期刊
EUROPEAN JOURNAL OF PHARMACEUTICAL SCIENCES
卷 165, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.ejps.2021.105921
关键词
X-ray microscopy; 3d non-invasive imaging; Spray dried particle characterization; Tablet characterization; Image-based Microporosity Quantification; Artificial Intelligence Image Processing
For oral solid dosage forms, the properties of disintegration and dissolution closely relate to the powders and particles used in their formulation. Three-dimensional non-invasive tomographic imaging plays an increasingly essential role in characterizing drug substances. The study used AI-based image analytics to quantify physical properties, revealing the root causes of differences in dissolution behavior between two tablets.
For oral solid dosage forms, disintegration and dissolution properties are closely related to the powders and particles used in their formulation. However, there remains a strong need to characterize the impact of particle structures on tablet compaction and performance. Three-dimensional non-invasive tomographic imaging plays an increasingly essential role in the characterization of drug substances, drug product intermediates, and drug products. It can reveal information hidden at the micro-scale which traditional characterization approaches fail to divulge due to a lack of resolution. In this study, two batches of spray-dried particles (SDP) and two corresponding tablets of an amorphous product, merestinib (LY2801653), were analyzed with 3D X-Ray Microscopy. Artificial intelligence-based image analytics were used to quantify physical properties, which were then correlated with dissolution behavior. The correlation derived from the image-based characterization was validated with conventional laboratory physical property measurements. Quantitative insights obtained from imageanalysis including porosity, pore size distribution, surface area and pore connectivity helped to explain the differences in dissolution behavior between the two tablets, with root causes traceable to the microstructure differences in their corresponding SDPs.
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