Researchers have found that artificial intelligence recognizes new breast cancer types that respond differently to a treatment. Using artificial intelligence, five new types of diseases were uncovered, each of them matched to different personalized treatments. The study applied AI and a machine-learning approach to gene sequences and molecular data from breast tumors, to reveal crucial differences among cancers that had previously been lumped into one type of disease. The researchers applied the AI-compatible computer software to a vast array of data available in the field of genetics, a molecular and cellular constituent of breast tumors, and data on patient survival. The goal of the study is to apply this technique different types of cancer and get information about their response and sensitivity to treatment, part of evolution, and how to tackle drug resistan problem.
The US Food and Drug Administration has approved the
addition of overall survival (OS) data in labelling process of Gilteritinib, a
cancer drug which was indicated for adult patients who had relapsed or
refractory acute myeloid leukemia (AML) with a FLT3 mutation as detected by an
FDA-approved test. FLT3 is a receptor tyrosine kinase with important roles in
cell survival and proliferation. It is mutated in one -third of AML patients. Gliteritinib
acts as an inhibitor of AXL receptor tyrosine kinase, an enzyme in humans
encoded by AXL gene . The AXL gene plays a crucial role in facilitating immune
escape and drug resistance by cancer cell, leading to metastatic cancers.
According to results, treatment with the FLT3-targeted
therapeutic Gilteritinib has shown improved survival for patients with relapsed
or refractory acute myeloid leukemia harbouring an FLT3 mutation compared with
standard chemotherapy regiments.
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