Towards a digital twin of magnetic nanoparticle-mediated cancer therapy
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To overcome deficiencies of conventional cancer therapy, magnetic nanoparticle-based drugs have emerged as a promising approach to achieve more specific tumor targeting. Alternatively, cells can be loaded with magnetic nanoparticles and targeted to the tumor using an externally applied magnetic field. Such personalized immunotherapy with T cells has achieved impressive clinical responses in several previously untreatable hematological tumors. However, to date, the parameters required for successfully accumulating nanoparticles or magnetized cells in the tumor tissue are poorly understood. We, therefore, present steps and challenges towards a digital twin of magnetic nanoparticle-mediated cancer therapy. This includes a computational model for the magnetic targeting of nanoparticles. We show how a physics-based model of the transport of magnetic nanoparticles in an external magnetic field can be integrated with a multiphase tumor growth model based on porous media theory. Additionally, we show how to assess the sensitivity of the model output to the input parameters with a methodologically sound global sensitivity analysis and how a Bayesian calibration allows us to consistently integrate our computational model with experimental data. Model development and in vitro or in vivo experiments must complement each other in a feedback loop to develop a digital twin of nanoparticle-mediated cancer therapy, which will enable more personalized treatment strategies.
