Computational Modeling of Tumor Response to Drug Release from Vasculature-Bound Nanoparticles.

Systemically injected nanoparticle (NPs) targeting tumor vasculature offer a venue for anti-angiogenic therapies as well as cancer detection and imaging. Clinical application has been limited, however, due to the challenge of elucidating the complex interplay of nanotechnology, drug, and tumor param...

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Main Authors: Louis T Curtis, Min Wu, John Lowengrub, Paolo Decuzzi, Hermann B Frieboes
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2015-01-01
Series:PLoS ONE
Online Access:https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0144888&type=printable
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author Louis T Curtis
Min Wu
John Lowengrub
Paolo Decuzzi
Hermann B Frieboes
author_facet Louis T Curtis
Min Wu
John Lowengrub
Paolo Decuzzi
Hermann B Frieboes
author_sort Louis T Curtis
collection DOAJ
description Systemically injected nanoparticle (NPs) targeting tumor vasculature offer a venue for anti-angiogenic therapies as well as cancer detection and imaging. Clinical application has been limited, however, due to the challenge of elucidating the complex interplay of nanotechnology, drug, and tumor parameters. A critical factor representing the likelihood of endothelial adhesion is the NP vascular affinity, a function of vascular receptor expression and NP size and surface-bound ligand density. We propose a theoretical framework to simulate the tumor response to vasculature-bound drug-loaded NPs and examine the interplay between NP distribution and accumulation as a function of NP vascular affinity, size, and drug loading and release characteristics. The results show that uniform spatial distribution coupled with high vascular affinity is achievable for smaller NPs but not for larger sizes. Consequently, small (100 nm) NPs with high vascular affinity are predicted to be more effective than larger (1000 nm) NPs with similar affinity, even though small NPs have lower drug loading and local drug release compared to the larger NPs. Medium vascular affinity coupled with medium or larger sized NPs is also effective due to a more uniform distribution with higher drug loading and release. Low vascular affinity hampered treatment efficacy regardless of NP size, with larger NPs additionally impeded by heterogeneous distribution and drug release. The results further show that increased drug diffusivity mainly benefits heterogeneously distributed NPs, and would negatively affect efficacy otherwise due to increased wash-out. This model system enables evaluation of efficacy for vascular-targeted drug-loaded NPs as a function of critical NP, drug, and tumor parameters.
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spelling doaj-art-ceeda6a11c974cb387db01fedf69c9782025-08-20T02:15:38ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-011012e014488810.1371/journal.pone.0144888Computational Modeling of Tumor Response to Drug Release from Vasculature-Bound Nanoparticles.Louis T CurtisMin WuJohn LowengrubPaolo DecuzziHermann B FrieboesSystemically injected nanoparticle (NPs) targeting tumor vasculature offer a venue for anti-angiogenic therapies as well as cancer detection and imaging. Clinical application has been limited, however, due to the challenge of elucidating the complex interplay of nanotechnology, drug, and tumor parameters. A critical factor representing the likelihood of endothelial adhesion is the NP vascular affinity, a function of vascular receptor expression and NP size and surface-bound ligand density. We propose a theoretical framework to simulate the tumor response to vasculature-bound drug-loaded NPs and examine the interplay between NP distribution and accumulation as a function of NP vascular affinity, size, and drug loading and release characteristics. The results show that uniform spatial distribution coupled with high vascular affinity is achievable for smaller NPs but not for larger sizes. Consequently, small (100 nm) NPs with high vascular affinity are predicted to be more effective than larger (1000 nm) NPs with similar affinity, even though small NPs have lower drug loading and local drug release compared to the larger NPs. Medium vascular affinity coupled with medium or larger sized NPs is also effective due to a more uniform distribution with higher drug loading and release. Low vascular affinity hampered treatment efficacy regardless of NP size, with larger NPs additionally impeded by heterogeneous distribution and drug release. The results further show that increased drug diffusivity mainly benefits heterogeneously distributed NPs, and would negatively affect efficacy otherwise due to increased wash-out. This model system enables evaluation of efficacy for vascular-targeted drug-loaded NPs as a function of critical NP, drug, and tumor parameters.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0144888&type=printable
spellingShingle Louis T Curtis
Min Wu
John Lowengrub
Paolo Decuzzi
Hermann B Frieboes
Computational Modeling of Tumor Response to Drug Release from Vasculature-Bound Nanoparticles.
PLoS ONE
title Computational Modeling of Tumor Response to Drug Release from Vasculature-Bound Nanoparticles.
title_full Computational Modeling of Tumor Response to Drug Release from Vasculature-Bound Nanoparticles.
title_fullStr Computational Modeling of Tumor Response to Drug Release from Vasculature-Bound Nanoparticles.
title_full_unstemmed Computational Modeling of Tumor Response to Drug Release from Vasculature-Bound Nanoparticles.
title_short Computational Modeling of Tumor Response to Drug Release from Vasculature-Bound Nanoparticles.
title_sort computational modeling of tumor response to drug release from vasculature bound nanoparticles
url https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0144888&type=printable
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