Nevia utilizes a machine learning platform to analyze vaginal secretions for the early detection of diseases such as ovarian cancer, which is often diagnosed at late stages. By enabling timely diagnosis, Nevia aims to improve survival rates and empower women to take control of their health.
Funding
$5.1M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Ovarian cancer is often diagnosed at late stages, leading to low survival rates due to the lack of effective early-detection methods. Current diagnostic approaches often fail to identify the disease in its nascent stages, resulting in delayed treatment and poorer outcomes for women. There is a critical need for innovative technologies that can enable earlier and more accurate detection of ovarian cancer.
Solution
Nevia is developing a machine-learning platform that analyzes vaginal secretions to detect biomarkers indicative of early-stage ovarian cancer. The platform utilizes a simple vaginal swab to collect samples, which are then analyzed to identify specific biomarkers associated with the disease. Nevia's machine-learning algorithms process the biomarker data to identify patients at risk, enabling timely diagnosis and intervention. By providing an early-detection solution, Nevia aims to improve survival rates and empower women to proactively manage their health.
Target Audience
Nevia's primary target audience includes women's health clinics, gynecologists, and healthcare providers focused on women's health and early cancer detection.
Features
- Vaginal swab sample collection for biomarker analysis
- Machine-learning algorithms for data processing and patient identification
- Biomarker identification for early-stage ovarian cancer detection