Evidence map›Paper›PMID 41879930›Full record

ArticleBulletin of mathematical biology2026

The Role of Viral Dynamics and Infectivity in Models of Oncolytic Virotherapy for Tumours with Different Motility.

David Morselli, Federico Frascoli, Marcello E Delitala

Abstract read
In one paragraph

Article in Bulletin of mathematical biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

David MorselliDepartment of Mathematics, University College London, 25 Gordon Street, London, WC1H 0AY, United Kingdom. d.morselli@ucl.ac.uk.ORCID http://orcid.org/0000-0002-9321-2701
Federico FrascoliDepartment of Mathematics, School of Science, Computing and Emerging Technologies, Swinburne University of Technology, John Street, Hawthorn, 3122, VIC, Australia.ORCID http://orcid.org/0000-0003-4159-6229
Marcello E DelitalaDepartment of Mathematical Sciences "G. L. Lagrange", Politecnico di Torino, Corso Duca degli Abruzzi 24, Torino, 10129, Italy.ORCID http://orcid.org/0000-0002-5347-5654

Funding

Australian National Health and Medical Research Council NHMRC IDEAS 2013058Australian Research Council DP230100485Ministero dell'Istruzione, dell'Università e della Ricerca E11G18000350001
6 · The paper itself

Abstract

The use of ad-hoc engineered viruses in the fight against tumours is one of the greatest ideas in cancer therapeutics within the last three decades. Although some remarkable successes have been obtained, it is still not entirely clear how to achieve reliable protocols that can be routinely employed with confidence on a significant range of tumours. In this work, we concentrate on the study of different mathematical descriptions of virotherapy with the aim of better understanding the role of viral infectivity and viral dynamics in positive therapeutic outcomes. In particular, we compare probabilistic, individual approaches with continuous, spatially inhomogeneous models and investigate the importance of different tumour motility and different mathematical representations of viral infectivity. Some of these formulations also allow us to arrive at better analytical characterisation of how waves of viral infections arise and propagate in tumours, providing interesting insights into therapy dynamics. Similarly to previous studies, oscillatory behaviours, stochasticity and cancers' diffusivities are all central to the eradication or the escape of tumours under virotherapy. Here, though, our results also show that the ability of viruses to infect tumours seems, in certain cases, more important to a final positive outcome than tumours' motility or even reproductivity. This could hopefully represent a first step into better insights into viral dynamics that may help clinicians to achieve consistently better outcomes.

Indexed as

Models, BiologicalNeoplasmsOncolytic VirotherapyOncolytic VirusesAnimalsCell MovementComputer SimulationHumansMathematical ConceptsStochastic ProcessesBifurcation analysisContinuum modelsIndividual-based modelsOncolytic virusTravelling waves

Identifiers

PMID41879930
PMCPMC13018097

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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.