uPath PD-L1 (SP263) image analysis, NSCLC (CE-IVD)

Ready-to-use, fast, consistent and automated algorithm for clinical decision support

Thumbnail view of Roche uPath PD-L1 (SP263) whole slide image analysis, NSCLC (CE-IVD)

uPath image analysis algorithms

An intelligent and insightful digital pathology solution requires image analysis tools that empower pathologists to confidently and objectively assess whole tissue slide images. The algorithm is indicated for use as an aid in identifying patients for treatment with therapies with the ≥ 50% PD-L1 TC positivity cutoff in accordance with the approved therapeutic product labeling.


Roche uPath PD-L1 (SP263) image analysis, NSCLC features
  • Pathologist-trained artificial intelligence algorithm: Resulting in objective and reproducible scoring of VENTANA DP 200 slide scanner slide images stained with the VENTANA PD-L1 (SP263) Assay
  • Integrated into the Roche uPath enterprise software: Seamless viewing, aligning and syncing functionality, sharing capabilities, and reporting
  • Whole slide analysis (WSA): Automated pre-computing of the slide image prior to pathologist assessment, providing fast results for user-defined regions of interest (ROI)
  • Quick automated scoring: Quickly calculates PD-L1 (SP263) tumor cell staining positivity, aiding potential treatment strategies at the ≥ 50% cutoff
  • Clear visual overlay: Highlighting positively and negatively stained tumor cells for easy reference

Integrated and ready-to-use

Validated on the VENTANA PD-L1 (SP263) Assay, for use within Roche uPath enterprise software.

Quick and automated

Pathologist-trained artificial intelligence algorithm for quick image analysis.

Accurate, consistent and confident

Actionable assessment of scanned slide images that are objective and reproducible, aiding in informing on potential treatment strategies.

Reference: uPath PD-L1 (SP263) image analysis for Non-Small Cell Lung Cancer Algorithm Guide   

uPath PD-L1 (SP263) image analysis, NSCLC (CE-IVD) is not yet commercially avaiable in Sweden