Literature DB >> 9401351

A mathematical model of drug resistance: heterogeneous tumors.

J C Panetta1.   

Abstract

A mathematical model is developed to describe the growth and control of a heterogeneous tumor. The main aspect of the model is that it takes into account induced drug resistance. The mathematical model is a system of two ordinary differential equations that describes the growth of the cancer along with the effects of chemotherapy. The model is analyzed to determine what some of the critical parameters are; how we determine an effective treatment; how combination chemotherapy should be delivered; and how this model may help us develop more effective cancer chemotherapeutic treatments.

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Year:  1998        PMID： 9401351     DOI： 10.1016/s0025-5564(97)00080-1

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


  17 in total

1.  Spatio-temporal tumour model for analysis and mechanism of action of intracellular drug accumulation.

Authors:  Somna Mishra; V K Katiyar
Journal:  J Biosci       Date:  2008-09       Impact factor: 1.826

Review 2.  Toward an Ising model of cancer and beyond.

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Journal:  Phys Biol       Date:  2011-02-07       Impact factor: 2.583

3.  Model-based assessment of erlotinib effect in vitro measured by real-time cell analysis.

Authors:  Stephan Benay; Christophe Meille; Stefan Kustermann; Isabelle Walter; Antje Walz; P Alexis Gonsard; Elina Pietilae; Nicole Kratochwil; Athanassios Iliadis; Adrian Roth; Thierry Lave
Journal:  J Pharmacokinet Pharmacodyn       Date:  2015-03-31       Impact factor: 2.745

Review 4.  The dynamics of drug resistance: a mathematical perspective.

Authors:  Orit Lavi; Michael M Gottesman; Doron Levy
Journal:  Drug Resist Updat       Date:  2012-03-03       Impact factor: 18.500

Review 5.  Molecular biology of breast cancer metastasis. The use of mathematical models to determine relapse and to predict response to chemotherapy in breast cancer.

Authors:  S E Clare; F Nakhlis; J C Panetta
Journal:  Breast Cancer Res       Date:  2000-07-21       Impact factor: 6.466

6.  Addressing genetic tumor heterogeneity through computationally predictive combination therapy.

Authors:  Boyang Zhao; Justin R Pritchard; Douglas A Lauffenburger; Michael T Hemann
Journal:  Cancer Discov       Date:  2013-12-06       Impact factor: 39.397

7.  Multi-objective optimal chemotherapy control model for cancer treatment.

Authors:  S Algoul; M S Alam; M A Hossain; M A A Majumder
Journal:  Med Biol Eng Comput       Date:  2010-10-01       Impact factor: 2.602

8.  The impact of cell density and mutations in a model of multidrug resistance in solid tumors.

Authors:  James Greene; Orit Lavi; Michael M Gottesman; Doron Levy
Journal:  Bull Math Biol       Date:  2014-02-20       Impact factor: 1.758

Review 9.  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

10.  Optimum multi-drug regime for compartment model of tumour: cell-cycle-specific dynamics in the presence of resistance.

Authors:  Bharti Panjwani; Vijander Singh; Asha Rani; Vijay Mohan
Journal:  J Pharmacokinet Pharmacodyn       Date:  2021-03-22       Impact factor: 2.745
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