Stimuli-sensitive nano-drug delivery with programmable size changes to enhance accumulation of therapeutic agents in tumors.


Journal

Drug delivery
ISSN: 1521-0464
Titre abrégé: Drug Deliv
Pays: England
ID NLM: 9417471

Informations de publication

Date de publication:
Dec 2023
Historique:
entrez: 10 3 2023
pubmed: 11 3 2023
medline: 14 3 2023
Statut: ppublish

Résumé

Nano-based drug delivery systems hold significant promise for cancer therapies. Presently, the poor accumulation of drug-carrying nanoparticles in tumors has limited their success. In this study, based on a combination of the paradigms of intravascular and extravascular drug release, an efficient nanosized drug delivery system with programmable size changes is introduced. Drug-loaded smaller nanoparticles (secondary nanoparticles), which are loaded inside larger nanoparticles (primary nanoparticles), are released within the microvascular network due to temperature field resulting from focused ultrasound. This leads to the scale of the drug delivery system decreasing by 7.5 to 150 times. Subsequently, smaller nanoparticles enter the tissue at high transvascular rates and achieve higher accumulation, leading to higher penetration depths. In response to the acidic pH of tumor microenvironment (according to the distribution of oxygen), they begin to release the drug doxorubicin at very slow rates (i.e., sustained release). To predict the performance and distribution of therapeutic agents, a semi-realistic microvascular network is first generated based on a sprouting angiogenesis model and the transport of therapeutic agents is then investigated based on a developed multi-compartment model. The results show that reducing the size of the primary and secondary nanoparticles can lead to higher cell death rate. In addition, tumor growth can be inhibited for a longer time by enhancing the bioavailability of the drug in the extracellular space. The proposed drug delivery system can be very promising in clinical applications. Furthermore, the proposed mathematical model is applicable to broader applications to predict the performance of drug delivery systems.

Identifiants

pubmed: 36895188
doi: 10.1080/10717544.2023.2186312
pmc: PMC10013474
doi:

Substances chimiques

Doxorubicin 80168379AG
Nanoparticle Drug Delivery System 0
Drug Carriers 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2186312

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Auteurs

Mohammad Souri (M)

Department of NanoBiotechnology, Pasteur Institute of Iran, Tehran, Iran.

Mohammad Kiani Shahvandi (M)

Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran.

Mohsen Chiani (M)

Department of NanoBiotechnology, Pasteur Institute of Iran, Tehran, Iran.

Farshad Moradi Kashkooli (F)

Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran.

Ali Farhangi (A)

Department of NanoBiotechnology, Pasteur Institute of Iran, Tehran, Iran.

Mohammad Reza Mehrabi (MR)

Department of NanoBiotechnology, Pasteur Institute of Iran, Tehran, Iran.

Arman Rahmim (A)

Departments of Radiology and Physics, University of British Columbia, Vancouver, British Columbia, Canada.
Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, British Columbia, Canada.

Van M Savage (VM)

Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, California, USA.
Department of Computational Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.
Santa Fe Institute, Santa Fe, New Mexico, USA.

M Soltani (M)

Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran.
Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Canada.
Centre for Biotechnology and Bioengineering (CBB), University of Waterloo, Waterloo, Canada.
Advanced Bioengineering Initiative Center, Multidisciplinary International Complex, K. N. Toosi University of Technology, Tehran, Iran.

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Classifications MeSH