Rational nanoparticle design: Optimization using insights from experiments and mathematical models

Richfield, Owen; Piotrowski-Daspit, Alexandra S.; Shin, Kwangsoo; Saltzman, W. Mark

doi:10.1016/j.jconrel.2023.07.018

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2024

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Cited by 3 publications

References 115 publications

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The interaction between particles and vascular endothelium in blood flow

Li,

Zou,

et al. 2024

Advanced Drug Delivery Reviews

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The interaction between particles and vascular endothelium in blood flow

Li,

Zou,

et al. 2024

Advanced Drug Delivery Reviews

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Predicting the removal efficiency of titanium dioxide nanoparticles in an activated sludge system using fate modeling depending on the operating conditions

Ban,

Portus,

Lee

et al. 2024

Journal of Water Process Engineering

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A Minimal PBPK Model Describes the Differential Disposition of Silica Nanoparticles In Vivo

Parrot,

Cave,

Pelaez

et al. 2024

Preprint

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Nanoparticles (NPs) have emerged as promising candidates for drug delivery due to their tunable physical and chemical properties. Among these, silica nanoparticles (SiNPs) are particularly valued for their biocompatibility and adaptability in applications like drug delivery and medical imaging. However, predicting SiNP biodistribution and clearance remains a significant challenge. To address this, we developed a minimal physiologically-based pharmacokinetic (mPBPK) model to simulate the systemic disposition of SiNPs, calibrated using in vivo PK data from mice. The model assesses how variations in surface charge, size, porosity, and geometry influence SiNP biodistribution across key organs, including the kidneys, lungs, liver, and spleen. A global sensitivity analysis identified the most influential parameters, with the unbound fraction and elimination rate constants for the kidneys and MPS emerging as critical determinants of SiNP clearance. Non-compartmental analysis (NCA) further revealed that aminated SiNPs exhibit high accumulation in the liver, spleen, and kidneys, while mesoporous SiNPs primarily accumulate in the lungs. Rod-shaped SiNPs showed faster clearance compared to spherical NPs. The mPBPK model was extrapolated to predict SiNP behavior in humans, yielding strong predictive accuracy with Pearson correlation coefficients of 0.98 for mice and 0.92 for humans. This model provides a robust framework for predicting the pharmacokinetics of diverse SiNPs, offering valuable insights for optimizing NP-based drug delivery systems and guiding the translation of these therapies from preclinical models to human applications.

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Rational nanoparticle design: Optimization using insights from experiments and mathematical models

Cited by 3 publications

References 115 publications

The interaction between particles and vascular endothelium in blood flow

The interaction between particles and vascular endothelium in blood flow

Predicting the removal efficiency of titanium dioxide nanoparticles in an activated sludge system using fate modeling depending on the operating conditions

A Minimal PBPK Model Describes the Differential Disposition of Silica Nanoparticles In Vivo

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