journal article·2011-08

Effect of bases with different solubility on the release behavior of risperidone loaded PLGA microspheres

Zhenhua Hu, Yajun Liu, Weien Yuan, Fei Wu, Jing Su, Tuo Jin

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Abstract

Poly (D, L-lactide-co-glycolide) (PLGA) microspheres are attractive delivery vehicles due to their excellent sustained release capabilities. One major problem with PLGA microspheres is that the hydrophobic properties of PLGA generally cause a lag period in the process of drug release, leading to fluctuation of drug concentration in the blood and various resulting adverse reactions. Herein, Mg(OH)₂, an inorganic base, and arginine, an organic base, were separately co-encapsulated into risperidone-loaded PLGA microspheres at varying concentration using the solvent evaporation method to improve release profiles from the microspheres. High encapsulation efficiencies were obtained in all formulations. The surface of base-free microspheres was smooth, whereas a few pores formed in base co-encapsulated microspheres. After 7-days degradation, many inter-connecting pores were formed in the interior of the microspheres containing 10 mg Mg(OH)₂. The final pH in the microspheres with Mg(OH)₂ was higher than in those with arginine after 28-days degradation. The initial release of risperidone from microspheres containing Mg(OH)₂ was higher than from those containing arginine, and the latter release exhibited a more uniform pattern. Microspheres with 5mg and 10mg arginine exhibited zero-order release kinetics. However, both bases eliminated the lag phase of release. These results indicate that the incorporation of bases has potential in addressing the problem of the lag period in drug release from PLGA microspheres, and improving release behavior toward an ideal model.
Source: europepmc · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Advanced Drug Delivery Systems · biodegradable polymer synthesis and properties · Nanocomposite Films for Food Packaging

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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