The Use of Artificial Intelligence in the Formulation of Effervescent Tablets: A Review - Arunraj, Kalathum Padikkal; Haritha, Koradath Meethal; Khulood, Machilakath Thandamparmbil; Sana, Palasserri Ayisha; Thanha, Kuriyedath Parambil Khadeeja; Pramod, Kannissery (Mini Reviews in Medicinal Chemistry, 2025)
Artificial Intelligence (AI) is emerging as a valuable tool in pharmaceutical formulations, including the development of effervescent tablets (ETs). This review highlights how AI techniques are being explored to support ET formulation designs, optimize component ratios, predict disintegration and dissolution behavior, and control reactions through artificial neural networks, support vector machines, and machine learning. These techniques have been applied in recent studies to enhance stability, improve disintegration times, and flavor masking. Computational fluid dynamics simulations of effervescence and dissolution are underexplored for ETs. Data-driven approaches, like response surface modeling, require ingredient concentrations, tablet properties, consumer preferences, and predictive analytics for optimization. However, limited comprehensive datasets, complex reactions, environmental sensitivities, and ethical/regulatory considerations pose challenges. Overcoming these obstacles, as identified in the current literature, could enable AI to innovate ET development and personalization.
Keywords: Artificial Intelligence