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As a first step, researchers at IBM have developed smarter software to find patterns in large groups of genes that signify whether a group of patients with common symptoms has a certain variation of a disease-which should lead to better diagnoses for individuals. For example, the scientists developed a genetic screen for leukemia using algorithms that can efficiently examine large numbers of gene combinations. They used it to identify a unique signature of about 100 genes in Mayo patients with a common form of leukemia (see top image). In a separate test at Columbia University, doctors used the screen to diagnose the disease, with 100 percent accuracy. The hope is that the analysis software can be extended to other cancers and to cardiovascular disease.

Down the road, databases that incorporate such genetic data, combined with pattern recognition algorithms, could allow doctors to detect disease before symptoms emerge and create treatment plans customized to patients. “I am convinced,” says de Groen, “that in five years, for some tumors, we’ll be able to say, We know from your DNA and study of your tumor that this drug will work, and with little toxicity.’” But translating prototypes into practical systems that can handle the extra genomic data and still be searchable-and affordable-will take a while.

Critical to implementation of the systems is overcoming concerns about security and patient privacy. In addition to enforcing “military-level security” on patient data, says de Groen, clinicians “have to make people understand that there are tons of benefits in having their information available.” And, he adds, policymakers must ensure that such medical information cannot be hijacked or used to deprive patients of insurance or other services. Currently, use of the Mayo database is restricted to project coordinators. But starting in January 2004, password-protected access will gradually be granted to Mayo doctors who file protocols that demonstrate a need to use the data in their research. Longer-term plans call for the database to be accessible to any doctor with a patient waiting in his or her office.

Ultimately, after the technical and social issues have been resolved, collaborations between infotech companies and clinicians will mean widespread improvements in patient care. “It might take a decade, but information will transform medicine for the ordinary Joe on the street,” says IBM’s Kovac. If she’s right, a quick database search might become a standard part of any medical checkup.

Projects Using Advanced Database Tools in Medicine Institution Application/Strategy Duke University School of Medicine (Durham, NC) Combining genetic markers, medical images, and clinical histories in an electronic health-care database Hadassah Hospital (Jerusalem, Israel) Integrating gene expression profiles and medical images into electronic patient records iCapture Research Centre, University of British Columbia
(Vancouver, British Columbia) Correlating genetic markers and environmental factors with heart and lung diseases, using pattern discovery algorithms Kobe General Hospital (Kobe, Japan) Integrating patient records and genetic data for personalized care Mayo Clinic (Rochester, MN) Unifying patient records in a single cross-searchable database; later versions will include genomic information University of California, San Diego, School of Medicine (San Diego, CA) Testing a secure database that allows doctors and patients to access clinical records over the Internet; developing faster computing tools to analyze gene expression for diagnosis and treatment of cancer

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