A System Biology-Based Approach for Designing Combination Therapy in Cancer Precision Medicine
In this paper, we have used an agent-based stochastic tumor growth model and presented a mathematical and theoretical perspective to cancer therapy. This perspective can be used to theoretical study of precision medicine and combination therapy in individuals. We have conducted a series of in silico...
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Online Access: | http://dx.doi.org/10.1155/2020/5072697 |
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doaj-a953dd428b454e0289eafd74bbc2bcd72020-11-25T03:26:07ZengHindawi LimitedBioMed Research International2314-61332314-61412020-01-01202010.1155/2020/50726975072697A System Biology-Based Approach for Designing Combination Therapy in Cancer Precision MedicineS. H. Sabzpoushan0Department of Biomedical Engineering, Iran University of Science and Technology (IUST), Tehran 16846-13114, IranIn this paper, we have used an agent-based stochastic tumor growth model and presented a mathematical and theoretical perspective to cancer therapy. This perspective can be used to theoretical study of precision medicine and combination therapy in individuals. We have conducted a series of in silico combination therapy experiments. Based on cancer drugs and new findings of cancer biology, we hypothesize relationships between model parameters which in some cases represent individual genome characteristics and cancer drugs, i.e., in our approach, therapy players are delegated by biologically reasonable parameters. In silico experiments showed that combined therapies are more effective when players affect tumor via different mechanisms and have different physical dimensions. This research presents for the first time an algorithm as a theoretical viewpoint for the prediction of effectiveness and classification of therapy sets.http://dx.doi.org/10.1155/2020/5072697 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
S. H. Sabzpoushan |
spellingShingle |
S. H. Sabzpoushan A System Biology-Based Approach for Designing Combination Therapy in Cancer Precision Medicine BioMed Research International |
author_facet |
S. H. Sabzpoushan |
author_sort |
S. H. Sabzpoushan |
title |
A System Biology-Based Approach for Designing Combination Therapy in Cancer Precision Medicine |
title_short |
A System Biology-Based Approach for Designing Combination Therapy in Cancer Precision Medicine |
title_full |
A System Biology-Based Approach for Designing Combination Therapy in Cancer Precision Medicine |
title_fullStr |
A System Biology-Based Approach for Designing Combination Therapy in Cancer Precision Medicine |
title_full_unstemmed |
A System Biology-Based Approach for Designing Combination Therapy in Cancer Precision Medicine |
title_sort |
system biology-based approach for designing combination therapy in cancer precision medicine |
publisher |
Hindawi Limited |
series |
BioMed Research International |
issn |
2314-6133 2314-6141 |
publishDate |
2020-01-01 |
description |
In this paper, we have used an agent-based stochastic tumor growth model and presented a mathematical and theoretical perspective to cancer therapy. This perspective can be used to theoretical study of precision medicine and combination therapy in individuals. We have conducted a series of in silico combination therapy experiments. Based on cancer drugs and new findings of cancer biology, we hypothesize relationships between model parameters which in some cases represent individual genome characteristics and cancer drugs, i.e., in our approach, therapy players are delegated by biologically reasonable parameters. In silico experiments showed that combined therapies are more effective when players affect tumor via different mechanisms and have different physical dimensions. This research presents for the first time an algorithm as a theoretical viewpoint for the prediction of effectiveness and classification of therapy sets. |
url |
http://dx.doi.org/10.1155/2020/5072697 |
work_keys_str_mv |
AT shsabzpoushan asystembiologybasedapproachfordesigningcombinationtherapyincancerprecisionmedicine AT shsabzpoushan systembiologybasedapproachfordesigningcombinationtherapyincancerprecisionmedicine |
_version_ |
1715216277213020160 |