Evidence map›Paper›PMID 31501963›Full record

ArticleBiomechanics and modeling in mechanobiology2020

Computational modeling of therapy on pancreatic cancer in its early stages.

Jiao Chen, Daphne Weihs, Fred J Vermolen

Open access · hybridAbstract read
In one paragraph

Article in Biomechanics and modeling in mechanobiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.2field-weighted citation impact, top 19% 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

14 citing papers in PubMed, 23 citations in OpenAlex.

  1. Article
  2. A Mathematical Model for Chemo-Mechanically Induced Collective Cell Motility on Planar Elastic Substrates.International journal for numerical methods in biomedical engineering · 2026
    Article
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  9. Co-delivery systems: hope for clinical application?Drug delivery and translational research · 2022
    Review
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  12. Article
  13. Review
  14. Mathematical Modeling to Address Challenges in Pancreatic Cancer.Current topics in medicinal chemistry · 2020
    Article
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

3 authors at 2 institutions in 2 countries.

Jiao ChenDelft Institute of Applied Mathematics, Delft University of Technology, Delft, The Netherlands. j.chen-6@tudelft.nl.ORCID http://orcid.org/0000-0002-4033-5636
Daphne WeihsFaculty of Biomedical Engineering, Technion-Israel Institute of Technology, Haifa, Israel.
Fred J VermolenDelft Institute of Applied Mathematics, Delft University of Technology, Delft, The Netherlands.
Delft University of Technology · NLTechnion – Israel Institute of Technology · IL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

More than eighty percent of pancreatic cancer involves ductal adenocarcinoma with an abundant desmoplastic extracellular matrix surrounding the solid tumor entity. This aberrant tumor microenvironment facilitates a strong resistance of pancreatic cancer to medication. Although various therapeutic strategies have been reported to be effective in mice with pancreatic cancer, they still need to be tested quantitatively in wider animal-based experiments before being applied as therapies. To aid the design of experiments, we develop a cell-based mathematical model to describe cancer progression under therapy with a specific application to pancreatic cancer. The displacement of cells is simulated by solving a large system of stochastic differential equations with the Euler-Maruyama method. We consider treatment with the PEGylated drug PEGPH20 that breaks down hyaluronan in desmoplastic stroma followed by administration of the chemotherapy drug gemcitabine to inhibit the proliferation of cancer cells. Modeling the effects of PEGPH20 + gemcitabine concentrations is based on Green's fundamental solutions of the reaction-diffusion equation. Moreover, Monte Carlo simulations are performed to quantitatively investigate uncertainties in the input parameters as well as predictions for the likelihood of success of cancer therapy. Our simplified model is able to simulate cancer progression and evaluate treatments to inhibit the progression of cancer.

Indexed as

Computer SimulationAnisotropyCell DeathCell DivisionCell Line, TumorCell MovementDeoxycytidineExtracellular MatrixGemcitabineHumansHyaluronoglucosaminidaseInjectionsMonte Carlo MethodNeoplasm StagingNumerical Analysis, Computer-AssistedPancreatic NeoplasmsDeoxycytidineGemcitabineHyaluronoglucosaminidasePEGPH20Cancer therapyCell migrationMathematical modelingMonte Carlo simulationsPancreatic cancer

Identifiers

PMID31501963
PMCPMC7105451
OpenAlexW2972978704

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.