From Fitting the Average to Fitting the Individual: A Cautionary Tale for Mathematical Modelers.

ABSTRACT: An outstanding challenge in the clinical care of cancer is moving from a one-size-fits-all approach that relies on population-level statistics towards personalized therapeutic design. Mathematical modeling is a powerful tool in treatment personalization, as it allows for the incorporation of patient-specific data so that treatment can be tailor-designed to the individual. Herein, we work with a mathematical model of murine cancer immunotherapy that has been previously-validated against the average of an experimental dataset. We ask the question: what happens if we try to use this same model to perform personalized fits, and therefore make individualized treatment recommendations? Typically, this would be done by choosing a single fitting methodology, and a single cost function, identifying

SUBMITTER: Luo MC 

PROVIDER: S-EPMC9097280 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature