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
Highlights
IntroductionCurrent pharmaceutical research exhibits increasing interest in printing technology, since it combines dosing strength flexibility with accuracy and precision of established printing technologies, making it a tempting tool for personalized medicine
Sandra Stranzinger and Matthias Wolfgang contributed to this work.Highlights Near-infrared hyperspectral imaging (NIR-HSI) for inkjet-printed formulations Strong correlation between active pharmaceutical ingredient (API) mass predicted by NIR-HSI and High-Performance Liquid Chromatography (HPLC) data Visualization of active pharmaceutical ingredients (APIs) distributions in single- and multilayered systems Development of predictive NIR-HSI models for quantitative API determinationCurrent pharmaceutical research exhibits increasing interest in printing technology, since it combines dosing strength flexibility with accuracy and precision of established printing technologies, making it a tempting tool for personalized medicine
In order to screen viable API-substrate combinations, all six substrates were printed with metformin hydrochloride using the patterns described in Section “Printing Pattern for Calibration and Test Samples.”
Summary
Current pharmaceutical research exhibits increasing interest in printing technology, since it combines dosing strength flexibility with accuracy and precision of established printing technologies, making it a tempting tool for personalized medicine. The need for personalized and accurate drug dosing, as well as improved dose compliance and adherence, has created a unique opportunity for inkjet technology in the field of pharmaceutics [1,2,3,4]. Et al recently published a comprehensive review on the pharmaceutical application of inkjet printing technologies discussing about current technologies and future challenges [5]. Inkjet printing offers potential for accurate, consistent, spatially localized, low-cost, and high-speed dispensing of a large variety of multicomponent systems containing one or several active pharmaceutical ingredients (APIs) and excipients in a microarray format which makes it possible to achieve uniform distribution of the constituents [6]
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