Literature DB >> 17069522

Mathematical modeling of cancer progression and response to chemotherapy.

Sandeep Sanga1, John P Sinek, Hermann B Frieboes, Mauro Ferrari, John P Fruehauf, Vittorio Cristini.   

Abstract

The complex, constantly evolving and multifaceted nature of cancer has made it difficult to identify unique molecular and pathophysiological signatures for each disease variant, consequently hindering development of effective therapies. Mathematical modeling and computer simulation are tools that can provide a robust framework to better understand cancer progression and response to chemotherapy. Successful therapeutic agents must overcome biological barriers occurring at multiple space and time scales and still reach targets at sufficient concentrations. A multiscale computer simulator founded on the integration of experimental data and mathematical models can provide valuable insights into these processes and establish a technology platform for analyzing the effectiveness of chemotherapeutic drugs, with the potential to cost-effectively and efficiently screen drug candidates during the drug-development process.

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Year:  2006        PMID: 17069522     DOI: 10.1586/14737140.6.10.1361

Source DB:  PubMed          Journal:  Expert Rev Anticancer Ther        ISSN: 1473-7140            Impact factor:   4.512


  38 in total

1.  Tackling the problems of tumour chemotherapy by optimal drug scheduling.

Authors:  Ambili Remesh
Journal:  J Clin Diagn Res       Date:  2013-05-31

Review 2.  Predictive oncology: a review of multidisciplinary, multiscale in silico modeling linking phenotype, morphology and growth.

Authors:  Sandeep Sanga; Hermann B Frieboes; Xiaoming Zheng; Robert Gatenby; Elaine L Bearer; Vittorio Cristini
Journal:  Neuroimage       Date:  2007-06-07       Impact factor: 6.556

3.  Multiparameter computational modeling of tumor invasion.

Authors:  Elaine L Bearer; John S Lowengrub; Hermann B Frieboes; Yao-Li Chuang; Fang Jin; Steven M Wise; Mauro Ferrari; David B Agus; Vittorio Cristini
Journal:  Cancer Res       Date:  2009-04-14       Impact factor: 12.701

4.  A New Ghost Cell/Level Set Method for Moving Boundary Problems: Application to Tumor Growth.

Authors:  Paul Macklin; John S Lowengrub
Journal:  J Sci Comput       Date:  2008-06-01       Impact factor: 2.592

5.  The effect of interstitial pressure on therapeutic agent transport: coupling with the tumor blood and lymphatic vascular systems.

Authors:  Min Wu; Hermann B Frieboes; Mark A J Chaplain; Steven R McDougall; Vittorio Cristini; John S Lowengrub
Journal:  J Theor Biol       Date:  2014-04-19       Impact factor: 2.691

Review 6.  Computational approaches to analyse and predict small molecule transport and distribution at cellular and subcellular levels.

Authors:  Kyoung Ah Min; Xinyuan Zhang; Jing-yu Yu; Gus R Rosania
Journal:  Biopharm Drug Dispos       Date:  2013-12-10       Impact factor: 1.627

7.  Computer simulation of glioma growth and morphology.

Authors:  Hermann B Frieboes; John S Lowengrub; S Wise; X Zheng; Paul Macklin; Elaine L Bearer; Vittorio Cristini
Journal:  Neuroimage       Date:  2007-03-23       Impact factor: 6.556

Review 8.  In silico cancer modeling: is it ready for prime time?

Authors:  Thomas S Deisboeck; Le Zhang; Jeongah Yoon; Jose Costa
Journal:  Nat Clin Pract Oncol       Date:  2008-10-14

9.  Of mice and men: the evolution of animal welfare guidelines for cancer research.

Authors:  N Dey; P De; B R Smith; B Leyland-Jones
Journal:  Br J Cancer       Date:  2010-05-25       Impact factor: 7.640

10.  Multiscale modelling and nonlinear simulation of vascular tumour growth.

Authors:  Paul Macklin; Steven McDougall; Alexander R A Anderson; Mark A J Chaplain; Vittorio Cristini; John Lowengrub
Journal:  J Math Biol       Date:  2008-09-10       Impact factor: 2.259

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