Big Data in Biomedicine Conference set for May 24-25

The two-day event at Stanford will focus on ways of using big data to advance precision health.

- By Jennie Dusheck

Last year's conference drew more than 500 attendees and another 2,000 who watched the events online.
Saul Bromberger

The 2017 Big Data in Biomedicine Conference, set for May 24-25 at the Stanford University School of Medicine, will explore success stories of and opportunities for harnessing big data for both research and clinical care.

This year’s meeting, titled “Big Data in Biomedicine: Transforming Lives Through Precision Health,” will focus on precision health in action, highlighting the Precision Medicine Initiative, the Chan Zuckerberg Initiative and other promising new initiatives.

“We’re living in a time of unprecedented complexity — and historic opportunity,” said Lloyd Minor, MD, dean of the School of Medicine, who will give introductory remarks at the conference. “Big data, artificial intelligence and other technological breakthroughs enable us to fulfill our promise to predict, prevent and cure — precisely — on a global scale.”

Last year’s event brought more than 500 attendees to the campus, while another 2,000 watched online via live-streamed video. This year, the conference, which debuted in 2013, is expected to once again draw hundreds of researchers and leaders from academia, health care, government and industry. Presenters will discuss the National Institutes of Health Precision Medicine All of Us research program; NIH’s National Library of Medicine; and the Chan Zuckerberg Initiative.

Biomedical data comes from diverse sources, including millions of electronic health records, wearable sensors and biomedical databases. Searching hundreds of millions of de-identified personal medical records — for relationships among diseases, treatments and outcomes — can quickly reveal new avenues for clinical research. The cutting-edge approach can point to previously unsuspected opportunities for treatment as well as opportunities to improve patient care. It’s one of the drivers of precision health at Stanford Medicine, whose goal is to anticipate and prevent disease in the healthy and precisely diagnose and treat disease in the ill.

But the big data approach means repurposing data collected for other uses, most often for diagnostics and billing. Utilizing such data means solving myriad challenges, such as standardizing the metadata that characterizes each data set and finding better ways to make databases accessible to researchers.

Topics this year include recent big data success stories connected to cancer, cardiovascular disease and clinical trials; new opportunities for taking advantage of big data; the interface between regulatory science — the study of the science of regulating research and development — and data science; the interface between artificial intelligence and interpretation of biomedical imaging; and network science, including, for example, how to analyze complex relational data in biological data or social data.

This year’s speakers will include Marc Tessier-Lavigne, PhD, president of Stanford; Stephen Quake, professor of bioengineering at Stanford; Jennifer Van Eyk, MD, professor of medicine at Cedars-Sinai Medical Center; Russ Altman, MD, PhD, professor of bioengineering, of genetics and of medicine at Stanford; Michelle Rohrer, PhD, senior vice president and global head of product development regulatory and policy at Genentech Roche; Greg Moore, MD, PhD, vice president of Healthcare Google; Cori Bargmann, PhD, president of science for the Chan Zuckerberg Initiative; Nikesh Kotecha, PhD, vice president of informatics for the Parker Institute; Jessica Mega, MD, MPH, of Verily Life Sciences; and Nancy Brown, CEO of the American Heart Association.

Registration and more information is available online.

About Stanford Medicine

Stanford Medicine is an integrated academic health system comprising the Stanford School of Medicine and adult and pediatric health care delivery systems. Together, they harness the full potential of biomedicine through collaborative research, education and clinical care for patients. For more information, please visit

2023 ISSUE 3

Exploring ways AI is applied to health care