration. Software and Internet connections help.

Researchers tend to choose formats and procedures on an ad hoc, project by project basis. They haven't paid enough attention to making their procedures and data sets work with those produced by other teams. This has got to change, and Sage Bionetworks is working hard on it.

Research is labor-intensive. It needs desperately to scale, as I have pointed out throughout this article, but to do so it needs entire new paradigms for thinking about biological models, workflow, and teamwork. This too is part of Sage Bionetworks' mission.

Certain problems are particularly resistant in research:

  • Conditions that affect small populations have trouble raising funds for research. The Sage Congress initiatives can lower research costs by pooling data from the affected population and helping researchers work more closely with patients.

  • Computation and statistical methods are very difficult fields, and biological research is competing with every other industry for the rare individuals who know these well. All we can do is bolster educational programs for both computer scientists and biologists to get more of these people.

  • There's a long lag time before one knows the effects of treatments. As Heywood's keynote suggested, this is partly solved by collecting longitudinal data on many patients and letting them talk among themselves.

Another process change has revolutionized the computer field: agile programming. That paradigm stresses close collaboration with the end-users whom the software is supposed to benefit, and a willingness to throw out old models and experiment. BRIDGE and other patient initiatives hold out the hope of a similar shift in medical research.

All these things are needed to rescue the study of genetics. It's a lot to do all at once. Progress on some fronts were more apparent than others at this year's Sage Congress. But as more people get drawn in, and sometimes fumbling experiments produce maps for changing direction, we may start to see real outcomes from the efforts in upcoming years.

All articles in this series, and others I've written about Sage Congress, are available through a bit.ly bundle.

OSCON 2012 — Join the world's open source pioneers, builders, and innovators July 16-20 in Portland, Oregon. Learn about open development, challenge your assumptions, and fire up your brain.

Save 20% on registration with the code RADAR20

May 01 2012

Recombinant Research: Sage Congress plans for patient engagement

Clinical trials are the pathway for approving drug use, but they aren't good enough. That has become clear as a number of drugs (Vioxx being the most famous) have been blessed by the FDA, but disqualified after years of widespread use reveal either lack of efficacy or dangerous side effects. And the measures taken by the FDA recently to solve this embarrassing problem continue the heavy-weight bureaucratic methods it has always employed: more trials, raising the costs of every drug and slowing down approval. Although I don't agree with the opinion of Avik S. A. Roy (reprinted in Forbes) that Phase III trials tend to be arbitrary, I do believe it is time to look for other ways to test drugs for safety and efficacy.

First article in the series: Recombinant Research: Sage Congress Promotes Data Sharing in Genetics.

But the Vioxx problem is just one instance of the wider malaise afflicting the drug industry. They just aren't producing enough new medications, either to solve pressing public needs or to keep up their own earnings. Vicki Seyfert-Margolis of the FDA built on her noteworthy speech at last year's Sage Congress (reported in one of my articles about the conference) with the statistic that drug companies have submitted 20% fewer medications to the FDA between 2001 and 2007. Their blockbuster drugs produce far fewer profits than before as patents expire and fewer new drugs emerge (a predicament called the "patent cliff"). Seyfert-Margolis intimated that this crisis in the cause of layoffs in the industry, although I heard elsewhere that the companies are outsourcing more research, so perhaps the downsizing is just a reallocation of the same money.

Benefits of patient involvement

The field has failed to rise to the challenges posed by new complexity. Speakers at Sage Congress seemed to feel that genetic research has gone off the tracks. As the previous article in this series explained, Sage Bionetworks wants researchers to break the logjam by sharing data and code in GitHub fashion. And surprisingly, pharma is hurting enough to consider going along with an open research system. They're bleeding from a situation where as much as 80% of each clinical analysis is spent retrieving, formatting, and curating the data. Meanwhile, Kathy Giusti of the Multiple Myeloma Research Foundation says that in their work, open clinical trials are 60% faster.

Attendees at a breakout session where I sat in, including numerous managers from major pharma companies, expressed confidence that they could expand public or "pre-competitive" research in the direction Sage Congress proposed. The sector left to engage is the one that's central to all this work--the public.

If we could collect wide-ranging data from, say, 50,000 individuals (a May 2013 goal cited by John Wilbanks of Sage Bionetworks, a Kauffman Foundation Fellow), we could uncover a lot of trends that clinical trials are too narrow to turn up. Wilbanks ultimately wants millions of such data samples, and another attendee claimed that "technology will be ready by 2020 for a billion people to maintain their own molecular and longitudinal health data." And Jamie Heywood of PatientsLikeMe, in his keynote, claimed to have demonstrated through shared patient notes that some drugs were ineffective long before the FDA or manufacturers made the discoveries. He decried the current system of validating drugs for use and then failing to follow up with more studies, snorting that, "Validated means that I have ceased the process of learning."

