Expanding the Role of Quantitative Continuous Scoring and the Future of Computational Pathology

This final segment broadens the discussion beyond TROP2 to explore the broader implications of QCS and computational pathology for biomarker development and clinical practice. Dr. Wistuba explains that QCS represents a platform capable of objectively quantifying protein expression across multiple cellular compartments, including membrane, cytoplasmic, nuclear, and immune cell populations, using digital image analysis. This flexibility creates opportunities to apply the approach to a wide range of biomarkers, including additional ADC targets, immune markers, and even routine diagnostic proteins.

The discussion highlights the growing challenge of tissue stewardship in lung cancer, where limited biopsy material must support an expanding list of diagnostic and predictive tests. Computational analysis may help maximize information from small specimens and could facilitate future approaches such as multiplex IHC, which would require digital and algorithm-based interpretation. Early evidence suggesting that computational assessment of markers such as PD-L1 can perform comparably to traditional manual scoring further supports the potential clinical value of this approach.

Dr. Santos describes QCS as a potential “game changer” for how protein expression is interpreted across oncology, emphasizing the role of artificial intelligence in enabling more precise and reproducible biomarker evaluation. Both experts express strong enthusiasm for the broader application of this technology across tumor types and targets.

In closing, Dr. Wistuba underscores the central takeaway of the program: TROP2 NMR represents an early example of a new generation of computationally derived predictive biomarkers that could improve patient selection for targeted therapies. However, the ultimate impact will depend on prospective clinical validation and the ability to implement these tools consistently across laboratories. If successful, computational pathology may usher in a new era of digital, quantitative diagnostics that more directly links tumor biology to treatment decisions.