Prediction of silica nanoparticle biodistribution using a calibrated physiologically based model: Unbound fraction and elimination rate constants for the kidneys and phagocytosis identified as major determinants.

IF 0.7 4区 医学 Q4 PHARMACOLOGY & PHARMACY
Madison Parrot, Joseph Cave, Maria J Pelaez, Hamidreza Ghandehari, Prashant Dogra, Venkata Yellepeddi
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引用次数: 0

Abstract

Objectives: This study aimed to develop a minimal physiologically based pharmacokinetic (mPBPK) model to predict the biodistribution of silica nanoparticles (SiNPs) and evaluate how variations in surface charge, size, porosity, and geometry influence their systemic disposition.

Materials: The mPBPK model was calibrated using in vivo pharmacokinetic data from mice administered aminated, mesoporous, and rod-shaped SiNPs. Human data were collected from clinical trial data from Cornell dots.

Materials: The mPBPK model incorporated physiological parameters and nanoparticle-specific characteristics to simulate SiNP biodistribution and was built in Matlab 2024a. Global sensitivity analysis identified influential parameters, including the unbound fraction and elimination rate constants for the kidneys and mononuclear phagocyte system (MPS). The model was extrapolated to predict human pharmacokinetics, with accuracy evaluated using Pearson correlation coefficients. Non-compartmental analysis (NCA) assessed organ-specific accumulation and biodistribution patterns.

Results: Global sensitivity analysis revealed that the unbound fraction and elimination rate constants for the kidneys and MPS were major determinants of SiNP biodistribution. NCA indicated that aminated SiNPs initially accumulated in the liver, spleen, and kidneys but redistributed due to their high unbound fraction, while mesoporous SiNPs localized in the lungs. Rod-shaped SiNPs exhibited high lung exposure. The extrapolated model showed high predictive accuracy, with Pearson correlation coefficients of 0.98 for mice and 0.99 for humans.

Conclusion: The mPBPK model effectively predicts the pharmacokinetics of diverse SiNPs, offering insights to optimize nanoparticle-based drug delivery systems and facilitating their translation from preclinical models to clinical applications.

使用校准的生理模型预测二氧化硅纳米颗粒的生物分布:肾脏和吞噬作用的未结合分数和消除速率常数被确定为主要决定因素。
目的:本研究旨在建立一个基于最小生理的药代动力学(mPBPK)模型来预测二氧化硅纳米颗粒(SiNPs)的生物分布,并评估表面电荷、大小、孔隙度和几何形状的变化如何影响它们的系统配置。材料:mPBPK模型使用小鼠体内药代动力学数据进行校准,这些数据来自胺化的、介孔的和杆状的sinp。人体数据是从康奈尔点的临床试验数据中收集的。材料:mPBPK模型结合生理参数和纳米颗粒特异性来模拟SiNP的生物分布,并在Matlab 2024a中构建。全局敏感性分析确定了影响参数,包括肾脏和单核吞噬细胞系统(MPS)的未结合分数和消除速率常数。该模型被外推以预测人体药代动力学,并使用Pearson相关系数评估准确性。非区室分析(NCA)评估了器官特异性积累和生物分布模式。结果:全局敏感性分析显示,肾脏和MPS的未结合分数和消除速率常数是SiNP生物分布的主要决定因素。NCA表明,胺化SiNPs最初积聚在肝脏、脾脏和肾脏,但由于其高未结合分数而重新分布,而介孔SiNPs则局限于肺部。杆状SiNPs表现出高的肺部暴露。外推模型显示出很高的预测精度,小鼠的Pearson相关系数为0.98,人类的Pearson相关系数为0.99。结论:mPBPK模型有效预测了不同SiNPs的药代动力学,为优化基于纳米颗粒的药物传递系统提供了见解,并促进了其从临床前模型到临床应用的转化。
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来源期刊
CiteScore
1.70
自引率
12.50%
发文量
116
审稿时长
4-8 weeks
期刊介绍: The International Journal of Clinical Pharmacology and Therapeutics appears monthly and publishes manuscripts containing original material with emphasis on the following topics: Clinical trials, Pharmacoepidemiology - Pharmacovigilance, Pharmacodynamics, Drug disposition and Pharmacokinetics, Quality assurance, Pharmacogenetics, Biotechnological drugs such as cytokines and recombinant antibiotics. Case reports on adverse reactions are also of interest.
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