Hot-melt extrusion and 3D printing are enabling manufacturing approaches for patient-centred medicinal products. Hot-melt extrusion is a flexible and continuously operating technique which is a crucial part of a typical processing cycle of printed medicines. In this work we use hot-melt extrusion for manufacturing of medicinal films containing
indomethacin (IND) and
polycaprolactone (PCL), extruded strands with
nitrofurantoin monohydrate (NFMH) and poly (
ethylene oxide) (PEO), and feedstocks for 3D printed
dosage forms with
nitrofurantoin anhydrate (NFAH),
hydroxyapatite (HA) and
poly (lactic acid) (PLA). These feedstocks were printed into a prototype solid
dosage form using a desktop 3D printer. These model formulations were characterized using near-infrared chemical imaging (NIR-CI) and, more specifically, the image analytical data were analysed using multivariate curve resolution-alternating least squares (MCR-ALS). The MCR-ALS algorithm predicted the spatial distribution of IND and PCL in the films with reasonable accuracy. In the extruded strands both the chemical mapping of the components in the formulation as well as the solid form of the active compound could be visualized. Based on the image information the total
nitrofurantoin and PEO contents could be estimated., The
dehydration of NFMH to NFAH, a process-induced solid form change, could be visualized as well. It was observed that the level of
dehydration increased with increasing processing time (recirculation during the mixing phase of molten PEO and
nitrofurantoin). Similar results were achieved in the 3D printed solid
dosage forms produced from the extruded feedstocks. The results presented in this work clearly demonstrate that NIR-CI in combination with MCR-ALS can be used for chemical mapping of both active compound and
excipients, as well as for visualization of solid form variation in the final product. The suggested NIR-CI approach is a promising process control tool for characterization of innovative patient-centred medicinal products.