Careful control over the quality of pharmaceutical products is vital for the safety and
health of patients. With the ongoing process of new drug formulation and the growing
use of the existing pharmaceutical products, there is an increasing need for progress in
pharmaceutical technology and advances in process quality control with the aim of
improving the quality of end products and optimizing production efficiency.
Improving the production of pharmaceuticals with respect to their safety and quality is
the main goal of the process analytical technology (PAT) guidelines issued by the
American Food and Drug Administration (FDA). A special emphasis is placed on
developing new tools that would enable real-time and in-line monitoring of critical
quality attributes of materials and end products, thus enabling the identification and
evaluation of product and process variables that may be critical to product quality.
Coated pharmaceutical pellets that can be enclosed in capsules or compressed into
tablets are increasingly used in the production of solid dosage forms. Compared to
single-unit dosage forms, pellets offer the advantage of more favourable active
ingredient release profiles and drug absorption, which improves the therapeutic effects
of a medical treatment. In addition, their physical properties and flow characteristics
make production processes easier and more efficient. The biggest advantage of pellets
is the possibility of applying coatings, offering a high degree of precision and flexibility.
The amount of active ingredient included in the coating can be divided into desired
dose strengths without formulation or process changes. With the increasing use of
pellets as controlled release systems, beside mean coating thickness, the inter-pellet
and intra-pellet coating uniformity (morphological coating uniformity) are becoming
more and more important quality attributes of coated pellets. Monitoring all of these
quality attributes of coated pellets is thus of great importance for assuring the desired
end product characteristics.
The coating process is the most important production step affecting the critical quality
attributes of coated pellets. It is a complex multivariable process allowing many
possibilities for end product variability. A failed coating process can result in a
discarded batch of pellets, causing a financial and environmental burden. In accordance
with PAT guidelines, in-line and real-time monitoring of pellet coating process would
bring many benefits, not only in improving the quality of dosage forms of coated
pellets, but also for understanding and optimization of coating processes.
In most production settings, pre-defined process parameters are used to ensure the
repeatability of end product characteristics. The endpoint of a coating process is
determined by in-process sample acquisition and an off-line analytical method is used
to determine the quality of coating. The quality of coated pellets is thus tested at the
end of the process, not allowing for timely adjustments of process parameters to
modify the end product quality. In addition, the analytical techniques are often time
consuming and imprecise due to small number of pellets analysed.
In this dissertation, we propose a machine vision system as a PAT tool for monitoring
the coating process allowing for automatic contactless in-line assessment of critical
quality attributes of coated pellets in real-time. We designed a measuring system that
enables fast in-line acquisition of high-quality images of pellets in the existing visibility
conditions of a Wurster coating apparatus. We developed fast computer vision
algorithms for image analysis and accurate determination of pellet borders on the
acquired images. These results enable the monitoring of coating thickness of pellets in
real-time, during the coating process. The advantage of an automatic machine vision
system is that large number of measurements can be obtained in a relatively short time,
yielding good statistical estimations of pellet shape and size properties and their
distributions throughout the coating process. In this dissertation, we propose methods
for analysing measurements, obtained by the machine vision system, that allow the
evaluation of additional quality parameters that cannot be determined with currently
used methods for assessing quality of coated pellets, at least not with this level of
accuracy, time efficiency and quality of statistical estimations.
We propose an analysis of the pellets’ shape parameters obtained from the pellet
borders measurements, which is a valuable information as pellets’ shape properties
affect the quality of several steps of pharmaceutical production process. Monitoring the
specific shape parameters of pellets through the course of the coating process enables
the evaluation of morphological coating uniformity, which is an important quality
parameter of coated pellets, especially with controlled release systems. Equally as
important is the inter-pellet coating uniformity that occurs mainly due to differences in
size of pellets in the coating process. In the dissertation, we propose a method of
statistical analysis of pellet size distributions, obtained with the machine vision system
throughout the coating process, that enables evaluation of the dependence of coating
thickness on pellet size, evaluation of coating thickness distribution, and inter-pellet
coating uniformity parameters.
We conducted several pellet coating experiments in a laboratory-size Wurster coating
apparatus that we monitored with the machine vision system. In the dissertation, a
wholesome analysis of each experimental coating process is presented, as enabled by
the in-line measurements of machine vision system. The in-line results show
consistency with the course of each process. We also found a very good agreement with
the results of a reference method.
Many different analytical methods and procedures are in use for the off-line evaluation
of quality parameters of coated pharmaceutical pellets. Pellet samples, collected during
the experimental coating processes, were analysed with five additional analytical
methods. As part of the dissertation, a quantitative comparison of the results for pellet
coating quality parameters measurements is presented together with a qualitative
assessment of the methodological features of the methods that affect their adequacy for
quality control of coated pharmaceutical pellets.
The machine vision system, together with the newly presented methods for analysis of
in-line data for the evaluation of the key quality parameters of coated pellets, enables a
comprehensive assessment of quality of coated pellets, giving new insight into the
coating process. Information obtained through the presented coating analysis could
lead to a deeper understanding of the coating process and thus improve the quality
control of coated pharmaceutical pellets, which is in accordance with the goals of the
PAT guidelines.
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