Optimization of mangifera indica L. Kernel extract-loaded nanoemulsions via response surface methodology, characterization, stability, and skin permeation for anti-acne cosmeceutical application

Abstract

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This study aimed to optimize nanoemulsions loading with Mangifera indica L. kernel extract using response surface methodology for enhancing the stability and skin permeation of the extract. Central composite design was employed for optimization and evaluation of three influencing factors including hydrophile-lipophile balance (HLB), % co-surfactant (PEG-7 glyceryl cocoate), and surfactant-to-oil ratio (SOR) on physical properties of the nanoemulsions. The desired nanoemulsions were then incorporated with the extract and characterized. Physicochemical properties of the extract-loaded nanoemulsions and their antibacterial effects against Propionibacterium acnes were also evaluated after storage at various conditions and compared to those of the initial. Ex vivo skin permeation was also investigated. The factors significantly (p < 0.05) influenced on droplet size, polydispersity index (PDI), and zeta potential, especially HLB of the surfactant and its combined effects with co-surfactant and SOR. The extract-loaded nanoemulsions revealed a very small spherical droplets (size of 26.14 ± 0.22 nm) with narrow size distribution (PDI of 0.16 ± 0.02). The formulation also presented an excellent stability profile and successfully enhanced antibacterial stability of the extract comparing with the extract solution. Ex vivo skin permeation study illustrated that the extract in nanoemulsions could be delivered through a primary skin barrier to reach viable epidermis dermis layers. In conclusion, the affinity of surfactant and hydrophilicity of the system play a crucial role in nanoemulsions’ characteristics. Such results might provide promising anti-acne nanoemulsions with the notable capacities of extract stabilization and permeation enhancing which will be further clinically evaluated.