Big data conference builds foundations for precision health

Speakers at Stanford’s annual big data conference said the success of precision health depends on data that reflects the global diversity of humans, the well and the unwell, and a rainbow of data from genomes, microbiomes and tissue samples.

Stanford cardiologist Euan Ashley talks with Claudia Williams, senior advisor for health technology and innovation at the White House Office of Science and Technology Policy, during the Big Data in Biomedicine Conference.   
Saul Bromberger

The movement to revolutionize health care and promote populationwide wellness will depend on melding diverse kinds of data from people in every corner of the globe, several speakers said at Stanford Medicine’s fourth annual Big Data in Biomedicine Conference.

Lloyd Minor, MD, dean of the School of Medicine, opened this year’s conference —titled “Enabling Precision Health” — by noting that, “Without big data, there is no precision health. Data makes possible everything that precision health promises — true patient-centered care based upon prediction and prevention rather than relying exclusively on diagnosis and treatment.”

The conference, held May 25-26 at the Li Ka Shing Center for Learning and Knowledge, drew some 500 attendees and more than 2,100 remote viewers.

Now that the era of big data has arrived, breaking down barriers and looking for ways to exploit the rich interactions at the boundaries between different kinds of data — such as the particular mix of bacteria in the gut and the self-reported status of a person’s health and mood — is attracting attention. “Innovation,” said Claudia Williams, MS, senior advisor for health technology and innovation at the White House Office of Science and Technology Policy, “often comes at edges.”

Lloyd Minor, dean of the Stanford School of Medicine, welcomes conference participants.
Saul Bromberger

Turning patients into partners

That can include policy changes such as tax credits for people who donate their data or finding ways to allow patients themselves to generate innovations. Williams talked extensively about making patients partners in research; for example, she talked about a parent who tracked her child’s symptoms over time, noting which antibiotics had what effects on which symptoms. Such a parent might work well with a physician willing to look at that information and add other data from the child’s medical records into the mix.

“We focus a lot on motivating patients to share data,” Williams said, “and less on feedback loops and friction points.” One friction point is that patients can’t always get the data they themselves provided. Patients are legally entitled to receive all of their data in any form they request, said Williams. She advocates making that process easier and requiring health-care providers to comply more consistently.

Another major source of new data is biobanks, which Rohit Gupta, director of the Spectrum Biobank at Stanford, said are more than just freezers full of samples. “A sample’s purpose is to produce data.” And that data should include the information in the samples themselves and the information about the patients — all integrated into a single database.

More than 500 people attended the May 24-25 conference, and another 2,100 watched the events online.
Saul Bromberger

The power of biobanks

Some in the audience audibly sighed covetously when Oxford professor of medicine and epidemiology Martin Landray, PhD, described how the UKBiobank database contains both specimens and associated self-reports from hundreds of thousands of individuals. Landray was asked procedural questions about how easy it was for researchers to obtain data from the UKBiobank and estimates of how long it took to obtain the data.

Then, just a couple of hours later at the conference, Kathy Hudson, PhD, deputy director for science, outreach and policy at the National Institutes of Health, announced a $142 million grant to establish the world’s largest research biobank at the Mayo Clinic in Minnesota, as part of President Obama’s Precision Medicine Initiative. The new biobank will collect samples and information from 1 million individuals as part of the PMI Cohort program.

In a panel discussion on genomics, Carlos Bustamante, PhD, professor of genetics and of biomedical data science at Stanford, and other speakers agreed on the importance of broadening genomic databases to include people from all over the world, not just those of primarily European descent, as is now the case.

The future of big data and precision health is all about bringing together many kinds of data from many kinds of people, and about sharing data among patients as well as researchers. As Minor later said, “data is the ultimate rocket fuel that will launch us to the exciting and unchartered universe of proactive, predictive and precise health care.”



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