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.


Chemical and Biochemical Engineering


Research presented in this work was supported by the National Science Foundation CBET-CDS&E grant no. 1609642.

Keywords and Phrases

Brownian Dynamics; Colloidal Filtration; Creeping Flow; Drug Delivery

International Standard Serial Number (ISSN)


Document Type

Article - Journal

Document Version


File Type





© 2018 Royal Society Publishing, All rights reserved.

Publication Date

01 Mar 2018