Nevia Bio Completes a M Seed Round to Build a Machine Learning-Enabled Platform for Early Detection of Women-Related Diseases

The funding will be used to support the company’s clinical trials in ovarian cancer, and to expand its pipeline to additional indications in women’s health space, in addition to enhancing the company’s data science capabilities.

Ovarian cancer is detected late in the vast majority of patients resulting in poor survival rates and high cost of care, due to lack of efficient early detection methods. Methods which are used today include ultrasound and blood tests presenting low sensitivity and specificity, resulting in diagnosis at late stages of the disease.

The Nevia groundbreaking platform decodes information from women’s vaginal secretions by applying Machine Learning tools to identify specific proprietary biomarkers signatures to detect the disease in its early and late stages. The use of an untapped biofluid and an innovative scientific approach will enable the detection of women’s related diseases, saving and improving women’s lives. Specifically, a simple vaginal swab will be collected from women, proprietary protein panel will be measured which will enable detection of ovarian cancer. 

Since commencing activity in 2020, Nevia has conducted clinical trials, established a biobank of more than 900 samples of vaginal secretions from women of different populations and diseases. This novel biobank is linked to a digital database and enables the company to apply Machine Learning tools on the data collected, and to identify specific features characterizing patients, which can be used to detect, and potentially manage the disease. 

With the support of additional funding and the engagement with healthcare oriented VCs, Nevia is now expanding its clinical collaborations in ovarian cancer and adding additional indications to its pipeline. Recently Nevia announced appointing Dr. Anula Jayasuriya as Chairperson of Board of Directors, which supports the company’s capabilities in its clinical and business development. 

“This is an important milestone for Nevia, and we are thrilled to announce this funding, which will support our mission of bringing innovative solutions into the women’s health growing market. Our investors joining these efforts show a growing interest in our sector and we are excited to pursue our continued clinical development. I thank the Nevia talented team for their high professionality, great teamwork and dedication. We are all engaged in bringing novel solutions to saving the lives of many women” said Dr. Inbal Zafir-Lavie, CEO and co-founder.

Hila Karah, Managing Partner at Pitagno HealthTech: “I’m excited to add Nevia to Pitango HealthTech portfolio. Neiva, a promising clinical stage development company, has a unique approach to the detection of early stage Ovarian Cancer, the devastating “silent killer”, as well as other women’s diseases. I believe that the excellent team, led by professional women, coupled with advanced science of proteomic and AI will bring a non invasive, easily applied tool to the diagnosis of many unmet women’s health issues. 

About Nevia

Nevia‘s platform is designed to decode biomarkers data from vaginal secretions, by the use of machine learning and data science strategies. These specific proprietary biomarkers enable identification of women’s diseases. The first proof of concept is detection of ovarian cancer using a simple vaginal swab. Nevia is backed by leading VCs Pitango HealthTech and ALIVE Israel HealthTech Fund and additional investors from the healthcare field, with a strong board of directors and advisory board. The Haifa based company is led by Dr. Inbal Zafir-Lavie and Dr. Shlomit Yehudai-Reshef, both experts in the life science field, with strong entrepreneurial and managerial skills

Media Contact:

Inbal Zafir-Lavie, PhD
CEO and Co-founder
[email protected]

Photo – https://mma.prnewswire.com/media/2196563/Nevia_Bio_team.jpg

SOURCE Nevia Bio

Originally published at https://www.prnewswire.com/news-releases/nevia-bio-completes-a-3m-seed-round-to-build-a-machine-learning-enabled-platform-for-early-detection-of-women-related-diseases-301912363.html
Images courtesy of PixaBay

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