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A mathematical model to predict nanomedicine pharmacokinetics and tumor delivery
Towards clinical translation of cancer nanomedicine, it is important to systematically investigate the various parameters related to nanoparticle (NP) physicochemical properties, tumor characteristics, and inter-individual variability that affect the tumor delivery efficiency of therapeutic nanomate...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7078505/ https://www.ncbi.nlm.nih.gov/pubmed/32206211 http://dx.doi.org/10.1016/j.csbj.2020.02.014 |
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author | Dogra, Prashant Butner, Joseph D. Ruiz Ramírez, Javier Chuang, Yao-li Noureddine, Achraf Jeffrey Brinker, C. Cristini, Vittorio Wang, Zhihui |
author_facet | Dogra, Prashant Butner, Joseph D. Ruiz Ramírez, Javier Chuang, Yao-li Noureddine, Achraf Jeffrey Brinker, C. Cristini, Vittorio Wang, Zhihui |
author_sort | Dogra, Prashant |
collection | PubMed |
description | Towards clinical translation of cancer nanomedicine, it is important to systematically investigate the various parameters related to nanoparticle (NP) physicochemical properties, tumor characteristics, and inter-individual variability that affect the tumor delivery efficiency of therapeutic nanomaterials. Comprehensive investigation of these parameters using traditional experimental approaches is impractical due to the vast parameter space; mathematical models provide a more tractable approach to navigate through such a multidimensional space. To this end, we have developed a predictive mathematical model of whole-body NP pharmacokinetics and their tumor delivery in vivo, and have conducted local and global sensitivity analyses to identify the factors that result in low tumor delivery efficiency and high off-target accumulation of NPs. Our analyses reveal that NP degradation rate, tumor blood viscosity, NP size, tumor vascular fraction, and tumor vascular porosity are the key parameters in governing NP kinetics in the tumor interstitium. The impact of these parameters on tumor delivery efficiency of NPs is discussed, and optimal values for maximizing NP delivery are presented. |
format | Online Article Text |
id | pubmed-7078505 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-70785052020-03-23 A mathematical model to predict nanomedicine pharmacokinetics and tumor delivery Dogra, Prashant Butner, Joseph D. Ruiz Ramírez, Javier Chuang, Yao-li Noureddine, Achraf Jeffrey Brinker, C. Cristini, Vittorio Wang, Zhihui Comput Struct Biotechnol J Research Article Towards clinical translation of cancer nanomedicine, it is important to systematically investigate the various parameters related to nanoparticle (NP) physicochemical properties, tumor characteristics, and inter-individual variability that affect the tumor delivery efficiency of therapeutic nanomaterials. Comprehensive investigation of these parameters using traditional experimental approaches is impractical due to the vast parameter space; mathematical models provide a more tractable approach to navigate through such a multidimensional space. To this end, we have developed a predictive mathematical model of whole-body NP pharmacokinetics and their tumor delivery in vivo, and have conducted local and global sensitivity analyses to identify the factors that result in low tumor delivery efficiency and high off-target accumulation of NPs. Our analyses reveal that NP degradation rate, tumor blood viscosity, NP size, tumor vascular fraction, and tumor vascular porosity are the key parameters in governing NP kinetics in the tumor interstitium. The impact of these parameters on tumor delivery efficiency of NPs is discussed, and optimal values for maximizing NP delivery are presented. Research Network of Computational and Structural Biotechnology 2020-02-29 /pmc/articles/PMC7078505/ /pubmed/32206211 http://dx.doi.org/10.1016/j.csbj.2020.02.014 Text en © 2020 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Research Article Dogra, Prashant Butner, Joseph D. Ruiz Ramírez, Javier Chuang, Yao-li Noureddine, Achraf Jeffrey Brinker, C. Cristini, Vittorio Wang, Zhihui A mathematical model to predict nanomedicine pharmacokinetics and tumor delivery |
title | A mathematical model to predict nanomedicine pharmacokinetics and tumor delivery |
title_full | A mathematical model to predict nanomedicine pharmacokinetics and tumor delivery |
title_fullStr | A mathematical model to predict nanomedicine pharmacokinetics and tumor delivery |
title_full_unstemmed | A mathematical model to predict nanomedicine pharmacokinetics and tumor delivery |
title_short | A mathematical model to predict nanomedicine pharmacokinetics and tumor delivery |
title_sort | mathematical model to predict nanomedicine pharmacokinetics and tumor delivery |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7078505/ https://www.ncbi.nlm.nih.gov/pubmed/32206211 http://dx.doi.org/10.1016/j.csbj.2020.02.014 |
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