When cancer spreads, tiny amounts of cells can break away from tumors and circulate in the bloodstream. A liquid biopsy is a means to detect the presence of cancer by detecting these cancer cells floating in blood samples.
Researchers at the USC Viterbi School of Engineering and the USC Dornsife College of Letters, Arts and Sciences have developed a new AI algorithm to automate the detection of a few cancer cells among millions of normal blood cells. In approximately 10 minutes, the algorithm is able to find the “needles in the haystack,” to detect cancer more quickly, determine if cancer has returned and potentially, inform treatments.
The new algorithm, named RED (Rare Event Detection) is outlined a PhD in the USC Department of Aerospace and Mechanical Engineering (focused on machine learning and artificial intelligence). RED works differently than existing computational tools for liquid biopsies that require a human to be in the loop. In fact, instead of looking for specific, known features of a cancer cell and grouping the millions of cells down into smaller groups, RED does not even need to know what the “needle” it is searching for looks like, that in addition to removing human bias, We are able to find more signal than the old approach. We were able to find twice as many interesting cells compared to the old approach. This new approach is already paying significant dividends and is being applied to understand outcomes for cancers like breast cancer, pancreatic cancer and multiple myeloma.
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