Revista de Bioprocessamento e Biotécnicas

Optimizing Lipase-catalyzed Synthesis of Retinyl Laurate for Nutraceuticals Using Artificial Neural Networks and Ultrasound Enhancement

Abstract

Huang Li

The synthesis of retinyl laurate, a valuable nutraceutical compound, through lipase-catalyzed esterification presents a promising approach. However, traditional methods often face challenges with low efficiency and yield. This article introduces an innovative method that combines Artificial Neural Network (ANN) optimization with ultrasound support to enhance the lipase-catalyzed synthesis of retinyl laurate. Retinyl laurate, derived from vitamin A (retinol) and lauric acid, is known for its beneficial effects in skin care and nutrition. Traditional chemical synthesis methods are not only inefficient but also involve toxic reagents. Lipase-catalyzed esterification offers a more sustainable and effective alternative. By integrating ANN optimization with ultrasound assistance, this novel approach aims to further improve the efficiency and yield of the synthesis process. We discuss the benefits of this integrated method, explore its potential applications in the food and pharmaceutical industries and suggest directions for future research to advance this technology.