ArticleAAPS PharmSciTech2025
Application of a Two-Phase Experiment Design and Optimization Method to Formulate Ciprofloxacin-Loaded Bovine Serum Albumin Nanoparticles with High-Entrapment Efficiency for Targeting Urinary Tract Infections.
Article in AAPS PharmSciTech, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
9 authors.
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Abstract
Urinary tract infections (UTIs), predominantly caused by uropathogenic Escherichia coli (UPEC), pose a global health concern due to rising antibiotic resistance and biofilm formation. Albumin nanoparticles (NPs) offer a promising strategy for UTI treatment, with site-specific selectivity, improved bioavailability, and sustained drug release. This study focused on developing an optimized method for formulating ciprofloxacin-loaded albumin nanoparticles (CPF-loaded BSA NPs) to treat UPEC and its biofilms effectively. A desolvation method was used to synthesize the nanoparticles, and a two-phase experimental design was used for optimization. Evaluation parameters included size, polydispersity index, zeta potential, morphology, encapsulation efficiency, drug release, storage stability, cytotoxicity, and effectiveness against UPEC. The optimized CPF-loaded BSA NPs exhibited desirable characteristics such as small particle size (123 nm), low polydispersity index (0.178), optimum zeta potential (-31.8), and high encapsulation efficiency (> 80%). They also exhibited low cytotoxicity, high stability, and sustained drug release, making them an ideal drug delivery system. Critically, they demonstrated effectiveness against UPEC and its biofilm. This study suggests that the optimized CPF-loaded BSA NPs, synthesized using our optimized desolvation technique, hold the potential for effectively treating UTIs caused by UPEC.
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Identifiers
40316780What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.