Rupa Haldavnekar
University of Oklahoma, OK·Biomedical Engineering
Ovarian cancer is often found late, after it has already spread, because there are few good ways to catch it early. A simple blood test that picks up the earliest signs of the disease could change this.
- Fields
Biomedical Engineering
Engineering
Medicine & Clinical Research
- Topics
ovarian cancer
early cancer detection
liquid biopsy
- Grants
- 1 known grant, through Jan 2029
What they work on
- Develop a surface-enhanced Raman spectroscopy (SERS) sensing approach, a light-based method that reads molecular fingerprints, to detect subtle blood-based changes signaling early ovarian tumor formation.
- Profile how the immune system responds during early ovarian cancer, using SERS-based immunophenotyping of liquid biopsies together with organotypic tumor models that mimic real tumor tissue.
- Integrate SERS data with artificial intelligence, predictive modeling and high-dimensional analysis into a multimodal platform that identifies early signatures of ovarian tumorigenesis.
More about the research
This project aims to build such an approach. It looks for subtle changes in the blood, including how the immune system responds during early disease, that may signal that a tumor is starting to form.
Why it matters
Ovarian cancer is usually diagnosed at a late stage, when outcomes are poor. A minimally invasive blood test that detects the earliest molecular and immune changes of the disease could allow earlier diagnosis and improve outcomes for patients. The sensing and data-analysis tools developed here may also support broader cancer detection research.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Mahmoud Almasri
University of Missouri-Columbia, MO·Engineering
Develop a Surface Enhanced Raman Spectroscopy sensor that uses metal nanoantennas on a side-polished optical fiber to quickly detect and measure Salmonella types in poultry samples.
Haoran Wei
University of Wisconsin-Madison, WI·Engineering·Early-career
Determine how a contaminant's chemical properties, its binding to the sensor surface, and water acidity and salts control SERS (surface-enhanced Raman spectroscopy) sensitivity, using adsorption measurements, controlled water experiments, and density functional theory modeling.
Pietro Strobbia
University of Cincinnati, OH·Chemistry
Identify which functional DNA sequence features control the performance of catalytic surface-enhanced Raman scattering (SERS) sensors, using inverse design and machine learning.
The school
University of Oklahoma: 11 labs on PI Pages, $474M a year on research, 225 research doctorates a year.
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