New Image Analysis Approach for Particle Size Monitoring of Pharmaceutical Solids
Dr. Niklas Sandler
Senior Researcher, Division of Pharmaceutical Technology
University of Helsinki-Finland
If visual or image information is used in science,
exact descriptors for this information is usually needed.
The utilization of descriptive image information
in pharmaceutical powder technology is rather limited.
Subsequently, the development of this discipline is a
challenge within physical characterization of pharmaceutical
solids and process monitoring. In this paper, a
new image analysis approach for monitoring of particle
size is briefly described. Also, it is shown how the generated
image information can be utilized in the prediction
of tableting behavior of granules using multivariate
methods i.e., chemometrics.
The characterization of powders and granular materials
is of great interest within the pharmaceutical sciences.
As approximately 80% of all drug products are
solids i.e., tablets or capsules, the understanding of the
physical characteristics of powders and granules is
essential [1]. For the pharmaceutical industry, a comprehensive
knowledge of these materials has a major economic
impact. The physical characteristics of solid particulates
have to be considered and studied throughout
the development process of a product, from the preformulation
stage to large-scale manufacturing. In development
and manufacturing, many powder handling steps
are involved, including crystallization, blending, granulation,
and compaction. Thus, different kinds of interactions
between particles and between particles and
process equipment occur. All these interactions together
with specific behavior bulk materials in certain unit
operations may give rise to many problems.
The bulk properties of a material depend to a great
extent on its particle size distribution. Various techniques
for measuring the particle size distribution of powders
exist. Common methods used with pharmaceutical solids
are sieving and laser diffraction. Asingle measurement
technique cannot be used to cover the wide size range
from nanometers to millimeters. Moreover, many aspects
have to be considered before making the proper choice of
measurement principle e.g., the capital costs versus running
costs, speed of operation, degree of skill required
for operation, and most importantly, the end-use requirement.
Different particle size analysis techniques are well
described in the literature [2]. Most often, microscopy is
(has to be) used to verify the particle size measured by
“black box” techniques. In order to avoid parallel
methodologies, efforts to enhance imaging technologies
in particle size have to be made and fortunately, during
the recent years, this has happened. In this paper, one
approach; a fast particle sizing technique based on surface
imaging of undispersed particles, is presented.
When considering classical IAor the measurement of dispersed individual particles. The reluctance of the
use of IAin routine analysis of particle morphology e.g.,
due to relative slowness of the process and the large size
of the image as a dataset has been discussed in the literature
[3]. Orientation effects of particles can also distort
the generated IAdata. Since image processing tasks are
needed, the IA procedure is usually performed semiautomatically
and a skilled operator is usually needed.
The largest source of error in optical IAis probably the
sample preparation i.e., the dispersion of the powder.
However, automatic sample preparation techniques have
been developed lately and automated on-line systems for
various processes have also been successfully used over
the past decade.
The inspection of surface information can be made
in terms of qualitative or quantitative properties. To
obtain quantitative information, exact descriptors for the
image information are required. In order to receive qualitative
data, generalization of the image information is
possible. Akey property of a bulk particulate material is
a typical pattern of the image field-of-view called “texture”
(Figure 1.). Texture is related to distribution of the
spatial variation in grey scale levels (or color levels in
color images) and can be connected to general bulk-particle
characteristics. Global measurements of the texture
that are observed in an image can portray information
about the size of the particles. Smaller particles lead to
finer textures and larger particles to coarser textures.
Apparently, the presentation geometry, e.g., the magnification
and resolution used, will affect the outcome.
Standardized imaging conditions for these kind of textural
comparisons are therefore needed. An advantage of
textural methods is that particles do not have to be separated
from each other and identified individually.
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