But patients have good reasons to keep a close hold on their health data, fearing that an insurance company, an identity thief, a drug marketer, or even their own employer will find and misuse it. They already have little enough control over it, because the annoying consent forms we always have shoved in our faces when we come to a clinic give away a lot of rights. Current laws allow all kinds of funny business, as shown in the famous case of the Vermont law against data mining, which gave the Supreme Court a chance to say that marketers can do anything they damn please with your data, under the excuse that it's de-identified.

In a noteworthy poll by Sage Bionetworks, 80% of academics claimed they were comfortable sharing their personal health data with family members, but only 31% of citizen advocates would do so. If that 31% is more representative of patients and the general public, how many would open their data to strangers, even when supposedly de-identified?

The Sage Bionetworks approach to patient consent

It's basic research that loses. So Wilbanks and a team have been working for the past year on a "portable consent" procedure. This is meant to overcome the hurdle by which a patient has to be contacted and give consent anew each time a new researcher wants data related to his or her genetics, conditions, or treatment. The ideal behind portable consent is to treat the entire research community as a trusted user.

The current plan for portable consent provides three tiers:

Tier 1

No restrictions on data, so long as researchers follow the terms of service. Hopefully, millions of people will choose this tier.

Tier 2

A middle ground. Someone with asthma may state that his data can be used only by asthma researchers, for example.

Tier 3

Carefully controlled. Meant for data coming from sensitive populations, along with anything that includes genetic information.

Synapse provides a trusted identification service. If researchers find a person with useful characteristics in the last two tiers, and are not authorized automatically to use that person's data, they can contact Synapse with the random number assigned to the person. Synapse keeps the original email address of the person on file and will contact him or her to request consent.

Portable consent also involves a lot of patient education. People will sign up through a software wizard that explains the risks. After choosing portable consent, the person decides how much to put in: 23andMe data, prescriptions, or whatever they choose to release.

Sharon Terry of the Genetic Alliance said that patient advocates currently try to control patient data in order to force researchers to share the work they base on that data. Portable consent loosens this control, but the field may be ready for its more flexible conditions for sharing.

Pharma companies and genetics researchers have lots to gain from access to enormous repositories of patient data. But what do the patients get from it? Leaders in health care already recognize that patients are more than experimental subjects and passive recipients of treatment. The recent ONC proposal for Stage 2 of Meaningful Use includes several requirements to share treatment data with the people being treated (which seems kind of a no-brainer when stated this baldly) and the ONC has a Consumer/Patient Engagement Power Team.

Sage Congress is fully engaged in the patient engagement movement too. One result is the BRIDGE initiative, a joint project of Sage Bionetworks and Ashoka with funding from the Robert Wood Johnson Foundation, to solicit questions and suggestions for research from patients. Researchers can go for years researching a condition without even touching on some symptom that patients care about. Listening to patients in the long run produces more cooperation and more funding.

Portable consent requires a leap of faith, because as Wilbanks admits, releasing aggregates of patient data mean that over time, a patient is almost certain to be re-identified. Statistical techniques are just getting too sophisticated and compute power growing too fast for anyone to hide behind current tricks such as using only the first three digits of a five-digit postal code. Portable consent requires the data repository to grant access only to bona fide researchers and to set terms of use, including a ban on re-identifying patients. Still, researchers will have rights to do research, redistribute data, and derive products from it. Audits will be built in.

But as mentioned by Kelly Edwards of the University of Washington, tools and legal contracts can contribute to trust, but trust is ultimately based on shared values. Portable consent, properly done, engages with frameworks like Synapse to create a culture of respect for data.

In fact, I think the combination of the contractual framework in portable consent and a platform like Synapse, with its terms of use, might make a big difference in protecting patient privacy. Seyfert-Margolis cited predictions that 500 million smartphone users will be using medical apps by 2015. But mobile apps are notoriously greedy for personal data and cavalier toward user rights. Suppose all those smartphone users stored their data in a repository with clear terms of use and employed portable consent to grant access to the apps? We might all be safer.

The final article in this series will evaluate the prospects for open research in genetics, with a look at the grip of journal publishing on the field, and some comparisons to the success of free and open source software.

Next: Breaking Open Rewards and Incentives. All articles in this series, and others I've written about Sage Congress, are available through a bit.ly bundle.

OSCON 2012 — Join the world's open source pioneers, builders, and innovators July 16-20 in Portland, Oregon. Learn about open development, challenge your assumptions, and fire up your brain.

