Researchers at IBM, Berg Pharma, Memorial Sloan Kettering, UC Berkeley and other institutions are exploring how artificial intelligence and big data can be used to develop better treatments for diseases.
But one of the biggest challenges for making full use of these computational tools in medicine is that vast amounts of data have been locked away — or never digitized in the first place.
The results of earlier research efforts or the experiences of individual patients are often trapped in the archives of pharmaceutical companies or the paper filing cabinets of doctors’ offices.
Patient privacy issues, competitive interests and the sheer lack of electronic records have prevented information sharing that could potentially reveal broader patterns in what appeared to any single doctor like an isolated incident.
When you can analyze clinical trials, genomic data and electronic medical records for 100,000 patients, “you see patterns that you don’t notice in a couple,” said Michael Keiser, an instructor at the UC San Francisco School of Medicine.