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Optimization of vascular-targeting drugs in a computational model of tumor growth.
- Source :
-
Physical Review E: Statistical, Nonlinear & Soft Matter Physics . Apr2012, Vol. 85 Issue 4, p1-12. 12p. - Publication Year :
- 2012
-
Abstract
- A biophysical tool is introduced that seeks to provide a theoretical basis for helping drug design teams assess the most promising drug targets and design optimal treatment strategies. The tool is grounded in a previously validated computational model of the feedback that occurs between a growing tumor and the evolving vasculature. In this paper, the model is particularly used to explore the therapeutic effectiveness of two drugs that target the tumor vasculature: angiogenesis inhibitors (Als) and vascular disrupting agents (VDAs). Using sensitivity analyses, the impact of VDA dosing parameters is explored, as is the effects of administering a VDA with an AI. Further, a stochastic optimization scheme is utilized to identify an optimal dosing schedule for treatment with an AI and a chemotherapeutic. The treatment regimen identified can successfully halt simulated tumor growth, even after the cessation of therapy. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 15393755
- Volume :
- 85
- Issue :
- 4
- Database :
- Academic Search Index
- Journal :
- Physical Review E: Statistical, Nonlinear & Soft Matter Physics
- Publication Type :
- Academic Journal
- Accession number :
- 77502328
- Full Text :
- https://doi.org/10.1103/PhysRevE.85.041914