Save 20% on registration with the code RADAR20

April 30 2012

Recombinant Research: Sage Congress promotes data sharing in genetics

Given the exponential drop in the cost of personal genome sequencing (you can get a basic DNA test from 23andMe for a couple hundred dollars, and a full sequence will probably soon come down to one thousand dollars in cost), a new dawn seems to be breaking forth for biological research. Yet the assessment of genetics research at the recent Sage Congress was highly cautionary. Various speakers chided their own field for tilling the same ground over and over, ignoring the urgent needs of patients, and just plain researching the wrong things.

Sage Congress also has some plans to fix all that. These projects include tools for sharing data and storing it in cloud facilities, running challenges, injecting new fertility into collaboration projects, and ways to gather more patient data and bring patients into the planning process. Through two days of demos, keynotes, panels, and breakout sessions, Sage Congress brought its vision to a high-level cohort of 230 attendees from universities, pharmaceutical companies, government health agencies, and others who can make change in the field.

In the course of this series of articles, I'll pinpoint some of the pain points that can force researchers, pharmaceutical companies, doctors, and patients to work together better. I'll offer a look at the importance of public input, legal frameworks for cooperation, the role of standards, and a number of other topics. But we'll start by seeing what Sage Bionetworks and its pals have done over the past year.

Synapse: providing the tools for genetics collaboration

Everybody understands that change is driven by people and the culture they form around them, not by tools, but good tools can make it a heck of a lot easier to drive change. To give genetics researchers the best environment available to share their work, Sage Bionetworks created the Synapse platform.

Synapse recognizes that data sets in biological research are getting too large to share through simple data transfers. For instance, in his keynote about cancer research (where he kindly treated us to pictures of cancer victims during lunch), UC Santa Cruz professor David Haussler announced plans to store 25,000 cases at 200 gigabytes per case in the Cancer Genome Atlas, also known as TCGA in what seems to be a clever pun on the four nucleotides in DNA. Storage requirements thus work out to 5 petabytes, which Haussler wants to be expandable to 20 petabytes. In the face of big data like this, the job becomes moving the code to the data, not moving the data to the code.

Synapse points to data sets contributed by cooperating researchers, but also lets you pull up a console in a web browser to run R or Python code on the data. Some effort goes into tagging each data set with associated metadata: tissue type, species tested, last update, number of samples, etc. Thus, you can search across Synapse to find data sets that are pertinent to your research.

One group working with Synapse has already harmonized and normalized the data sets in TCGA so that a researcher can quickly mix and run stats on them to extract emerging patterns. The effort took about one and half full-time employees for six months, but the project leader is confident that with the system in place, "we can activate a similar size repository in hours."

This contribution highlights an important principle behind Synapse (appropriately called "viral" by some people in the open source movement): when you have manipulated and improved upon the data you find through Synapse, you should put your work back into Synapse. This work could include cleaning up outlier data, adding metadata, and so on. To make work sharing even easier, Synapse has plans to incorporate the Amazon Simple Workflow Service (SWF). It also hopes to add web interfaces to allow non-programmers do do useful work with data.

The Synapse development effort was an impressive one, coming up with a feature-rich Beta version in a year with just four coders. And Synapse code is entirely open source. So not only is the data distributed, but the creators will be happy for research institutions to set up their own Synapse sites. This may make Synapse more appealing to geneticists who are prevented by inertia from visiting the original Synapse.

Mike Kellen, introducing Synapse, compared its potential impact to that of moving research from a world of journals to a world like GitHub, where people record and share every detail of their work and plans. Along these lines, Synapse records who has used a data set. This has many benefits:

  • Researchers can meet up with others doing related work.

  • It gives public interest advocates a hook with which to call on those who benefit commercially from Synapse--as we hope the pharmaceutical companies will--to contribute money or other resources.

  • Members of the public can monitor accesses for suspicious uses that may be unethical.

There's plenty more work to be done to get data in good shape for sharing. Researchers must agree on some kind of metadata--the dreaded notion of ontologies came up several times--and clean up their data. They must learn about data provenance and versioning.

But sharing is critical for such basics of science as reproducing results. One source estimates that 75% of published results in genetics can't be replicated. A later article in this series will examine a new model in which enough metainformation is shared about a study for it to be reproduced, and even more important to be a foundation for further research.

With this Beta release of Synapse, Sage Bionetworks feels it is ready for a new initiative to promote collaboration in biological research. But how do you get biologists around the world to start using Synapse? For one, try an activity that's gotten popular nowadays: a research challenge.

The Sage DREAM challenge

Sage Bionetworks' DREAM challenge asks genetics researchers to find predictors of the progression of breast cancer. The challenge uses data from 2000 women diagnosed with breast cancer, combining information on DNA alterations affecting how their genes were expressed in the tumors, clinical information about their tumor status, and their outcomes over ten years. The challenge is to build models integrating the alterations with molecular markers and clinical features to predict which women will have the most aggressive disease over a ten year period.

