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Prediction of Solid-State Form of SLS 3D Printed Medicines Using NIR and Raman Spectroscopy
Selective laser sintering (SLS) 3D printing is capable of revolutionising pharmaceutical manufacturing, by producing amorphous solid dispersions in a one-step manufacturing process. Here, 3D-printed formulations loaded with a model BCS class II drug (20% w/w itraconazole) and three grades of hydroxy...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8949593/ https://www.ncbi.nlm.nih.gov/pubmed/35335965 http://dx.doi.org/10.3390/pharmaceutics14030589 |
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author | Trenfield, Sarah J. Januskaite, Patricija Goyanes, Alvaro Wilsdon, David Rowland, Martin Gaisford, Simon Basit, Abdul W. |
author_facet | Trenfield, Sarah J. Januskaite, Patricija Goyanes, Alvaro Wilsdon, David Rowland, Martin Gaisford, Simon Basit, Abdul W. |
author_sort | Trenfield, Sarah J. |
collection | PubMed |
description | Selective laser sintering (SLS) 3D printing is capable of revolutionising pharmaceutical manufacturing, by producing amorphous solid dispersions in a one-step manufacturing process. Here, 3D-printed formulations loaded with a model BCS class II drug (20% w/w itraconazole) and three grades of hydroxypropyl cellulose (HPC) polymer (-SSL, -SL and -L) were produced using SLS 3D printing. Interestingly, the polymers with higher molecular weights (HPC-L and -SL) were found to undergo a uniform sintering process, attributed to the better powder flow characteristics, compared with the lower molecular weight grade (HPC-SSL). XRPD analyses found that the SLS 3D printing process resulted in amorphous conversion of itraconazole for all three polymers, with HPC-SSL retaining a small amount of crystallinity on the drug product surface. The use of process analytical technologies (PAT), including near infrared (NIR) and Raman spectroscopy, was evaluated, to predict the amorphous content, qualitatively and quantitatively, within itraconazole-loaded formulations. Calibration models were developed using partial least squares (PLS) regression, which successfully predicted amorphous content across the range of 0–20% w/w. The models demonstrated excellent linearity (R(2) = 0.998 and 0.998) and accuracy (RMSEP = 1.04% and 0.63%) for NIR and Raman spectroscopy models, respectively. Overall, this article demonstrates the feasibility of SLS 3D printing to produce solid dispersions containing a BCS II drug, and the potential for NIR and Raman spectroscopy to quantify amorphous content as a non-destructive quality control measure at the point-of-care. |
format | Online Article Text |
id | pubmed-8949593 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-89495932022-03-26 Prediction of Solid-State Form of SLS 3D Printed Medicines Using NIR and Raman Spectroscopy Trenfield, Sarah J. Januskaite, Patricija Goyanes, Alvaro Wilsdon, David Rowland, Martin Gaisford, Simon Basit, Abdul W. Pharmaceutics Article Selective laser sintering (SLS) 3D printing is capable of revolutionising pharmaceutical manufacturing, by producing amorphous solid dispersions in a one-step manufacturing process. Here, 3D-printed formulations loaded with a model BCS class II drug (20% w/w itraconazole) and three grades of hydroxypropyl cellulose (HPC) polymer (-SSL, -SL and -L) were produced using SLS 3D printing. Interestingly, the polymers with higher molecular weights (HPC-L and -SL) were found to undergo a uniform sintering process, attributed to the better powder flow characteristics, compared with the lower molecular weight grade (HPC-SSL). XRPD analyses found that the SLS 3D printing process resulted in amorphous conversion of itraconazole for all three polymers, with HPC-SSL retaining a small amount of crystallinity on the drug product surface. The use of process analytical technologies (PAT), including near infrared (NIR) and Raman spectroscopy, was evaluated, to predict the amorphous content, qualitatively and quantitatively, within itraconazole-loaded formulations. Calibration models were developed using partial least squares (PLS) regression, which successfully predicted amorphous content across the range of 0–20% w/w. The models demonstrated excellent linearity (R(2) = 0.998 and 0.998) and accuracy (RMSEP = 1.04% and 0.63%) for NIR and Raman spectroscopy models, respectively. Overall, this article demonstrates the feasibility of SLS 3D printing to produce solid dispersions containing a BCS II drug, and the potential for NIR and Raman spectroscopy to quantify amorphous content as a non-destructive quality control measure at the point-of-care. MDPI 2022-03-08 /pmc/articles/PMC8949593/ /pubmed/35335965 http://dx.doi.org/10.3390/pharmaceutics14030589 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Trenfield, Sarah J. Januskaite, Patricija Goyanes, Alvaro Wilsdon, David Rowland, Martin Gaisford, Simon Basit, Abdul W. Prediction of Solid-State Form of SLS 3D Printed Medicines Using NIR and Raman Spectroscopy |
title | Prediction of Solid-State Form of SLS 3D Printed Medicines Using NIR and Raman Spectroscopy |
title_full | Prediction of Solid-State Form of SLS 3D Printed Medicines Using NIR and Raman Spectroscopy |
title_fullStr | Prediction of Solid-State Form of SLS 3D Printed Medicines Using NIR and Raman Spectroscopy |
title_full_unstemmed | Prediction of Solid-State Form of SLS 3D Printed Medicines Using NIR and Raman Spectroscopy |
title_short | Prediction of Solid-State Form of SLS 3D Printed Medicines Using NIR and Raman Spectroscopy |
title_sort | prediction of solid-state form of sls 3d printed medicines using nir and raman spectroscopy |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8949593/ https://www.ncbi.nlm.nih.gov/pubmed/35335965 http://dx.doi.org/10.3390/pharmaceutics14030589 |
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