Artificial Intelligence-Integrated Self-Emulsifying Drug Delivery Systems (AI-SEDDS)
Abstract
Self-emulsifying drug delivery systems (SEDDS) are lipid-based formulations generally containing oil, surfactant and co-surfactant or a cosolvent. Dilution results in formation of fine dispersions, enabling solubilization of lipophilic drugs and/or improving their dissolution and/or absorption. While formulation of SEDDS remains largely empirical and requires extensive experimentation, artificial intelligence (AI) can be leveraged for predictive excipient selection, design of critical quality attribute (CQA) space, multi-objective optimization, precipitation risk ranking and active design of experiments. This review proposes an AI-integrated SEDDS loop encompassing molecular descriptors, excipients, formulation design, gastrointestinal performance and pharmacokinetic (PK) outcomes. Bayesian optimization, explainable AI, supersaturable and solid SEDDS, digital twin and self-driving lab concepts are also discussed. The overall perspective is that AI should complement traditional pharmaceutical experimentation and that standardized dataset creation and external validation are critical enablers.
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