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Evvy Secures $40 Million to Expand Women’s Health Research via Vaginal Microbiome Data

Evvy Secures $40 Million to Expand Women’s Health Research via Vaginal Microbiome Data

Evvy, a women’s health company specializing in at-home vaginal microbiome testing, announced on Tuesday that it has closed a $40 million Series B funding round led by Catalio Capital Management. Since its founding in 2021 by Priyanka Jain, Laine Bruzek, and Pita Navarro, the startup has developed what it describes as the world’s only at-home test certified by both the Clinical Laboratory Improvement Amendments (CLIA) and the College of American Pathologists’ Clinical Laboratory Improvement Program (CLEP).

The platform allows patients to collect swab samples at home and mail them to Evvy’s laboratory. There, the samples undergo metagenomic next-generation sequencing (mNGS). The resulting data is reviewed by clinicians registered on the Evvy platform and made available in the patient’s health portal. According to CEO and co-founder Priyanka Jain, results are delivered alongside a clinical diagnosis, interpretation, and actionable next steps, including personalized prescription care when necessary.

Today, Evvy reports serving over 100,000 patients and collaborating with 3,000 practitioners across the United States. The company states it has contributed to 15 peer-reviewed publications and abstracts, identified novel bacterial vaginosis (BV) subtypes, and discovered hundreds of previously uncatalogued vaginal microbiome genomes.

Jain emphasized that the funding will support Evvy’s broader mission to build a comprehensive dataset linking microbiome biology, symptoms, interventions, and health outcomes. She argued that current precision medicine efforts are flawed due to a lack of high-quality, representative data on female biology. “You can’t build precision medicine for women on data sets that never adequately measured female biology in the first place,” Jain said, noting that leading AI models often struggle to address women’s health questions accurately.

To bridge this gap, Evvy launched an AI assistant named EvvyAI in May. The tool translates collected microbiome data into real-time guidance for users and directs them to clinicians for issues requiring expert opinion. Jain believes that pairing AI with large-scale biological data can help identify patterns across molecular signals, hormones, treatments, and fertility outcomes that traditional medicine has难以 connect.

Beyond its core vaginal health focus, Evvy is making its first major expansion into the fertility space. The company is currently compiling data to link vaginal microbiomes to infertility, gynecological cancers, preterm birth, IVF success rates, and recurrent pregnancy loss. Last year, it initiated a prospective study utilizing its tests in IVF clinics.

Jain expressed hope that expanded data collection will help the medical community move away from dismissing unexplained conditions. “Women shouldn’t have to accept unexplained infertility, unexplained recurrence or unexplained symptoms as answers when what they often mean is that medicine hasn’t caught up to the data yet,” she said.

Long-term, Jain envisions Evvy creating a modern equivalent to the Pap smear—an at-home, non-invasive test providing regular, data-rich insights into infections, inflammation, PCOS, endometriosis, premenopause, and HPV progression. With other companies like JunoBio, TinyHealth, and Daye also entering the vaginal health space, Jain stated, “I don’t think we can wait for traditional research methods to catch up. I believe women, as patients, can be part of pushing the industry forward.”

3 responses to “Evvy Secures $40 Million to Expand Women’s Health Research via Vaginal Microbiome Data”

  1. Over 100,000 patients is impressive. I hope this leads to better answers for those suffering from unexplained infertility.

  2. I’m skeptical about at-home tests replacing clinical exams. How reliable is the self-collection process for accurate microbiome analysis?

  3. Finally, funding directed toward women’s health data gaps. This could revolutionize how we understand conditions like endometriosis.

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