Spray Drying Process Development
and Tableting Compaction
Spray drying is commonly used to produce amorphous solid dispersions (ASD) to improve the bioavailability of poorly water-soluble drugs. In this study, imaging techniques such as focused ion beam-scanning electron microscopy (FIB-SEM) and X-ray microcomputed tomography (XRCT) were used to study the microstructure of spray dried (SD) particles. Spray drying at higher outlet temperature (Tout) was found to produce more spherical hollow particles with smooth surface and thinner walls, while more raisin-like particles with thicker walls were generated at lower Tout. For the first time, a patent-pending artificial intelligence–facilitated XRCT image analysis tool was developed to make quantitative analysis of thousands of particles individually possible. The particle size distribution through XRCT image analysis, generally in line with what is measured by laser diffraction, has better consistency and reproducibility.
Machine learning segmented XRM images of spray dried particles allows quantification of internal void space, wall thickness, particle shape, and more. The morphological properties were compared across different outlet temperatures and process conditions.
XRM local tomography allows for non-destructive visualization of particle morphology, which can be tied to process parameters, dissolution performance, and tableting performance.
The image analysis reveals envelope density as a more sensitive physical attribute for process change than conventional bulk/tap density. Further, the tensile strength of SD particle compacts correlates with the particle wall thickness, and this is likely caused by the larger interparticle contact area generated by more deformation of particles with thinner walls. The knowledge gained here can help enable SD particle engineering and drug product with more robust process and optimized performance.
Amorphous solid dispersion characterization methods differ depending on the approach taken to analyze and the samples. Listed below are the most commonly used methodologies:
Modernize your ASD characterization program with artificial intelligence
XRM imaging technology and artificial intelligence assisted analysis provides simultaneous insight at each level accessible from a bulk sample.
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