The SeDeM expert diagram system: its performance and predictability in direct compressible formulations containing novel excipients and different types of activ

Abstract

The SeDeM Expert Diagram System is a galenic pre-formulation system, which evaluates the suitability of excipients and active pharmaceutical ingredients (API's) for direct compression into tablets as well as predicting possible formulations (i.e. ratios of API:excipient) to obtain acceptable direct compressible tablets. In this study, the prediction ability of the SeDeM Expert Diagram System with a special focus on testing the limits of the system was investigated. Three different active pharmaceutical ingredients (API's) in combination with a mix of classic and novel excipients which are currently in use in the wider pharmaceutical community were utilized. The API's and seven excipients were selected based on their physicochemical properties in order to determine the system's ability to predict ratios of API:excipient for acceptable direct compression tablets (e.g. acceptable weight variation as well as sufficient strength to withstand handling). Predicted formulations were tableted and evaluated according to the set criteria. If a tablet formulation failed to meet the criteria, the ratio of excipient to API was increased in 5% increments until a successful formulation was obtained, while the reverse was applied if a formulation was successful. The SeDeM Expert Diagram System proved to be proficient at predicting acceptable tablet formulations, with a few exceptions. The SeDeM system gave successful predictions for only two excipients (FlowLac® 100 and StarLac®) in the case of paracetamol as API. Contrary to predictions by SeDeM for paracetamol, drug loads between 15 and 30% were prepared depending on the excipient. This may be attributed to the ability of the novel excipients to compensate for the elastic properties of paracetamol. With regard to furosemide, none of the predicted formulations rendered acceptable tablets. This could be attributed to the cohesive properties of furosemide forming interactive mixtures with the excipient particles being coated by the relatively small furosemide particles (86.77% < 50 μm) imparting poor flow to the powder particles. In the case of pyridoxine, most of the formulations were predicted acceptable. This work indicates that in cases where the predicted formulation proved to be unsuccessful, by following an increment wise step-up in excipient:API ratio as formulation approach, it is possible to identify an acceptable formulation saving valuable time spent on formulation by a trial and error approach.

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