Enzymatic synthesis of dilaurylazelate ester for nanocosmeceutical application

Azelaic acid (AzA) and its derivatives have been known to be effective in the treatment of acne and various cutaneous hyperpigmentary disorders for cosmeceutical application. Currently, azelaic acid is available in the market as a 20% azelaic acid cream for the treatment of acne, and has been approved for use by the Food and Drug Administration (FDA). However, high concentration (20%) of azelaic acid is needed to guarantee the drug availability in the skin, which caused an increase the incidence of side effects such as irritation, dryness, and redness of the skin associated with exposure to high levels of undissolved dispersed azelaic acid having an inherent low pH. A derivative of azelaic acid with even better characteristics than the original starting material may be produced through the modification to azelaic acid, especially the efficacy of a relatively low dosage of AzA derivatives in the treatment of acne. Dilaurylazelate ester was produced through the esterification of azelaic acid with lauryl alcohol using immobilized lipase B from Candida antarctica (Novozym 435). The chemical and physical characterization of dilaurylazelate ester was analyzed in order to be effectively applied in cosmeceutical application. The chemical characterization was determined by Fourier-Transform Infrared spectroscopy (FT-IR), Gas Chromatography Mass Spectroscopy (GCMS), and Nuclear Magnetic Resonance (NMR) in order to verify and elucidate the structure of product. The normal fibroblasts cell line (3T3) was used to assess the cytotoxicity of dilaurylazelate ester and the antibacterial activity against the pathogen bacteria Propionibacterium acnes ATCC 11827 was studied. Response surface methodology (RSM) and artificial neural network (ANN) were used to optimize and predict various performance parameters of the enzymatic reaction conditions, namely enzyme amount, reaction time, reaction temperature and molar ratio of substrates that could affect on the degree of percentage conversion of dilaurylazelate ester. The optimization and prediction capabilities of RSM and ANN were then compared. The results obtained showed, ANN model predicted is more accurately compared to RSM since ANN model has lower percentage of residual square error (0.35%). The higher prediction accuracy of ANN model was due to generation of the model by multiple iterative calculations whereas single step calculation in the case of RSM. Nanoemulsion has been chosen to be a carrier in encapsulation of dilaurylazelate ester for the treatment of acne. In this work, a D-optimal mixture design was used to determine the optimal composition of nanoemulsion-based system loaded with dilaurylazelate ester. The ultimate goal of the present work was to determine the optimum level of five independent variables (linoleic acid, T80:PF68, glycerol, dilaurylazelate ester, and water) in the nanoemulsion composition with minimum average droplet size. Under the optimal conditions, the predicted average droplet size was obtained 161.90nm, which possessed a good stability over 3 months’ storage at different temperatures. In addition, physicochemical characterizations of the optimal nanoemulsion showed its suitability for topical application due to its stability against phase separation. The permeation study revealed that when nanoemulsion was used as carrier vehicle, permeability of dilaurylazelate ester was significantly improved. Besides, cytotoxicity result further supported the safety and suitability of formulation to be used as a topical product in cosmeceutical fields with IC50 higher than 100μg/ml is considered non-toxic and also was classified as dermally non-irritant with a human irritancy equivalent. In vivo skin analysis towards healthy volunteers showed a significant improvement in the stratum corneum in skin hydration, which would be useful in treating the dry skin of acne patients