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Mathematical Oncology for Precision Radiation Therapy
Research Interest
The Grassberger Lab (or Mathematical Oncology for Precision Radiation Therapy Research Group) uses a variety of mathematical models and data analysis techniques to understand the response of tumors and normal tissue to radiation alone and in combination with other therapies. Our methods range from Markov Chain Monte Carlo simulations for lymphocyte dynamics in animal models to Deep Learning to predict hepatic toxicity using patient data. The clinical environment at University of Washington and Fred Hutch Cancer Center provides a unique environment for our research, with proton & neutron therapy, two different FLASH capable delivery systems and excellent collaborators in radiation oncology, medical oncology & immunology.
FLASH & ultra-high dose rate radiation
FLASH & ultra-high dose rate radiation
Using pre-clinical experiments we are studying the impact of FLASH on various endpoints, using two different FLASH capable proton delivery systems. FLASH is a high impact topic in radiation oncology, and given our unique experimental capabilities and collaborators we can explore novel questions in this field.
Re-Irradiation
Re-Irradiation
Re-Irradiation is an emerging problem of high clinical relevance in radiation oncology. Better systemic agents and the emerging role of radiation in metastatic disease are leading to increasing numbers of re-irradiation, with little clinical data to guide RT dose constraints and patient selection.
Immune Response to Radiotherapy
Immune Response to Radiotherapy
While animal experiments demonstrated that RT can synergize with immunotherapy, clinical trials have been negative up to now. We're studying the immune response in patients to understand how to make RT less immuno-suppressive (lymphocyte-sparing RT) and investigate biomarkers to personalize RT in the context of immunotherapy.
We have a wide range of interests - for a more complete selection of research areas see Research
Our research has been funded by
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