학술논문

Chitosan/tripolyphosphate nanoparticles in active and passive microchannels.
Document Type
Article
Source
Research in Pharmaceutical Sciences. Feb2021, Vol. 16 Issue 1, p79-93. 15p.
Subject
*COMPUTATIONAL fluid dynamics
*NANOPARTICLES
*NANOPARTICLE size
*RATE of nucleation
*DISCONTINUOUS precipitation
*CHITOSAN
Language
ISSN
1735-5362
Abstract
Background and purpose: In recent years, the interest in chitosan nanoparticles has increased due to their application, especially in drug delivery. The main aim of this work was to find a suitable method for simulating pharmaceutical nanoparticles with computational fluid dynamics (CFD) modeling and use it for understanding the process of nanoparticle formation in different types of microchannels. Experimental approach: Active and passive microchannels were compared to find the advantages and disadvantages of each system. Twenty-eight experiments were done on microchannels to quantify the effect of 4 parameters and their interactions on the size and polydispersity index (PDI) of nanoparticles. CFD was implemented by coupling reactive kinetics and the population balance method to simulate the synthesis of chitosan/tripolyphosphate nanoparticles in the microchannel. Findings/Results: The passive microchannel had the best performance for nanoparticle production. The most uniform microspheres and the narrowest standard deviation (124.3 nm, PDI = 0.112) were achieved using passive microchannel. Compared to the active microchannel, the size and PDI of the nanoparticles were 28.7% and 70.5% higher for active microchannels, and 55.43% and 105.3% higher for simple microchannels, respectively. Experimental results confirmed the validity of CFD modeling. The growth and nucleation rates were determined using the reaction equation of chitosan and tripolyphosphate. Conclusion and implications: CFD modeling by the proposed method can play an important role in the prediction of the size and PDI of chitosan/tripolyphosphate nanoparticles in the same condition and provide a new perspective for studying the production of nanoparticles by numerical methods. [ABSTRACT FROM AUTHOR]