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Searching Synergistic Dose Combinations for Anticancer Drugs

Recent development has enabled synergistic drugs in treating a wide range of cancers. Being highly context-dependent, however, identification of successful ones often requires screening of combinational dose on different testing platforms in order to gain the best anticancer effects. To facilitate t...

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Detalles Bibliográficos
Autores principales: Yin, Zuojing, Deng, Zeliang, Zhao, Wenyan, Cao, Zhiwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5972206/
https://www.ncbi.nlm.nih.gov/pubmed/29872399
http://dx.doi.org/10.3389/fphar.2018.00535
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author Yin, Zuojing
Deng, Zeliang
Zhao, Wenyan
Cao, Zhiwei
author_facet Yin, Zuojing
Deng, Zeliang
Zhao, Wenyan
Cao, Zhiwei
author_sort Yin, Zuojing
collection PubMed
description Recent development has enabled synergistic drugs in treating a wide range of cancers. Being highly context-dependent, however, identification of successful ones often requires screening of combinational dose on different testing platforms in order to gain the best anticancer effects. To facilitate the development of effective computational models, we reviewed the latest strategy in searching optimal dose combination from three perspectives: (1) mainly experimental-based approach; (2) Computational-guided experimental approach; and (3) mainly computational-based approach. In addition to the introduction of each strategy, critical discussion of their advantages and disadvantages were also included, with a strong focus on the current applications and future improvements.
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spelling pubmed-59722062018-06-05 Searching Synergistic Dose Combinations for Anticancer Drugs Yin, Zuojing Deng, Zeliang Zhao, Wenyan Cao, Zhiwei Front Pharmacol Pharmacology Recent development has enabled synergistic drugs in treating a wide range of cancers. Being highly context-dependent, however, identification of successful ones often requires screening of combinational dose on different testing platforms in order to gain the best anticancer effects. To facilitate the development of effective computational models, we reviewed the latest strategy in searching optimal dose combination from three perspectives: (1) mainly experimental-based approach; (2) Computational-guided experimental approach; and (3) mainly computational-based approach. In addition to the introduction of each strategy, critical discussion of their advantages and disadvantages were also included, with a strong focus on the current applications and future improvements. Frontiers Media S.A. 2018-05-22 /pmc/articles/PMC5972206/ /pubmed/29872399 http://dx.doi.org/10.3389/fphar.2018.00535 Text en Copyright © 2018 Yin, Deng, Zhao and Cao. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Pharmacology
Yin, Zuojing
Deng, Zeliang
Zhao, Wenyan
Cao, Zhiwei
Searching Synergistic Dose Combinations for Anticancer Drugs
title Searching Synergistic Dose Combinations for Anticancer Drugs
title_full Searching Synergistic Dose Combinations for Anticancer Drugs
title_fullStr Searching Synergistic Dose Combinations for Anticancer Drugs
title_full_unstemmed Searching Synergistic Dose Combinations for Anticancer Drugs
title_short Searching Synergistic Dose Combinations for Anticancer Drugs
title_sort searching synergistic dose combinations for anticancer drugs
topic Pharmacology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5972206/
https://www.ncbi.nlm.nih.gov/pubmed/29872399
http://dx.doi.org/10.3389/fphar.2018.00535
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