By Admin at 6 Dec 2016, 11:19 AM
The era of personalized medicine is upon us, and cancer is no longer viewed as a disease with a single cause and treatment. Instead, it’s known that millions of causes, resulting in unique variations, trigger the collection of diseases known as cancer, and their treatment requires similarly complex and varied forms of treatment.
It’s clear that technology represents the future of cancer treatment and, ultimately, its cure. Supercomputers can analyze masses of genetic data to reveal patterns that give researchers and physicians a new avenue of attack. This is why some of the newest, yet perhaps most powerful, assets in the war against cancer aren’t doctors or cancer specialists but mathematicians.
Eric Schadt, a specialist in molecular and computational biology, is one such asset. He started the Icahn Institute for Genomics and Multiscale Biology at Mount Sinai Hospital, which, among other things, has high-performance supercomputers for “quantitative analysis of massive datasets to create predictive models of human disease.”
The problem, as Schadt and others like him have found, is that massive amounts of data are needed to detect noteworthy patterns. Wired reported:
“With enough data, the theory goes, there’s not a disease that isn’t druggable.
But as Schadt has learned, it’s not enough to plumb the depths of an individual’s DNA. It requires a universe of data — exabytes worth — to detect patterns in a population, apply machine learning, find the network of mutations responsible for disease, and do something about it.
The bigger these data sets become, the more accurate and powerful the models and the predictors become. The problem is getting these exabytes of genetic data.”
The U.S. National Institutes of Health (NIH) has kicked off the Precision Medicine Initiative Cohort Program, which aims to recruit 1 million people who are willing to share their health and genetic information to help researchers create individualized treatments. However, even this may not be enough.
“We need 100 Mount Sinais to achieve the scale required to recognize the patterns in patient data that guide you to diagnoses and treatments,” Schadt told Wired, which is on the order of 10 million people or more.
Schadt maintains that medical centers, which are isolated from each other and competitive with their data, will not be able to amass the collaborative mega-datasets needed to cure cancer. Instead, he believes this will happen outside the medical establishment, at firms like Sema4, which is the genetic data company he started.
Sema4 is acquiring and expanding genetic-testing companies with the goal of creating a searchable platform that will allow physicians to diagnose their patients, scientists to engage in more ambitious research and pharmaceutical companies, which will pay to use the system, to find patients for clinical trials.
Ultimately, Schadt envisions a future of medicine where people regularly share genetic, medical and lifestyle information that’s collected via glucometers, blood pressure trackers and inhalers, such that their health information could be continually monitored for disease.
As it stands, medical centers hold a virtual monopoly over patient data, but in the future massive amounts of genetic data will be freely available to researchers and other organizations, which is what’s needed to prompt medical breakthroughs. The hope is that one day every disease, including cancer, could be treatable.
Source:
Wired October 19, 2016
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