Speaker
Description
To personalize cancer radiation therapy, we must give the right dose and dose fractionation, at the right time, dynamically adapted, to best harness the radiobiological effects of radiation as well as synergy with the patient’s immune system. I present the latest developments in the mathematical and computational modelling in radiation oncology to develop digital twins – constructs that mimic the structure and behavior of the patient and the tumor to make predictions and inform decisions that realize value. I present different simple approaches to build predictive pipelines and how to integrate those into clinical decision making towards the concept of real-time adaptive personalized radiation treatments. I will discuss past, present, and future clinical trials of such model-guided treatments.
