- The “omics” approach have given us countless methods to evaluate subsets of patient response profiles, but we still don’t have a reliable predictive test for the vast majority of patients. We need to go back to the foundation and study the immune system and tumor tissue to develop better predictive tests to improve patient response.
- There is excitement about the application of AI to the pathology space to advance the understanding of complex immune responses in cancer cells and serve as a guided tool for pathologists. Flagship is excited to apply these advancements in machine learning and AI to our digital analysis tools.
- Multiplexing, combination studies and the development of predictive biomarkers beyond PD-LI were consistent themes. Drug developers are struggling with how to translate the scores of data produced by these approaches into actionable insight. Flagship has developed tools to translate these complex data sets into actionable approaches.
Flagship’s cTA platform applies computational tissue analysis to data and images to deliver an immune response profile with sufficient breadth, depth and speed to support predictive medicine approaches for your drug.
We were proud to present four scientific posters at AACR demonstrating how our cTA platform delivers this actionable insight. Please follow these links for full poster content posted on Flagship’s Resources page.
- Analysis of Multiplexed Immunotherapy Targets and Secreted Ligands Using Computational Tumor Microenvironment Profiling, presented Monday, April 16, 2018
- Computational Analysis of Multiplexed Immunohistochemistry for Understanding Immune Profiles in Clinical Biopsy Samples, presented Monday, April 16, 2018
- Comparison of Multiplexed Imaging Mass Cytometry with Monoplex Immunohistochemistry in FFPE Tissue, presented Tuesday, April 17, 2018
- A Methodology for Designing and Validating Computational Pathology Scores for Immune Cell Clustering in Tumor Biopsy Samples, presented Wednesday, April 18, 2018