(96h) A Model-based Analysis of the Tissue-Targeting Efficacy of Ligand-Directed Nanoparticles

Active delivery of drug nanoparticles involve modifying the particle surface with a targeting ligand. The rationale is that the surface-attached ligand can direct an intravenously-injected particle to certain receptor proteins overexpressed by cancer cells of the target tissue. However, despite the growing effort to conjugate nanoparticles with a variety of targeting ligands, the therapeutic benefit from such strategy remains poorly investigated. In this study, we develop a Brownian Dynamics model to quantitatively understand the gain in the targeting efficacy arising from such ligand targeting. Using the model, we consider different levels of receptor expression in the target cell and evaluate how that affect the targeting efficacy. For each ligand expression level, we consider two different scenarios: 1) particles are captured only through cell-surface receptor molecules in the absence of non-specific recognition; 2) particle capture occurs through both receptor-mediated and nonspecific membrane recognition. Our analysis suggest that there could only marginal gain in the targeting efficacy from the ligand conjugation. In addition, we show that this gain becomes further small in the presence of nonspecific recognition.