4.7 Article

A mathematical model to predict nanomedicine pharmacokinetics and tumor delivery

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ELSEVIER
DOI: 10.1016/j.csbj.2020.02.014

Keywords

Cancer nanotherapy; Enhanced permeability and retention effect; Mechanistic mathematical modeling; PBPK; Pharmacokinetics; Sensitivity analysis

Funding

  1. National Science Foundation [DMS-1930583]
  2. National Institutes of Health (NIH) [1U01CA196403, 1U01CA213759, 1R01CA226537, 1R01CA222007, U54CA210181]

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Towards clinical translation of cancer nanomedicine, it is important to systematically investigate the various parameters related to nanoparticle (NP) physicochemical properties, tumor characteristics, and inter-individual variability that affect the tumor delivery efficiency of therapeutic nanomaterials. Comprehensive investigation of these parameters using traditional experimental approaches is impractical due to the vast parameter space; mathematical models provide a more tractable approach to navigate through such a multidimensional space. To this end, we have developed a predictive mathematical model of whole-body NP pharmacokinetics and their tumor delivery in vivo, and have conducted local and global sensitivity analyses to identify the factors that result in low tumor delivery efficiency and high off-target accumulation of NPs. Our analyses reveal that NP degradation rate, tumor blood viscosity, NP size, tumor vascular fraction, and tumor vascular porosity are the key parameters in governing NP kinetics in the tumor interstitium. The impact of these parameters on tumor delivery efficiency of NPs is discussed, and optimal values for maximizing NP delivery are presented. (C) 2020 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.

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