Modelling, inference and simulation of personalized breast cancer therapy

Relatore

Arnoldo Frigessi - Oslo Centre for Biostatistics and EpidemiologyUniversity of Oslo (Norway)

Abstract
Mathematical modelling and simulation have emerged as a potentially powerful, time- and cost effective approach to personalised cancer treatment. In order to predict the effect of a therapeutic regimen for an individual patient, it is necessary to initialize and to parametrize the model so to mirror exactly this patient's tumour. I will present a comprehensive approach to model and simulate a breast tumor treated by two different chemotherapies in combination and not.  In the multiscale model we represent individual tumour and normal cells, with their cell cycle and others intracellular processes (depending on key molecular characteristics), the formation of blood vessels and their disruption, extracellular processes, as the diffusion of oxygen, drugs and important molecules (including VEGF which modulates vascular dynamics) . The model is informed by data estimated from routinely acquired measurements of the patient's tumour, including histopathology, imaging, and molecular profiling. We implemented a computer system which simulates a cross-section of the tumour under a 12 weeks therapy regimen. We show how the model is able to reproduce patients from a clinical trial, both responders and not. We show by scenario simulation, that other drug regimens might have led to a different outcome. Approximate Bayesian Computation (ABC) is used to estimate some of the parameters.

Organizzatore

Angela Montanari