The need for new control strategies for particulate matter in parenterals.

An undesirable characteristic in lyophilized parenteral products is the potential presence of particulate matter in the final product, which may affect patient safety. In this study, quality risk management tools described in the International Conference on Harmonization Guideline Q9 were used to estimate the risks for a pharmaceutical manufacturing line, based on three critical quality attributes: (1) visible particulate matter; (2) lyo-cake collapse traces; and (3) lyo-cake melt-back traces. Together with a Process Failure Mode Effect Analysis (PFMEA), an input-output analysis of the individual unit operations identified seven major material classes of extrinsic particulate matter. In addition to the process assessment, an experimental investigation of the location of impurities in lyophilized products was performed. To that end, intentionally contaminated vials were examined to locate the particulate matter and its possible migration. The results emphasize the importance of a full transmission mode release testing since the particles may enter the interior of the lyo-cake. A theoretical explanation of the observed impurity locations is provided.

X-ray imaging: A potential enabler of automated particulate detection and cake-structure analysis in lyophilized products?

The presence of particulate matter in parenteral products is a major concern since it affects the patients' safety and is one of the main reasons for product recalls. Conventional quality control is based on a visual inspection, which is a labour-intensive task. Limited to clear solutions and the surface of lyophilised products, it cannot be applied to opaque containers. This study assesses the application of X-ray imaging for detecting the particulate matter in a pharmaceutical lyophilized product. The most common types of particulates (i.e., steel, glass, lyo stopper, polymers and organics in different size classes) were intentionally spiked in vials. After optimizing all relevant parameters of the X-ray set-up, all classes of particulates were detected. At the same time, due to contrast enhancement, the inherent structures of lyophilized cake became obvious. This work addresses the potential and limits of X-ray technology in that regard, paving the way for automated image-based particulate matter detection. Moreover, this paper discusses using this approach to predict critical quality attributes (CQAs) of the drug product based on the cake structure attributes.