Predicting the vascular adhesion of deformable drug carriers in narrow capillaries traversed by blood cell

TL;DR

This study introduces a hybrid computational model combining Lattice Boltzmann and Immersed Boundary methods to predict how deformable drug carriers adhere to vessel walls in narrow capillaries, considering blood flow and cell interactions.

Contribution

The paper presents a novel hybrid simulation approach to predict adhesion strength of deformable particles in capillaries, accounting for cell deformation and ligand-receptor interactions.

Findings

Deformable particles show varying adhesion based on aspect ratio and stiffness.

Cell deformation influences ligand-receptor bond engagement.

The model predicts adhesion dynamics over time in narrow capillaries.

Abstract

In vascular targeted therapies, blood-borne carriers should realize sustained drug release from the luminal side towards the diseased tissue. In this context, such carriers are required to firmly adhere to the vessel walls for a sufficient period of time while resisting force perturbations induced by the blood flow and circulating cells. Here, a hybrid computational model, combining a Lattice Boltzmann (LBM) and Immersed Boundary Methods (IBM), is proposed for predicting the strength of adhesion of particles in narrow capillaries (7.5 $\mu \mathrm{m})$ traversed by blood cells. While flowing down the capillary, globular and biconcave deformable cells ( $7 \mu \mathrm{m}$ ) encounter $2 \mu \mathrm{m}$ discoidal particles, adhering to the vessel walls. Particles present aspect ratios ranging from $0.25$ to $1.0$ and a mechanical stiffness varying from rigid $(\mathrm{Ca}=0)$ to soft $\left(\mathrm{Ca}=10^{-3}\right)$. Cell-particle interactions are quantitatively predicted over time via three independent parameters: the cell membrane stretching $\delta p$; the cell-to-particle distance $r$, and the number of engaged ligand-receptor bonds $N_{\mathrm{L}}$.