October 7th 4pm CET (10am EST)
A persistent challenge in the field of immunotherapy is the fact that only a minority of patients respond, especially those therapies that rely on immune activation such as checkpoint inhibitors due to the complex and heterogeneous immune escape mechanisms which can develop in each patient. Therefore, the development of robust biomarkers, enabling rational patient selection and the design of precise combination therapies, is key for the continued success and improvement afforded by this valuable treatment.
The relevance to understand the entire tumor heterogeneity, its immune environment and contextual relationship requires the spatial quantification of different immune and tumor cells along with the genetic background of the individual cancer
How to apply multiplexing technologies to visualize biomarker candidates on a single slide with the assistance of machine intelligence including images digitization, computer-based image analysis, and further (molecular) data breakdown through machine learning tools
The availability of digital tools in histopathology allows interpreting the high-dimensional complexity of the spatial and immunological heterogeneity in tissue and integrating big (molecular) data to select the best and most effective treatment including combination and advanced therapies.
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