Evidence map›Paper›PMID 36649330›Full record

ArticlePLoS computational biology2023

Examining the efficacy of localised gemcitabine therapy for the treatment of pancreatic cancer using a hybrid agent-based model.

Adrianne L Jenner, Wayne Kelly, Michael Dallaston, Robyn Araujo, Isobelle Parfitt, Dominic Steinitz, Pantea Pooladvand, Peter S Kim, Samantha J Wade, Kara L Vine

Abstract read
In one paragraph

Article in PLoS computational biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

10 authors.

Adrianne L JennerSchool of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.ORCID 0000-0001-9103-7092
Wayne KellySchool of Computer Science, Queensland University of Technology, Brisbane, Queensland, Australia.ORCID 0000-0002-8554-4589
Michael DallastonSchool of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.
Robyn AraujoSchool of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.ORCID 0000-0002-3360-2214
Isobelle ParfittSchool of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.ORCID 0000-0002-0422-9844
Dominic SteinitzTweag Software Innovation Lab, London, United Kingdom.ORCID 0000-0002-7143-2412
Pantea PooladvandSchool of Mathematics and Statistics, University of Sydney, Sydney, New South Wales, Australia.ORCID 0000-0001-8205-0914
Peter S KimSchool of Mathematics and Statistics, University of Sydney, Sydney, New South Wales, Australia.ORCID 0000-0002-1492-4744
Samantha J WadeIllawarra Health and Medical Research Institute, Wollongong, New South Wales, Australia.ORCID 0000-0002-9494-8518
Kara L VineIllawarra Health and Medical Research Institute, Wollongong, New South Wales, Australia.ORCID 0000-0001-6871-1149

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The prognosis for pancreatic ductal adenocarcinoma (PDAC) patients has not significantly improved in the past 3 decades, highlighting the need for more effective treatment approaches. Poor patient outcomes and lack of response to therapy can be attributed, in part, to a lack of uptake of perfusion of systemically administered chemotherapeutic drugs into the tumour. Wet-spun alginate fibres loaded with the chemotherapeutic agent gemcitabine have been developed as a potential tool for overcoming the barriers in delivery of systemically administrated drugs to the PDAC tumour microenvironment by delivering high concentrations of drug to the tumour directly over an extended period. While exciting, the practicality, safety, and effectiveness of these devices in a clinical setting requires further investigation. Furthermore, an in-depth assessment of the drug-release rate from these devices needs to be undertaken to determine whether an optimal release profile exists. Using a hybrid computational model (agent-based model and partial differential equation system), we developed a simulation of pancreatic tumour growth and response to treatment with gemcitabine loaded alginate fibres. The model was calibrated using in vitro and in vivo data and simulated using a finite volume method discretisation. We then used the model to compare different intratumoural implantation protocols and gemcitabine-release rates. In our model, the primary driver of pancreatic tumour growth was the rate of tumour cell division. We were able to demonstrate that intratumoural placement of gemcitabine loaded fibres was more effective than peritumoural placement. Additionally, we quantified the efficacy of different release profiles from the implanted fibres that have not yet been tested experimentally. Altogether, the model developed here is a tool that can be used to investigate other drug delivery devices to improve the arsenal of treatments available for PDAC and other difficult-to-treat cancers in the future.

Indexed as

Carcinoma, Pancreatic DuctalPancreatic NeoplasmsAlginatesCell Line, TumorDeoxycytidineGemcitabineHumansTumor MicroenvironmentAlginatesDeoxycytidineGemcitabine

Identifiers

PMID36649330
PMCPMC9891514

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Registered trials

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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.