Big Data Optimises Personalised Cancer Therapy in Italy

June 6, 2013 – 8:51 am

When choosing optimal treatments for cancer patients, doctors must consider a number of factors: age, general health, weight, the medical history of family members, the current state of the disease and much more. Big data, in the form of a collaboration between IBM and the National Cancer Institute of Milan, may be able to connect those dots.

Begun in 2012, the project uses data analysis technology to correlate a patient’s personal data and disease profile with available information of past cases and clinical guidelines. To determine whether a patient should undergo chemotherapy, for example, the physician can match his or her individual case with a series of comparable past cases. The outcome will guide the physician and patient in choosing an appropriate therapy.

The method is based on the IBM Clinical Genomics Analysis Platform (Cli-G), which was developed by scientists at IBM Research in Haifa, Israel. The technology is comparable to its cousin, IBM’s Watson, which came to fame by defeating human opponents in the quiz show Jeopardy. Watson has moved on from show business and is currently involved in a project similar to Cli-G at the Sloan Kettering Cancer Center in New York. In both cases, anonymised comparative data are collected from hospitals and health organisations in the region to help guide treatment alternatives.

Researchers report that the process results in more accurate, personalised decisions and leads to a better treatment. “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,” says Marco  Pierotti, Scientific Director at the Istituto Nazionale dei Tumori.

In recognition of its achievement, the Clinical Genomics team received the Innovation Award ICT in Health on 7 May 2013 at the Politecnico di Milano. The award programme is sponsored by the ICT Observatory on Health, School of Management, Politecnico di Milano.

By: Thomas Klein


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