Evidence map›Paper›PMID 29240712›Full record

ArticleMolecules (Basel, Switzerland)2017

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

Hongjie Gao, Zuojing Yin, Zhiwei Cao, Le Zhang

Open access · goldAbstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.3field-weighted citation impact, top 20% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
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  3. An integrated platform forFrontiers in genetics · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 1 country.

Hongjie GaoCollege of Computer and Information Science, Southwest University, Chongqing 400715, China. ghjbarry@126.com.
Zuojing YinSchool of Life and Technology, Tongji University, Shanghai 200092, China. ZuoJing_Yin@tongji.edu.cn.
Zhiwei CaoSchool of Life and Technology, Tongji University, Shanghai 200092, China. zwcao@tongji.edu.cn.
Le ZhangCollege of Computer and Information Science, Southwest University, Chongqing 400715, China. zhangle06@scu.edu.cn.
Tongji University · CNSichuan University · CNSouthwest University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Computer SimulationDrug SynergismModels, BiologicalA549 CellsAlgorithmsAntineoplastic AgentsCell MovementCell ProliferationCell SurvivalCellular MicroenvironmentDose-Response Relationship, DrugDrug CombinationsHumansAntineoplastic AgentsDrug Combinationsagent-based modeldrug combinationoptimizationparameter estimationsynergistic effect

Identifiers

PMID29240712
PMCPMC6149923
OpenAlexW2772168100

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.