Image analysis and crystallisation
Admin / November 4, 2022
Image analysis can be used for various scientific researches and methodologies. One of the newest is its application and usage for monitoring and controlling of the crystallization process. Recent studies have shown that image analysis can play an integral part through image analysis algorithms.
Particle characterization is critical for pharmaceutical crystallisation because properties such as particle size distribution (PSD), particle shape, and polymorphic form all have a significant impact on downstream processes and bioavailability. These critical process parameters can be continuously monitored with image analysis, which aids in the understanding, design, and control of crystallisation processes. As a result, it has become a hot topic in academia and industry, particularly with the rise of continuous processing, where product quality must be ensured through real-time monitoring and feedback control.
Furthermore, offline sampling requires time, and particle attributes can change during sampling due to growth, agglomeration, and polymorphic transformation. Inline microscopy is an effective tool because images contain a wealth of information that is easy to read and accessible at a glance. As a result, inline microscopy is a well-established technique for obtaining qualitative data such as the onset of nucleation, growth, dissolution, shape and aggregation. This information, when combined with image analysis, can be quantified to directly measure particle size distribution, particle counts, and various shape parameters.
Other important parameters that can be calculated from these measurements include the agglomeration degree, number concentration, solid concentration, yield, nucleation rate and growth rate. Image analysis is useful for process control because it provides access to a large number of key parameters. Moreover, the outcome of image analysis can vary depending on the algorithm and sampling method used. Microscopy is used in some way or another in almost every crystallisation process. Image analysis combined with inline microscopy has a significant advantage over other methods because it reveals the individual particles, aggregates, needles, air bubbles that are measured.
Another critical point is the image acquisition system, which determines the image quality. Analysing an image is influenced by a variety of factors: such as lighting conditions, solid concentration, depth of field, background and resolution. Flow-through systems produce high-quality images and, as demonstrated by multiple authors, can work around the particle concentration limitation by continuously dilution of the suspension with filtered mother liquor. Some even suggested that crystallisation be monitored through the transparent tubing of a tubular crystallizer. There are also systems that image the particles from various angles with multiple cameras, effectively gaining 3D information on the particles.
Particle characterization is critical for pharmaceutical crystallisation because properties such as particle size distribution (PSD), particle shape, and polymorphic form all have a significant impact on downstream processes and bioavailability. These critical process parameters can be continuously monitored with image analysis, which aids in the understanding, design, and control of crystallisation processes. As a result, it has become a hot topic in academia and industry, particularly with the rise of continuous processing, where product quality must be ensured through real-time monitoring and feedback control.
Furthermore, offline sampling requires time, and particle attributes can change during sampling due to growth, agglomeration, and polymorphic transformation. Inline microscopy is an effective tool because images contain a wealth of information that is easy to read and accessible at a glance. As a result, inline microscopy is a well-established technique for obtaining qualitative data such as the onset of nucleation, growth, dissolution, shape and aggregation. This information, when combined with image analysis, can be quantified to directly measure particle size distribution, particle counts, and various shape parameters.
Other important parameters that can be calculated from these measurements include the agglomeration degree, number concentration, solid concentration, yield, nucleation rate and growth rate. Image analysis is useful for process control because it provides access to a large number of key parameters. Moreover, the outcome of image analysis can vary depending on the algorithm and sampling method used. Microscopy is used in some way or another in almost every crystallisation process. Image analysis combined with inline microscopy has a significant advantage over other methods because it reveals the individual particles, aggregates, needles, air bubbles that are measured.
Another critical point is the image acquisition system, which determines the image quality. Analysing an image is influenced by a variety of factors: such as lighting conditions, solid concentration, depth of field, background and resolution. Flow-through systems produce high-quality images and, as demonstrated by multiple authors, can work around the particle concentration limitation by continuously dilution of the suspension with filtered mother liquor. Some even suggested that crystallisation be monitored through the transparent tubing of a tubular crystallizer. There are also systems that image the particles from various angles with multiple cameras, effectively gaining 3D information on the particles.