Cicada Health is developing a non-invasive salivary biosensing platform that captures continuous hormone data overnight through a sleep-time oral wearable. The research-stage technology aims to replace single-point lab draws with nightly hormone curves, revealing timing, slope, and variability that snapshots miss. The platform is currently in benchtop validation and is not yet available for sale or medical use.
Funding
Funding not disclosed
Founders
Product
Problem
Hormones are rhythmic, pulsatile, and context-dependent, yet standard measurement relies on single-point blood draws that capture just one moment in a moving signal. This fragmented approach—combining lab portals, apps, notes, and symptom logs—produces noisy, incomplete data that misses the timing, slope, and variability essential for understanding hormonal dynamics.
Solution
Cicada Health is developing a non-invasive salivary biosensing platform that captures continuous hormone insight during sleep via an oral wearable. The device repeatedly samples saliva across the night to construct a curve of hormone levels, revealing the shape of the signal rather than a single value. The platform is being validated through benchtop prototypes, saliva matrix testing, and a path toward a wearable form factor. This approach reduces the friction of repeated measurement while providing longitudinal data that could support research and eventually clinical insight.
Target Audience
Primary users are researchers and clinical investigators studying hormonal rhythms and dynamics, with future potential for individuals requiring longitudinal hormone monitoring.
Features
- Sleep-time oral wearable designed for hands-free, at-home hormone sampling
- Salivary biosensing technology targeting free dynamic hormone signals
- Nightly curve generation to capture signal shape, timing, and variability
- Benchtop prototype validation under controlled test conditions
- Saliva matrix testing to assess sensor performance in realistic biological environments
- Research-stage workflow designed for longitudinal data collection rather than single-point measurement