Digital Pathology: Slides, AI, & Challenges

Pathology has progressed from glass slides to AI-driven digital diagnostics, promising to transform disease detection while facing adoption and market challenges

Bo Wang, Head of Biomedical AI at Xaira Therapeutics, puts it simply: “Pathology is the cornerstone of diagnosis, especially when it comes to cancer.” While continuously developing since ancient times, by the late 2000s the pathology workflow with glass slides, physical archives, and in-person consultations couldn’t keep pace with modern demands. It slowed diagnoses, made collaboration cumbersome, and limited access. High-resolution images were massive—often gigabytes each—and required costly whole-slide imaging (WSI) systems, which lacked FDA clearance for years.

By the mid-2010s, that changed. Advances in WSI, falling storage costs, and FDA approval sparked the rise of digital pathology—scanning slides for easier sharing, annotation, and remote consultation. Computationally minded researchers quickly recognized the value of these datasets, and startups emerged, often spun out of collaborations with hospitals and labs holding vast archives of digitized slides.

In this article: How it started — How it’s going — Time for Foundation Models — The Market Players — Not Only Cancer — Current State of the Industry