Malignancies induce a general immune response. The tumor micro‑environment consists of a variety of immune cells, such as:
Image from The Johanna Joyce Lab, Memorial Sloan Kettering Cancer Center
Myloid cells are a certain type of immune cell which emanate from stem cells in the bone marrow and travel to the site of the tumor.
Cancer cells may impede the normal development of these myeloid cells and subvert their usual function.
Once corrupted by the cancer, some of these cells may engage in immune-suppressive activities and may become Myeloid Derived Suppressor Cells (MDSCs).
Image from OncLive, Myeloid Cell Subtype Attracts Growing Interest as Immune System Target
MDSCs are the subject of ongoing cutting-edge research and are being targeted by the newest immunotherapy drugs.
ITUS has identified certain sub-classes of MDSCs as being diagnostic in nature and has developed proprietary protocols for analyzing the cells in the blood of cancer patients.
In addition to MDSCs, ITUS is evaluating sub-classes of other immune cells in its analysis.
What is Artificial Intelligence?
Artificial intelligence (AI) refers to the ability of a computer system to simulate human intelligence, with the capacity to perform a greater number of concurrent analyses more quickly than a human typically can.
ITUS is developing a software application using a proprietary neural network, an AI system that focuses on complex pattern recognition. Our neural network has been specifically trained to distinguish between the immunological responses of cancer patients and healthy patients, relying on up to 13 quantitative parameters to analyze test results. As more and more samples are processed, the neural network learns to make more accurate and reliable distinctions. In addition to this enhanced efficiency, the neural network is not subject to human error or bias, which may lead to better results.