Using cell-free DNA and Machine Learning to detect ovarian cancer earlier
Using cell-free DNA and Machine Learning to detect ovarian cancer earlier
Our mission is to accurately rule in or out ovarian cancer earlier when it's easier to treat and improve the treatment planning of women with ovarian masses.
We take cell-free DNA found in standard blood samples and apply advanced machine learning models to identify ovarian cancer in early stages.
While transvaginal ultrasounds and CA-125 blood tests are used in ovarian cancer, there is a lack of reliable screening tests for early stage detection when 5 year survival rates are over 90% vs late stage diagnosis which is 31%. We are using new technology and approaches to disrupt the status quo.
Our flagship blood test helps screen patients for the most common and lethal type of ovarian cancer - High Grade Serous Ovarian Cancer (HGSOC) - to help inform the best course of treatment. For any woman with a pelvic mass, we are taking the guessing game out of the detection and treatment process especially for HGSOC which is the most common and most lethal form of ovarian cancer.
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