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Mission

Women with health insurance who are diagnosed with Ovarian Cancer on average spend $3,000 out of pocket on the disease each year. After completing treatment, 70% of cases the disease will return. For many women in resource limited environments, monitoring the disease is cost prohibitive. The FDA approved blood test to monitor reoccurrence of of HE4 is a $650. A women still needs to take off work, and come into a doctor's office to do this blood test. Additionally, urine offers a less harmful sampling procedure for repeated testing.

Problem

Many cancers are detected with a blood test by using biomarkers. However, for someone to schedule this blood test, usually other symptoms are accompanied to warrant the testing. However, ovarian cancer often presents with ambiguous symptoms such as cramping, frequent urination and irregular bleeding. These symptoms are already present in the general population at equal frequency, so they are not good indicators of the disease. In fact, ovarian cancer can present with no symptoms at all especially in the early stages. Additionally, the typical CA-125 blood test misses 50% of early ovarian cancer cases.

Catching the disease in early stages leads to best survival outcomes.

Catching the disease in early stages leads to best survival outcomes.

Innovation

Urine contains HE4 biomarker targets as well but are currently not used in the marketplace. To date, there is no affordable risk assessment test for women for use in the home. The current FDA cleared Ovarian Cancer risk tests, are $650 per test with blood taken from the arm. Our goal is to design a simple LFA test for a HE4 biomarker. This would allow women presenting symptoms, to afford to assess their risk of malignancy.

Funding

Engineering

With funding from Temple University‚Äôs BeYourOwnBoss Bowl award for 20K, we were able to partner with a lateral flow R&D lab, and  accelerate the development and optimization of lateral flow immunoassay with innovative ultra-sensitive nanoparticle probes, covalent binding chemistry and quantitative smartphone based reader technologies.

Absorbance of patient positive urine sample for ovarian cancer on left and negative patient urine sample on right.

Absorbance of patient positive urine sample for ovarian cancer on left and negative patient urine sample on right.

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