Development of a 3D Mathematical Model for a Doxorubicin Controlled Release System using Pluronic Gel for Breast Cancer Treatment
Authors: W. Kaowumpai, D. Koolpiruck, K. Viravaidya
Abstract:
Female breast cancer is the second in frequency after cervical cancer. Surgery is the most common treatment for breast cancer, followed by chemotherapy as a treatment of choice. Although effective, it causes serious side effects. Controlled-release drug delivery is an alternative method to improve the efficacy and safety of the treatment. It can release the dosage of drug between the minimum effect concentration (MEC) and minimum toxic concentration (MTC) within tumor tissue and reduce the damage of normal tissue and the side effect. Because an in vivo experiment of this system can be time-consuming and labor-intensive, a mathematical model is desired to study the effects of important parameters before the experiments are performed. Here, we describe a 3D mathematical model to predict the release of doxorubicin from pluronic gel to treat human breast cancer. This model can, ultimately, be used to effectively design the in vivo experiments.
Keywords: Breast Cancer, Doxorubicin, Controlled ReleaseSystem, Diffusion and Convection Equation.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1334654
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[1] B. Reisfeld, S. Kalyanasundaram, and K. Leong "A mathematical model of polymeric controlled drug release and transport in the brain" Journal of Controlled Release vol.36. pp. 199-207, 1995.
[2] Brannon-Peppas L 1997 Polymers in Controlled Drug Delivery , Medical Plastics and Biomaterials Magazine, (Online) Available at: http://www.devicelink.com/mpb/archive/97/11/003.html
[3] W. Kaowumpai, D. Koolpiruck, and K. Viravaidya "Development of a mathematical model for Doxorubicin controlled release system using Pluronic gel for breast cancer" Papers of Technical Meeting on Medical and Biological Engineering, IEE Japan vol.06, no. 95-115, pp. 65-69, 2006.
[4] S. Kalyanasundaram, V. D. Calhoun, K. W. Andleong. "A finite element model for predicting the distribution of drugs delivered in tracranially to the brain" Am J Physiol Regul Integr Comp Physiol vol. 273. pp. 1810-1821. 1997.
[5] Wikipedia, the free encyclopedia. (Online) Available at: http://en.wikipedia.org/wiki/Logistic_function.
[6] Natonal Institutes of Health National Library of Medicine Bethesda, (Online) Available at: http://vhnet.nlm.nih.gov/
[7] V. L. Andolina, et al. Mammographic Imaging (A practical guide). J.B.Lipp. incott Co. Philadelphia. 1992.
[8] American Joint Committee on Cancer.
[9] D. Christopher, Abramson Cancer Center of the University of Pennsylvania.
[10] D. S .Fischer, et al. The Cancer Chemotheraphy Handbook. Mosby an Affiliate of Elsevier. 2003.
[11] Steven B. Halls Professional Corporation, (Online) Available at: http://www.halls.md/bsa/bsaVu5.htm
[12] C. F. Lacy, et al. Drag Information Handbook International with Canadian and International Drug Monographs. Lexi-Comp. 2005.
[13] Charlie's Clinical Calculators, (Online) Available at: http://www.fpnotebook.com/REN80.htm
[14] D. Caminada, C. Escher, and K. Fent, "Cytotoxicity of pharmaceuticals found in aquatic systems: Comparison of PLHC-1 and RTG-2 fish cell lines" ScienceDirect - Aquatic Toxicology vol. 79. pp. 114-123. 2006.
[15] Jan Lankelma, Rafael Ferna'ndez Luque, Henk Dekker, Wim Schinkel, and Herbert M. Pinedo. "A Mathematical Model of Drug Transport in Human Breast Cancer" Microvascular Research vol 59, pp. 149-161, 2000.