Evidence map›Paper›PMID 41540296›Full record

ArticlePharmaceutical research2026

From Blood Flow to Tumor Cell Internalization: A Multistage Computational Model of Nanoparticle Dynamics.

Álvaro González-Garcinuño, Eva Martin Del Valle, Sasa Kenjeres

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Article in Pharmaceutical research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Álvaro González-GarcinuñoDepartment of Chemical Engineering, University of Salamanca, Plaza Los Caídos s/n, 37008, Salamanca, Spain. alvaro_gonzalez@usal.es.
Eva Martin Del ValleDepartment of Chemical Engineering, University of Salamanca, Plaza Los Caídos s/n, 37008, Salamanca, Spain.
Sasa KenjeresDepartment of Chemical Engineering, Faculty of Applied Sciences, Delft University of Technology, Delft,. Van der Maasweg 9, 2629 HZ, Delft, The Netherlands. s.kenjeres@tudelft.nl.

Funding

Ministerio de Universidades CAS23/00128
6 · The paper itself

Abstract

backgroundUnderstanding 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.

methodsA 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.

resultsThe 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%

conclusionsA 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.

Indexed as

Models, BiologicalNanoparticlesNeoplasmsAnimalsBiological TransportComputer SimulationHumansParticle SizeTissue DistributionaffinityCFDnanoparticles trackingtransport modellingtumour environment

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.