Literature DB >> 17599363

Optimal control of treatment in a mathematical model of chronic myelogenous leukemia.

Seema Nanda1, Helen Moore, Suzanne Lenhart.   

Abstract

We consider a mathematical model of drug therapy for chronic myelogenous leukemia for an individual patient over a fixed time horizon. The disease dynamics are given by a system of ordinary differential equations that describe the interaction between naive T cells, effector T cells and leukemic cancer cells in a hypothetical patient. We introduce two drug therapies into this model, one a targeted therapy, and the other a broad cytotoxic therapy. Our goal is to find treatment regimens that minimize the cancer cell count and the deleterious effects of the drugs for a given patient. We examine the control setting analytically, and include numerical solutions to illustrate the optimal regimens under various assumptions.

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Year:  2007        PMID: 17599363     DOI: 10.1016/j.mbs.2007.05.003

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  16 in total

Review 1.  Quantitative modeling of chronic myeloid leukemia: insights from radiobiology.

Authors:  Tomas Radivoyevitch; Lynn Hlatky; Julian Landaw; Rainer K Sachs
Journal:  Blood       Date:  2012-02-21       Impact factor: 22.113

2.  Evaluating optimal therapy robustness by virtual expansion of a sample population, with a case study in cancer immunotherapy.

Authors:  Syndi Barish; Michael F Ochs; Eduardo D Sontag; Jana L Gevertz
Journal:  Proc Natl Acad Sci U S A       Date:  2017-07-17       Impact factor: 11.205

3.  Optimization of combination therapy for chronic myeloid leukemia with dosing constraints.

Authors:  Helen Moore; Lewis Strauss; Urszula Ledzewicz
Journal:  J Math Biol       Date:  2018-07-10       Impact factor: 2.259

4.  Cancer Behavior: An Optimal Control Approach.

Authors:  Pedro J Gutiérrez; Irma H Russo; J Russo
Journal:  Int J Immunol Stud       Date:  2009

5.  Model-Based Adaptive Optimal Design (MBAOD) Improves Combination Dose Finding Designs: an Example in Oncology.

Authors:  Philippe B Pierrillas; Sylvain Fouliard; Marylore Chenel; Andrew C Hooker; Lena E Friberg; Mats O Karlsson
Journal:  AAPS J       Date:  2018-03-07       Impact factor: 4.009

6.  Evolutionary Dynamics of Chronic Myeloid Leukemia Progression: the Progression-Inhibitory Effect of Imatinib.

Authors:  Robert C Jackson; Tomas Radivoyevitch
Journal:  AAPS J       Date:  2016-03-23       Impact factor: 4.009

7.  Optimal control of hepatitis C antiviral treatment programme delivery for prevention amongst a population of injecting drug users.

Authors:  Natasha K Martin; Ashley B Pitcher; Peter Vickerman; Anna Vassall; Matthew Hickman
Journal:  PLoS One       Date:  2011-08-11       Impact factor: 3.240

8.  dNTP Supply Gene Expression Patterns after P53 Loss.

Authors:  Tomas Radivoyevitch; Yogen Saunthararajah; John Pink; Gina Ferris; Ian Lent; Mark Jackson; Damian Junk; Charles A Kunos
Journal:  Cancers (Basel)       Date:  2012-11-20       Impact factor: 6.639

9.  Drug target optimization in chronic myeloid leukemia using innovative computational platform.

Authors:  Ryan Chuang; Benjamin A Hall; David Benque; Byron Cook; Samin Ishtiaq; Nir Piterman; Alex Taylor; Moshe Vardi; Steffen Koschmieder; Berthold Gottgens; Jasmin Fisher
Journal:  Sci Rep       Date:  2015-02-03       Impact factor: 4.379

10.  A patient-specific therapeutic approach for tumour cell population extinction and drug toxicity reduction using control systems-based dose-profile design.

Authors:  Suhela Kapoor; V P Subramanyam Rallabandi; Chandrashekhar Sakode; Radhakant Padhi; Prasun K Roy
Journal:  Theor Biol Med Model       Date:  2013-12-26       Impact factor: 2.432

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