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运用智能制药技术方法设计载氯法齐明脂质纳米粒

Design of Clofazimine-Loaded Lipid Nanoparticles Using Smart Pharmaceutical Technology Approaches.

作者信息

Rouco Helena, Virzì Nicola Filippo, Menéndez-Rodríguez Carolina, Potel Carmen, Diaz-Rodriguez Patricia, Landin Mariana

机构信息

Departamento de Farmacología, Farmacia y Tecnología Farmacéutica, Grupo I+D Farma (GI-1645), Facultad de Farmacia, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain.

Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), 15706 Santiago de Compostela, Spain.

出版信息

Pharmaceutics. 2025 Jul 2;17(7):873. doi: 10.3390/pharmaceutics17070873.

Abstract

: Clofazimine (CFZ) is a versatile antimicrobial active against several bacterial species, although its reduced aqueous solubility and the occurrence of side effects limit its use. Nanostructured lipid carriers (NLCs) constitute an interesting approach to increase drug bioavailability and safety. However, the development of nanoparticle-based formulations is challenging. In the present work, a combination of smart pharmaceutical technology approaches was proposed to develop CFZ-loaded NLCs, taking advantage of previous knowledge on NLCs screening. : A design space previously established using Artificial Intelligence (AI) tools was applied to develop CFZ-loaded NLC formulations. After formulation characterization, Neurofuzzy Logic (NFL) and in silico docking simulations were employed to enhance the understanding of lipid nanocarriers. Then, the performance of formulations designed following NFL guidelines was characterized in terms of biocompatibility, using murine fibroblasts, and antimicrobial activity against several strains of . : The followed approach enabled CFZ-loaded NLC formulations with optimal properties, including small size and high antimicrobial payload. NFL was useful to investigate the existing interactions between NLC components and homogenization conditions, that influence CFZ-loaded NLCs' final properties. Also, in silico docking simulations were successfully applied to examine interactions and affinity between the drug and the lipid matrix components. Finally, the designed CFZ-loaded formulations demonstrated suitable biocompatibility, together with antimicrobial activity. : The implementation of smart strategies during nanoparticle-based therapeutics development, such as those described in this manuscript, would enable the more efficient design of new systems for suitable antimicrobial delivery.

摘要

氯法齐明(CFZ)是一种对多种细菌具有抗菌活性的多功能药物,尽管其水溶性降低和副作用的出现限制了其使用。纳米结构脂质载体(NLCs)是提高药物生物利用度和安全性的一种有趣方法。然而,基于纳米颗粒的制剂开发具有挑战性。在本研究中,结合智能药物技术方法,利用先前关于NLCs筛选的知识,提出开发载CFZ的NLCs。:应用先前使用人工智能(AI)工具建立的设计空间来开发载CFZ的NLC制剂。在制剂表征后,采用神经模糊逻辑(NFL)和计算机对接模拟来加深对脂质纳米载体的理解。然后,按照NFL指南设计的制剂的性能通过使用小鼠成纤维细胞的生物相容性以及对几种菌株的抗菌活性进行表征。:所采用的方法能够制备出具有最佳性能的载CFZ的NLC制剂,包括小尺寸和高抗菌载量。NFL有助于研究NLC成分与均质化条件之间的现有相互作用,这些相互作用会影响载CFZ的NLCs的最终性能。此外,计算机对接模拟成功应用于检查药物与脂质基质成分之间的相互作用和亲和力。最后设计的载CFZ制剂表现出合适的生物相容性以及抗菌活性。:在基于纳米颗粒的治疗药物开发过程中实施智能策略,如本手稿中所述,将能够更有效地设计适合抗菌递送的新系统。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/649b/12300866/5e97c94d1c5a/pharmaceutics-17-00873-g001.jpg

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