Trenfield, Sarah J;
Januskaite, Patricija;
Goyanes, Alvaro;
Wilsdon, David;
Rowland, Martin;
Gaisford, Simon;
Basit, Abdul W;
(2022)
Prediction of Solid-State Form of SLS 3D Printed Medicines Using NIR and Raman Spectroscopy.
Pharmaceutics
, 14
(3)
, Article 589. 10.3390/pharmaceutics14030589.
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Abstract
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.
| Type: | Article |
|---|---|
| Title: | Prediction of Solid-State Form of SLS 3D Printed Medicines Using NIR and Raman Spectroscopy |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.3390/pharmaceutics14030589 |
| Publisher version: | https://doi.org/10.3390/pharmaceutics14030589 |
| Language: | English |
| Additional information: | © 2022 MDPI. This is an open access article distributed under the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). |
| Keywords: | 3D printing; additive manufacturing; 3D printed drug products; manufacturing formulations; process analytical technology (PAT); oral drug delivery systems and technologies; printlets; personalized pharmaceuticals; digital healthcare |
| UCL classification: | UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > UCL School of Pharmacy > Pharmaceutics UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > UCL School of Pharmacy |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10145632 |
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