Senescope
Senescope is an AI-powered platform that detects senescence-associated nuclear morphology in standard clinical samples, including blood smears, biopsies, and biofluids. The technology applies deep learning to routine images to quantify aging and chronic disease risk, with published validation in Nature Aging, The Lancet Digital Health, and Breast Cancer Research. The platform requires no consumables and integrates into existing clinical workflows.
- Healthcare Technology
- Digital Health
- Artificial Intelligence
- Data & Analytics
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Traditional disease risk assessment often relies on invasive procedures, expensive imaging, or biomarkers that only become detectable after symptoms emerge. Clinicians lack tools to quantify the underlying biological aging processes—such as cellular senescence—that precede chronic diseases and cancer, limiting opportunities for early intervention and personalized treatment planning.
Solution
Senescope provides an AI-powered platform that detects senescence-associated nuclear morphology in standard clinical samples, including blood smears, biopsies, and biofluids. The technology applies deep learning to routine images, converting subtle cellular changes into quantitative risk readouts for aging and chronic disease. By using samples already collected in standard care, the platform requires no consumables and integrates into existing clinical workflows. The resulting insights enable clinicians to assess future disease risk—such as breast cancer or COPD—and monitor treatment response, making advanced diagnostics broadly accessible.
Target Audience
Primary customers are clinicians and healthcare providers seeking earlier disease detection and risk stratification, as well as researchers conducting aging and chronic disease studies.
Features
- Deep learning models that quantify senescence-associated nuclear morphology from standard tissue and biofluid images
- Applications validated in peer-reviewed studies including Nature Aging (2022, 2024), The Lancet Digital Health (2024), Breast Cancer Research (2025), and GeroScience (2025)
- Risk prediction for future breast cancer from healthy donor breast tissue and benign breast disease biopsies
- Senescence assessment in sputum samples within a randomized trial of nicotinamide riboside for COPD
- No consumable required—works with routine clinical material including biopsies, blood smears, and biofluids
- Automated, scalable analysis that rapidly quantifies biomarkers of aging and disease