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Effect of Vascular Normalization on Drug Delivery to Different Stages of Tumor Progression: In-Silico Analysis Publisher



Moradi Kashkooli F1, 2 ; Soltani M1, 3, 4, 5, 6 ; Rezaeian M1 ; Meaney C2 ; Hamedi MH1 ; Kohandel M2
Authors
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Authors Affiliations
  1. 1. Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran
  2. 2. Department of Applied Mathematics, University of Waterloo, Waterloo, ON, Canada
  3. 3. Advanced Bioengineering Initiative Center, Computational Medicine Center, K. N. Toosi University of Technology, Tehran, Iran
  4. 4. Department of Electrical and Computer Engineering, University of Waterloo, Ontario, Canada
  5. 5. Centre for Biotechnology and Bioengineering (CBB), University of Waterloo, Waterloo, ON, Canada
  6. 6. Cancer Biology Research Center, Cancer Institute of Iran, Tehran University of Medical Sciences, Tehran, Iran

Source: Journal of Drug Delivery Science and Technology Published:2020


Abstract

Vascular normalization (VN) by anti-angiogenic factors may be efficacious for improving drug delivery in solid tumors. In the present study, a 3D computational model is employed to provide supporting evidence of VN therapy's efficacy by investigating the effect of VN on the distribution of interstitial fluid velocity (IFV), interstitial fluid pressure (IFP), and solute transport. In addition, tumors of various sizes, representing the stages of tumor progression, are investigated to see at which sizes VN therapy is efficient. To model a reasonable distribution of heterogeneous microvascular density (MVD) in the tumor, two different zones–a necrotic core and a vascularized exterior–are considered. Three different types of VN therapy are examined in this study: 0% VN (treatment without VN), 50% VN, and 100% VN. A mathematical function is also used to model the highly heterogeneous distribution of MVD in a tumor. The results demonstrate that VN may improve the drug delivery to solid tumors by decreasing IFP and enhancing drug extravasation from the microvascular network. However, these advantages are largely dependent on the size of tumor, being stronger for specific ranges of tumor size. The best treatment results are obtained by: 50% VN for tumors up to a 7 mm size, 100% VN for 7–13 mm tumors, and 0% VN for larger than 13 mm tumors. Consequently, for the best drug delivery efficacy, VN therapy must be applied to tumors at a specific stage of tumor progression. Results are obtained by examining the area under the curve (AUC) metric, an important evaluation criterion for drug delivery. The findings of this study can serve as qualitative guidelines for designing VN therapy as an adjuvant treatment. © 2020 Elsevier B.V.
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