Applying Machine Learning to the Visual Inspection of Filled Injectable Drug Products.

With machine learning (ML), we see the potential to better harness the intelligence and decision-making abilities of human inspectors performing manual visual inspection (MVI) and apply this to automated visual inspection (AVI) with the inherent improvements in throughput and consistency. This article is intended to capture current experience with this new technology and provides points to consider for successful application to AVI of injectable drug products. The technology is available today for such AVI applications.

Achieving "Zero" Defects for Visible Particles in Injectables.

The reduction of visible particles in injectable products is an important element in the consistent delivery of high-quality parenteral products. An important part of this effort is the control of particles that may emanate from the primary packaging materials. The (), with the support of the Pharmaceutical Manufacturers Forum (PMF), has undertaken the task of developing test methods to assess the cleanliness of primary packaging components used in the manufacturing of sterile injectable products.