Near-infrared chemical imaging (NIR-CI) of 3D printed pharmaceuticals
| Autor: | Johanna Aho, Dhara Raijada, Jukka Rantanen, Milad Khorasani, Magnus Edinger, Johan Bøtker |
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| Rok vydání: | 2016 |
| Předmět: |
Chemical imaging
Materials science Chemistry Pharmaceutical Polyesters Indomethacin Mixing (process engineering) Pharmaceutical Science 02 engineering and technology 030226 pharmacology & pharmacy Dosage form Polyethylene Glycols Excipients 03 medical and health sciences chemistry.chemical_compound 0302 clinical medicine Phase (matter) Nitrofurantoin Monohydrate Technology Pharmaceutical Organic chemistry Least-Squares Analysis Dosage Forms Spectroscopy Near-Infrared Ethylene oxide 021001 nanoscience & nanotechnology Durapatite Nitrofurantoin Pharmaceutical Preparations chemistry Chemical engineering Printing Three-Dimensional Polycaprolactone Extrusion 0210 nano-technology |
| Zdroj: | International Journal of Pharmaceutics. 515:324-330 |
| ISSN: | 0378-5173 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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