Introducing Paige.AI

Today I am proud to announce that Breyer Capital is leading the Series A financing of Paige:AI, a new company revolutionizing clinical diagnosis and treatment in oncology through the use of artificial intelligence. Paige.AI has signed an exclusive license with Memorial Sloan Kettering Cancer Center to gain access to its intellectual property in computational pathology, as well as exclusive rights to its library of 25 million pathology slides.

Pathology is at the cornerstone of most cancer diagnoses, yet most pathologic diagnoses rely on manual, subjective processes developed ages ago. While slide digitization has been around for over a decade, it has failed to gain traction because digital slides alone have done little to improve workflows.

Computational pathology will provide the missing link in the adoption of digital pathology, moving this vital field forward with support tools to help pathologists make decisions with greater speed, accuracy, objectivity and reproducibility — and at a lower cost. Armed with AI enabled systems, pathologists will spend less time compiling data and more time interpreting data. They will better understand how a patient’s diagnosis affects treatment and recovery.

In 2018 PAIGE’s slide viewer was rolled out institution-wide at Memorial Sloan Kettering Cancer Center and is the single entry point for pathologists and cancer researchers.

I believe we are entering the market with three core assets: better data, better expertise, and better people.

Data: Successful AI systems rely on a massive amount of data to train robust, reproducible algorithms. Paige.AI has a partnership with Memorial Sloan Kettering Cancer Center (MSK) and has exclusive access to all of MSK’s intellectual property in the field of computational pathology as well as exclusive rights to their library of 25 million pathology slides.

Domain Expertise: Raw image data is not enough to excel in complex pathology tasks. A successful AI must be trained on the highest quality (clinician-generated) domain-specific annotations. Paige.AI is innovating the annotation process, not only by developing dedicated annotation tools, but also by incorporating de-identified clinical data, treatment data, genomic analysis and survival data into comprehensive deep learning models.

Exceptional Talent: Paige.AI’s ML team of PhDs and computation experts is led by the founding father of Computational Pathology: Thomas Fuchs. Fuchs is the director of Computational Pathology in The Warren Alpert Center for Digital and Computational Pathology at MSK, and professor at Weill-Cornell, where he teaches Machine Learning. Dr. Fuchs published the first Computational Pathology paper in 2008, a review of the field in 2011 and more than 90 publications in machine learning and medicine.

Globally, we are taking a major step forward in harnessing machine learning and more fully realizing its promise for cancer diagnosis and treatment. Paige.AI is poised to become a powerhouse in computational pathology and an undisputed leader among thousands of healthcare AI competitors.