Elastic recovery in roll compaction simulation.

Roll compaction/dry granulation is a widely used granulation method in the pharmaceutical industry. The simulation of the process is of great interest, especially in the early phase of formulation development of solid dosage forms. The hybrid modeling approach allows to predict the roll compaction process parameters to produce ribbons with a desired solid fraction. Based on the process parameters, compacts (ribblets) of the same solid fraction are produced on a single punch press. So far, the prediction accuracy for the solid fraction of the ribbons was not satisfactory. It was found that the lack in prediction accuracy was due to the elastic recovery, which was not considered in the model. In this study, the fast in-die and the slow out-of-die elastic recovery of different excipients with varying compaction properties were investigated. A method was established to compensate for the elastic recovery of compacts in roll compaction simulation and to improve the prediction accuracy of the solid fraction considerably. The results were successfully implemented into the model through an additional learning step. Moreover, the findings were transferred to the mimicking of an API containing formulation. By modeling, it was possible to accurately predict the process settings to obtain ribbons with the desired solid fraction using only a small amount of material.