Evidence map›Paper›PMID 38724586›Full record

ReviewNPJ Regenerative medicine2024

Exploiting in silico modelling to enhance translation of liver cell therapies from bench to bedside.

Candice Ashmore-Harris, Evangelia Antonopoulou, Simon M Finney, Melissa R Vieira, Matthew G Hennessy, Andreas Muench, Wei-Yu Lu, Victoria L Gadd, Alicia J El Haj, Stuart J Forbes and 1 more

Abstract readReview
In one paragraph

Review in NPJ Regenerative medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Review
  5. 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

11 authors.

Candice Ashmore-HarrisCentre for Regenerative Medicine, Institute for Regeneration and Repair, The University of Edinburgh, Edinburgh BioQuarter, 5 Little France Drive, Edinburgh, EH16 4UU, UK.ORCID http://orcid.org/0000-0001-9270-8599
Evangelia AntonopoulouMathematical Institute, University of Oxford, Oxford, OX2 6GG, UK.ORCID http://orcid.org/0000-0002-2801-6210
Simon M FinneyMathematical Institute, University of Oxford, Oxford, OX2 6GG, UK.ORCID http://orcid.org/0000-0003-4150-0784
Melissa R VieiraHealthcare Technologies Institute (HTI), Institute of Translational Medicine, University of Birmingham, Birmingham, B15 2TH, UK.ORCID http://orcid.org/0009-0002-7956-0213
Matthew G HennessyDepartment of Engineering Mathematics, University of Bristol, BS8 1TW, Bristol, UK.ORCID http://orcid.org/0000-0002-5928-6256
Andreas MuenchMathematical Institute, University of Oxford, Oxford, OX2 6GG, UK.
Wei-Yu LuCentre for Inflammation Research, Institute for Regeneration and Repair, The University of Edinburgh, Edinburgh, EH16 4UU, UK.
Victoria L GaddCentre for Regenerative Medicine, Institute for Regeneration and Repair, The University of Edinburgh, Edinburgh BioQuarter, 5 Little France Drive, Edinburgh, EH16 4UU, UK.ORCID http://orcid.org/0000-0003-1819-8660
Alicia J El HajHealthcare Technologies Institute (HTI), Institute of Translational Medicine, University of Birmingham, Birmingham, B15 2TH, UK.ORCID http://orcid.org/0000-0003-3544-5678
Stuart J ForbesCentre for Regenerative Medicine, Institute for Regeneration and Repair, The University of Edinburgh, Edinburgh BioQuarter, 5 Little France Drive, Edinburgh, EH16 4UU, UK.
Sarah L WatersMathematical Institute, University of Oxford, Oxford, OX2 6GG, UK. waters@maths.ox.ac.uk.ORCID http://orcid.org/0000-0001-5285-0523

Funding

RCUK | Medical Research Council (MRC) MR/T015489/1
6 · The paper itself

Abstract

Cell therapies are emerging as promising treatments for a range of liver diseases but translational bottlenecks still remain including: securing and assessing the safe and effective delivery of cells to the disease site; ensuring successful cell engraftment and function; and preventing immunogenic responses. Here we highlight three therapies, each utilising a different cell type, at different stages in their clinical translation journey: transplantation of multipotent mesenchymal stromal/signalling cells, hepatocytes and macrophages. To overcome bottlenecks impeding clinical progression, we advocate for wider use of mechanistic in silico modelling approaches. We discuss how in silico approaches, alongside complementary experimental approaches, can enhance our understanding of the mechanisms underlying successful cell delivery and engraftment. Furthermore, such combined theoretical-experimental approaches can be exploited to develop novel therapies, address safety and efficacy challenges, bridge the gap between in vitro and in vivo model systems, and compensate for the inherent differences between animal model systems and humans. We also highlight how in silico model development can result in fewer and more targeted in vivo experiments, thereby reducing preclinical costs and experimental animal numbers and potentially accelerating translation to the clinic. The development of biologically-accurate in silico models that capture the mechanisms underpinning the behaviour of these complex systems must be reinforced by quantitative methods to assess cell survival post-transplant, and we argue that non-invasive in vivo imaging strategies should be routinely integrated into transplant studies.

Identifiers

PMID38724586
PMCPMC11081951

What OpenQuestion holds

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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.