Lung PD-L1 AI: Development and Validation of an Automated PD-L1 Tumor Proportion Scoring Algorithm in Non-Small Cell Lung Cancer

Manual tumor proportion scoring of PD-L1 expression is the current gold standard for clinical reporting in non-small cell lung cancer (NSCLC) cases. However, scoring challenges include the existence of multiple PD-L1 assays, intra-tumor heterogeneity and inter-observer variability which may lead to variability in PD-L1 scoring and suboptimal treatment decisions.

Join Indica Labs in this 1-hour webinar to learn about the development and validation of Lung PD-L1 AI, an automated PD-L1 Tumor Proportion Scoring algorithm for NSCLC samples. The webinar will also include a demonstration of how the algorithm seamlessly integrates into the HALO AP® diagnostic digital pathology platform to assist scoring PD-L1 in NSCLC cases.

• Understand the current challenges with PD-L1 scoring in NSCLC
• Learn how Lung PD-L1 AI was developed and validated
• Learn how to deploy Lung PD-L1 AI in HALO AP to support PD-L1 scoring and increase scoring consistency

Dr. David Dorward

Consultant Thoracic Pathologist

Royal Infirmary of Edinburgh

Dr. David Dorward is a Consultant Pathologist who specializes in the diagnosis and molecular profiling of lung cancer. His research has predominantly focused on understanding lung inflammation in response to infection, injury and cancer but he also has a growing interest in the application of digital pathology in clinical practice. As well as exploring the opportunities provided by integrating digital reporting into routine histopathology practice, David has been collaborating with Indica on the development of a number of AI tools. He is currently Digital Pathology lead for both NHS Lothian and the Scottish Pathology Network (SPAN).

Daniela Rodrigues

Imaging Scientist, AI Diagnostics

Indica Labs

Daniela Rodrigues earned her degree in Pathologic, Cytologic, and Thanatological Anatomy from the Polytechnic Institute of Porto. She received her master’s in quality Control from the Faculty of Pharmacy in 2018, undertook a specialization in Medical Informatics from the Faculty of Medicine of the University of Porto in 2021 and recently completed a post-graduation course in Medical Statistics. She previously worked as a research fellow in Neuroscience and Toxicology and grew her skill set in microscopy and digital pathology-based image analysis while working at the microscopy core facility at i3S – Instituto de Investigação e Inovação em Saúde, University of Porto, where she provided image analysis support to several digital pathology projects. Currently, she works as an Imaging Scientist in the AI Diagnostics group managing the development of multiple AI-based products. 

• 10+ best pathology resources for tissue image analysis
• Why and how should pathologists keep up with AI? w/ David Harrison, University of St. Andrews
• Virtual H&E. How Instapath uses optical sectioning microscopy to accelerate pathology diagnosis w/ David Tulman, Instapath
• What’s up in Digital Pathology – a crossover podcast with Beyond the Scope
• Is this the year of AI in pathology? And what about ChatGPT? A crossover podcast with Beyond the Scope.