利用人工神经网络和响应面法制备利伐沙班固体脂质纳米颗粒并进行优化。

IF 3 4区医学 Q2 CHEMISTRY, APPLIED

Journal of microencapsulation Pub Date : 2025-01-01 Epub Date: 2025-01-05 DOI:10.1080/02652048.2024.2437362

Fatemeh Ghorbannejad Nashli, Sareh Aghajanpour, Ali Farmoudeh, Seyed Sajad Hosseini Balef, Meshkat Torkamanian, Alireza Razavi, Hamid Irannejad, Pedram Ebrahimnejad

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引用次数: 0

摘要

目的：本研究旨在通过优化固体脂质纳米颗粒（SLN）以实现最小平均直径和最大包裹效率（EE）、提高溶解度、生物利用度和穿越血脑屏障的能力来改善利伐沙班的递送。方法：采用中心复合设计，合成32个SLN配方。响应面法（RSM）和人工神经网络（ANN）模型基于5个自变量预测了平均直径和EE。结果：优化后的SLN平均粒径为159.8±15.2 nm，多分散性指数为0.46，zeta电位为-28.8 mV， EE为74.3%±5.6%。人工神经网络模型在平均直径和EE上都表现出更高的精度，优于RSM模型。通过扫描电镜（SEM）、差示扫描量热法（DSC）和傅里叶变换红外光谱（FTIR）证实了结构的完整性和稳定性。结论：人工神经网络模型的高准确性突出了其在优化药物配方和改进基于sln的给药系统方面的潜力。

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Preparation and optimisation of solid lipid nanoparticles of rivaroxaban using artificial neural networks and response surface method.

Aims: This study aimed to improve rivaroxaban delivery by optimising solid lipid nanoparticles (SLN) for minimal mean diameter and maximal entrapment efficiency (EE), enhancing solubility, bioavailability, and the ability to cross the blood-brain barrier.

Methods: A central composite design was employed to synthesise 32 SLN formulations. Response surface methodology (RSM) and artificial neural networks (ANN) models predicted mean diameter and EE based on five independent variables.

Results: The optimised SLN formulation achieved a mean particle diameter of 159.8 ± 15.2 nm, with a Polydispersity index of 0.46, a zeta potential of -28.8 mV, and an EE of 74.3% ± 5.6%. The ANN model showed superior accuracy for both mean diameter and EE, outperforming the RSM model. Structural integrity and stability were confirmed by scanning electron microscopy (SEM), differential scanning calorimetry (DSC), and Fourier-transform infrared spectroscopy (FTIR).

Conclusion: The high accuracy of the ANN model highlights its potential in optimising pharmaceutical formulations and improving SLN-based drug delivery systems.

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来源期刊

Journal of microencapsulation 工程技术-工程：化工

CiteScore

6.30

自引率

2.60%

发文量

审稿时长

3 months

期刊介绍： The Journal of Microencapsulation is a well-established, peer-reviewed journal dedicated to the publication of original research findings related to the preparation, properties and uses of individually encapsulated novel small particles, as well as significant improvements to tried-and-tested techniques relevant to micro and nano particles and their use in a wide variety of industrial, engineering, pharmaceutical, biotechnology and research applications. Its scope extends beyond conventional microcapsules to all other small particulate systems such as self assembling structures that involve preparative manipulation. The journal covers: Chemistry of encapsulation materials Physics of release through the capsule wall and/or desorption from carrier Techniques of preparation, content and storage Many uses to which microcapsules are put.