Poly(lactic-co-glycolic acid) microsphere production based on quality by design: a review

PLGA公司 乙醇酸 材料科学 生物相容性 乳酸 药物输送 化学工程 纳米技术 纳米颗粒 遗传学 生物 工程类 冶金 细菌
作者
Yabing Hua,Yuhuai Su,Hui Zhang,Nan Liu,Zengming Wang,Xiang Gao,Jing Gao,Aiping Zheng
出处
期刊:Drug Delivery [Taylor & Francis]
卷期号:28 (1): 1342-1355 被引量:129
标识
DOI:10.1080/10717544.2021.1943056
摘要

Poly(lactic-co-glycolic acid) (PLGA) has garnered increasing attention as a candidate drug delivery polymer owing to its favorable properties, including its excellent biocompatibility, biodegradability, non-toxicity, non-immunogenicity, and mechanical strength. PLAG are specifically used as microspheres for the sustained/controlled and targeted delivery of hydrophilic or hydrophobic drugs, as well as biological therapeutic macromolecules, including peptide and protein drugs. PLGAs with different molecular weights, lactic acid (LA)/glycolic acid (GA) ratios, and end groups exhibit unique release characteristics, which is beneficial for obtaining diverse therapeutic effects. This review aims to analyze the composition of PLGA microspheres, and understand the manufacturing process involved in their production, from a quality by design perspective. Additionally, the key factors affecting PLGA microsphere development are explored as well as the principles involved in the synthesis and degradation of PLGA and its interaction with active drugs. Further, the effects elicited by microcosmic conditions on PLGA macroscopic properties, are analyzed. These conditions include variations in the organic phase (organic solvent, PLGA, and drug concentration), continuous phase (emulsifying ability), emulsifying stage (organic phase and continuous phase interaction, homogenization parameters), and solidification process (relationship between solvent volatilization rate and curing conditions). The challenges in achieving consistency between batches during manufacturing are addressed, and continuous production is discussed as a potential solution. Finally, potential critical quality attributes are introduced, which may facilitate the optimization of process parameters.
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