Synthesis and characterization of acetyl curcumin-loaded core/shell liposome nanoparticles via an electrospray process for drug delivery, and theranostic applications

Abstract

Despite substantial advancements in divergent drug delivery systems (DDS), there is still room for novel and innovative nanoparticle-mediated drug delivery methodologies such as core/shell liposomes to deliver drugs in a kinetically controlled manner into the active site without any side effects. Herein, ((1E,6E)-3,5-dioxohepta-1,6-diene-1,7-diyl) bis (2-methoxy-4,1-phenylene) diacetate acetyl curcumin (AC)-loaded poly(lactic-co-glycolic acid) (PLGA) core/shell liposome nanoparticles (ACPCSLNPs) were prepared using an electron spray method under an applied electric field, which facilitated the uniform formation of nano-sized liposome nanoparticles (LNPs). Then, kinetically controlled and sustained drug release profiles were investigated using the as-prepared ACPCSLNPs. Moreover, the inner polymeric core could not only induce the generation of electrostatic interactions between the polymer and drug molecules but could also affect the prominent repulsions between the polar head groups of lipids and the nonpolar drug molecules. As a result, the sustained maximum release of the drug molecules (similar to 48.5%) into the system was observed over a long period (similar to 4 days). Furthermore, cell cytotoxicity studies were conducted in a human cervical cancer cell line (HeLa) and a healthy human dermal fibroblast cell line (HDFa) by employing all AC loaded LNPs along with free drugs. Multicolor cell imaging was also observed in HeLa cells using ACPCSLNPs. Notably, more curcumin was released from the ACPCSLNPs than AC due to the presence of polar group attractions and polar-polar interactions between the lipid head groups and curcumin since curcumin is more soluble than AC in aqueous medium. In addition, the predictions of the release kinetic patterns were also investigated thoroughly using the exponential-based Korsmeyer-Peppas (K-P) and Higuchi models for drug-loaded LNPs and PLGA NPs, respectively.