Towards a Better Understanding of the Post-Gastric Behavior of Enteric-Coated Formulations.

PURPOSE: The aim of our work was to develop a biorelevant dissolution method for a better understanding of the in vivo performance of delayed-release tablet formulations. METHODS: The typical pH profile and residence times in the stomach and small intestine were determined in fasted conditions based on the published results of swallowable monitoring devices. Then, a multi-stage pH shift dissolution method was developed by adding different amounts of phosphate-based buffer solutions to the initial hydrochloric acid solution. Because of the highly variable in vivo residence times in the stomach, two alternatives of the method were applied, modeling rapid and slow gastric emptying as well. This approach provided an opportunity to study the effect of the acidic treatment on post gastric release. Six enteric-coated low-dose acetylsalicylic acid (ASA) formulations including the reference Aspirin Protect were tested as a model compound. Moreover, the thickness of the coating of each formulation was investigated by scanning electron microscope. RESULTS: Comparing the in vitro results to the known properties of the formulations, the new method was found to be more discriminative than the USP dissolution method. Ingredients affecting the in vitro dissolution, and thus probably the in vivo performance, were identified in both the tablet core and the coating of the tested formulations. The limited available in vivo data also indicated an increased predictivity. CONCLUSION: Overall, the presented method may be an efficient tool to support the development of enteric coated generic formulations.

Evaluation of floatability characteristics of gastroretentive tablets using VIS imaging with artificial neural networks.

Gastroretentive dosage forms are recommended for several active substances because it is often necessary for the drug to be released from the carrier system into the stomach over an extended period. Among gastroretentive dosage forms, floating tablets are a very popular pharmaceutical technology. In this study, it was investigated whether a rapid, nondestructive method can be used to characterize the floating properties of a tablet. To accomplish our objective, the same composition was compressed, and varied compression forces were applied to achieve the desired tablet. In addition to physical examinations, digital microscopic images of the tablets were captured and analyzed using image analysis techniques, allowing the investigation of the floatability of the dosage form. Image processing algorithms and artificial neural networks (ANNs) were utilized to classify the samples based on their strength and floatability. The input dataset consisted solely of the acquired images. It has been shown by our research that visible imaging coupled with pattern recognition neural networks is an efficient way to categorize these samples based on their floatability. Rapid and non-destructive digital imaging of tablet surfaces is facilitated by this method, offering insights into both crushing strength and floating properties.