Near-Infrared Hyperspectral Imaging as a Monitoring Tool for On-Demand Manufacturing of Inkjet-Printed Formulations

Sandra Stranzinger, Matthias Wolfgang, Emma Klotz, Otto Scheibelhofer, Patrizia Ghiotti, Johannes G. Khinast, Wen Kai Hsiao, Amrit Paudel*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This study evaluates the potential use of near-infrared hyperspectral imaging (NIR-HSI) for quantitative determination of the drug amount in inkjet-printed dosage forms. We chose metformin hydrochloride as a model active pharmaceutical ingredient (API) and printed it onto gelatin films using a piezoelectric inkjet printing system. An industry-ready NIR-HSI sensor combined with a motorized movable linear stage was applied for spectral acquisition. Initial API-substrate screening revealed best printing results for gelatin films with TiO2 filling. For calibration of the NIR-HSI system, escalating drug doses were printed on the substrate. After spectral pre-treatments, including standard normal variate (SNV) and Savitzky-Golay filtering for noise reduction and enhancement of spectral features, principal component analysis (PCA) and partial least squares (PLS) regression were applied to create predictive models for the quantification of independent printed metformin hydrochloride samples. It could be shown that the concentration distribution maps provided by the developed HSI models were capable of clustering and predicting the drug dose in the formulations. HSI model prediction showed significant better correlation to the reference (HPLC) compared to on-board monitoring of dispensed volume of the printer. Overall, the results emphasize the capability of NIR-HSI as a fast and non-destructive method for the quantification and quality control of the deposited API in drug-printing applications. Graphical abstract: [Figure not available: see fulltext.]

Original languageEnglish
Article number211
JournalAAPS PharmSciTech
Volume22
Issue number6
DOIs
Publication statusPublished - Aug 2021

Keywords

  • Inkjet technology
  • Near-infrared hyperspectral imaging (NIR-HSI)
  • Personalized medicine
  • Predictive models
  • Process Analytical Technology (PAT)

ASJC Scopus subject areas

  • Pharmaceutical Science

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