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Modeling Particle Shape-Dependent Dynamics in Nanomedicine
Open accessAbstract
One of the major challenges in nanomedicine is to improve nanoparticle cell selectivity and adhesion efficiency through designing functionalized nanoparticles of controlled sizes, shapes, and material compositions. Recent data on cylindrically shaped filomicelles are beginning to show that non-spherical particles remarkably improved the biological properties over spherical counterpart. Despite these exciting advances, non-spherical particles have not been widely used in nanomedicine applications due to the lack of fundamental understanding of shape effect on targeting efficiency. This paper intends to investigate the shape-dependent adhesion kinetics of non-spherical nanoparticles through computational modeling. The ligand-receptor binding kinetics is coupled with Brownian dynamics to study the dynamic delivery process of nanorods under various vascular flow conditions. The influences of nanoparticle shape, ligand density, and shear rate on adhesion probability are studied. Nanorods are observed to contact and adhere to the wall much easier than their spherical counterparts under the same configuration due to their tumbling motion. The binding probability of a nanorod under a shear rate of 8 s(-1) is found to be three times higher than that of a nanosphere with the same volume. The particle binding probability decreases with increased flow shear rate and channel height. The Brownian motion is found to largely enhance nanoparticle binding. Results from this study contribute to the fundamental understanding and knowledge on how particle shape affects the transport and targeting efficiency of nanocarriers, which will provide mechanistic insights on the design of shape-specific nanomedicine for targeted drug delivery applications.
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Multifunctional polymeric micelles as cancer-targeted, MRI-ultrasensitive drug delivery systems
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Self-citationBiologically erodable microspheres as potential oral drug delivery systems
Mathiowitz, E., Jacob, J. S., Jong, Y. S., Carino, G. P., Chickering, D. E., Chaturvedi, P., Santos, C. A., Vijayaraghavan, K., Montgomery, S., Bassett, M., et al. (1997) · Nature · doi:10.1038/386410a0 · Cited by 823
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Principles of nanoparticle design for overcoming biological barriers to drug delivery
Blanco, E., Shen, H., & Ferrari, M. (2015) · Nature Biotechnology · doi:10.1038/nbt.3330 · Cited by 7,002
Duan, X., & Li, Y. (2013) · Small · doi:10.1002/smll.201201390 · Cited by 926
Integrating Artificial Intelligence and Nanotechnology for Precision Cancer Medicine
Adir, O., Poley, M., Chen, G., Froim, S., Krinsky, N., Shklover, J., Shainsky‐Roitman, J., Lammers, T., & Schroeder, A. (2020) · Advanced Materials · doi:10.1002/adma.201901989 · Cited by 496
Effect of physicochemical and surface properties on in vivo fate of drug nanocarriers
Zhao, Z., Ukidve, A., Krishnan, V., & Mitragotri, S. (2019) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2019.01.002 · Cited by 444
Organ-on-a-chip platforms for studying drug delivery systems
Bhise, N. S., Ribas, J., Manoharan, V., Zhang, Y. S., Polini, A., Massa, S., Dokmeci, M. R., & Khademhosseini, A. (2014) · Journal of Controlled Release · doi:10.1016/j.jconrel.2014.05.004 · Cited by 381
Metadata
- Authors
- Shah, S., Liu, Y., Hu, W., & Gao, J.
- Venue
- Journal of Nanoscience and Nanotechnology
- Publisher
- American Scientific Publishers
- Published
- 2011-02-01
- Volume
- 11
- Issue
- 2
- Pages
- 919-928
- ISSN
- 1533-4880 (ISSN-L)
- OpenAlex
- W2057262708
- Cited by
- 189
- References
- 2
- FWCI
- 5.93
- Type
- journal article
- Language
- en
- Open access
- green
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