Unlimited opportunities spring from Big Data in biotechnology
A frequent buzzword in business these days is "Big Data." But how do investors and developers in the biotechnology industry make the best use of it?
"We all hear about Big Data, and nobody knows what it is," said Lesa Mitchell, vice president of innovation and networks for the Ewing Marion Kauffman Foundation, as she opened a plenary panel on the subject at the recent Partnering for Cures Conference in New York City. In fact, said Mitchell, when people bandy the term about "in some cases, we all mean completely different things."
As Mitchell predicted, panel members offered different ideas on what Big Data means for biomedicine, healthcare and drug development -- and on how best to harness it.
A Rapid Expansion
"The field is expanding so rapidly there's almost no area where Big Data doesn't have an impact, both on the basic science discovery side in research and on the healthcare patient care side," said Gary J. Nabel, senior vice president and chief scientific officer at the pharmaceutical giant Sanofi.
However, healthcare is the area "where there is the biggest gap between what is being done with Big Data and what could be done with Big Data," said Jeff Hammerbacher, co-founder and chief scientist at Cloudera.
"There is a tremendous amount we can do, not just on the research and development side of biology in the lab, but also inside of the hospitals themselves in determining what treatments be given to which patients and how do we assign the scarce resources of nurses and doctors," said Hammerbacher, who is also an assistant professor at the Icahn School of Medicine at Mount Sinai. "Outside of the hospital, there's a tremendous amount we can do to understand how the drugs we are releasing in the world are actually having an impact on people's lives."
Thomas Frieden, MD, MPH, director of the Centers for Disease Control and Prevention, agreed. "We haven't really unlocked the power of data to improve clinical care," he said. In the best health systems, clinicians and care providers are able to use Big Data at the bedside in "real time."
Using Big Data in the Real World
So what areas of bioscience and healthcare are ripe for using Big Data today?
"There are tremendous opportunities to build better systems for doctors and scientists; it's almost infinite," said Andy Palmer, founder of Koa Labs. "But the quantity of data that is available to scientists and doctors for research right now is very limited."
But the work on building those systems is really starting to take off.
"We're just starting to see data come out of academic medical centers about medication side effects, drug-drug interactions," said Roni Zeiger, MD, co-founder and CEO of Smart Patients, a medical informatics company that leverages data from patient networks. "There is now a rich enough set of data that not only contains not just the fact that a patient is taking a specific medication, but a bunch of other data points associated with it, like what procedures came before, what diagnoses came after. The next step is more about the questions than the answers," Zeiger said.
Clinical trials databases, which he called "very messy," are a place to start. Networking by patients is helping them clear a path through that messy thicket of data so they can ask questions and find answers about trials that are right for them, he said.
We've also got data from participants in those clinical trials that we collect and can share with other researchers, Nabel said. "So we are both users of Big Data and providers of Big Data."
Catching Up to ‘Real Time'
From his perspective as a "disease detective," the CDC's Frieden sees an opportunity for mining Big Data to unlock the genome of microbes to help scientists track disease outbreaks.
"We're still using techniques from more than 100 years ago," he said. "If we get to the whole genome level, we're going to be able to unlock a remarkable amount of information - what we call advanced molecular detection. It will allow us to use real-time detection, next generation detection."
Nabel agreed. "Between the molecular modeling and the structural biology there's an enormous amount of information to be uncovered," he said.
But right now, a lot of what is being called Big Data in bioscience is a lot of "noise," the panelists agreed. Better systems are needed, not only to help collect the data, but also to analyze it and make it usable.
"Building capacity for thoughtful analysis is crucial," Frieden said.
The panelists see challenges ahead, but also great opportunities.
"We are at the very beginning of the process of discovering the power of Big Data in scientific research," Palmer said.
[Photo by - justgrimes]