Literature DB >> 33095747

Pseudo-spectral method for controlling the drug dosage in cancer.

Mostafa Nazari1, Morteza Nazari2, Mohammad Hadi Noori Skandari2.   

Abstract

A mixed chemotherapy-immunotherapy treatment protocol is developed for cancer treatment. Chemotherapy pushes the trajectory of the system towards the desired equilibrium point, and then immunotherapy alters the dynamics of the system by affecting the parameters of the system. A co-existing cancerous equilibrium point is considered as the desired equilibrium point instead of the tumour-free equilibrium. Chemotherapy protocol is derived using the pseudo-spectral (PS) controller due to its high convergence rate and simple implementation structure. Thus, one of the contributions of this study is simplifying the design procedure and reducing the controller computational load in comparison with Lyapunov-based controllers. In this method, an infinite-horizon optimal control problem is proposed for a non-linear cancer model. Then, the infinite-horizon optimal control of cancer is transformed into a non-linear programming problem. The efficient Legendre PS scheme is suggested to solve the proposed problem. Then, the dynamics of the system is modified by immunotherapy is another contribution. To restrict the upper limit of the chemo-drug dose based on the age of the patients, a Mamdani fuzzy system is designed, which is not present yet. Simulation results on four different dynamics cases how the efficiency of the proposed treatment strategy.

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Year:  2020        PMID: 33095747      PMCID: PMC8687205          DOI: 10.1049/iet-syb.2020.0054

Source DB:  PubMed          Journal:  IET Syst Biol        ISSN: 1751-8849            Impact factor:   1.615


  15 in total

1.  Mixed immunotherapy and chemotherapy of tumors: modeling, applications and biological interpretations.

Authors:  L G de Pillis; W Gu; A E Radunskaya
Journal:  J Theor Biol       Date:  2005-09-08       Impact factor: 2.691

Review 2.  Causes, consequences, and reversal of immune system aging.

Authors:  Encarnacion Montecino-Rodriguez; Beata Berent-Maoz; Kenneth Dorshkind
Journal:  J Clin Invest       Date:  2013-03-01       Impact factor: 14.808

3.  Optimal dosing of cancer chemotherapy using model predictive control and moving horizon state/parameter estimation.

Authors:  Tao Chen; Norman F Kirkby; Raj Jena
Journal:  Comput Methods Programs Biomed       Date:  2012-06-25       Impact factor: 5.428

4.  Multiple model predictive control for optimal drug administration of mixed immunotherapy and chemotherapy of tumours.

Authors:  N Sharifi; S Ozgoli; A Ramezani
Journal:  Comput Methods Programs Biomed       Date:  2017-03-16       Impact factor: 5.428

Review 5.  Role of optimal control theory in cancer chemotherapy.

Authors:  G W Swan
Journal:  Math Biosci       Date:  1990-10       Impact factor: 2.144

6.  Chemotherapy for tumors: an analysis of the dynamics and a study of quadratic and linear optimal controls.

Authors:  L G de Pillis; W Gu; K R Fister; T Head; K Maples; A Murugan; T Neal; K Yoshida
Journal:  Math Biosci       Date:  2006-05-26       Impact factor: 2.144

7.  Determination of an optimal control strategy for drug administration in tumor treatment using multi-objective optimization differential evolution.

Authors:  Fran Sérgio Lobato; Vinicius Silvério Machado; Valder Steffen
Journal:  Comput Methods Programs Biomed       Date:  2016-04-11       Impact factor: 5.428

8.  Adaptive back-stepping cancer control using Legendre polynomials.

Authors:  Saeed Khorashadizadeh; Ali Akbarzadeh Kalat
Journal:  IET Syst Biol       Date:  2020-02       Impact factor: 1.615

9.  Cancer dynamics for identical twin brothers.

Authors:  Ali Ghaffari; Mostafa Khazaee
Journal:  Theor Biol Med Model       Date:  2012-02-06       Impact factor: 2.432

10.  Adaptive non-linear control for cancer therapy through a Fokker-Planck observer.

Authors:  Ehsan Shakeri; Gholamreza Latif-Shabgahi; Amir Esmaeili Abharian
Journal:  IET Syst Biol       Date:  2018-04       Impact factor: 1.615

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