Design of an expert system for the development and formulation of push-pull osmotic pump tablets containing poorly water-soluble drugs.

The purpose of this article was to build an expert system for the development and formulation of push-pull osmotic pump tablets (PPOP). Hundreds of PPOP formulations were studied according to different poorly water-soluble drugs and pharmaceutical acceptable excipients. The knowledge base including database and rule base was built based on the reported results of hundreds of PPOP formulations containing different poorly water-soluble drugs and pharmaceutical excipients and the experiences available from other researchers. The prediction model of release behavior was built using back propagation (BP) neural network, which is good at nonlinear mapping and learning function. Formulation design model was established based on the prediction model of release behavior, which was the nucleus of the inference engine. Finally, the expert system program was constructed by VB.NET associating with SQL Server. Expert system is one of the most popular aspects in artificial intelligence. To date there is no expert system available for the formulation of controlled release dosage forms yet. Moreover, osmotic pump technology (OPT) is gradually getting consummate all over the world. It is meaningful to apply expert system on OPT. Famotidine, a water insoluble drug was chosen as the model drug to validate the applicability of the developed expert system.