The objective of this manuscript is to provide quantitative insights into the tissue distribution of nanoparticles. Published pharmacokinetics of nanoparticles in plasma, tumor and 13 different tissues of mice were collected from literature. A total of 2018 datasets were analyzed and biodistribution of graphene oxide, lipid, polymeric, silica, iron oxide and gold nanoparticles in different tissues was quantitatively characterized using Nanoparticle Biodistribution Coefficients (NBC). It was observed that typically after intravenous administration most of the nanoparticles are accumulated in the liver (NBC = 17.56 %ID/g) and spleen (NBC = 12.1 %ID/g), while other tissues received less than 5 %ID/g. NBC values for kidney, lungs, heart, bones, brain, stomach, intestine, pancreas, skin, muscle and tumor were found to be 3.1 %ID/g, 2.8 %ID/g, 1.8 %ID/g, 0.9 %ID/g, 0.3 %ID/g, 1.2 %ID/g, 1.8 %ID/g, 1.2 %ID/g, 1.0 %ID/g, 0.6 %ID/g and 3.4 %ID/g, respectively. Significant variability in nanoparticle distribution was observed in certain organs such as liver, spleen and lungs. A large fraction of this variability could be explained by accounting for the differences in nanoparticle physicochemical properties such as size and material. A critical overview of published nanoparticle physiologically-based pharmacokinetic (PBPK) models is provided, and limitations in our current knowledge about in vitro and in vivo pharmacokinetics of nanoparticles that restrict the development of robust PBPK models is also discussed. It is hypothesized that robust quantitative assessment of whole-body pharmacokinetics of nanoparticles and development of mathematical models that can predict their disposition can improve the probability of successful clinical translation of these modalities.
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http://dx.doi.org/10.1016/j.addr.2023.114708 | DOI Listing |
Pharmaceutics
December 2024
Wits Advanced Drug Delivery Platform, Department of Pharmacy and Pharmacology, School of Therapeutic Sciences, Faculty of Health Sciences, University of the Witwatersrand, 7 York Road, Parktown, Johannesburg 2193, South Africa.
The effectiveness of paclitaxel (PTX) in treating non-small-cell lung carcinoma (NSCLC) is restricted by its poor pharmacokinetic profile and side effects. This limitation stems from the lack of a suitable delivery vector to efficiently target cancer cells. Therefore, there is a critical need to develop an efficient carrier for the optimised delivery of PTX in NSCLC therapy.
View Article and Find Full Text PDFPharmaceutics
November 2024
Guangdong Provincial Key Laboratory of Advanced Drug Delivery, Guangdong Provincial Engineering Center of Topical Precise Drug Delivery System, Guangdong Pharmaceutical University, No. 280 University Town Outer Ring East Road, Guangzhou 510006, China.
Background: Internal ocular diseases, such as macular edema, uveitis, and diabetic macular edema require precise delivery of therapeutic agents to specific regions within the eye. However, the eye's complex anatomical structure and physiological barriers present significant challenges to drug penetration and distribution. Traditional eye drops suffer from low bioavailability primarily due to rapid clearance mechanisms.
View Article and Find Full Text PDFMolecules
December 2024
Department of Molecular Biology and Genetics, Faculty of Arts and Science, Necmettin Erbakan University, Konya 42090, Turkey.
In the present study, ultra-small, magnetic, oleyl amine-coated FeO nanoparticles were synthesized and stabilized with a cationic ligand, cetyltrimethylammonium bromide, and an anticancer drug, methotrexate, was incorporated into a micelle-like nanoparticle structure for glioblastoma treatment. Nanoparticles were further characterized for their physicochemical properties using spectroscopic methods. Drug incorporation efficiency, drug loading, and drug release profile of the nanoparticles were investigated.
View Article and Find Full Text PDFInt J Nanomedicine
January 2025
State Key Laboratory of Ophthalmology, Optometry and Visual Science, National Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, People's Republic of China.
Background: Developing carrier-free nanomedicines via self-assembly of two antitumor drug molecules is a potential strategy for enhancing the combination treatment of tumors. Similarly, conventional chemotherapy combined with photodynamic therapy may synergistically improve the antitumor effect while minimizing the adverse reactions associated with antitumor treatment. Hyaluronic acid (HA) can bind to overexpressed HA receptors on the tumor cell surface, increasing cell internalization and resulting in good tumor-targeting properties.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, P.O. Box 2457, 11451, Riyadh, Saudi Arabia.
This study focuses on the use of machine learning (ML) models to predict the biodistribution of nanoparticles in various organs, using a dataset derived from research on nanoparticle behavior for cancer treatment. The dataset includes both categorical and numerical variables related to nanoparticle properties, with a focus on their distribution across organs such as the tumor, heart, liver, spleen, lung, and kidney tissues. In order to address the complex and non-linear nature of the data, three machine learning models were utilized: Bayesian Ridge Regression (BRR), Kernel Ridge Regression (KRR), and K-Nearest Neighbors (KNN).
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