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

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.

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Journal
PLoS ONE
Published
2025-02-07
DOI
https://doi.org/10.1371/journal.pone.0315194
Citations
1
Primary Topic
Computational Drug Discovery Methods
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article
Field-Weighted Citation Impact
1.50
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article

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

Iván David Patiño Arcila, Fabián Mauricio Vélez Salazar
1 citations
PLoS ONE
Computational Drug Discovery Methods
1.50
article

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

Iván David Patiño Arcila, Fabián Mauricio Vélez Salazar
article en
1 citations

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.

PLoS ONEVol. 20(2)
Institución Universitaria Pascual Bravo (CO)
Good health and well-being
Openalex Percentile: Top 20%
Computational Drug Discovery Methods
1.50
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