Vol. 7, Issue 2, Part D (2025)

A solid dosage form is a therapeutic formulation in which the active pharmaceutical ingredient and excipients are delivered in a stable solid state (e.g. tablets, capsules, powders, granules). These forms are widely used because they are relatively easy to manufacture, transport, handle, store, and administer and they tend to improve patient compliance due to convenience and precise dosing. In vitro characterization of solid dosage form refers to laboratory-based testing of pharmaceutical products like tablets and capsules to assess their physical, chemical and biopharmaceutical properties. These tests are critical for ensuring product quality, stability and performance prior to in vivo studies. However, conventional in vitro methods often face limitations including lack of accuracy, limited precision, poor reproducibility of in -vivo behaviour which can hinder efficient formulation development and quality control. Artificial Intelligence [AI] offers transformative potential by optimizing and predicting in vitro performance of solid dosage forms. AI models can quickly analyse large formulation and test datasets, find patterns and predict outcomes like dissolution profiles or bioavailability with high accuracy. Various AI tools and techniques include Machine Learning, Deep Learning, Cheminformatics and QSAR modelling. This review article elaborates on the fundamentals of in vitro characterization of solid dosage forms, highlights its limitations, explores the integration of Artificial Intelligence in addressing these challenges and discusses the tools and technologies that are shaping the future of pharmaceutical formulation and testing.