Microfluidic-assisted preparation of PLGA nanoparticles for drug delivery purposes: experimental study and computational fluid dynamic simulation.

Computational fluid dynamic Microfluidics Nanoparticles Nanoprecipitation Polylactic-coglycolicacid

Journal

Research in pharmaceutical sciences
ISSN: 1735-5362
Titre abrégé: Res Pharm Sci
Pays: Iran
ID NLM: 101516968

Informations de publication

Date de publication:
Oct 2019
Historique:
entrez: 5 12 2019
pubmed: 5 12 2019
medline: 5 12 2019
Statut: epublish

Résumé

This study, for the first time, tries to provide a simultaneous experimental and computational fluid dynamic (CFD) simulation investigation for production of uniform, reproducible, and stable polylactic-co-glycolic acid (PLGA) nanoparticles. CFD simulation was carried out to observe fluid flow behavior and micromixing in microfluidic system and improve our understanding about the governing fluid profile. The major objective of such effort was to provide a carrier for controlled and sustained release profile of different drugs. Different experimental parameters were optimized to obtain PLGA nanoparticles with proper size and minimized polydispersity index. The particle size, polydispersity, morphology, and stability of nanoparticles were compared. Microfluidic system provided a platform to control over the characteristics of nanoparticles. Using microfluidic system, the obtained particles were more uniform and harmonious in size, more stable, monodisperse and spherical, while particles produced by batch method were non-spherical and polydisperse. The best size and polydispersity index in the microfluidic method was obtained using 2% PLGA and 0.0625% (w/v) polyvinyl alcohol (PVA) solutions, and the flow rate ratio of 10:0.6 for PVA and PLGA solutions. CFD simulation demonstrated the high mixing intensity of about 0.99 at optimum condition in the microfluidic system, which is the possible reason for advantageous performance of this system. Altogether, the results of microfluidic-assisted method were found to be more reproducible, predictable, and controllable than batch method for producing a nanoformulation for delivery of drugs.

Identifiants

pubmed: 31798663
doi: 10.4103/1735-5362.268207
pii: RPS-14-459
pmc: PMC6827194
doi:

Types de publication

Journal Article

Langues

eng

Pagination

459-470

Informations de copyright

Copyright: © 2019 Research in Pharmaceutical Sciences.

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Auteurs

Parisa Shokoohinia (P)

Student Research Committee, Kermanshah University of Medical Sciences, Kermanshah, I.R. Iran.

Marziyeh Hajialyani (M)

Pharmaceutical Sciences Research Center, Health Institute, Kermanshah University of Medical Sciences, Kermanshah, I.R. Iran.

Komail Sadrjavadi (K)

Pharmaceutical Sciences Research Center, Health Institute, Kermanshah University of Medical Sciences, Kermanshah, I.R. Iran.

Mona Akbari (M)

CFD Research Center, Department of Chemical Engineering, Faculty of Engineering, Razi University, Kermanshah, I.R. Iran.

Masoud Rahimi (M)

CFD Research Center, Department of Chemical Engineering, Faculty of Engineering, Razi University, Kermanshah, I.R. Iran.

Salar Khaledian (S)

Nano Drug Delivery Research Center, Health Institute, Kermanshah University of Medical Sciences, Kermanshah, I.R. Iran.

Ali Fattahi (A)

Pharmaceutical Sciences Research Center, Health Institute, Kermanshah University of Medical Sciences, Kermanshah, I.R. Iran.
Medical Biology Research Center, Health Institute, Kermanshah University of Medical Sciences, Kermanshah, I.R. Iran.

Classifications MeSH