In this webinar, Aditya Pratapa and Lorcan Sherry present a new workflow for analyzing multiplex immunoflurescence images.
Spatial Signatures are a new class of highly predictive biomarkers that measure the interactions and cellular densities of tumor and immune cells that compose the tumor microenvironment. Based on multiplex immunofluorescence, spatial signatures provide a deeper understanding of complex interactions between tumors and the immune system, enabling improved patient stratification for immunotherapies. A significant hurdle to date has been in developing a data analysis workflow that is straightforward and user-friendly to transform the data rich images into meaningful quantitative spatial signatures.
In this webinar, Aditya and Lorcan review the key features of the new PhenoImager HT 2.0 data analysis workflow. This workflow introduces a simplified framework from scanning to analyzing spectrally unmixed multiplex immunofluorescence images generated on the PhenoImager HT platform. The ready-to-analyze data can be directly imported into image analysis software such as Visiopharm. This presentation covers key aspects of data analysis elements such as image QC, segmentation, phenotyping, and verification – all essential for creating outputs that support the development of a spatial signature.
Key Topics Include:
- Understand Akoya’s new HT 2.0 data analysis workflow
- The challenges in multiplex immunofluorescence analysis and the use of AI and cell lineage segmentation considerations
- Explore OracleBio’s image analysis workflow incorporating Visiopharm
- Evaluation of analysis data to facilitate spatial profiling and interpretation
- Categories: Cancer & Oncology Research, Cell & Molecular Biology, Drug Discovery & Development, Microbiology & Immunology, Microscopy, Preclinical Imaging
- Tags: cancer immunotherapy, image analysis, immuno-oncology, immunofluorescence (IF), spatial biology, tumor microenvironment (TME)
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Chief Scientific Officer
Senior Data Scientist