Proscia to Broaden Pathology AI Capabilities with Biomarker Detection for Skin Tissue
Expanding the industry’s most comprehensive portfolio of AI applications
PHILADELPHIA and PARIS, Oct. 15, 2025 (GLOBE NEWSWIRE) -- Proscia®, a pathology AI company, will add AI biomarker detection for skin tissue to its Concentriq® software platform, empowering pathologists to drive efficiency and precision. Powered by Primaa, Cleo Skin* will strengthen Concentriq's lead in offering the industry’s broadest portfolio of AI solutions on a single platform.
Dermatopathology is among the most diverse areas of pathology, with more than 500 distinct classifications.1 This variation is compounded by relatively high pathologist disagreement in some instances. While overall inter-observer concordance is estimated at 90–95%, certain distinctions, such as differentiating malignant melanoma from benign melanocytic nevi, can prove challenging.2
“This addition underscores our commitment to making AI practical where it can have the greatest impact,” said David West, Proscia’s CEO. “By expanding our AI offerings in skin, we will enable pathologists to deliver faster, more consistent results in one of the most challenging areas of pathology, all within the workflows they trust.”
The AI biomarker detection application automatically identifies all potential mitotic objects and mitotic hotspots, as well as perineural invasion, which are key indicators of various skin diseases. In combination with lesion classification, including melanoma, basal cell carcinoma, and squamous cell carcinoma, these capabilities can help drive efficiency. The application also measures tumor margins and lesion dimensions, further driving precise and comprehensive evaluation.
“We are proud to bring the capabilities of Cleo Skin to Concentriq,” said Fanny Sockeel, Primaa’s CEO. “We are not only offering dermatopathologists the chance to deliver fast and confident results but also giving laboratories even more reason to advance their AI journey on Proscia’s platform.”
Along with today’s announcement, Primaa will join the Proscia Ready partner alliance. Proscia Ready is made up of solution providers helping life sciences organizations and diagnostic laboratories accelerate the scaled adoption of digital pathology with confidence through a comprehensive approach.
To learn more, join Proscia's Access25 virtual event on October 28th at 11:30AM.
*This application is not intended for diagnostic use with Concentriq. Contact the original manufacturer for details about indications for use in your region.
About Proscia
Proscia is rewiring pathology for precision medicine to improve patient outcomes. Its software, AI, and real-world data fuel the development and use of novel therapies and diagnostics, driving the fight against humanity’s most challenging diseases, like cancer. 16 of the top 20 pharmaceutical companies and a global laboratory network on track to deliver more than 8 million diagnoses annually rely on Proscia’s solutions each day. For more information, visit proscia.com and follow Proscia on LinkedIn and X.
About Primaa
Primaa develops artificial intelligence software capable of detecting various cancer biomarkers. The Cleo Breast (for breast) and Cleo Skin (for skin) tools support physicians in making their diagnoses, providing greater reliability and optimizing the time required for examination analysis. Co-founded in 2018 by Marie Sockeel, pathologist, together with Fanny Sockeel and Stéphane Sockeel, the company counts 25 employees. To learn more, visit primaalab.com.
Contact:
Leah Horvat
Marketing Coordinator, Proscia
leah.horvat@proscia.com
856.625.6144
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1 Feramisco, J. D., Sadreyev, R. I., Murray, M. L., Grishin, N. V. & Tsao, H. Phenotypic and genotypic analyses of genetic skin disease through the online mendelian inheritance in man (omim) database. J. Investig. Dermatol. 129, 2628–2636 (2009).
2 Ianni, J.D., Soans, R.E., Sankarapandian, S. et al. Tailored for Real-World: A Whole Slide Image Classification System Validated on Uncurated Multi-Site Data Emulating the Prospective Pathology Workload. Sci Rep 10, 3217 (2020). https://doi.org/10.1038/s41598-020-59985-2
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