Application of a handheld NIR spectrometer in prediction of drug content in inkjet printed orodispersible formulations containing prednisolone and levothyroxine

A1 Journal article (refereed)


Internal Authors/Editors


Publication Details

List of Authors: Vakili H, Wickström H, Desai D, Preis M, Sandler N
Publisher: Elsevier
Publication year: 2017
Journal: International Journal of Pharmaceutics
Journal acronym: ijpharm
Volume number: 524
Issue number: 1-2
Start page: 414
End page: 423
ISSN: 0378-5173


Abstract

Quality control tools to assess the quality of printable orodispersible formulations are yet to be defined. Four different orodispersible dosage forms containing two poorly soluble drugs, levothyroxine and prednisolone, were produced on two different edible substrates by piezoelectric inkjet printing. Square shaped units of 4 cm2 were printed in different resolutions to achieve an escalating drug dose by highly accurate and uniform displacement of droplets in picoliter range from the printhead onto the substrates. In addition, the stability of drug inks in a course of 24 h as well as the mechanical properties and disintegration behavior of the printed units were examined. A compact handheld near–infrared (NIR) spectral device in the range of 1550–1950 nm was used for quantitative estimation of the drug amount in printed formulations. The spectral data was treated with mean centering, Savitzky–Golay filtering and a third derivative approach. Principal component analysis (PCA) and orthogonal partial least squares (OPLS) regression were applied to build predictive models for quality control of the printed dosage forms. The accurate tuning of the dose in each formulation was confirmed by UV spectrophotometry for prednisolone (0.43–1.95 mg with R2 = 0.999) and high performance liquid chromatography for levothyroxine (0.15–0.86 mg with R2 = 0.997). It was verified that the models were capable of clustering and predicting the drug dose in the formulations with both Q2 and R2Y values between 0.94–0.99.


Keywords

Multivariate analysis, NIR spectroscopy, Orodispersible formulations, Personalized medicine, Piezoelectric inkjet printing, Quality control

Last updated on 2019-22-08 at 06:31