Melanin-aware ai platform for objective dermatology & clinical trials

Our mission is to provide standardized, data-driven clinical decision support that ensures equitable skin health outcomes across all populations. Methodology & Technology: Our platform utilizes a proprietary deep learning architecture optimized for the analysis of diverse skin tones. The methodology involves automated lesion quantification, boundary detection, and longitudinal severity tracking. Unlike traditional "black box" AI, our system provides structured data outputs designed for seamless API integration into existing EHR systems and Decentralized Clinical Trial (DCT) platforms. Proof to Date & Metrics: The platform has been validated through active pilot deployments and strategic institutional collaborations with Temple University and Worcester Polytechnic Institute (WPI). Key metrics from current validation include: Efficiency: Automated analysis and structured reporting in <3.8 seconds per image. Reliability: Inter-rater agreement scores of κ > 0.9, significantly reducing site-to-site variability. Traction: Active pilot activity with Clinical Research of Philadelphia and Dermatology Partners focusing on remote lesion severity tracking. Next Steps & Validation Plans: We are currently seeking co-development partners, CROs, and pharmaceutical organizations to initiate larger-scale validation studies within Phase II/III clinical trials. Our immediate validation goals include: Head-to-head validation of automated scoring against gold-standard manual assessments (e.g., PASI/EASI) in melanin-rich populations. Expansion of our longitudinal dataset to include rare inflammatory conditions. Pilot engagements with teledermatology to evaluate clinical throughput improvements.