Evidence map›Paper›PMID 40325283›Full record

ArticleJournal of pharmacokinetics and pharmacodynamics2025

Stochastic pharmacodynamics of a heterogeneous tumour-cell population.

Van Thuy Truong, Paolo Vicini, James Yates, Vincent Dubois, Grant Lythe

Abstract read
In one paragraph

Article in Journal of pharmacokinetics and pharmacodynamics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Van Thuy TruongSchool of Mathematics, University of Leeds, Leeds, LS2 9JT, UK. vn.thuy.truong@gmail.com.
Paolo ViciniConfo Therapeutics, Technologiepark 94, Zwijnaarde, 9052, Ghent, Belgium.
James YatesDMPK, Preclinical Sciences, RTech, GSK, Gunnels Wood Road, Stevenage, HRT, SG1 2NY, UK.
Vincent DuboisClinical Pharmacology and Quantitative Pharmacology, AstraZeneca, Granta Park, Cambridge, CB21 6GH, UK.
Grant LytheSchool of Mathematics, University of Leeds, Leeds, LS2 9JT, UK.

Funding

European Union's Horizon 2020 programme H2020-MSCA-ITN 76469
6 · The paper itself

Abstract

Standard pharmacodynamic models are ordinary differential equations without the features of stochasticity and heterogeneity. We develop and analyse a stochastic model of a heterogeneous tumour-cell population treated with a drug, where each cell has a different value of an attribute linked to survival. Once the drug reduces a cell's value below a threshold, the cell is susceptible to death. The elimination of the last cell in the population is a natural endpoint that is not available in deterministic models. We find formulae for the probability density of this extinction time in a collection of tumour cells, each with a different regulator value, under the influence of a drug. There is a logarithmic relationship between tumour population size and mean time to extinction. We also analyse the population under repeated drug doses and subsequent recoveries. Stochastic cell death and division events (and the relevant mechanistic parameters) determine the ultimate fate of the cell population. We identify the critical division rate separating long-term tumour population growth from successful multiple-dose treatment.

Indexed as

Antineoplastic AgentsModels, BiologicalNeoplasmsCell DeathHumansStochastic ProcessesAntineoplastic AgentsCancerHeterogeneityModellingPharmacodynamicsStochasticTargeted therapy

Identifiers

PMID40325283
PMCPMC12053371

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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.