Several hidden aspects of the challenge make it a clever vehicle for Sage Bionetworks' values and goals. First, breast cancer is a scourge whose urgency is matched by its stubborn resistance to diagnosis. The famous 2009 recommendations of U.S. Preventive Services Task Force, after all the controversy was aired, left us with the dismal truth that we don't know a good way to predict breast cancer. Some women get mastectomies in the total absence of symptoms based just on frightening family histories. In short, breast cancer puts the research and health care communities in a quandary.

We need finer-grained predictors to say who is likely to get breast cancer, and standard research efforts up to now have fallen short. The Sage proposal is to marshal experts in a new way that combines their strengths, asking them to publish models that show the complex interactions between gene targets and influences from the environment. Sage Bionetworks will publish data sets at regular intervals that it uses to measure the predictive ability of each model. A totally fresh data set will be used at the end to choose the winning model.

The process behind the challenge--particularly the need to upload code in order to run it on the Synapse site--automatically forces model builders to publish all their code. According to Stephen Friend, founder of Sage Bionetworks, "this brings a level of accountability, transparency, and reproducibility not previously achieved in clinical data model challenges."

Finally, the process has two more effects: it shows off the huge amount of genetic data that can be accessed through Synapse, and it encourages researchers to look at each other's models in order to boost their own efforts. In less than a month, the challenge already received more than 100 models from 10 sources.

The reward for winning the challenge is publication in a respected journal, the gold medal still sought by academic researchers. (More on shattering this obelisk later in the series.) Science Translational Medicine will accept results of the evaluation as a stand-in for peer review, a real breakthrough for Sage Bionetworks because it validates their software-based, evidence-driven process.

Finally, the DREAM challenge promotes use of the Synapse infrastructure, and in particular the method of bringing the code to the data. Google is donating server space for the challenge, which levels the playing field for researchers, freeing them from paying for their own computing.

A single challenge doesn't solve all the problems of incentives, of course. We still need to persuade researchers to put up their code and data on a kind of genetic GitHub, persuade pharmaceutical companies to support open research, and persuade the general public to share data about the phonemes (life data) and genes--all topics for upcoming articles in the series.

Next: Sage Congress Plans for Patient Engagement. All articles in this series, and others I've written about Sage Congress, are available through a bit.ly bundle.

OSCON 2012 — Join the world's open source pioneers, builders, and innovators July 16-20 in Portland, Oregon. Learn about open development, challenge your assumptions, and fire up your brain.

Save 20% on registration with the code RADAR20

April 19 2012

Sage Congress: The synthesis of open source with genetics

For several years, O'Reilly Radar has been covering the exciting
potential that open source software, open data, and a general attitude
of sharing and cooperation bring to health care. Along with many
exemplary open source projects in areas directly affecting the
public — such as the VA's Blue
Button
in electronic medical records and the href="http://wiki.directproject.org/">Direct project in data
exchange — the study of disease is undergoing a paradigm shift.

Sage Bionetworks stands at the
center of a wide range of academic researchers, pharmaceutical
companies, government agencies, and health providers realizing that
the old closed system of tiny teams who race each other to a cure has
got to change. Today's complex health problems, such as Alzheimer's,
AIDS, and cancer, are too big for a single team. And these
institutions are slowly wrenching themselves out of the habit of data
hoarding and finding ways to work together.

A couple weeks ago I talked to the founder of Sage Bionetworks,
Stephen Friend, about recent advances in open source in this area, and
the projects to be highlighted at the upcoming http://sagecongress.org/">Sage Commons congress. Steve is careful
to call this a "congress" instead of a "conference" because all
attendees are supposed to pitch in and contribute to the meme pool. I
covered Sage Congress in a series of
articles last year
. The following podcast ranges over
topics such as:

  • what is Sage Bionetworks [Discussed at the 00:25 mark];
  • the commitment of participants to open source software [Discussed at the 01:01 mark];
  • how open source can support a business model in drug development [Discussed at the 01:40 mark];
  • a look at the upcoming congress [Discussed at the 03:47 mark];
  • citizen-led contributions or network science [Discussed at the 06:12 mark];
  • data sharing philosophy [Discussed at the 09:01 mark];
  • when projects are shared with other institutions [Discussed at the 12:43 mark];
  • how to democratize medicine [Discussed at the 17:10 mark];
  • a portable legal consent approach where the patient controls his or her own data [Discussed at the 20:07 mark];
  • solving the problem of non-sharing in the industry [Discussed at the 22:15 mark]; and
  • key speakers at the congress [Discussed at the 26:35 mark].

Sessions from the congress will be broadcast live via webcast and posted on the Internet.

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