Development, optimization, and assessment of losartan nano-bilosomes to mitigate diabetes-induced microvascular complications in Sprague Dawley rats

JOURNAL OF DRUG DELIVERY SCIENCE AND TECHNOLOGY(2024)

引用 0|浏览2
暂无评分
摘要
Losartan has a significant renal protection effect in type 2 diabetic patients. It was loaded into bilosomes to overcome its low oral bioavailability and improve its renal protective effects. The bilosomes were optimized using a 23 factorial design. Bile salt type and concentration and phospholipid concentration influenced the vesicles percent drug entrapment efficiency (%EE), vesicle size (VS), polydispersity index (PDI) and zeta potential (ZP). The %EE varied from 71.73 +/- 0.91 % to 92.34 +/- 0.75 %. VS varied from 146.87 +/- 3.56 to 286.29 +/- 1.72 nm while PDI ranged from 0.28 +/- 0.02 to 0.46 +/- 0.03. ZP was high enough (-28.34 +/- 0.61 to -35.64 +/- 1.38 mV) to afford colloidal stability to the bilosomes. The bilosomes had the ability to prolong the release of the drug, with the percentage of losartan released after 12 h ranging from 64.31 +/- 1.03 % to 88.48 +/- 0.93 %. An optimized formulation was selected and used orally in an in vivo diabetic nephropathy rats model to study its ability to improve losartan nephroprotective effects. The diabetic group exhibited elevated serum creatinine, blood urea nitrogen (BUN), urine albumin, and inflammatory cytokines. Losartan bilosomes demonstrated reduced BUN and proteinuria compared to the free drug. Additionally, they outperformed the free drug in enhancing kidney function, preserving renal cellular structure, and mitigating diabetic renal inflammation and fibrosis. This was evidenced by significantly lower levels of tumor necrosis factor-alpha, interleukin-6, nuclear factor kappa, and macrophage markers. These findings conclusively demonstrate the promising potential of losartan bilosomes as an effective oral formulation to mitigate diabetic nephropathy.
更多
查看译文
关键词
Diabetes mellitus,Losartan,Bilosomes,Oral drug delivery,Diabetic nephropathy
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要