many of the same tools we see being utilized by consumers today in cloud computing and social media.
“We’re imagining a world where consumers are an active participant in their health, supported by data, and tied together by models that help us all understand that data,” he said.
Karkanias displayed an example of one of these tools: a personalized health dashboard with “news feeds” of relevant data that is stored in the cloud and accessible from anywhere. The data available on the dashboard would go beyond what’s in your electronic medical record—it would also include information for family members who play an active role in your health, information on scientific studies that directly relate to your health, models that show possible outcomes of decisions you make about food, exercise, and so forth, information on how your disease might progress, etc.
“We do this for financial planning,” Karkanias said. “It would be very interesting to think about that model for healthcare.”
Such models could also use the power of social networks to give patients access to information and resources provided by other patients with similar conditionals—data that could help patients research and decide on a treatment plan, as well as help physicians make recommendations.
“Imagine doing this for physicians,” Karkanias said. “‘The last 1000 people who were treated this way, these were their outcomes.'”
Erik Nilsson, Insilicos:
Insilicos develops biomarker discovery software that has the potential to improve disease diagnoses and enable the development of new therapies. By making valuable medical data available in what Nilsson calls a “cloud cluster,” Insilicos has created “cheap supercomputers for everybody,” he said. And he agreed that scientists could benefit from a collaborative lab and clinical information system “in neutral territory.”
Right now, “It’s like your data’s on Jupiter, and you can’t get there. You’ll never live there, you can’t see it—you can send robots,” he said. “And that’s not instinctive—you want your data close.”
In the future he says the healthcare industry will see a greater emphasis on computer power dedicated to biomarker research.
Stephen Friend, Sage Bionetworks:
Sage Bionetworks is a nonprofit biomedical research organization aimed at coordinating a link between academic and commercial biomedical researchers through a digital “commons.” Sage is located at the Fred Hutchinson Cancer Research Center, and is financially supported through a combination of philanthropic donations, research grants, and commercial partnerships.
As health IT capabilities grow, according to Friend, researchers will have to amend not only what they do, but how they go about doing it—the emphasis will become less about research and clinical data, and more about how that data is stored, accessed, and used. “The approaches that we’ve been taking to develop therapies have to be looked at,” he said.
“The reality is that our way of developing drugs is in a pitiful state, and the reason is that our concept of who has Alzheimer’s, or schizophrenia, or any other system-based disease, has to be taken down,” he said. “We’re not looking at the serious heterogeneity of what causes these diseases—tracking all of the systems alone, you’re not going to know why that person got Alzheimer’s, or that person had a heart attack.”
Medical research, according to Friend, has become a “tower of Babel,” a “walled garden too mired in academia.” Between all the studies and reams and reams of data spread across countless academic institutions and research organizations, it’s nearly impossible to get real breakthroughs to patients. “Scientists are not thinking of their data as an ingredient to the solution. They’re thinking of it as an ingredient to their next paper,” he said.
But through the Sage Commons, Friend said, researchers and physicians could develop ways to share and manage data, tools, and models for understanding disease—enabling a pool of resources that isn’t limited by intellectual property.
“To do that we’re going to have to have an adoption of standards around the genomics data,” he said. And while this may not be an easy task, Friend says it’s the needed resolution to a broken system. He added, “We have to change how we’re working. It’s not just the what, but how.”
