Synthetic Approaches and AI-Assisted Characterization of API-Based Ionic Liquids: A Strategy to Enhance Physicochemical Properties

Numerous active pharmaceutical ingredients (APIs) face challenges such as limited water solubility, poor absorption in the body (bioavailability), and instability due to polymorphic transformations. To address these issues, API-based ionic liquids (API-ILs) have emerged as a powerful and innovative solution, capable of improving the physicochemical properties of APIs while preserving their original molecular identity. This review explores a range of synthetic methods such as metathesis, neutralization, mechano-chemical techniques, and microwave-assisted synthesis that enable the creation of customized, task-specific ionic liquids. It also highlights a broad array of characterization tools, from conventional methods like NMR, FTIR, DSC, and XRD, to advanced AI-driven technologies including machine learning-based NMR prediction, MALDI matrix modelling, and SERS analysis. These tools accelerate the understanding and fine-tuning of API-ILs for pharmaceutical use. Additionally, the review compiles recent examples of bioactive API-ILs, showcasing their improved solubility, permeability, thermal resistance, and multifunctional therapeutic potential. The use of artificial intelligence in the analysis and design of ionic liquids is opening new frontiers in drug formulation and eco-friendly pharmaceutical development. Ultimately, API-ILs represents a promising avenue for enhancing drug delivery through various routes, including oral, transdermal, and injectable systems.