Amissa Health converts patient-reported menopause symptoms and wearable data into structured, longitudinal documentation for clinical review. This platform provides clinicians with visit-ready insights to support data-informed decision-making in midlife women's health. The system also generates real-world datasets for menopause research and discovery.
Funding
$510K 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
Collecting real-world data for Alzheimer's and women's health research is challenging due to difficulties in participant onboarding, adherence, and data management. Traditional methods often rely on infrequent clinician visits, leading to limited and potentially biased data.
Solution
Amissa Health provides a platform that streamlines wearable data collection and analysis for research and clinical use, focusing on Alzheimer's disease and women's health. The platform integrates with popular wearables like the Apple Watch to passively collect biometric and symptom data from study participants and patients. Amissa's solution facilitates remote monitoring of participant activity and adherence, generates actionable insights from complex data, and ensures compliance with IRB and NIH standards. By transforming wearable data into quantifiable metrics, Amissa enables researchers and clinicians to improve understanding, personalize care, and accelerate discoveries in key areas of focus.
Target Audience
The primary target audience includes researchers at universities, hospitals, and research institutions studying Alzheimer's disease and women's health, as well as clinicians focused on providing personalized care for women experiencing perimenopause.
Features
- Integration with Apple Watch for continuous, real-world data collection
- Remote participant monitoring and automated notifications to improve study adherence
- Machine learning models for predicting preclinical Alzheimer's disease based on wearable data
- Digital biomarkers for identifying perimenopause onset, symptom severity, and correlations with other health issues
- Tools for designing studies, onboarding participants, and sharing results
- Compliance support for IRB and NIH standards
- Secure, cloud-based platform for data storage and analysis