A hierarchical multiscale model for predicting the vascular behavior of blood-borne nanomedicines

In the field of nanomedicine, there is a pressing need for predictive, quantitative tools to rationally design and optimize carriers for therapeutic and imaging applications. Current nano/microfabrication technologies allow us to control a large number of parameters, including the size, shape surface properties, and mechanical stiffness. These design parameters affect the biophysical behavior of nanomedicines in terms of blood longevity, tissue deposition, drug release, contrast imaging amplification, and more. Thus, sophisticated, multiscale and multiphysics computational models are needed to predict the behavior of nanomedicines and guide the fabrication process toward optimal delivery systems. This work is a first step toward the realization of a fully integrated simulation platform. Here a computational model for describing blood flow in the microvasculature, particle transport, and molecular interaction with the vascular walls is presented. The model predicts particle deposition within a tumor microvasculature as a function of different design parameters. The simulations show that there is a complex interaction between the morphology of the vascular network, the particle surface and mechanical properties, and the particle deposition on the vascular walls. Specifically, the computational model shows and provides interpretation of how the stiffness affects significantly the probability of adhesion onto the vascular walls and the distribution along the network of blood-borne nanomedicines.