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IVIVC of Octreotide in PLGA-Glucose Microsphere Formulation, Sandostatin® LAR

Authors
Song, J.-S.Kim, S.-Y.Nam, J.-H.Lee, J.Song, S.-Y.Seong, H.
Issue Date
Sep-2022
Publisher
Springer Science and Business Media Deutschland GmbH
Keywords
In vitro release; In vitro-in vivo correlation (IVIVC); Octreotide; Pharmacokinetic parameter; Poly(lactide-co-glycolide)-glucose
Citation
AAPS PharmSciTech, v.23, no.7
Journal Title
AAPS PharmSciTech
Volume
23
Number
7
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/59108
DOI
10.1208/s12249-022-02359-w
ISSN
1530-9932
1522-1059
Abstract
Abstract: In vitro-in vivo correlation (IVIVC) analysis reveals a relationship between in vitro release and in vivo pharmacokinetic response of the drug of interest. Sandostatin LAR Depot (SLD) for endocrine tumors and acromegaly is a sustained-release formulation of octreotide, a cyclic oligomer of 8 amino acids, which prolongs therapeutic efficacy and enhances medication compliance of octreotide. Since the efficacy of SLD is dependent on the pharmacokinetic characteristics of octreotide released from a biodegradable matrix polymer, poly(lactide-co-glycolide)-glucose, of SLD, the IVIVC of SLD is critical for predicting an in vivo behavior of the octreotide. In this study, in vitro release of octreotide from SLD was investigated using the release test media each containing 0.02% or 0.5% surfactant and having different pH values of 7.4 and 5.5. In vivo pharmacokinetic profiles of SLD were determined by LC–MS/MS analysis of the systemic blood concentration of octreotide after the SLD injection to rodents. In IVIVC analysis, the Weibull model was adopted as a drug release model for biodegradable microsphere formulation. The IVIVC analyses revealed the in vitro release test condition of SLD with the highest IVIV correlation coefficient. By applying the in vitro release data to the model derived from the IVIVC analysis, pharmacokinetic parameters of SLD could be predicted with the prediction error of ± 10 ~ 15%. IVIVC analysis and pharmacokinetic prediction model of SLD in our study can be an efficient tool for the development of long-acting pharmaceutical dosage forms. Graphical Abstract: [Figure not available: see fulltext.]. © 2022, The Author(s), under exclusive licence to American Association of Pharmaceutical Scientists.
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