Artificial intelligence-aided endoscopic in-line particle size analysis during the pellet layering process.

ABSTRACT: In this study, an artificial intelligence-based machine vision system was developed for in-line particle size analysis during the pellet layering process. Drug-layered pellets were produced by coating microcrystalline cellulose cores with an ibuprofen-containing layering liquid until the target drug content was achieved. Drug content increases with pellet size; therefore, particle size monitoring can ensure product safety and quality. The direct imaging system, consisting of a rigid endoscope, a light source, and a high-speed camera, provides real-time information about pellet size and layer uniformity, enabling timely intervention in the case of out-of-spec products. A convolutional neural network-based instance segmentation algorithm was employed to detect particles in focus, ensuring th

SUBMITTER: Peterfi O 

PROVIDER: S-EPMC12491717 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature