A Model-Based Analysis of Tissue Targeting Efficacy of Nanoparticles
Tissue targeting is a critical challenge for systemic delivery of drug nanocarriers. To overcome this challenge, major research efforts have been undertaken to design ligand-conjugated nanoparticles. However, limited work has been done to quantitatively assess the effectiveness of such approach. In this work, using a mechanistic spatio-temporal model, I investigate the effectiveness of ligand-directed tissue targeting. By applying an approach from the colloidal filtration theory, I develop a Brownian dynamics model of nanoparticle-cell interaction. The model incorporates a single cell and its surrounding flow field. It considers both specific (receptor-mediated) and nonspecific (bare cell surface-mediated) recognition of nanoparticles subject to convective and diffusive motion. Using the model, I investigate how the specific and non-specific interactions compare in determining the overall targeting efficacy. My analysis provides some interesting findings that contradict the general notion that effective targeting is possible based upon the differential receptor expression in cancer and non-cancer cells. I show that such strategy may yield only a marginal gain in the targeting efficacy. Moreover, non-specific interaction may have an important influence on particle recognition by cells even at high receptor expression levels.
D. Barua, "A Model-Based Analysis of Tissue Targeting Efficacy of Nanoparticles," Journal of the Royal Society Interface, vol. 15, no. 140, Royal Society Publishing, Mar 2018.
The definitive version is available at https://doi.org/10.1098/rsif.2017.0787
Chemical and Biochemical Engineering
Keywords and Phrases
Brownian Dynamics; Colloidal Filtration; Creeping Flow; Drug Delivery
International Standard Serial Number (ISSN)
Article - Journal
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