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Molecules 2017, 22(12), 2209; doi:10.3390/molecules22122209

Developing an Agent-Based Drug Model to Investigate the Synergistic Effects of Drug Combinations

College of Computer and Information Science, Southwest University, Chongqing 400715, China
School of Life and Technology, Tongji University, Shanghai 200092, China
College of Computer Science, Sichuan University, Chengdu 610065, China
Authors to whom correspondence should be addressed.
Received: 27 October 2017 / Revised: 6 December 2017 / Accepted: 7 December 2017 / Published: 14 December 2017
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The growth and survival of cancer cells are greatly related to their surrounding microenvironment. To understand the regulation under the impact of anti-cancer drugs and their synergistic effects, we have developed a multiscale agent-based model that can investigate the synergistic effects of drug combinations with three innovations. First, it explores the synergistic effects of drug combinations in a huge dose combinational space at the cell line level. Second, it can simulate the interaction between cells and their microenvironment. Third, it employs both local and global optimization algorithms to train the key parameters and validate the predictive power of the model by using experimental data. The research results indicate that our multicellular system can not only describe the interactions between the microenvironment and cells in detail, but also predict the synergistic effects of drug combinations. View Full-Text
Keywords: agent-based model; parameter estimation; synergistic effect; drug combination; optimization agent-based model; parameter estimation; synergistic effect; drug combination; optimization

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Gao, H.; Yin, Z.; Cao, Z.; Zhang, L. Developing an Agent-Based Drug Model to Investigate the Synergistic Effects of Drug Combinations. Molecules 2017, 22, 2209.

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