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

Abstract

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.

Keywords: 3D printing; Design of experiments; Fused deposition modelling; Hot-melt extrusion; Paliperidone palmitate; Personalized medicine; Predictive models.