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Mathematical modeling in cancer nanomedicine: a review
Cancer continues to be among the leading healthcare problems worldwide, and efforts continue not just to find better drugs, but also better drug delivery methods. The need for delivering cytotoxic agents selectively to cancerous cells, for improved safety and efficacy, has triggered the application...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6449316/ https://www.ncbi.nlm.nih.gov/pubmed/30949850 http://dx.doi.org/10.1007/s10544-019-0380-2 |
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author | Dogra, Prashant Butner, Joseph D. Chuang, Yao-li Caserta, Sergio Goel, Shreya Brinker, C. Jeffrey Cristini, Vittorio Wang, Zhihui |
author_facet | Dogra, Prashant Butner, Joseph D. Chuang, Yao-li Caserta, Sergio Goel, Shreya Brinker, C. Jeffrey Cristini, Vittorio Wang, Zhihui |
author_sort | Dogra, Prashant |
collection | PubMed |
description | Cancer continues to be among the leading healthcare problems worldwide, and efforts continue not just to find better drugs, but also better drug delivery methods. The need for delivering cytotoxic agents selectively to cancerous cells, for improved safety and efficacy, has triggered the application of nanotechnology in medicine. This effort has provided drug delivery systems that can potentially revolutionize cancer treatment. Nanocarriers, due to their capacity for targeted drug delivery, can shift the balance of cytotoxicity from healthy to cancerous cells. The field of cancer nanomedicine has made significant progress, but challenges remain that impede its clinical translation. Several biophysical barriers to the transport of nanocarriers to the tumor exist, and a much deeper understanding of nano-bio interactions is necessary to change the status quo. Mathematical modeling has been instrumental in improving our understanding of the physicochemical and physiological underpinnings of nanomaterial behavior in biological systems. Here, we present a comprehensive review of literature on mathematical modeling works that have been and are being employed towards a better understanding of nano-bio interactions for improved tumor delivery efficacy. |
format | Online Article Text |
id | pubmed-6449316 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-64493162019-04-17 Mathematical modeling in cancer nanomedicine: a review Dogra, Prashant Butner, Joseph D. Chuang, Yao-li Caserta, Sergio Goel, Shreya Brinker, C. Jeffrey Cristini, Vittorio Wang, Zhihui Biomed Microdevices Article Cancer continues to be among the leading healthcare problems worldwide, and efforts continue not just to find better drugs, but also better drug delivery methods. The need for delivering cytotoxic agents selectively to cancerous cells, for improved safety and efficacy, has triggered the application of nanotechnology in medicine. This effort has provided drug delivery systems that can potentially revolutionize cancer treatment. Nanocarriers, due to their capacity for targeted drug delivery, can shift the balance of cytotoxicity from healthy to cancerous cells. The field of cancer nanomedicine has made significant progress, but challenges remain that impede its clinical translation. Several biophysical barriers to the transport of nanocarriers to the tumor exist, and a much deeper understanding of nano-bio interactions is necessary to change the status quo. Mathematical modeling has been instrumental in improving our understanding of the physicochemical and physiological underpinnings of nanomaterial behavior in biological systems. Here, we present a comprehensive review of literature on mathematical modeling works that have been and are being employed towards a better understanding of nano-bio interactions for improved tumor delivery efficacy. Springer US 2019-04-04 2019 /pmc/articles/PMC6449316/ /pubmed/30949850 http://dx.doi.org/10.1007/s10544-019-0380-2 Text en © The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Article Dogra, Prashant Butner, Joseph D. Chuang, Yao-li Caserta, Sergio Goel, Shreya Brinker, C. Jeffrey Cristini, Vittorio Wang, Zhihui Mathematical modeling in cancer nanomedicine: a review |
title | Mathematical modeling in cancer nanomedicine: a review |
title_full | Mathematical modeling in cancer nanomedicine: a review |
title_fullStr | Mathematical modeling in cancer nanomedicine: a review |
title_full_unstemmed | Mathematical modeling in cancer nanomedicine: a review |
title_short | Mathematical modeling in cancer nanomedicine: a review |
title_sort | mathematical modeling in cancer nanomedicine: a review |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6449316/ https://www.ncbi.nlm.nih.gov/pubmed/30949850 http://dx.doi.org/10.1007/s10544-019-0380-2 |
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