Big Data in Precision Health focuses on how to make technology work for patient care

Dozens of speakers gathered at Stanford to discuss health, artificial intelligence and evolving technology and how it all could affect patient care at the annual Big Data in Precision Health conference.

Dean Lloyd Minor gives introductory remarks on May 23 at the conference, which was held at the Li Ka Shing Center for Learning and Knowledge.
Rod Searcey

As vast troves of health data accumulate because of wearable technologies, genome sequencing and an increased interest from patients in monitoring their own health, scientists and doctors face a challenge: how to get this data into the hands of those who need it the most ¾ health care professionals, doctors and a growing list of researchers applying new technologies to patient care.

This challenge was explored by several speakers at the School of Medicine’s Big Data in Precision Health Conference, which ran May 23-24 at the Li Ka Shing Center for Learning and Knowledge. Speakers from academia, government and industry shared lessons on wrangling immense data sets to develop useable, actionable solutions in health care and new lines of research.

“We’ve translated fundamental discoveries into advances in therapeutics, and we’ll continue to do that,” said medical school Dean Lloyd Minor, MD. “But now we also have the unique opportunity to make discoveries not necessarily based on mechanistic analyses, but on deriving information from vast treasure troves of data that already exist .... That’s really the power of big data.”

Keynote speaker Eric Dishman, director of the National Institutes of Health’s All of Us research program, explained the program’s mission: to gather health data from more than 1 million people in the United States to improve and accelerate health research and care.

While describing the aims of the program, Dishman related the story of his diagnosis, at age 19, with a rare form of kidney cancer. Doctors who saw the diagnosis extrapolated information from the average population of people who had his disease, most of whom were ages 65 to 70. He was told he had nine months to live. “It was a wake-up call to me,” said Dishman, who is now 50. “Everyone is doing the best they can with the data they have, but it doesn’t mean that’s the truth for any given individual.”

Bringing precision health to the masses

The morning session of May 23 focused on questions about the body’s transition from health to disease. Susie Spielman, director of strategic initiatives for Stanford’s Department of Radiology, is a program leader for Project Baseline, a collaboration between Stanford, Duke and Verily that aims to map human health in unprecedented detail. She led off the session, detailing the project’s goal of analyzing 10,000 individuals’ health data to answer a question that’s key to nearly all precision health research efforts: How do you define “normal” for any given individual?

Computer scientist Andrew Ng discussed artificial intelligence at the conference.
Rod Searcey

“As we move to population cohorts, the scale increases to millions of individuals, and as genome sequencing continues to roll out, tens of millions of genetic variants. Data at that scale becomes quite challenging,” said Manuel Rivas, PhD, an assistant professor of biomedical data science, who spoke on population health. That challenge, he said, is what motivates him to think about statistical methods and computational tools capable of carrying out analyses on massive amounts of data, creating summaries that are useful in answering questions fundamental to biology.

In the afternoon, the focus shifted to a high-profile embodiment of precision health today: cancer immunotherapy. Crystal Mackall, MD, professor of medicine and of pediatrics at Stanford, is a leading researcher in engineering immune cells to fight cancer. In back-to-back talks, she and Adnan Jairdar, MD, a medical officer at the Food and Drug Administration, detailed the yin and yang of innovation and regulation: how cutting-edge treatments that reprogram a patient’s own immune cells to fight tumors make it out of the lab and into the hands of doctors.

Topping off the discussion on cancer immunotherapies, Jennifer Wargo, MD, associate professor of surgical oncology and of genomic medicine at MD Anderson Cancer Center, highlighted what she believes is an emerging frontier in precision health: the microbiome, or the microorganisms in our bodies. Her work looks at the connection between the makeup of the gut microbiome and immunotherapy success. Indeed, the type and number of bacteria living in a person’s gut actually does alter the outcome of immunotherapies ⎯ a result that theoretically could enhance success of these kinds of cancer treatments, Wargo said.

‘Man plus machine’

Day Two of the conference opened with a focus on machine learning and artificial intelligence, highlighting its purpose and potential in health care. Dekel Gelbman, the CEO of FDNA, a digital health platform that harnesses artificial intelligence to identify rare diseases based on physical facial features, said that the role of the company’s facial recognition capabilities is to augment diagnoses. Clinicians using the technology report accurate diagnoses, and that’s great, he said. But the best feedback is when they say the platform helped show them diagnostic information they wouldn’t have otherwise seen.

(From left) Carla Pugh moderates a panel on digital health and technology featuring Jennifer Schneider, Leanne Williams, Lisa Suennen and Rich Mahoney at the conference.
Rod Searcey

Andrew Ng, PhD, an adjunct professor of computer science at Stanford and a globally recognized leader in artificial intelligence, brought the power of AI in diagnostics to the stage in a demonstration of a smartphone app that processes pictures of X-ray images and spits out the likely medical conditions associated with the X-ray’s composition.

“Because AI technology is still evolving … only AI experts have a very good sense of the potential of AI, while only health care experts have a very good sense of how health care could benefit,” Ng said. “The approach that I believe will be successful in this era is getting AI people to learn more about health care, and get health care people to learn more about AI.”

The final conference session focused on digital health. Four speakers discussed the intersection of health, digital technologies, venture capitalism, quality of life and behavior as it relates to health.

“We often hear about the fear that robots are going to take over and kill us all,” said Rich Mahoney, PhD, CEO of Seismic, which creates wearable robotics. Mahoney’s technology is called Powered Clothing and looks like a pliable combination of undergarments and a bodysuit. But integrated into the fabric are electromechanical muscles that work to boost the wearer’s core muscles. With sensors that can feel the motion of the person, Powered Clothing is designed to tell when a person is, for example, standing up, and physically helps to bring them upright. The technology could help improve the quality of life for older individuals who may be experiencing a loss of mobility.

“We don’t specify other industries as ‘digital.’ It’s not ‘digital transportation’ or ‘digital manufacturing,’” said Lisa Suennen, senior managing director at GE Ventures, who said she views technology as a means to better patient care. “We need to get to a point where we’re comfortable enough with technology in health care that it’s simply part of health care.”



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