Issue 61, 2017

Real-time monitoring of granule properties during high shear wet granulation by near-infrared spectroscopy with a chemometrics approach

Abstract

We developed an in-line near-infrared spectroscopy (NIRS) monitoring method enabling a rapid and non-invasive analysis of granule properties during the high shear wet granulation (HSWG) process. Eleven batches were manufactured and used as the calibration dataset and an additional batch was manufactured and used as the validation dataset. The HSWG process was directly monitored using an acousto-optical tunable filter (AOTF)-NIR spectrometer and the NIR spectra related to the physical and chemical changes of the granules were acquired. The particle size, tapped density, bulk density, and powder flowability of the granules were qualitatively and quantitatively evaluated by a chemometrics approach. Principal component analysis (PCA) and partial least square regression (PLSR) were applied for the qualitative and quantitative modelling of the granule properties. The PCA score plots showed a clear relationship between the granule properties and the granulation progress and provided an effective means for the endpoint determination of the manufacturing process. The PLSR models constructed for the quantitative evaluation of the granule properties were demonstrated to be predictive with high accuracy. These findings allow HSWG to be monitored in-line and controlled effectively. A better understanding of the process by NIRS with chemometrics will contribute to developing high-quality drug products using the required quality-by-design approach.

Graphical abstract: Real-time monitoring of granule properties during high shear wet granulation by near-infrared spectroscopy with a chemometrics approach

Article information

Article type
Paper
Submitted
09 May 2017
Accepted
29 Jul 2017
First published
03 Aug 2017
This article is Open Access
Creative Commons BY license

RSC Adv., 2017,7, 38307-38317

Real-time monitoring of granule properties during high shear wet granulation by near-infrared spectroscopy with a chemometrics approach

F. Shikata, S. Kimura, Y. Hattori and M. Otsuka, RSC Adv., 2017, 7, 38307 DOI: 10.1039/C7RA05252A

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.

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