Analysis of film coating thickness and surface area of pharmaceutical pellets using fluorescence microscopy and image analysis

Andersson, Martin; Holmquist, Björn; Lindquist, Jörgen; Nilsson, Olle; Wahlund, Karl-Gustav

doi:10.1016/s0731-7085(99)00289-7

Cited by 48 publications

(16 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In different studies image analysis was applied to evaluate the film characteristics, such as film thickness or integrity [10][11][12][13][14][15][16][17]. The often applied dynamic image analysis measures the particle size of a high number of particles, which are detected as a particle flow passing through a measuring field [18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

In-line spatial filtering velocimetry for particle size and film thickness determination in fluidized-bed pellet coating processes

Folttmann

Knop

Kleinebudde

et al. 2014

European Journal of Pharmaceutics and Biopharmaceutics

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 99%

In-line spatial filtering velocimetry for particle size and film thickness determination in fluidized-bed pellet coating processes

Folttmann

Knop

Kleinebudde

et al. 2014

European Journal of Pharmaceutics and Biopharmaceutics

View full text Add to dashboard Cite

“…In spite of their evident closeness, the size distribution will repeat the distribution of the layer thickness only under an assumption that the latter is uniform. This assumption is acceptable as it is shown in Reference [10]. However measuring the size distribution of all samples in a process demands the use of quite expensive analytical equipment, which is not reasonable just for a conventional monitoring of the process end point.…”

Section: Process Monitoring Tasks and Application Of Image Analysismentioning

confidence: 99%

“…Existing in-line applications are often limited to visual monitoring of processes or capturing some geometrical properties of objects (e.g., particles) from process snapshots [10,11]. Being a direct analytical technique for morphological properties of an analyte is indeed one of the main advantages of the image analysis.…”

Section: Introductionmentioning

confidence: 99%

Monitoring of pellet coating process with image analysis—a feasibility study

Kucheryavski

Esbensen

Bogomolov³

2010

Journal of Chemometrics

View full text Add to dashboard Cite

Image analysis is an efficient technique used in many areas of science and industry. However, in process analytical applications it tends to be an ancillary tool, used mainly for visual monitoring or measuring some geometrical properties. At the same time, there are many other important aspects of the process samples appearance, besides measurable distances, that may be connected to the information of interest. In the present paper, the methods of image analysis were applied to at-line monitoring of fluid bed pellet coating process. The quantitative description of images of pellet samples, taken from different process stages, has been obtained using two different approaches: wavelet decomposition and angle measure technique (AMT). Both methods revealed a strong correlation between image features and process parameters. However, the AMT results turned out to be more accurate and stable. It has been shown that pellet images, taken with a conventional digital camera, can be used for at-line monitoring of the process course, specifically, the growth of pellets due to the coating. An algorithm for precise counting of pellets has been developed. Combined with the sample weighing, it enables an accurate determination of the mean added pellets' weight. The method can be used for the determination of the mean layer thickness, either by itself for at-line analysis or as a reference technique, when modeling the process from in-line spectroscopy data.

show abstract

“…Starting in the 1990s, coated particles were investigated, for example by cutting them in their equatorial plane and then examining the cut by SEM, see, e.g., [3]. Andersson et al [4] also cut coated particles, took images with a fluorescence microscope and evaluated these using image processing algorithms. However, these methods of characterization are either cumbersome to apply and destructive, or they provide information restricted to the sample surface.…”

Section: Introductionmentioning

confidence: 99%