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Protein aggregation, which takes place both in vivo and in vitro, is an important degradative pathway for all proteins. Protein aggregates have distinct physicochemical and biological properties that are important to study and characterize from the perspective of both fundamental and applied sciences. The size of protein aggregates varies across a huge range, spanning several orders of magnitude. Currently, protein aggregates larger than hundreds of nanometers in diameter are impossible to physically fractionate. Here, we present a new method to fractionate microscopic proteinaceous particles using preparative fluorescence-activated cell sorting technology. © 2013 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 102:2128–2135, 2013

Accurate monitoring of the sub-visible particle load in protein biopharmaceuticals is increasingly important to drug development. Manufacturers are expected to characterize and control sub-visible protein particles in their products due to their potential immunogenicity. Light obscuration, the most commonly used analytical tool to count microscopic particles, does not allow discrimination between potentially harmful protein aggregates and harmless pharmaceutical components, e.g. silicone oil, commonly present in drug products. Microscopic image analysis in flow-microscopy techniques allows not only counting, but also classification of sub-visible particles based on morphology. We present a novel approach to define software filters for analysis of particle morphology in flow-microscopic images enhancing the capabilities of flow-microscopy. Image morphology analysis was applied to analyze flow-microscopy data from experimental test sets of protein aggregates and silicone oil suspensions. A combination of four image morphology parameters was found to provide a reliable basis for automatic distinction between silicone oil droplets and protein aggregates in protein biopharmaceuticals resulting in low misclassification errors. A novel, custom-made software filter for discrimination between proteinaceous particles and silicone oil droplets in flow-microscopy imaging analysis was successfully developed.