Best Practices to Quantify and Identify Particulate Matter on the Interior Surfaces of Single-Use Systems

Abstract

The manufacturing of a wide range of biopharmaceuticals, from antibodies and vaccines to cell-based therapies, increasingly takes place in single-use processing equipment. Manufactured in clean rooms and sealed and sterilized, single-use systems (SUS) are ready-to-use and easily scalable. Controls in the ″clean-build″ manufacturing of SUS reduce the probability of occurrence of particulate matter in SUS. However, the size, complexity, and limited transparency of SUS clearly limit the detectability of particulate matter on the interior (fluid-contacting) surfaces of a SUS during a visual inspection, as demonstrated in a recent study. In applications downstream of final filters or in aseptic processing, particulate matter on the surfaces of a SUS could detach and contaminate the final drug product. A realistic assessment of this risk requires reliable test methods that quantify and identify particulate matter present on the interior surfaces of SUS. Clearly problematic is the common certification of the cleanliness of a SUS via a force-fit adaptation of the pharmacopoeial standard USP <788> entitled ″Particulate Matter in Injections″ USP <788> does not describe a procedure for extraction of particulate matter from the interior surfaces of SUS. In addition, application of Method 1 Light Obscuration significantly limits the probability of detection for particles in the visible size range (≥ 100 µm). In this paper we describe best practices for extracting, counting, sizing and chemically identifying particulate matter on the interior surfaces of SUS. Highly effective procedures for the extraction of particulate matter result from application of the qualification methodology described in a recently published ASTM standard. Filtration of the liquid extract concentrates particulate matter onto the surface of a membrane filter, allowing rapid particle counting and sizing using automated membrane microscopy, along with detailed chemical identification using infrared microscopy and/or automated confocal Raman microscopy.