Microsoft Develops AI to Help Cancer Doctors Find the Right Treatments

There are hundreds of new cancer drugs in development and new research published minute to minute, helping doctors treat patients with personalized combinations that target the specific building blocks of their disease. The problem is there’s too much to read and too many drug combinations for doctors to choose the best option every time. Enter a Microsoft Research machine-learning project, dubbed Hanover, that aims to ingest all the papers and help predict which drugs and which combinations are most effective, according to the company. Researchers at Oregon Health & Science University’s Knight Cancer Institute are working with Hanover’s architect, Hoifung Poon, to use the system to find drug combinations effective in fighting acute myeloid leukemia, an often-fatal cancer where treatment hasn’t improved much in decades. They include Jeff Tyner, and the institute’s director, Brian Druker, best known for pioneering Gleevec, a blockbuster drug for a different type of leukemia now owned by Novartis, that’s helped double those patients’ five-year survival rate since the 1990s.”


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