Literature DB >> 8652742

Optimal control problems arising in cell-cycle-specific cancer chemotherapy.

A Swierniak1, A Polanski, M Kimmel.   

Abstract

We explore mathematical properties of models of cancer chemotherapy including cell-cycle dependence. Using the mathematical methods of control theory, we demonstrate two assertions of interest for the biomedical community: 1 Periodic chemotherapy protocols are close to the optimum for a wide class of models and have additional favourable properties. 2 Two possible approaches, (a) to minimize the final count of malignant cells and the cumulative effect of the drug on normal cells, or (b) to maximize the final count of normal cells and the cumulative effect of the drug on malignant cells, lead to similar principles of optimization. From the mathematical viewpoint, the paper provides a catalogue of simplest mathematical models of cell-cycle dependent chemotherapy. They can be classified based on the number of compartments and types of drug action modelled. In all these models the optimal controls are complicated by the singular and periodic trajectories and multiple solutions. However, efficient numerical methods have been developed. In simpler cases, it is also possible to provide an exhaustive classification of solutions. We also discuss developments in estimation of cell cycle parameters and cell-cycle dependent drug action.

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Year:  1996        PMID: 8652742

Source DB:  PubMed          Journal:  Cell Prolif        ISSN: 0960-7722            Impact factor:   6.831


  10 in total

Review 1.  Linear quadratic and tumour control probability modelling in external beam radiotherapy.

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Journal:  J Math Biol       Date:  2008-09-30       Impact factor: 2.259

2.  Cell cycle checkpoint models for cellular pharmacology of paclitaxel and platinum drugs.

Authors:  Ardith W El-Kareh; Rachel E Labes; Timothy W Secomb
Journal:  AAPS J       Date:  2008-02-05       Impact factor: 4.009

3.  Nitric oxide induces apoptosis in NALM-6, a leukaemia cell line with low cyclin E protein levels.

Authors:  M Mozart; R Scuderi; F Celsing; M Aguilar-Santelises
Journal:  Cell Prolif       Date:  2001-12       Impact factor: 6.831

4.  Analysis of cell cycle dynamics using probabilistic cell cycle models.

Authors:  Evren Gurkan-Cavusoglu; Jane E Schupp; Timothy J Kinsella; Kenneth A Loparo
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2011

Review 5.  Mathematical modeling as a tool for planning anticancer therapy.

Authors:  Andrzej Swierniak; Marek Kimmel; Jaroslaw Smieja
Journal:  Eur J Pharmacol       Date:  2009-10-13       Impact factor: 4.432

6.  Quantitative analysis of the effects of iododeoxyuridine and ionising radiation treatment on the cell cycle dynamics of DNA mismatch repair deficient human colorectal cancer cells.

Authors:  Evren Gurkan-Cavusoglu; Jane E Schupp; Timothy J Kinsella; Kenneth A Loparo
Journal:  IET Syst Biol       Date:  2013-08-01       Impact factor: 1.615

7.  A flexible and qualitatively stable model for cell cycle dynamics including DNA damage effects.

Authors:  Clark D Jeffries; Charles R Johnson; Tong Zhou; Dennis A Simpson; William K Kaufmann
Journal:  Gene Regul Syst Bio       Date:  2012-04-11

8.  Treatment Analysis in a Cancer Stem Cell Context Using a Tumor Growth Model Based on Cellular Automata.

Authors:  Ángel Monteagudo; José Santos
Journal:  PLoS One       Date:  2015-07-15       Impact factor: 3.240

9.  Cell cycle time series gene expression data encoded as cyclic attractors in Hopfield systems.

Authors:  Anthony Szedlak; Spencer Sims; Nicholas Smith; Giovanni Paternostro; Carlo Piermarocchi
Journal:  PLoS Comput Biol       Date:  2017-11-17       Impact factor: 4.475

Review 10.  In silico modelling of treatment-induced tumour cell kill: developments and advances.

Authors:  Loredana G Marcu; Wendy M Harriss-Phillips
Journal:  Comput Math Methods Med       Date:  2012-07-12       Impact factor: 2.238

  10 in total

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