Abstract: Poor aqueous solubility is a major barrier in drug development, affecting bioavailability, therapeutic efficacy, and formulation design. Estimates suggest that 70–90% of drug candidates and nearly 40% of marketed drugs exhibit limited solubility. This review examines both conventional and advanced approaches for solubility enhancement. Traditional strategies such as particle size reduction, salt formation, prodrug design, and solid dispersion have demonstrated measurable improvements, though challenges with stability, scalability, and reproducibility persist. In recent years, nanotechnology-based systems, including nanoparticles, liposomes, dendrimers, and metalorganic frameworks (MOFs), have emerged as promising platforms, offering superior solubility and bioavailability. However, these approaches face practical limitations in large-scale manufacturing and regulatory approval. Artificial intelligence (AI) contributes by predicting solubility behavior and streamlining formulation optimization, thereby complementing experimental strategies. Together, these innovations represent a shift toward more efficient and precise drug development. Improving solubility is not only critical for reducing dose requirements but also for enhancing patient adherence and clinical outcomes. The integration of nanotechnology with AI-based models provides a forward-looking path for overcoming current barriers in oral drug delivery. Future research should focus on addressing issues of cost-effectiveness, regulatory harmonization, and commercial scalability to ensure that these approaches translate successfully into clinical practice.
Thulasingam et al. (Mon,) studied this question.