SkinAtlas™ Platform
A New Era of Predictive Skin Analytics
A dataset built for translational and clinical development.
SkinAtlas™ is an expansive repository of skin data comprised of multiple streams—molecular data derived from the dermal biomarker patch, imaging, and patient metadata. It can include samples from multiple skin diseases and skin cancers, and longitudinal samples across time from the same individual—ideal for drug development workflows.
What’s Inside:
- Molecular profiles from patch-based sampling (e.g., transcriptomic signatures).
- Imaging data to connect phenotype with biology.
- Clinical and patient metadata to support stratification and subgroup discovery.
- Longitudinal sampling to track biology over time.
How It's Used
AI/ML models can be trained on labeled phenotypes (e.g., diseased vs. normal) and then applied to new samples to classify, stratify, or predict outcomes—such as response to therapy.
Common Partner Use Cases
Stratification and selection of patients based on gene expression profiles
Biomarker identification of specific diseases and disease subsets
Tracking and prediction of drug response (before/ after dosing)
New target identification
Development of complementary and companion diagnostics
Disease characterization and phenotyping
Built to Scale
The same core platform can support multiple sectors and indications—where the skin is a target organ or a surrogate window into systemic immune biology—by enabling consistent sampling and analytics.