465247 A Novel Approach for Mechanistic Modeling and Simulation of Convection-Diffusion-Reaction Systems: Application to Nanoparticle Transport in Tumor Tissues

Wednesday, November 16, 2016: 4:09 PM
Monterey II (Hotel Nikko San Francisco)
Mohammad Islam, Sutapa Barua and Dipak Barua, Chemical and Biochemical Engineering, Missouri University of Science and Technology, Rolla, MO

We present a novel Brownian Dynamics (BD) simulation approach to model convection-diffusion-reaction systems. The simulation approach combines the Method of Regularized Stokeslets (MRS) with a time-adaptive BD algorithm. The combined method has unique ability to mechanistically model convection and diffusion-driven transport of reactive particles in heterogeneous porous medium. The BD algorithm takes intelligent decisions to advance particle position based on distance from their reactive partners. In the bulk fluid, particles away from their reactive partners are treated as point objects, and advanced with larger step sizes. In contrast, in the vicinity of any reactive partner, particles are treated as circular objects of defined size, and advanced with sub-nanometer step sizes. Such adaptive approach enables efficient and robust computation, while capturing particle interaction with their partners with high resolution details. We have applied this approach to model drug-delivery nanoparticle transport in the heterogeneous interstitial space of tumor tissues. The model takes into account both diffusion and convection transport of nanoparticles, and their interaction with the cell boundaries. Using the model, we have analyzed tissue penetration efficacy of nanoparticles as function of particle size. Our analysis provides new insights contradicting the findings of several recent publications. We show that experiments based on artificial tissue systems, which are usually carried out in the absence of convective transport and particle-cell interaction, may yield misleading conclusion on size-dependent tissue penetration efficacy of nanoparticles. We have validated our model analysis and predictions using in vitro breast tumor tissue grown on a microfluidic system.

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