Evidence map›Paper›PMID 38180543›Full record

ArticleJournal of mathematical biology2024

A robust optimal control framework for controlling aberrant RTK signaling pathways in esophageal cancer.

Souvik Roy, Zui Pan, Naif Abu Qarnayn, Mesfer Alajmi, Ali Alatawi, Asma Alghamdi, Ibrahem Alshaoosh, Zahra Asiri, Berlinda Batista, Shreshtha Chaturvedi and 6 more

Abstract read
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In one paragraph

Article in Journal of mathematical biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.4field-weighted citation impact, top 14% of its field
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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. 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

16 authors at 1 institution in 1 country.

Souvik Roy *Department of Mathematics, The University of Texas at Arlington, Arlington, TX, 76019-0407, USA. souvik.roy@uta.edu.ORCID 0000-0002-6134-1381
Zui Pan *College of Nursing and Health Innovation, The University of Texas at Arlington, Arlington, TX, 76019-0407, USA.ORCID 0000-0003-4105-901X
Naif Abu Qarnayn *Department of Mathematics, The University of Texas at Arlington, Arlington, TX, 76019-0407, USA.ORCID 0000-0002-5296-4667
Mesfer Alajmi *Department of Mathematics, The University of Texas at Arlington, Arlington, TX, 76019-0407, USA.ORCID 0009-0007-9010-2332
Ali Alatawi *Department of Mathematics, The University of Texas at Arlington, Arlington, TX, 76019-0407, USA.ORCID 0000-0001-8628-8188
Asma Alghamdi *Department of Mathematics, The University of Texas at Arlington, Arlington, TX, 76019-0407, USA.ORCID 0009-0003-2763-875X
Ibrahem Alshaoosh *Department of Mathematics, The University of Texas at Arlington, Arlington, TX, 76019-0407, USA.
Zahra Asiri *Department of Mathematics, The University of Texas at Arlington, Arlington, TX, 76019-0407, USA.ORCID 0000-0003-4894-5196
Berlinda Batista *Department of Mathematics, The University of Texas at Arlington, Arlington, TX, 76019-0407, USA.
Shreshtha Chaturvedi *Department of Mathematics, The University of Texas at Arlington, Arlington, TX, 76019-0407, USA.ORCID 0000-0002-7839-1959
Olusola Dehinsilu *Department of Mathematics, The University of Texas at Arlington, Arlington, TX, 76019-0407, USA.ORCID 0000-0002-1121-6523
Hussein Edduweh *Department of Mathematics, The University of Texas at Arlington, Arlington, TX, 76019-0407, USA.ORCID 0000-0001-5280-093X
Rodina El-Adawy *Department of Mathematics, The University of Texas at Arlington, Arlington, TX, 76019-0407, USA.ORCID 0000-0003-3597-3104
Emran Hossen *Department of Mathematics, The University of Texas at Arlington, Arlington, TX, 76019-0407, USA.ORCID 0000-0001-5062-9796
Bardia Mojra *Department of Computer Science, The University of Texas at Arlington, Arlington, TX, 76019-0407, USA.ORCID 0000-0002-5094-2886
Jashmon Rana *Department of Mathematics, The University of Texas at Arlington, Arlington, TX, 76019-0407, USA.
The University of Texas at Arlington · US

Funding

Interdisciplinary Research Program, UTA 2021-772National Science Foundation 2212938
6 · The paper itself

Abstract

This study presents a new framework for obtaining personalized optimal treatment strategies targeting aberrant signaling pathways in esophageal cancer, such as the epidermal growth factor (EGF) and vascular endothelial growth factor (VEGF) signaling pathways. A new pharmacokinetic model is developed taking into account specific heterogeneities of these signaling mechanisms. The optimal therapies are designed to be obtained using a three step process. First, a finite-dimensional constrained optimization problem is solved to obtain the parameters of the pharmacokinetic model, using discrete patient data measurements. Next, a sensitivity analysis is carried out to determine which of the parameters are sensitive to the evolution of the variants of EGF receptors and VEGF receptors. Finally, a second optimal control problem is solved based on the sensitivity analysis results, using a modified pharmacokinetic model that incorporates two representative drugs Trastuzumab and Bevacizumab, targeting EGF and VEGF, respectively. Numerical results with the combination of the two drugs demonstrate the efficiency of the proposed framework.

Indexed as

Epidermal Growth FactorEsophageal NeoplasmsHumansSignal TransductionVascular Endothelial Growth Factor AEpidermal Growth FactorVascular Endothelial Growth Factor AHER2 blockersMonoclonal antibodiesNon-linear conjugate gradientOptimizationWeibull distribution

Identifiers

PMID38180543
OpenAlexW4390615555

What OpenQuestion holds

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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.