Literature DB >> 24050133

Modeling of human tumor xenografts and dose rationale in oncology.

Monica Simeoni, Giuseppe De Nicolao, Paolo Magni, Maurizio Rocchetti, Italo Poggesi.   

Abstract

Xenograft models are commonly used in oncology drug development. Although there are discussions about their ability to generate meaningful data for the translation from animal to humans, it appears that better data quality and better design of the preclinical experiments, together with appropriate data analysis approaches could make these data more informative for clinical development. An approach based on mathematical modeling is necessary to derive experiment-independent parameters which can be linked with clinically relevant endpoints. Moreover, the inclusion of biomarkers as predictors of efficacy is a key step towards a more general mechanism-based strategy.

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Year:  2013        PMID: 24050133     DOI: 10.1016/j.ddtec.2012.07.004

Source DB:  PubMed          Journal:  Drug Discov Today Technol        ISSN: 1740-6749


  17 in total

1.  Biomarker- versus drug-driven tumor growth inhibition models: an equivalence analysis.

Authors:  Maria Luisa Sardu; Italo Poggesi; Giuseppe De Nicolao
Journal:  J Pharmacokinet Pharmacodyn       Date:  2015-07-26       Impact factor: 2.745

2.  Optimal Design for Informative Protocols in Xenograft Tumor Growth Inhibition Experiments in Mice.

Authors:  Giulia Lestini; France Mentré; Paolo Magni
Journal:  AAPS J       Date:  2016-06-15       Impact factor: 4.009

3.  Modeling NSCLC progression: recent advances and opportunities available.

Authors:  Ahmed Abbas Suleiman; Lucia Nogova; Uwe Fuhr
Journal:  AAPS J       Date:  2013-02-13       Impact factor: 4.009

4.  A predictive pharmacokinetic-pharmacodynamic model of tumor growth kinetics in xenograft mice after administration of anticancer agents given in combination.

Authors:  Nadia Terranova; Massimiliano Germani; Francesca Del Bene; Paolo Magni
Journal:  Cancer Chemother Pharmacol       Date:  2013-06-29       Impact factor: 3.333

5.  Murine Tumor Models for Oncolytic Rhabdo-Virotherapy.

Authors:  Theresa Falls; Dominic Guy Roy; John Cameron Bell; Marie-Claude Bourgeois-Daigneault
Journal:  ILAR J       Date:  2016

6.  Pharmacodynamic modeling of combined chemotherapeutic effects predicts synergistic activity of gemcitabine and trabectedin in pancreatic cancer cells.

Authors:  Xin Miao; Gilbert Koch; Robert M Straubinger; William J Jusko
Journal:  Cancer Chemother Pharmacol       Date:  2015-11-25       Impact factor: 3.333

7.  Systems pharmacology approaches for optimization of antiangiogenic therapies: challenges and opportunities.

Authors:  Satish Sharan; Sukyung Woo
Journal:  Front Pharmacol       Date:  2015-02-20       Impact factor: 5.810

8.  A review of mixed-effects models of tumor growth and effects of anticancer drug treatment used in population analysis.

Authors:  B Ribba; N H Holford; P Magni; I Trocóniz; I Gueorguieva; P Girard; C Sarr; M Elishmereni; C Kloft; L E Friberg
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2014-05-07

Review 9.  Advances and computational tools towards predictable design in biological engineering.

Authors:  Lorenzo Pasotti; Susanna Zucca
Journal:  Comput Math Methods Med       Date:  2014-08-03       Impact factor: 2.238

10.  Classical mathematical models for description and prediction of experimental tumor growth.

Authors:  Sébastien Benzekry; Clare Lamont; Afshin Beheshti; Amanda Tracz; John M L Ebos; Lynn Hlatky; Philip Hahnfeldt
Journal:  PLoS Comput Biol       Date:  2014-08-28       Impact factor: 4.475

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