Physiologically Based In vitro Models to Predict the Oral Dissolution and Absorption of a Solid Drug Delivery System

To understand the sophisticated dynamic behaviors of drug elution and permeation in the gastrointestinal tract (GIT), researchers have tried to reemerge it by employing various in vitro experimental models. However, official in vitro apparatuses routinely used for quality control purposes, employ simple, non-physiologic buffers, and hydrodynamics conditions, and can not accurately perform continuous, dynamic in vivo pharmacokinetics (PK) behaviors. Therefore, different angles of GI physiology information are incorporate into novel models to forecast the dissolution and permeation of drug solid dosage forms. This review, in general, discusses some related studies of physiologically-based mechanical models to predict human absorption following oral administration in four sections. First the GIT, taken out of a complex physiological environment, where the drug is absorbed, distributed, metabolized and excreted (ADME) in the human body, is considered as the physiological basis for active pharmaceutics ingredients (API) dissolved and permeated through the epithelial cell. The second part embodies the theoretical foundation of in vitro models to predict human absorption and the corresponding in vitro.in vivo correlations (IVIVC). The third section summarizes physiologically based dissolution models developed recently, ranging from dynamic compartmental dissolution models, to biorelevant dissolution models based on certain physiological factors, to biphasic dissolution models. The last part is devoted to combined dissolution and absorption models that can be employed to simulate the continuous, dynamic behavior of oral drug delivery being dissolved and subsequently permeated across the GIT. Along with physiologically-based mechanically models spring up, pharmaceutical researchers will harvest better level A IVIVC for oral drug delivery systems, especially for sustained and controlled release preparations. On the other way hand, it will successively promote more effective bionic models to optimize prescription, design formulation, and develop innovative products.