Leveraging 3D-Printed Microfluidic Micromixers for the Continuous Manufacture of Melatonin Loaded SNEDDS with Enhanced Antioxidant Activity and Skin Permeability
INTERNATIONAL JOURNAL OF PHARMACEUTICS(2024)
摘要
Vesicants are chemical warfare agents (CWAs) capable of causing severe skin damage and systemic toxicity. Melatonin, known for its anti-inflammatory and antioxidant properties, can mitigate the effects of these agents. Self-nano-emulsifying drug delivery systems (SNEDDS) containing a high melatonin concentration (5 %, 50 mg/ g) were optimized using a quality-by-design approach from biocompatible, non-irritant excipients with a particle size of about 100 nm. The melatonin-loaded SNEDDS showed a 43-fold greater permeability than a conventional melatonin cream. Chemical stability at ambient temperature (25 degrees C) was maintained for one year. The preparation of optimised melatonin-loaded SNEDDS using a simple mixing method was compared to microfluidic micromixers. Mixing was successfully achieved using a 3D-printed (fused deposition modeling or stereo- lithography) T-shaped toroidal microfluidic chip (with a channel geometry optimized by computational fluid dynamics), resulting in a scalable, continuous process for the first time with a substantial reduction in preparation time compared to other conventional mixing approaches. No statistically significant differences were observed in the key quality attributes, such as particle size and melatonin loading, between mixing method till kinetic equilibrium solubility is reached and mixing using the 3D-printed micromixers. This scalable, continuous, cost-effective approach improves the overall efficiency of SNEDDS production, reduces the cost of quality control for multiple batches, and demonstrates the potential of continuous microfluidic manufacture with readily customizable 3D-printed micromixers at points of care, such as military bases.
更多查看译文
关键词
Melatonin,SNEDDS,Topical administration,Antioxidant,Chemical weapons,3D printing,Microfluidic chips,Continuous manufacture
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn