Imagine making a spreadsheet of every meal you've ever eaten, every hand you've ever shook, every bit of dust that's ever gotten in your eye - and multiply it by about a million times. Then you begin to get a sense of the size of the data problem that is your body's immune system. Through a new AI project, Microsoft hopes to solve this data problem and make diagnosing nearly any disease as simple as a single blood test.
You see, stored within your immune system is a record of virtually every threat to your health that you've ever encountered. When an invader shows up -- be it the flu, cancer, or something weird you picked up while showering without flip-flops at the gym -- your body identifies it and launches a targeted attack. This works the the help of special cells called T-cells, which each carry a corresponding surface protein called a T-cell receptor with a genetic code designed to target a specific disease, signalled by what's called an antigen.
So if the immune system's T-cells each contain genetic markers of every pathogen the body has encountered, then decrypting those markers could theoretically give you a log of every threat you have ever faced. That's what Microsoft is hoping. In a new research effort with the Seattle biotech firm Adaptive, the company is working to decode the human immune system so that it can diagnose disease.
"Your immune system should know what you have before your doctor does," said Adaptive CEO Chad Robins at the annual JP Morgan Healthcare Conference in San Francisco on Wednesday.
The idea is, in essence, to make a map of the human body's immune responses -- of its T-cell receptors sequences and the codes of the antigens they have fought against. And using that map, eventually, the idea is to be able to diagnose practically any disease from a sample of blood.
Remember the massive spreadsheet we imagined earlier? That spreadsheet is the reason this problem calls for artificial intelligence.
"We're searching for patterns in a giant space," Peter Lee, vice president of AI Research for Microsoft, told Gizmodo. "In machine-learning, a problem this big is exotic."