Evidence map›Paper›PMID 39919263›Full record

ArticlePloS one2025

In-silico tool based on Boolean networks and meshless simulations for prediction of reaction and transport mechanisms in the systemic administration of chemotherapeutic drugs.

Fabián Mauricio Vélez Salazar, Iván David Patiño

Abstract read
In one paragraph

Article in PloS one, 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

2 authors.

Fabián Mauricio Vélez SalazarGrupo de Investigación e Innovación Ambiental (GIIAM), Institución Universitaria Pascual Bravo, Medellín, Colombia.ORCID https://orcid.org/0000-0002-7299-5970
Iván David PatiñoGrupo de Investigación e Innovación Ambiental (GIIAM), Institución Universitaria Pascual Bravo, Medellín, Colombia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Using in-house computational tools, this work focuses on investigating how the combination of the electric field magnitude (E), bloodstream velocity (λinl) and pharmaco-kinetic profile (PK) impacts the reaction and transport mechanisms of drug (RTMs) arising in electro-chemotherapeutic treatments. The first step implies retrieving the ratios between extracellular, free intracellular, and bound intracellular concentrations from numerical simulations, employing a meshless code developed, calibrated and validated in a previous work. Subsequently, a Boolean model is developed to determine the presence, interaction and rates of RTMs based on the comparison of the spatio-temporal evolution of the drug concentration ratios, being this the main contribution of the present work to the comprehension of the phenomena involved in the systemic administration of chemotherapeutic drugs in cancer tumors. Different combinations of E (0 kV/m, 46 kV/m, 70 kV/m), λinl (1x10-4m/s, 1x10-3m/s, 1x10-2m/s) and PK (One-short tri-exponential, mono-exponential) are examined. In general, results show that both the presence and relative importance of RTMs can differ between both PKs for a given combination of E and λinl. Additionally, for a given PK, radial uniformity of transmembrane transport rate is aversively affected by the increase of E and λinl, whereas radial homogeneity of association/dissociation rate is monotonously affected only by E. Regarding the axial uniformity of transmembrane transport rate, this is benefited by the increase of λinl and, in a lower extent, by the reduction of E.

Indexed as

Antineoplastic AgentsComputer SimulationBiological TransportHumansKineticsModels, BiologicalNeoplasmsAntineoplastic Agents

Identifiers

PMID39919263
PMCPMC11805580

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.