IBM is moving on from "Jeopardy" to finding treatments using genetic data. The company announced it has developed a data-analytics platform called Clinical Genomics that uses algorithms and analytics similar to that of Big Blue's Watson supercomputer to find treatments for conditions based on a patient's genetic profile.
Doctors can use Clinical Analytics to analyze patients' similarities, predict outcomes, evaluate risk benefits and view treatment options. In addition to genetic data, the software also takes into account a patient's age, gender, symptoms and past diagnoses.
The new platform combines knowledge of patient histories with automatic statistical analysis and machine learning, said Dr. Haim Nelken, manager of IBM Research's health care and privacy solutions division in Haifa, Israel.
"This is a standard-based generic framework that can be used in the context of various diseases and for a range of decision-support tasks, such as patients' similarity assessment, prospective outcome prediction, risk-benefits analysis, and presentation of the treatment options most likely to succeed," Nelken wrote in an email to eWEEK.
Researchers can access data through a standard Web browser on tablets or PCs.
IBM's Clinical Genomics fits into the growing trend in health care of using big data to develop personalized medicine, which is the ability to use a patient's personal genetic characteristics to prescribe medical treatment for conditions, such as cancer, hypertension and AIDS.
Clinical Genomics enables doctors to aggregate medical statistics and develop recommendations and weighted predictions, Nelken wrote. The software analyzes medical guidelines and the knowledge clinicians provide, and correlates it with patient data to provide doctors with personalized treatment options.
Before platforms such as Clinical Genomics, analyzing a patient's genetic profile along with other data such as family history required large-scale data sources, IBM reported.
Fondazione IRCCS Istituto Nazionale dei Tumori (INT), a research and treatment cancer center in Italy focused on preclinical and clinical oncology, is conducting a pilot project using Clinical Genomics, which IBM announced March 14.
"Making decisions in today's complex environment requires computerized methods that can analyze the vast amounts of patient information available to ease clinical decision making," Dr. Marco A. Pierotti, scientific director at INT, said in a statement. "By providing our physicians with vital input on what worked best for patients with similar clinical characteristics, we can help improve treatment effectiveness and the final patient outcome."
In the first stages of the trial at INT, researchers looked at data from patients suffering from Soft Tissue Sarcoma, a cancer of soft tissue in muscles, tendons, fat and blood vessels, said Nelken.
IBM hopes additional hospital systems will integrate Clinical Genomics into their personalized medicine programs. The platform will keep data anonymous and identify cases by search criteria such as age, gender, symptoms and diagnosis, IBM reported.
Using clinical genomics can improve treatment and limit the number of unnecessary procedures, said Nelken. (A recent survey in the March 2012 issue of the journal Health Affairs found that using computerized systems led doctors to order more lab tests.)
Clinical Genomics uses natural-language processing and machine-learning capabilities that are similar to Watson, IBM reported. The new platform's algorithms and analytics capabilities also complement the deep question and answering features of Watson, according to the company. On March 1, IBM announced a new advisory board of experts for Watson that will research how the supercomputing technology can help clinician workflows.
In another development in personalized medicine, Dell announced on Nov. 10 that it would donate its cloud infrastructure to the Translational Genomics Research Institute (TGen) to house data for a personalized medicine trial being conducted to find treatments for pediatric cancer. TGen is a nonprofit organization focused on using genomics to develop medical treatment.