Proof of concept of a predictive model of drug release from long-acting implants obtained by fused-deposition modeling

In the pharmaceutical field, there is a growing interest in manufacturing of drug delivery dosage forms adapted to the needs of a large variety of patients. 3D printing has proven to be a powerful tool allowing the adaptation of immediate drug delivery dosage forms. However, there are still few studies focusing on the adaptation of long acting dosage forms for patient suffering of neurological diseases. In this study, paliperidone palmitate (PP) was chosen as a model drug in combination with different polymers adapted for fused-deposition modeling (FDM). The impact of different printing parameters on the release of PP were investigated. The layer thickness and the infill percentage were studied using a quality by design approach. Indeed, by defining the critical quality attributes (CQA), a proof of concept of a prediction system, and a quality control system were studied through designs of experiments (DoE). The first part of this study was dedicated to the release of PP from a fix geometry. In the second part, the prediction system was developed to require only surface and surface to volume ratio. From that point, it was possible to get rid of a fix geometry and predict the amount of PP released from complex architectures.