@article{01J9XJKK29JPE4QYGMZXVM0DKY,
  abstract     = {{The pharmaceutical industry is progressing towards more continuous manufacturing techniques. To dry biopharmaceuticals, continuous freeze drying has several advantages on manufacturing and process analytical control compared to batch freeze-drying, including better visual inspection potential. Visual inspection of every freeze-dried product is a key quality assessment after the lyophilization process to ensure that freeze-dried products are free from foreign particles and defects. This quality assessment is labor-intensive for operators who need to assess thousands of samples for an extensive amount of time leading to certain drawbacks. Applying Artificial Intelligence, specifically computer vision, on high-resolution images from every freeze-dried product can quantitatively and qualitatively outperform human visual inspection. For this study, continuously freeze-dried samples were prepared based on a real-world pharmaceutical product using manually induced particles of different sizes and subsequently imaged using a tailor-made setup to develop an image dataset (with particle sizes from 50µm to 1 mm) used to train multiple object detection models. You Only Look Once version 7 (YOLOv7) outperforms human inspection by a large margin, obtaining particle detection precision of up to 88.9% while controlling the recall at 81.2%, thus detecting most of the object present in the images, with an inference time of less than 1 s per vial.}},
  articleno    = {{124629}},
  author       = {{Hervé, Quentin and Ipek, Nusret and Verwaeren, Jan and De Beer, Thomas}},
  issn         = {{0378-5173}},
  journal      = {{INTERNATIONAL JOURNAL OF PHARMACEUTICS}},
  keywords     = {{Freeze-drying,Continuous manufacturing,Quality analysis,Visual inspection,Deep learning,Computer vision}},
  language     = {{eng}},
  pages        = {{12}},
  title        = {{Automated particle inspection of continuously freeze-dried products using computer vision}},
  url          = {{http://doi.org/10.1016/j.ijpharm.2024.124629}},
  volume       = {{664}},
  year         = {{2024}},
}

Altmetric

View in Altmetric

Web of Science

Times cited: