Three months extended-release microspheres prepared by multi-microchannel microfluidics in beagle dog models

Ju Hee Kim, Choong Ho Ryu, Chan Hee Chon, Seyeon Kim, Sangno Lee, Ravi Maharjan, Nam Ah Kim, Seong Hoon Jeong

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

To evaluate in vivo drug release profiles in beagle dogs, finasteride-loaded PLGA microspheres were prepared using a novel method of IVL-PPF Microsphere® microfluidic device. Briefly, the dispersed phase (PLGA and finasteride in dichloromethane) was mixed with the continuous phase (0.25% w/v PVA aqueous solution) in the parallelized microchannels. After lyophilization, the diameter of the microspheres was around 40 μm (PLGA 7502A or 5002A) and around 30 µm (PLGA/PLA02A mixture). Their CV and span values suggested a narrow size distribution in repeated batch preparations. The in vivo drug release from the PLGA microspheres exhibited three substantial phases: an initial burst, a moderate release, and then a plateau. The microspheres based on PLGA 7502A (75:25 co-polymer) demonstrated extended drug release for around 1 month with a minimized initial burst release compared to PLGA 5002A (50:50 co-polymer). Moreover, the in vivo drug release profile in beagle dogs was proportionally related to the amount of drug loading. Furthermore, the addition of PLA02A into the fabrication of the microsphere synergistically extended the drug release up to 3 months. These results demonstrated the value of this method to achieve uniform microspheres and extend the drug release properties with interpretative in vivo PK profiles.

Original languageEnglish
Article number121039
JournalInternational Journal of Pharmaceutics
Volume608
DOIs
StatePublished - 25 Oct 2021

Keywords

  • Extended drug release
  • Finasteride
  • IVL-PPF Microsphere®
  • Microfluidics
  • Microsphere
  • PLGA

Fingerprint

Dive into the research topics of 'Three months extended-release microspheres prepared by multi-microchannel microfluidics in beagle dog models'. Together they form a unique fingerprint.

Cite this