- uPath PD-L1 (SP263) image analysis uses automated pre-computing and one-click scoring to enable quicker and accurate detection and measurement of tumour cell staining positivity
- Roche advances personalised healthcare with development of image analysis algorithms using artificial intelligence
- Faster, more accurate diagnoses are critical with non-small cell lung cancer, which accounts for about 85 percent of all lung cancer cases
Basel, June 26, 2020 - Roche (SIX: RO, ROG; OTCQX: RHHBY) today announced the CE-IVD launch of its automated digital pathology algorithm, the uPath PD-L1 (SP263) image analysis for non-small cell lung cancer (NSCLC). The algorithm provides pathologists with automated assessments of scanned slide images that are objective and reproducible and have the potential to aid diagnosis and, ultimately, targeted treatment options for patients.
Validated on the VENTANA PD-L1 (SP263) Assay, the algorithm is ready-to-use and integrated within the Roche uPath enterprise software, a universal digital platform for case management, collaboration and reporting. This algorithm will help pathologists to quickly determine whether tumours are positive for the PD-L1 biomarker, highlighting positively and negatively stained tumour cells with a clear visual overlay for easy reference. Patients with tumours that are positive for the PD-L1 biomarker may be eligible for targeted treatment.
Improving diagnostic consistency and certainty is crucial in providing faster, higher-quality and more accurate diagnoses to cancer patients,
said Thomas Schinecker, CEO, Roche Diagnostics.
Our uPath PD-L1 (SP263) image analysis for non-small cell lung cancer is the first next-generation CE-IVD PD-L1 algorithm to the clinical market. It expands on our growing digital pathology suite for VENTANA assays that aid physicians in providing the most accurate treatment decisions for patients with the most common type of lung cancer.
The algorithm’s whole-slide automated analysis uses artificial intelligence to provide, with one-click, an actionable assessment of the scanned slide images that is objective and reproducible. The uPath PD-L1 (SP263) image analysis (NSCLC) algorithm for digital pathology is for use on uPath enterprise software.