Research Articles
New Perspectives for Visual Characterization of Pharmaceutical Solids

https://doi.org/10.1002/jps.10529Get rights and content

Abstract

The utilization of descriptive image information in pharmaceutical powder technology is rather limited. Consequently, the development of this discipline is a challenge within physical characterization of pharmaceutical solids. The aim of this study was to develop and evaluate an inventive visual characterization approach for monitoring the granule growth in a fluidized‐bed granulation process and to use the generated image information in the prediction of tabletting behavior of granules. Surface images of samples from 34 granulations were continuously captured during the spraying and drying phases of the process and particle size distributions were determined. The gray scale difference matrix (GSDM) was derived from two surface images taken in controlled illumination conditions. The particle size calculation from the surface images was based on a multivariate Partial Least Square (PLS) model between the GSDM and sieve analysis measurements. The image information of the end‐point samples was also evaluated with respect to tabletting behavior of the granules produced. Principal component analysis (PCA) was used for data visualization. The introduced approach was suitable in particle size measurements of granules during all process phases and in the monitoring of different kinds of granule growth behavior. The visual inspection of the granule samples was powerful, enabling representational batch‐to‐batch comparisons. The tabletting behavior of the granules could be predicted directly from particle size information generated from the surface images. PCA as a projection method was efficient in data visualization. Development of process analytical technologies (PAT) aims at improving the efficiency of processes. The presented visual characterization approach can be an effective process analytical tool in particle size analysis also enabling the evaluation of the further product quality in the end of the granulation process. The idea of characterization of bulk surface images opens new perspectives for characterization of pharmaceutical solids. © 2004 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 93:165–176, 2004

Section snippets

INTRODUCTION

Granulation is an important unit operation in powder handling in the pharmaceutical industry. This process is carried out primarily to produce material of desirable particle size and shape to improve processing properties, i.e., blend uniformity, the flowability, and tabletting behavior, of powder masses. Consequently, the monitoring of particle growth kinetics is important in a granulation process. The principles and mechanisms of granule growth kinetics have been thoroughly described in the

Materials

A model formulation (batch size 3500 g) consisting of 5% wt/wt of caffeine (Orion Pharma, Espoo, Finland), 475 g microcrystalline cellulose (MCC) (Emcocel 50M, Penwest Pharmaceuticals, Nastola, Finland), 2200 g lactose monohydrate (Pharmatose 200M, DMV Pharma, Veghel, The Netherlands), and 500 g pregelatinized starch (Starch 1500, Colorcon, Indianapolis, IN). Polyvinylpyrrolidone (PVP) (Kollidon K25, BASF, Ludwigshafen, Germany) was used as a binder in the formulation (5% wt/wt). Solutions in

Particle Size Measurements

The mean particle sizes of the end‐point or the final product for each batch are presented in Table 1. We can see that the end‐point mean particle size measured by sieving varies from 223 to 1413 μm. The Pearson correlation coefficient between the mean sizes measured from surface images and the mean size measured by sieving is 0.97. A similar Pearson correlation coefficient (0.98) for particle mean size using the end‐point values for a fitted curve (the fitting is explained below) and sieve

CONCLUSIONS

This study introduced a system for analysis and control of a pharmaceutical manufacturing process. The technique is a proper tool in process control of pharmaceutical solids and powerful in granule growth kinetics research. Furthermore, surface image information can be used in the prediction of functional properties granules to estimate further prosessability. Fast screening of tabletting properties can be made using the combination of multivariate visualization and image information. In

Acknowledgements

The authors wish to thank student Heidi Kettunen for technical assistance with the imaging and students Antti Eskelinen and Tina Suominen for the technical assistance with the granulations.

Cited by (52)

  • Applications of machine vision in pharmaceutical technology: A review

    2021, European Journal of Pharmaceutical Sciences
  • An investigation of the acoustic emission generated during crystallization process of salicylic acid

    2017, Powder Technology
    Citation Excerpt :

    However, few studies deal with the AE monitoring of crystallization processes [22–24]. Acoustic monitoring techniques, in comparison to optical techniques such as spatial filtering technique, near infrared and image analysis [25–30], do not require a window or port into the process vessel. So, there is no need for equipment modifications and it can avoid the inaccurate measurements or impossible of data collection caused by fouling optical probe head or window.

View all citing articles on Scopus
View full text