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Research Papers

Nanocarrier Hydrodynamics and Binding in Targeted Drug Delivery: Challenges in Numerical Modeling and Experimental Validation

[+] Author and Article Information
Portonovo S. Ayyaswamy

Department of Mechanical Engineering and Applied Mechanics,
University of Pennsylvania,
Philadelphia, PA 19104

Vladimir Muzykantov

Department of Pharmacology,
and Center for Targeted Therapeutics and Translational Nanomedicine,
University of Pennsylvania,
Philadelphia, PA 19104

David M. Eckmann

Institute of Translational Medicine and Therapeutics,
Department of Anesthesiology and Critical Care,
and Department of Bioengineering,
University of Pennsylvania,
Philadelphia, PA 19104

Ravi Radhakrishnan

Institute of Translational Medicine and Therapeutics,
Department of Bioengineering,
Department of Chemical and Biomolecular Engineering,
University of Pennsylvania,
Philadelphia, PA 19104
e-mail: rradhak@seas.upenn.edu

1Corresponding author.

Manuscript received November 5, 2012; final manuscript received March 6, 2013; published online July 11, 2013. Assoc. Editor: Liang Zhu.

J. Nanotechnol. Eng. Med 4(1), 011001 (Jul 11, 2013) (15 pages) Paper No: NANO-12-1132; doi: 10.1115/1.4024004 History: Received November 05, 2012; Revised March 06, 2013

This review discusses current progress and future challenges in the numerical modeling of targeted drug delivery using functionalized nanocarriers (NC). Antibody coated nanocarriers of various size and shapes, also called functionalized nanocarriers, are designed to be injected in the vasculature, whereby they undergo translational and rotational motion governed by hydrodynamic interaction with blood particulates as well as adhesive interactions mediated by the surface antibody binding to target antigens/receptors on cell surfaces. We review current multiscale modeling approaches rooted in computational fluid dynamics and nonequilibrium statistical mechanics to accurately resolve fluid, thermal, as well as adhesive interactions governing nanocarrier motion and their binding to endothelial cells lining the vasculature. We also outline current challenges and unresolved issues surrounding the modeling methods. Experimental approaches in pharmacology and bioengineering are discussed briefly from the perspective of model validation.

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Figures

Grahic Jump Location
Fig. 2

Branching vessel geometry. The flow rates in the two branches are functions of the geometric variables describing the branch.

Grahic Jump Location
Fig. 1

Schematic of different length scales of NC dynamics. Top: at the micron length-scale, the hydrodynamics of particulate nature of blood and near-wall margination of NC is described. Bottom: at the 50–200 nm length scale, the near-wall adhesion of NC and resistance due to glycocalyx is described.

Grahic Jump Location
Fig. 3

Multiscale model for NC adhesion interactions with molecular specificity. NC with functionalized antibodies attached via tethers. The tether dynamics is described using a wormlike chain model (see inset). The antigens on the cell surface are treated with flexural dynamics, which are resolved using coarse-grained molecular dynamics or CGMD simulations.

Grahic Jump Location
Fig. 5

Threshold binding of NCs in silico (a) and in vivo (b) showing excellent agreement between model and experiment. The in silico prediction (a) describes the association constant Ka versus antibody density, while the in vivo results describe lung endothelial targeting of NC versus antibody density.

Grahic Jump Location
Fig. 6

Shear enhanced binding in silico (a) and in vitro (b) showing excellent agreement between model and experiment. Both panels depict shear-enhanced binding behavior below a shear threshold.

Grahic Jump Location
Fig. 4

Binding affinity (association constant or Ka) in vitro (a) and in silico (b) showing excellent agreement between simulation and experiment

Grahic Jump Location
Fig. 7

Calculated PMF at T = 310 °K for different values of the bond constant, k

Grahic Jump Location
Fig. 8

NC binding to HUVECs in flow under various antibody densities in cell culture experiments

Grahic Jump Location
Fig. 9

Schematic and data of EPL-click conjugation strategy, control of NC. (a) Schematic of the conjugation chemistry; (b) NC binding quantification; (c) effect of antibody density on NC; and (d)–(e) cell labeling and flow-cytomentry experiments, see main text.

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