By David Rosenbaum
It may sound like science fiction, but the ability to customize cancer treatment for an individual patient through his or her genetic profile is not so far away, according to Dr. Marco F. Ramoni, associate director of bioinformatics at the Partners Center for Personalized Genetic Medicine at Harvard Medical School.
According to Ramoni, many of the tools necessary for delivering on this promise already exist.
“The name of the game is to use a patient’s genetic makeup to make predictions about what treatment will work best for each individual,” Ramoni says. “My dream is that someone goes into a hospital and it has a genomic record of this person, so we can shape exactly what will work according to the genetic profile. We already have the tools to develop these records, to build the genomic profile, in the research labs. Now we must get them into the clinical centers.”
Today, much effort is being made to make these tools available to the clinical centers by integrating them into the information system of the hospital. But a sophisticated IT infrastructure is needed to collect this information and make it accessible and transportable.
In other words, healthcare enterprises need robust, searchable databases as well as processes for collecting as much data as possible. In a large medical center where thousands of patients are served every day, sophisticated IT infrastructure can make use of clinical information to make discoveries—and loop these discoveries back into treatment.
“The technology is here,” Ramoni emphasizes. “It’s a matter of how many resources you put on the task.”
According to Dan Fontaine, senior vice president for business affairs at the University of Texas M.D. Anderson Cancer Center, his hospital’s partnership with Oracle will allow staff to channel information resources toward advancing global knowledge about cancer.
“In the future, we’ll need to see a uniform system where we can capture medical information in a uniform way,” says Fontaine. “We’re creating a world of personalized data through which we can identify those patients who will be positively responsive to a specific therapy tailored to their cancer, determined by their genetic profile. It’s the computational advances, the ability to advance the analysis of the data, that’s helping us.”
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