Early Detection of Ovarian Cancer using Novel Sensor

Early Detection of Ovarian Cancer using Novel Sensor

Mijin Kim, PhD, has been awarded a Marie-Josée Kravis Women in Science Endeavor fellowship for her work on novel sensor technology for early detection of ovarian cancer in the year 2021. According to Kim, one of her main research focuses is related to the early detection of high-grade serous ovarian cancer which is really hard to detect at an early age. Carbon nanotubes that have been chemically and physically engineered to transduce a wide range of subtle variations in physiochemical properties of ovarian cancer biomarkers make up the latest sensor technology.

Kim went on to say that she had discovered a way to collect disease fingerprints from patient serum using an array of moderately specific nanosensors combined with machine learning algorithms, resulting in reliable detection of high-grade serous ovarian cancer from other conditions as a result of her biomedical research. She explained that using machine learning data analysis improves the identification of meaningful and complex disease characteristics from sensor readouts, addressing issues such as heterogeneity among large sample sizes and other uncontrollable variables. According to her, she and her colleagues created technologies that can detect ovarian cancer fingerprints in later stage ovarian cancer with a success rate of nearly 95%, which is substantially higher than traditional serum biomarker-based detection.

They also say that the serum contains several previously unknown or underappreciated biomarkers. They claim the technology has the potential to detect ovarian cancer in its early stages and could aid biomarker discovery efforts. Kim went on to say that her team is continuing to work on identifying biomarkers and enhancing sensor selectivity and specificity for ovarian cancer detection.


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