Quantification of inkjet-printed pharmaceuticals on porous substrates using Raman spectroscopy and near-infrared spectroscopy

Tools

Edinger, Magnus and Iftimi, Laura-Diana and Markl, Daniel and Al-Sharabi, Mohammed and Bar-Shalom, Daniel and Rantanen, Jukka and Genina, Natalja (2019) Quantification of inkjet-printed pharmaceuticals on porous substrates using Raman spectroscopy and near-infrared spectroscopy. AAPS PharmSciTech, 20 (5). 207. ISSN 1530-9932 (https://doi.org/10.1208/s12249-019-1423-y)

[thumbnail of Edinger-etal-AAPS-PST-2019-Quantification-of-inkjet-printed-pharmaceuticals-on-porous-substrates]
Preview
 Text. Filename: Edinger_etal_AAPS_PST_2019_Quantification_of_inkjet_printed_pharmaceuticals_on_porous_substrates.pdf
Accepted Author Manuscript
Download (593kB)| Preview

Abstract

The use of inkjet printing for pharmaceutical manufacturing is gaining interest for production of personalized dosage forms tailored to specific patients. As part of the manufacturing, it is imperative to ensure that the correct dose is printed. The aim of this study was to use inkjet printing for manufacturing of personalized dosage forms combined with the use of near-infrared (NIR) and Raman spectroscopy as complementary analytical techniques for active pharmaceutical ingredient (API) quantification of the inkjet-printed dosage forms. Three APIs, propranolol (0.5–4.1 mg), montelukast (2.1–12.1 mg), and haloperidol (0.6–4.1 mg) were inkjet printed in 1 cm2 areas on a porous substrate. The printed doses were non-destructively analyzed by transmission NIR and Raman spectroscopy (both transmission and backscatter). X-ray computed microtomography (μ-CT) analysis was undertaken for porosity measurements of the substrate. The API content was confirmed using high-performance liquid chromatography (HPLC), and the content in the dosage forms was modeled from the NIR and Raman spectra using partial least squares regression (PLS). HPLC analysis revealed a linear correlation of the number of layers printed to the API content. The resulting PLS models for both NIR and Raman had R2 values between 0.95 and 0.99. The best predictive model was obtained using NIR, followed by Raman spectroscopy. μ-CT revealed the substrate to be highly porous and optimal for inkjet printing. In conclusion, NIR and Raman spectroscopic techniques could be used complementary as fast API quantification tools for inkjet-printed medicines.

ORCID iDs

Edinger, Magnus, Iftimi, Laura-Diana, Markl, Daniel ORCID logoORCID: https://orcid.org/0000-0003-0411-733X, Al-Sharabi, Mohammed, Bar-Shalom, Daniel, Rantanen, Jukka and Genina, Natalja;
CORE (COnnecting REpositories)