Nanoparticle transport in cellular blood flow

Abstract

The biotransport of the intravascular nanoparticle (NP) is influenced by both the complex cellular flow environment and the NP characteristics. Being able to computationally simulate such intricate transport phenomenon with high efficiency is of far-reaching significance to the development of nanotherapeutics, yet challenging due to large length-scale discrepancies between NP and red blood cell (RBC) as well as the complexity of NP dynamics. Recently, a lattice-Boltzmann (LB) based multiscale simulation method has been developed to capture both NP scale and cellular level transport phenomenon at high computational efficiency. The basic components of this method include the LB treatment for the fluid phase, a spectrin-link method for RBCs, and a Langevin dynamics (LD) approach to capturing the motion of the suspended NPs. Comprehensive two-way coupling schemes are established to capture accurate interactions between each component.The accuracy and robustness of the LB-LD coupling method are demonstrated through the relaxation of a single NP with initial momentum and self-diffusion of NPs. This approach is then applied to study the migration of NPs in a micro-vessel under physiological conditions. It is shown that Brownian motion is most significant for the NP distribution in 20 vessels. For 1~100 particles, the Brownian diffusion is the dominant radial diffusive 2 mechanism compared to the RBC-enhanced diffusion. For ~500 particles, the Brownian diffusion and RBC-enhanced diffusion are comparable drivers for the particle radial diffusion process.

A unified analysis of nano-to-microscale particle dispersion in tubular blood flow

“…The SL method is solved by integrating equations 8 at each LB time step using a first-orderaccurate forward Euler scheme in consistency with the LB evolution equation to avoid excessive computational expense 28,31 .…”

“…Nanoscale particle (NP) dispersion in blood flow, on the other end of the spectrum, has recently received considerable attention due to the fast development of nano-drug delivery techniques that have the potential to revolutionize the traditional therapeutics 23 . Although the effective diffusivity of nanoscale solutes in blood flow were measured decades ago 24 , it is not until the past several years multiscale particle-level simulation techniques [25][26][27][28] become feasible. Tan et al 25 apply a coupled Brownian dynamics and immersed finite-element (FE) method to study the influence of RBCs on the NP dispersion in blood flows, showing substantial margination behavior for 100 nm particles.…”

“…In this work, we employ a recently developed 3D multiscale and multicomponent blood flow solver 2,28,29,31 to tackle the dispersive characteristics of spherical, rigid particles with sizes spanning nano-to-microscale in a tubular blood flow. Particle suspension dynamics in the presence of thermal fluctuation, RBC-particle direct and hydrodynamic interactions and wall-bounded confinement effect are captured under a unified 3D computational framework.…”

Multiscale method based on coupled lattice‐Boltzmann and Langevin‐dynamics for direct simulation of nanoscale particle/polymer suspensions in complex flows

“…24 Furthermore, the current method demonstrates that the long-distance many-body HI can be directly included via the LB-LD two-way coupling scheme, which was not shown in the work of Mynam et al 24 Compared to using mobility matrix approach to capture HI, 57 the direct two-way coupling approach, in addition to being more efficient, also has the flexibility of including the modified HI effects subject to complex geometries/boundaries. 30,76 Besides, the two-way coupled LB-LD approach embedded with the DLVO potentials allows simulating nanoscale particulate suspension across dilute-to-dense concentrations with good accuracy.…”

“…One example of such flows is blood flow suspended with numerous interacting nanoscale biomolecules and microscale blood cells through microfluidic systems [27][28][29] or biological structures. 30,31 The remainder of this article is organized as follows. In Section 2, the numerical method is presented.…”