DocumentCode :
1507722
Title :
A Minimal Model of Tumor Growth Inhibition in Combination Regimens Under the Hypothesis of No Interaction Between Drugs
Author :
Magni, Paolo ; Terranova, Nadia ; Del Bene, Francesca ; Germani, Massimiliano ; De Nicolao, Giuseppe
Author_Institution :
Dipt. di Ing. Ind. e dell´´Inf., Univ. degli Studi di Pavia, Pavia, Italy
Volume :
59
Issue :
8
fYear :
2012
Firstpage :
2161
Lastpage :
2170
Abstract :
One important issue in the preclinical development of an anticancer drug is the assessment of the compound under investigation when administered in combination with other drugs. Several experiments are routinely conducted in xenograft mice to evaluate if drugs interact or not. Experimental data are generally qualitatively analyzed on empirical basis. The ability of deriving from single drug experiments a reference response to the joint administrations, assuming no interaction, and comparing it to real responses would be key to recognize synergic and antagonist compounds. Therefore, in this paper, the minimal model of tumor growth inhibition (TGI), previously developed for a single drug, is reformulated to account for the effects of noninteracting drugs and simulate, under this hypothesis, combination regimens. The model is derived from a minimal set of basic assumptions that include and extend those formulated at cellular level for the single drug administration. The tumor growth dynamics is well approximated by the deterministic evolution of its expected value that is obtained through the solution of an ordinary and several partial differential equations. Under suitable assumptions on the cell death process, the model reduces to a lumped parameter model that represents the extension of the very popular Simeoni TGI model to the combined administration of noninteracting drugs.
Keywords :
cancer; drugs; tumours; Simeoni TGI model; antagonist compounds; anticancer drug; combination regimen; synergic compounds; tumor growth inhibition; xenograft mice; Compounds; Drugs; Equations; Mathematical model; Mice; Probability density function; Tumors; Anticancer drug discovery; Poisson models; drug combination regimen; pharmacodynamic models; preclinical studies; stochastic models; tumor growth models; xenograft mice; Animals; Antineoplastic Agents; Cell Line, Tumor; Drug Discovery; Drug Interactions; Humans; Mice; Models, Biological; Neoplasms, Experimental; Xenograft Model Antitumor Assays;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2012.2197680
Filename :
6194294
Link To Document :
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