Literature DB >> 23906150

On optimal chemotherapy with a strongly targeted agent for a model of tumor-immune system interactions with generalized logistic growth.

Urszula Ledzewicz1, Omeiza Olumoye, Heinz Schättler.   

Abstract

In this paper, a mathematical model for chemotherapy that takes tumor immune-system interactions into account is considered for a strongly targeted agent. We use a classical model originally formulated by Stepanova, but replace exponential tumor growth with a generalised logistic growth model function depending on a parameter v. This growth function interpolates between a Gompertzian model (in the limit v → 0) and an exponential model (in the limit v → ∞). The dynamics is multi-stable and equilibria and their stability will be investigated depending on the parameter v. Except for small values of v, the system has both an asymptotically stable microscopic (benign) equilibrium point and an asymptotically stable macroscopic (malignant) equilibrium point. The corresponding regions of attraction are separated by the stable manifold of a saddle. The optimal control problem of moving an initial condition that lies in the malignant region into the benign region is formulated and the structure of optimal singular controls is determined.

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Year:  2013        PMID: 23906150     DOI: 10.3934/mbe.2013.10.787

Source DB:  PubMed          Journal:  Math Biosci Eng        ISSN: 1547-1063            Impact factor:   2.080


  6 in total

1.  Dynamical properties of a minimally parameterized mathematical model for metronomic chemotherapy.

Authors:  Heinz Schättler; Urszula Ledzewicz; Behrooz Amini
Journal:  J Math Biol       Date:  2015-06-19       Impact factor: 2.259

Review 2.  Computational oncology--mathematical modelling of drug regimens for precision medicine.

Authors:  Dominique Barbolosi; Joseph Ciccolini; Bruno Lacarelle; Fabrice Barlési; Nicolas André
Journal:  Nat Rev Clin Oncol       Date:  2015-11-24       Impact factor: 66.675

3.  An agent-based modeling framework linking inflammation and cancer using evolutionary principles: description of a generative hierarchy for the hallmarks of cancer and developing a bridge between mechanism and epidemiological data.

Authors:  Gary An; Swati Kulkarni
Journal:  Math Biosci       Date:  2014-08-01       Impact factor: 2.144

4.  Optimal dynamic regimens with artificial intelligence: The case of temozolomide.

Authors:  Nicolas Houy; François Le Grand
Journal:  PLoS One       Date:  2018-06-26       Impact factor: 3.240

5.  On the Role of the Objective in the Optimization of Compartmental Models for Biomedical Therapies.

Authors:  Urszula Ledzewicz; Heinz Schättler
Journal:  J Optim Theory Appl       Date:  2020-09-30       Impact factor: 2.249

6.  Measuring differences between phenomenological growth models applied to epidemiology.

Authors:  Raimund Bürger; Gerardo Chowell; Leidy Yissedt Lara-Díaz
Journal:  Math Biosci       Date:  2021-02-08       Impact factor: 2.144

  6 in total

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