Angela Jarrett

I have only recently joined the Center for Computational Oncology as a J.T. Oden Fellow. My research will be focused on developing mathematical formulations of the effects of various therapies on cell proliferation. As a graduate student, my research focused on understanding the interactions between the immune system and persistent infections, such as Methicillin-resistant Staphylococcus aureus (MRSA). (Please see Figure.) Using different mathematical analyses in concert with experimental data, specifically uncertainty quantification, sensitivity analysis, and data assimilation, we worked not only to assess our models' structures but also to track down the driving interactions of the immune system that resulted in both clearance and persistence of infections. We hope to apply similar techniques to rigorously study cell proliferation in cancer models to help further develop our ability to predict the response of tumors to treatment, including immunotherapy.

A summary diagram of the interactions of uncertainty quantification (UQ), sensitivity analysis (SA), and data assimilation (DA) with a few of the important factors to be considered when pursuing model refinement/development with these analyses. In practice, these methods can be used separately, but to optimize the evolution of a model, they can be applied synergistically—where the results from one influences and informs the applications of the others. /blockquote]