AI application in immunotherapy mainly focuses on evaluating the effects of different treatments and helping doctors adjust their prescriptions.
A research team at UT Southwestern Medical Center and MD Anderson Cancer Center built an AI-powered technique for identifying which neoantigens (peptides produced by mutations in cancer cells’ genomes) are recognized by a patient’s immune system. Such AI algorithms would allow predicting cancer cells' response to immunotherapies. Our immune system’s T cells are constantly watching for signs of cancer and other invading bodies. When these cells recognize neoantigens, they bind together. However, some neoantigens remain unrecognized, allowing cancer to grow.
There are tens of thousands of types of neoantigens. Analyzing their ability to trigger T cells’ response is a tedious, costly, and time-consuming task. With the help of machine learning
, this is becoming possible. Here is what Tao Wang, PhD, Assistant Professor, Population and Data Sciences at UT Southwestern Medical Center, said about this matter
, “Determining which neoantigens bind to T cell receptors and which don't has seemed like an impossible feat. But with machine learning, we're making progress."
Having this knowledge would allow researchers to develop personalized T cell-based therapies and cancer vaccines, and it will help predict patients’ response to immunotherapies.