Speaker
Description
The words “resistance” and “relapse” are used interchangeably, and statements such as “treatment resistance remains a critical limitation to the success of cancer therapy” are flooding the introductions of research papers in (mathematical) oncology. Is this practice correct and appropriate? Does it matter in the clinic?
In this talk, I will contrast my preclinical research studies in targeted therapy (Non-Small Cell Lung Cancer) and radioimmunology (HPV+ Head & Neck cancer) to demonstrate that the distinction between resistance and relapse is not just semantics. A clear, measurable definition of resistant disease and how it’s different from therapy failure can change the disease management plan and outcomes.
Central to my message are the definitions of the terms “treatment resistance” and “treatment failure”. I will show how different mathematical and statistical models skew our perception of cancer treatment modeling, and what can be done to address such limitations. My conclusion is the word of caution and advocacy for a combination - a multiverse - of imperfect, yet complementary models to address the most urgent clinical needs in oncology.
