Tumor biology doesn't care about our scoring bins. It is inherently continuous and highly complex—yet our standard companion diagnostics still force pathologists to reduce rich, predictive data into simplistic, visual estimations. When patient outcomes hang in the balance, can we really afford high interobserver variability? In this panel style workshop, we will explore how advanced computational algorithms are moving diagnostics beyond visual estimation by delivering highly reproducible, cell-level quantitative signals. More importantly, we will bridge the gap between scientific promise and laboratory reality. Our panel includes digital pathology pioneers, AI developers, and regulatory leaders who will give you the practical playbook on what it takes to actually deploy these advanced tools. We will discuss how computational CDx devices on the horizon will fundamentally alter the way we practice medicine and how pathology is at the very forefront of this revolution.

Learning Objectives:

1. Understand the shift from manual scoring to digital pathology solutions, including their key regulatory landscapes.
2. Identify limitations in traditional visual diagnostics and why computational models are essential for modern therapies.
3. Examine a real-world case study for computational pathology's clinical utility and emerging trends shaping oncology.