序贯纳米沉淀法(SNaP)形成聚合物微粒的工艺和配方参数

IF 5.1 Q2 ENGINEERING, CHEMICAL
Parker K. Lewis, Nouha El Amri, Erica E. Burnham, Natalia Arrus and Nathalie M. Pinkerton*, 
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引用次数: 0

摘要

聚合物微颗粒(MPs)是一种有价值的药物缓释载体,但目前的制造技术在平衡尺寸控制和可扩展性方面存在重大挑战。工业合成过程提供高通量但精度有限,而实验室规模的技术提供精确的控制,但可扩展性差。本研究探索了顺序纳米沉淀(SNaP),一种用于聚合物微粒生产的两步控制沉淀工艺,以弥合实验室精度和工业可扩展性之间的差距。我们系统地研究了控制MPs形成的关键工艺参数,重点研究了用聚乙烯醇(PVA)稳定的聚乳酸(PLA) MPs。通过对涡旋和撞击射流混合几何形状的比较,我们证明涡旋混合在岩芯装配中具有优越的性能,特别是在聚合物浓度较高的情况下。我们建立了延迟时间(Td)和岩心流浓度(core)对颗粒大小的影响,证实了微粒在确定的操作边界内遵循Smoluchowski扩散限制生长动力学。通过这种方法,我们实现了对微颗粒尺寸(1.6-3.0 μm)的精确控制,具有窄的多分散性。在保持一致的尺寸控制的同时,成功地形成了具有不同稳定剂的MPs,进一步证明了SNaP的多功能性。最后,我们通过高效包封伊曲康唑(83-85%)并表征其缓释谱来验证SNaP的药学相关性。这些发现使SNaP成为一个强大的、可扩展的高质量药物微粒生产平台,对关键质量属性具有卓越的控制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Process and Formulation Parameters Governing Polymeric Microparticle Formation via Sequential NanoPrecipitation (SNaP)

Polymeric microparticles (MPs) are valuable drug delivery vehicles for extended-release applications, but current manufacturing techniques present significant challenges in balancing size control with scalability. Industrial synthesis processes provide high throughput but limited precision, while laboratory-scale technologies offer precise control but poor scalability. This study explores Sequential NanoPrecipitation (SNaP), a two-step controlled precipitation process for polymeric microparticle production, to bridge the gap between laboratory precision and industrial scalability. We systematically investigated critical process parameters governing MP formation, focusing on poly(lactic acid) (PLA) MPs stabilized with poly(vinyl alcohol) (PVA). By comparing vortex and impinging jet mixing geometries, we demonstrated that vortex mixing provides superior performance for core assembly, particularly at higher polymer concentrations. We established the influence of delay time (Td) and core stream concentration (Ccore) on particle size, confirming that microparticle assembly follows Smoluchowski diffusion-limited growth kinetics within defined operational boundaries. Through this approach, we achieved precise control over microparticle size (1.6–3.0 μm) with narrow polydispersity. The versatility of SNaP was further demonstrated by the successful formation of MPs with different stabilizers while maintaining consistent size control. Finally, we validated the pharmaceutical relevance of SNaP by encapsulating itraconazole with high efficiency (83–85%) and characterizing its sustained release profile. These findings establish SNaP as a robust, scalable platform for high-quality pharmaceutical microparticle production with superior control over critical quality attributes.

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来源期刊
ACS Engineering Au
ACS Engineering Au 化学工程技术-
自引率
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0
期刊介绍: )ACS Engineering Au is an open access journal that reports significant advances in chemical engineering applied chemistry and energy covering fundamentals processes and products. The journal's broad scope includes experimental theoretical mathematical computational chemical and physical research from academic and industrial settings. Short letters comprehensive articles reviews and perspectives are welcome on topics that include:Fundamental research in such areas as thermodynamics transport phenomena (flow mixing mass & heat transfer) chemical reaction kinetics and engineering catalysis separations interfacial phenomena and materialsProcess design development and intensification (e.g. process technologies for chemicals and materials synthesis and design methods process intensification multiphase reactors scale-up systems analysis process control data correlation schemes modeling machine learning Artificial Intelligence)Product research and development involving chemical and engineering aspects (e.g. catalysts plastics elastomers fibers adhesives coatings paper membranes lubricants ceramics aerosols fluidic devices intensified process equipment)Energy and fuels (e.g. pre-treatment processing and utilization of renewable energy resources; processing and utilization of fuels; properties and structure or molecular composition of both raw fuels and refined products; fuel cells hydrogen batteries; photochemical fuel and energy production; decarbonization; electrification; microwave; cavitation)Measurement techniques computational models and data on thermo-physical thermodynamic and transport properties of materials and phase equilibrium behaviorNew methods models and tools (e.g. real-time data analytics multi-scale models physics informed machine learning models machine learning enhanced physics-based models soft sensors high-performance computing)
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