NCT07157618

Prospective Pathology Foundation Models

Development and Clinical Application of Deep Learning-Based Prospective Pathology Foundation Models

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 2,000 (estimated)
• Sponsor: Nanfang Hospital, Southern Medical University · Academic / Other
• Sex: All
• Age: 18 Years – 75 Years
• Healthy volunteers: Not accepted

Summary

Histopathology remains the gold standard for disease diagnosis, yet faces challenges including pathologist shortages and diagnostic model limitations. This underscores the critical need to develop deep learning-based pathology foundation models integrating prospective imaging and clinical data. Such models would enhance diagnostic accuracy and efficiency, enabling tumor grading, histo-molecular classification, and intelligent chemotherapy guidance - ultimately optimizing clinical workflows. However, a critical gap remains: the absence of prospectively validated, pan-disease pathology foundation models. Developing clinically validated models is therefore imperative.

Conditions

• Pancancer

Timeline

• Start date: 2025-08-28
• Primary completion: 2028-07-01
• Completion: 2028-08-01
• First posted: 2025-09-05
• Last updated: 2025-09-05

Locations

2 sites across 1 country: China