Literature DB >> 23063290

Towards in silico oncology: adapting a four dimensional nephroblastoma treatment model to a clinical trial case based on multi-method sensitivity analysis.

Eleni Ch Georgiadi1, Dimitra D Dionysiou, Norbert Graf, Georgios S Stamatakos.   

Abstract

In the past decades a great progress in cancer research has been made although medical treatment is still widely based on empirically established protocols which have many limitations. Computational models address such limitations by providing insight into the complex biological mechanisms of tumor progression. A set of clinically-oriented, multiscale models of solid tumor dynamics has been developed by the In Silico Oncology Group (ISOG), Institute of Communication and Computer Systems (ICCS)-National Technical University of Athens (NTUA) to study cancer growth and response to treatment. Within this context using certain representative parameter values, tumor growth and response have been modeled under a cancer preoperative chemotherapy protocol in the framework of the SIOP 2001/GPOH clinical trial. A thorough cross-method sensitivity analysis of the model has been performed. Based on the sensitivity analysis results, a reasonable adaptation of the values of the model parameters to a real clinical case of bilateral nephroblastomatosis has been achieved. The analysis presented supports the potential of the model for the study and eventually the future design of personalized treatment schemes and/or schedules using the data obtained from in vitro experiments and clinical studies.
Copyright © 2012 Elsevier Ltd. All rights reserved.

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Year:  2012        PMID: 23063290     DOI: 10.1016/j.compbiomed.2012.08.008

Source DB:  PubMed          Journal:  Comput Biol Med        ISSN: 0010-4825            Impact factor:   4.589


  6 in total

Review 1.  Dendritic cell vaccination for glioblastoma multiforme: review with focus on predictive factors for treatment response.

Authors:  Joost Dejaegher; Stefaan Van Gool; Steven De Vleeschouwer
Journal:  Immunotargets Ther       Date:  2014-03-13

2.  A Modular Repository-based Infrastructure for Simulation Model Storage and Execution Support in the Context of In Silico Oncology and In Silico Medicine.

Authors:  Nikolaos A Christodoulou; Nikolaos E Tousert; Eleni Ch Georgiadi; Katerina D Argyri; Fay D Misichroni; Georgios S Stamatakos
Journal:  Cancer Inform       Date:  2016-10-27

Review 3.  Navigating Multi-Scale Cancer Systems Biology Towards Model-Driven Clinical Oncology and Its Applications in Personalized Therapeutics.

Authors:  Mahnoor Naseer Gondal; Safee Ullah Chaudhary
Journal:  Front Oncol       Date:  2021-11-24       Impact factor: 6.244

4.  Differentiation resistance through altered retinoblastoma protein function in acute lymphoblastic leukemia: in silico modeling of the deregulations in the G1/S restriction point pathway.

Authors:  Eleftherios Ouzounoglou; Dimitra Dionysiou; Georgios S Stamatakos
Journal:  BMC Syst Biol       Date:  2016-03-01

5.  Workflow-driven clinical decision support for personalized oncology.

Authors:  Anca Bucur; Jasper van Leeuwen; Nikolaos Christodoulou; Kamana Sigdel; Katerina Argyri; Lefteris Koumakis; Norbert Graf; Georgios Stamatakos
Journal:  BMC Med Inform Decis Mak       Date:  2016-07-21       Impact factor: 2.796

6.  In Silico Oncology: Quantification of the In Vivo Antitumor Efficacy of Cisplatin-Based Doublet Therapy in Non-Small Cell Lung Cancer (NSCLC) through a Multiscale Mechanistic Model.

Authors:  Eleni Kolokotroni; Dimitra Dionysiou; Christian Veith; Yoo-Jin Kim; Jörg Sabczynski; Astrid Franz; Aleksandar Grgic; Jan Palm; Rainer M Bohle; Georgios Stamatakos
Journal:  PLoS Comput Biol       Date:  2016-09-22       Impact factor: 4.475

  6 in total

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