By Rich Ptak
Along with
some 23,000 others, we attended IBM’s InterConnect 2016 event in Las Vegas. IBM
enlarged last year’s event with a special focus on customers who led nearly half
the sessions. In fact, for the first time, customers kicked off the event;
reviewing details of successes built on IBM offerings. It was some 30 minutes
before an IBM executive appeared on-stage.
There was
ample opportunity to interact with IBM experts, staff, customers and partners. IBM
also exposed details of the changes, results of their internal transformation
to a services-driven company. Major technologies featured included Cloud,
mobility, analytics and cognitive computing technologies. Here’s what struck us
as especially interesting.
Advancing and Speeding
Cancer Research
We found one
story of particular interest. We met with Dr. Piers Nash of the University of
Chicago’s Center for Data Intensive Science (CDIS). IBM Cloud Object Storage using
Cleversafe technology enables CDIS to centrally store and manage vast amounts
of genomic and clinical data to accelerate medical discoveries. This approach
allows researchers nationwide to collaborate via shared access to harmonized
data sets, speeding discovery and enabling precision medicine.
Cleversafe’s
object-based storage allows management of unstructured data and is able to
scale to handle petabytes of data. The combination allows CDIS to collect,
manage, secure and analyze petabytes of data. Dr. Nash indicated that these
capabilities are what makes CDIS efforts feasible.
CDIS hosts over
5 PB of data files. Genomic data and associated clinical metadata from centers
around the country is cleaned, standardized and made available to researchers through
a web portal and APIs.
Medical
research requires very large amounts of data for optimal results. Collaborative
research fuels major breakthroughs in precision medicine. CDIS efforts drive
advances in continuously updated, data-driven, analytics-informed discovery, diagnosis,
prognosis, and optimized treatment protocols. These speed diagnosis and allow
creation of customized treatment protocols for individual patients as it
advances algorithm-assisted, personalized medicine.