A mathematical model to study the effects of drugs administration on tumor growth dynamics
- PMID: 16516246
- DOI: 10.1016/j.mbs.2005.12.028
A mathematical model to study the effects of drugs administration on tumor growth dynamics
Abstract
A mathematical model for describing the cancer growth dynamics in response to anticancer agents administration in xenograft models is discussed. The model consists of a system of ordinary differential equations involving five parameters (three for describing the untreated growth and two for describing the drug action). Tumor growth in untreated animals is modelled by an exponential growth followed by a linear growth. In treated animals, tumor growth rate is decreased by an additional factor proportional to both drug concentration and proliferating cells. The mathematical analysis conducted in this paper highlights several interesting properties of this tumor growth model. It suggests also effective strategies to design in vivo experiments in animals with potential saving of time and resources. For example, the drug concentration threshold for the tumor eradication, the delay between drug administration and tumor regression, and a time index that measures the efficacy of a treatment are derived and discussed. The model has already been employed in several drug discovery projects. Its application on a data set coming from one of these projects is discussed in this paper.
Similar articles
-
A minimal model of tumor growth inhibition.IEEE Trans Biomed Eng. 2008 Dec;55(12):2683-90. doi: 10.1109/TBME.2008.913420. IEEE Trans Biomed Eng. 2008. PMID: 19126447
-
A minimal model of tumor growth inhibition in combination regimens under the hypothesis of no interaction between drugs.IEEE Trans Biomed Eng. 2012 Aug;59(8):2161-70. doi: 10.1109/TBME.2012.2197680. Epub 2012 May 3. IEEE Trans Biomed Eng. 2012. PMID: 22575633
-
Voreloxin, formerly SNS-595, has potent activity against a broad panel of cancer cell lines and in vivo tumor models.Cancer Chemother Pharmacol. 2009 Jun;64(1):53-65. doi: 10.1007/s00280-008-0850-3. Epub 2008 Oct 19. Cancer Chemother Pharmacol. 2009. PMID: 18931998
-
The challenge of selecting the 'right' in vivo oncology pharmacology model.Curr Opin Pharmacol. 2010 Aug;10(4):391-6. doi: 10.1016/j.coph.2010.06.012. Epub 2010 Jul 13. Curr Opin Pharmacol. 2010. PMID: 20634135 Review.
-
Evaluating drug efficacy and toxicology in three dimensions: using synthetic extracellular matrices in drug discovery.Acc Chem Res. 2008 Jan;41(1):139-48. doi: 10.1021/ar7000827. Epub 2007 Jul 27. Acc Chem Res. 2008. PMID: 17655274 Review.
Cited by
-
Negligible Long-Term Impact of Nonlinear Growth Dynamics on Heterogeneity in Models of Cancer Cell Populations.Bull Math Biol. 2025 Jan 3;87(2):18. doi: 10.1007/s11538-024-01395-w. Bull Math Biol. 2025. PMID: 39751987 Free PMC article.
-
Systems pharmacological analysis of paclitaxel-mediated tumor priming that enhances nanocarrier deposition and efficacy.J Pharmacol Exp Ther. 2013 Jan;344(1):103-12. doi: 10.1124/jpet.112.199109. Epub 2012 Oct 31. J Pharmacol Exp Ther. 2013. PMID: 23115220 Free PMC article.
-
Extended transit compartment model to describe tumor delay using Coxian distribution.Sci Rep. 2022 Jun 16;12(1):10086. doi: 10.1038/s41598-022-13836-4. Sci Rep. 2022. PMID: 35710563 Free PMC article.
-
Steering the Clinical Translation of Delivery Systems for Drugs and Health Products.Pharmaceutics. 2020 Apr 13;12(4):350. doi: 10.3390/pharmaceutics12040350. Pharmaceutics. 2020. PMID: 32294939 Free PMC article.
-
Modeling restoration of gefitinib efficacy by co-administration of MET inhibitors in an EGFR inhibitor-resistant NSCLC xenograft model: A tumor-in-host DEB-based approach.CPT Pharmacometrics Syst Pharmacol. 2021 Nov;10(11):1396-1411. doi: 10.1002/psp4.12710. Epub 2021 Oct 28. CPT Pharmacometrics Syst Pharmacol. 2021. PMID: 34708556 Free PMC article.
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources