درباره این اپیزود
Can a treatment decision depend on whether one pathologist sees 45% biomarker positivity and another sees 55%?
Visual immunohistochemistry scoring helped establish precision oncology. But as targeted therapies become more sensitive to subtle biological differences, categorical scores such as 0, 1+, 2+, and 3+ may no longer capture the information needed to identify the right patients.
In this episode, I speak with three Roche experts:
- Gordana Juric-Sekhar, MD, anatomic pathologist
- Saleh Miri, PhD, Director of Digital Pathology AI Algorithms
- Purvi Gaglani, Regulatory Affairs Lead for Digital Pathology
We discuss how computational pathology is changing companion diagnostics by moving biomarker assessment from visual estimates to continuous, cell-level measurements.
The conversation examines the limitations of manual IHC scoring, including interobserver variability, intraobserver variability, visual fatigue, borderline cases, tumor heterogeneity, and the inability of the human eye to measure complex spatial relationships.
Using TROP2 scoring in advanced non-small cell lung cancer as an example, Saleh explains the normalized membrane ratio. This computational metric measures protein expression at the cell membrane relative to total expression within the cell—something that can’t be reproduced through conventional visual scoring.
We also clarify the difference between computer-assisted scoring and a fully computational companion diagnostic. An assisted tool supports a pathologist’s visual interpretation. A computational CDx generates the biomarker measurement through algorithmic, cell-level analysis.
That doesn’t remove the pathologist.
Pathologists remain responsible for evaluating tissue quality, staining quality, scan quality, tumor selection, image analysis results, and the final clinical context. They can reject a stain, request a rescan, exclude inappropriate regions, question the result, or seek a second opinion.
The episode also examines the regulatory implications of computational companion diagnostics. Instead of evaluating a single IHC assay, regulators may need to assess the complete system - from tissue preparation and staining to scanning, image management, algorithmic analysis, display, and the final biomarker report.
Finally, we discuss what laboratories will need to implement these workflows, including validated scanning infrastructure, cybersecurity, tighter preanalytical process control, and training that helps pathologists interpret continuous computational measurements.
Episode Highlights
- 00:00 — Pathologists remain central to computational CDx
Why computational tools provide more precise measurements without replacing pathology expertise. - 01:09 — Why companion diagnostics are changing
Visual IHC scoring helped launch precision oncology, but the model is approaching its limits. - 04:53 — The current companion diagnostic landscape
How IHC, next-generation sequencing, liquid biopsy, and visual biomarker scoring are used today. - 07:01 — The mathematical burden placed on the human eye
Why manually assessing tens of thousands of tumor cells requires pathologists to estimate rather than calculate. - 08:39 — The borderline patient dilemma
A digital tool can distinguish measurements such as 74% and 76%, while that difference is difficult to reproduce visually. - 09:27 — Why spatial context matters
Computational pathology can measure biomarker heterogeneity, clustering, and relationships between tumor and immune cells. - 12:17 — Where manual scoring reaches its limits
Interobserver variability, intraobserver variability, fatigue, staining interpretation, and heterogeneous tumors. - 18:29 — Moving from judgment calls to quantified measurements
Why the next stage of precision oncology requires information beyond human visual perception. - 19:14 — Computer-assisted scoring versus computational CDx
The important distinction between helping a pathologist calculate an existing score and generating a new algorithmic measurement. - 23:22 — Computational pathology and decentralized workflows
How digital images can support remote review, access to expertise, and second opinions. - 27:48 — Why therapies require higher-resolution biomarkers
Modern targeted treatments may respond to biological differences that categorical scoring can’t capture. - 32:09 — TROP2 in advanced non-small cell lung cancer
The episode’s example of a biomarker requiring computational measurement. - 33:26 — Understanding the normalized membrane ratio
How the algorithm measures membrane expression relative to total protein expression at the individual-cell level. - 35:46 — Working with regulators on a new diagnostic model
Purvi discusses global health authority engagement and the FDA Breakthrough Device Designation. - 38:33 — The computational CDx as a system of systems
Why staining, scanning, image management, algorithms, displays, and reporting must be evaluated together. - 40:11 — Changes to validated workflow components
How using a different scanner, monitor, or other component could fall outside the defined device configuration. - 43:30 — Why computational pathology is becoming necessary
Continuous measurements can reveal biomarker-treatment relationships that may remain hidden within categorical scores. - 49:12 — The pathologist’s role in the workflow
Reviewing sample, staining, scan, image, algorithmic analysis, and the final biomarker result. - 53:39 — Digital second opinions
How image management systems can simplify collaboration without physically transporting glass slides. - 56:43 — What laboratories need to prepare
Validated infrastructure, cybersecurity, preanalytical control, training, and digital pathology literacy. - 58:49 — Learning to interpret computational results
The shift from visually estimated categories to continuous, quantitative biomarker measurements.
Resources Mentioned
- Full discussion on YouTube: https://youtu.be/oKW1xC6TTZg
Listen to the full discussion to understand how computational pathology could change companion diagnostics—and what pathologists, laboratories, and regulators must prepare for next.
