Evidence map›Paper›PMID 26058969›Full record

ArticleScientific reports2015

Modelling the Transport of Nanoparticles under Blood Flow using an Agent-based Approach.

Gavin Fullstone, Jonathan Wood, Mike Holcombe, Giuseppe Battaglia

Abstract read
In one paragraph

Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing 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

35 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Review
  6. Modeling of spatiotemporal dynamics of ligand-coated particle flow in targeted drug delivery processes.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  7. Review
  8. Article
  9. Rational nanoparticle design: Optimization using insights from experiments and mathematical models.Journal of controlled release : official journal of the Controlled Release Society · 2023
    Review
  10. Article
  11. Agent-Based Modeling of Complex Molecular Systems.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
  12. Review
  13. Article
  14. Article
  15. Review
  16. Review
  17. Review
  18. Article
  19. Article
  20. A mathematical model to predict nanomedicine pharmacokinetics and tumor delivery.Computational and structural biotechnology journal · 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

4 authors.

Gavin Fullstone1] Department of Chemistry, University College London, UK [2] MRC Centre for Molecular Virology, University College London, UK [3] Department of Computer Science, University of Sheffield, UK.
Jonathan WoodSheffield Institute for Translational Neuroscience, University of Sheffield, UK.
Mike HolcombeDepartment of Computer Science, University of Sheffield, UK.
Giuseppe Battaglia1] Department of Chemistry, University College London, UK [2] MRC Centre for Molecular Virology, University College London, UK.

Funding

Biotechnology and Biological Sciences Research Council
6 · The paper itself

Abstract

Blood-mediated nanoparticle delivery is a new and growing field in the development of therapeutics and diagnostics. Nanoparticle properties such as size, shape and surface chemistry can be controlled to improve their performance in biological systems. This enables modulation of immune system interactions, blood clearance profile and interaction with target cells, thereby aiding effective delivery of cargo within cells or tissues. Their ability to target and enter tissues from the blood is highly dependent on their behaviour under blood flow. Here we have produced an agent-based model of nanoparticle behaviour under blood flow in capillaries. We demonstrate that red blood cells are highly important for effective nanoparticle distribution within capillaries. Furthermore, we use this model to demonstrate how nanoparticle size can selectively target tumour tissue over normal tissue. We demonstrate that the polydispersity of nanoparticle populations is an important consideration in achieving optimal specificity and to avoid off-target effects. In future this model could be used for informing new nanoparticle design and to predict general and specific uptake properties under blood flow.

Indexed as

Blood CirculationNanoparticlesBiological TransportErythrocytesHumans

Identifiers

PMID26058969
PMCPMC4462051

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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.