Learning to share big data

A UW effort aims to help scientists make better use of the vast amounts of information being collected.

The full story was published in Seattle Business Magazine. read it here.

The University of Washington has launched a new project that could dramatically increase the power of academic research by giving a broad universe of scientists — including astronomers, physicists, chemists and biologists — faster and smarter ways of extracting information and meaning from the increasingly large amounts of data they have available to them.

“The Sequence” portrays genomic explosion

It isn’t the fault of the playwright Paul Mullin that his wonderful play, “The Sequence” promises a brilliant future. The voices sound rapturous, but a bit hollow, decades after those promises.

The actors who did a professional reading on Oct.5 will repeat that on Oct. 12 and Oct. 13 at the Bathhouse Theater, in cooperation with Seattle Public Theater. The three characters are Francis Collins, who is currently the head of the National Institutes of Health, and Craig Venter, a researcher credited with accelerating the project to decode the genome. The play concerns itself with both real events leading up to the 2003 success at mapping the genome, and adds a fictional journalist character.

When Mullin wrote his play, almost 10 years ago, the race to sequence the human genome seemed destined to shine a bright light of understanding on many areas of human disease. The logic of the time was  that once scientists sequenced the genetic code inside every cell that governs making proteins,  they could intervene to save people from mistakes in that code.

But from today’s perspective, the grand pronouncements and predictions seem quaintly simplistic. Yes, some new therapeutics rely on genetic insight for their actions on cells, but the staggering complexity of how the environment acts on the genome is stifling most direct gene therapy.

The “light” shown by the decoding revealed other “omes.” As if decoding just showed how many other codes are at work.  For example, proteomics is the study of how every one of thousands of proteins interact, a code requiring cloud computing and big data searches for patterns to even get a handhold on understanding what some call “systems” biology. There is also microbiomics, which is the study of how the microbes inside the human body can influence the production of those proteins. The list includes metabolomics, nutrigenomics, and others.

When explorers Lewis and Clark set off across the North American continent, they scaled the Rockies believing this was the pinnacle of their challenge on their way west. Alas, when they spied the Cascade Range further to the west, reports are they saw “mountains beyond mountains.” I have always thought that is an apt metaphor for the Human Genome project. It illuminated the mountain ranges of understanding that now remain.

Experts will be on hand to answer your questions following both of the upcoming performances.

Resources:

Great special publication by The Scientist on the future of genomics

$1.7 million to open science’s Friend

Two honors this summer have burnished the reputation of Seattle scientist Stephen Friend for his pursuit of what is called open science.  On top of White House honors in June, he received a grant last week that adds to his credibility as someone trying to change the culture. The phrase “open science” has dozens of meanings, but in Friend’s case it is primarily about opening up data that medical researchers once kept hidden from each other. He calls it a “geek sandbox.”

Just a few days ago, he won a $1.7 million grant from the Robert Wood Johnson Foundation.  The money goes to a project called Bridge, more about that later.

Friend has spent decades being an academic (at Fred Hutchinson Cancer Research Center) and working at the giant pharmaceutical company, Merck, but now he’s director of his own pioneering effort called Sage Bionetworks.

When he explains this passion for open science, he talks from his experience. He talks about trying to make data work for patients and not just to help scientists with tenure and startup companies.  He titled one of his speeches: “Dreaming of tenure and IPOs while patients die,” at a conference in 2012.

He speaks critically of the “medical industrial complex” getting in the way of helping patients. He’s building tools that are designed to let researchers share and network with patients to try to help solve some puzzles about chronic diseases. Already, they’ve had some success with modeling which women with breast cancer might respond best to certain medicines.

Friend was honored at the White House Office of Science and Technology in June as one of the leaders in open science. He announced new projects on Alzheimer’s disease and rheumatoid arthritis that may help predict which patients will respond to certain medications. Sage Bio’s work on modeling risk for breast-cancer patients was called a “geek sandbox” by one writer, who said the results (a new model) are less important than the building of a system where researchers collaborate and compete at the same time.

Friend’s particular passion is also a place where two Seattle strengths overlap, like Venn diagrams. Seattle is strong in software, everybody takes that for granted. Besides the behemoth of Microsoft, Seattle has hundreds of other companies exploring how to use algorithms to uncover signal patterns in the noise of data.  Among the newest of those companies are Socrata and Tableau Software.  Seattle is also strong in genomics and proteomics, and the study of diseases as complex systems that require millions and millions of data points to begin to understand. Software development is ahead of medicine in seeing the wisdom of open source design, he points out.

Friend believes that allowing medical researchers to see each other’s terabytes of data will allow patterns to emerge that spell answers for some diseases. In fact, he believes the institutions and the foundations that donate money must adhere to five concepts – including sharing with patients – or they will fail at finding answers for chronic diseases.

In a video discussion with the patient-advocacy group, Faster Cures, he listed these five rules for success.

1. Make use of massive genomics, proteomics and other “omics” data

2. Put that in the cloud so thousands can access it from anywhere and doesn’t use your server space.

3. Use network modeling of disease.

4. Give patients the ability to send you data (for example, measuring their health using a cell phone)

5. Use open social media to involve patients and share with other researchers instantly.

Friend’s colleague, Thea Norman, talked to us about coming to Seattle to join him and how she will help leverage the RWJF money to make patients bigger partners in research. Bridge is designed to help groups of patients donate their own medical data in a way that provides a basis for discovery for researchers. For example, melanoma patients have already donated photographs of their own skin abnormalities to help build a database that scientists can scan.

“He’s visionary and inspiring,” she explained, of her decision to leave a job in San Diego and move to Seattle to work with Friend. Her title is director of strategic development.

“We get the cream of the crop of software engineers,” she explained of the special strengths that Seattle brings to the open science work. Some of what Bridge will do is build the web-based platform where patients can volunteer their data, or read and download consent information. (John Wilbanks, also at Sage, is one of the designers of what is called Portable Legal Consent.)

The next blog in this series will explore some of the patient advocacy that is driving open science. As Friend says, patients are the key to the enormous energy needed for change.