The Mayo Foundation for Medical
Education and Research plans to partner with IBM to model diseases and,
it hopes, to find cures using the Blue Gene supercomputer.
The two organizations said Wednesday that they will jointly
develop new technologies and devices aimed at improving diagnosis,
curing diseases and developing individualized treatment. Mayo Clinic
will use IBM's Blue Gene supercomputer for mathematical modeling
required to understand gene and protein structures and their
interactions to get clues about disease causes. This may help Mayo
understand which genes might be responsible for certain diseases,
including various cancers.
Blue Gene, originally an IBM research project
to investigate how proteins fold into complex three-dimensional shapes,
has found use in other number-crunching fields of scientific research,
such as radio astronomy. IBM has had competition from others, such as Hewlett-Packard and Sun Microsystems, in the emerging life science market.
A project on individualized patient care, planned by Mayo and IBM,
involves using data-mining tools to provide customized information for
each patient to his or her practicing physician on demand. This could
enable doctors to access information regarding a patient's medical
history, in addition to research and clinical outcomes of other
patients under similar conditions, Mayo and IBM said.
"We are at a point with standards in technology and new
genomic-based analytic techniques where we can achieve more in the next
10 years than we've achieved in the last 100, and we see in IBM a
partner with a very unique capacity to deliver expertise and
innovation," Mayo CEO Denis Cortese said in a statement.
IBM and Mayo have digitized 4.4 million patient records in
nonintegrated formats into a unified system based on a standard
technology platform. Doctors and researchers will be able to access
these records for research purposes, while honoring patients' privacy
rights and government regulations. The partners said they will invest
in technology and human resources to develop a standard method of
integrating patient data to extend the types of data that can be
analyzed into an integrated database, using open technology