Artificial neural networks for optimizing liquid pharmaceutical dosage forms: Application of ibuprofen microemulsions stability

Abstract

Recent studies have focused on leveraging artificial neural networks (ANNs) to optimize the formulation of pharmaceutical drug micro-emulsions, specif-ically targeting the ideal composition of surfactants, co-surfactants, oil, wa-ter, and process factors that determine key characteristics like stability, drop-let size, and clarity of liquid dosage forms [1]. ANNs, a machine learning technique inspired by biological neural networks in animal brains, are capa-ble of identifying patterns and correlations within complex datasets, allowing them to forecast or optimize systems effectively. By training ANNs to rec-ognize these relationships, they can be used to enhance the formulation pro-cess, making predictions that guide optimization efforts [2]