Abstract
Characterizing and quantifying subvisible particles in protein drug products is critical to ensuring product quality. A variety of analytical methods are used to detect and make meaningful measurements of subvisible particles. Resonant mass measurement (RMM) is a novel technology that characterizes the subvisible particle content of samples on a particle-by-particle basis. The technology presents great promise in the study of therapeutic protein products. As an emerging tool in the biopharmaceutical field, the best practices and limitations of RMM for protein products have not been well established. One key challenge of particle analysis is producing robust and reliable data, with high precision and accuracy, for particle characterization. In this study, we develop a set of possible best practices for RMM using a model protein system. We test the effects of these practices on the repeatability and reproducibility of particle measurements. Additionally, we present the data collected under a rigorously controlled set of operating conditions at 3 collaborating sites as well as a summary of the resulting optimal practices. In employing these practices, we successfully obtained improved relative standard deviation values and achieved high reproducibility and repeatability in both sizing and concentration measurement results over a broad range of sample volumes.
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