Background: Understanding the transport of nanoparticles within blood vessels and their distribution in tumor tissues is crucial for the successful implementation of nanotechnological strategies in clinical practice. Although numerous studies have examined nanoparticle transport in blood flow, none have comprehensively investigated all the sequential steps a nanoparticle must undergo prior to internalization by target cells. Methods: A computational framework was developed in COMSOL Multiphysics to simulate nanoparticle (NP) transport from systemic administration through to tumor cell internalization. The model integrates three coupled stages: (1) NP movement within a non-Newtonian blood flow; (2) trans-endothelial transport; and (3) NP motion within the tumor stroma, incorporating affinity forces to capture ligand–receptor interactions. The tumor geometry was reconstructed, including cancer cells and fibroblasts, to reproduce physiological porosity. Multiple case studies were conducted to evaluate the impact of particle density, injection velocity, and size on NP biodistribution. Results: The computational model effectively simulates nanoparticle transport across all stages. Notably, it is the first model in the literature to incorporate the affinity of functionalized nanoparticles, which facilitates ligand–receptor interactions for targeted delivery. Simulation outcomes indicate that a low Stokes number is critical for ensuring a higher percentage of particles reach the end of the capillary network. Furthermore, surface modification of nanoparticles with ligands promotes more specific distribution within the stroma, reducing the percentage of nanoparticles that fail to reach target cells by approximately 50% Conclusions: A novel and comprehensive computational model has been developed to include the entire process of nanoparticle distribution following systemic administration, including specific recognition by cellular receptors.

Several studies have recommended the use of hydrogels for localized targeted delivery of chemotherapeutic drugs following tumor removal surgery. This approach aims to both fill the cavity and prevent cancer recurrence. The use of Multiphysics-based simulation emerges as a valuable strategy for minimizing experimental work, providing detailed insights into how drug release occurs in the tissue, and enabling the optimization of the design. In this study, we introduced a mathematical model, utilizing experimental data, to investigate the transport of liposomes carrying MZ1 from a thermosensitive hydrogel and their impact on the viability of breast cancer cells. The proposed comprehensive model considers not just the transport within the interstitial tissue, represented as a porous medium, but also the uptake by cells and its influence on cell viability, along with the potential lymphatic drainage. The six real patient-specific tumor shapes extracted from MRI scans were used to investigate how the size and form of the tumor can modify the transport pattern. The computational results revealed that the concentration of liposomes in the tissue is significantly influenced by their release from the hydrogel, which proved to be the limiting step. Liposome concentrations of approximately 0.1 % weight were found to be sufficient in ensuring minimal cell survival in the vicinity of the tumor.