Ciprofibrate-Loaded Nanoparticles Prepared by Nanoprecipitation: Synthesis, Characterization, and Drug Release.
Raissa Lohanna Gomes Quintino CorrêaRenan Dos SantosLindomar José Calumby AlbuquerqueGabriel Lima Barros de AraujoCharlotte Jennifer Chante Edwards-GayleFabio Furlan FerreiraFanny Nascimento CostaPublished in: Polymers (2021)
Ciprofibrate (CIP) is a highly lipophilic and poorly water-soluble drug, typically used for dyslipidemia treatment. Although it is already commercialized in capsules, no previous studies report its solid-state structure; thus, information about the correlation with its physicochemical properties is lacking. In parallel, recent studies have led to the improvement of drug administration, including encapsulation in polymeric nanoparticles (NPs). Here, we present CIP's crystal structure determined by PXRD data. We also propose an encapsulation method for CIP in micelles produced from Pluronic P123/F127 and PEO-b-PCL, aiming to improve its solubility, hydrophilicity, and delivery. We determined the NPs' physicochemical properties by DLS, SLS, ELS, SAXS and the loaded drug amount by UV-Vis spectroscopy. Micelles showed sizes around 10-20 nm for Pluronic and 35-45 nm for the PEO-b-PCL NPs with slightly negative surface charge and successful CIP loading, especially for the latter; a substantial reduction in ζ-potential may be evidenced. For Pluronic nanoparticles, we scanned different conditions for the CIP loading, and its encapsulation efficiency was reduced while the drug content increased in the nanoprecipitation protocol. We also performed in vitro release experiments; results demonstrate that probe release is driven by Fickian diffusion for the Pluronic NPs and a zero-order model for PEO-b-PCL NPs.
Keyphrases
- drug release
- drug delivery
- solid state
- cancer therapy
- water soluble
- crystal structure
- oxide nanoparticles
- drug administration
- randomized controlled trial
- photodynamic therapy
- high resolution
- drug induced
- case control
- healthcare
- emergency department
- quantum dots
- climate change
- risk assessment
- big data
- machine learning
- social media
- data analysis