Pharmaceutical Applications of Liposomal Technology

Abstract

mal drug delivery systems have become an essential component of modern pharmaceutical development because they improve drug solubility, enhance targeted delivery, and reduce systemic toxicity. Despite significant advances, predicting longterm liposomal stability and therapeutic efficiency during formulation development remains a major challenge. This study identifies a research gap in the integration of explainable artificial intelligence (XAI) with liposomal formulation optimization for early-stage pharmaceutical decision-making. We propose a conceptual AI-driven framework that combines physicochemical descriptors of liposomes with machine learning models to predict formulation stability, encapsulation efficiency, and drug release performance. The manuscript synthesizes recent developments between 2021 and 2026 while emphasizing computational pharmaceutical intelligence rather than conventional formulation optimization alone. The proposed research aims to reduce experimental iterations, accelerate  formulation screening, and improve reproducibility across diverse liposomal drug candidates This work establishes a foundation for intelligent pharmaceutical manufacturing and personalized nanomedicine through data-driven formulation design