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Flow Microscopy: Dynamic Image Analysis for Particle Counting

Flow Microscopy: Dynamic Image Analysis for Particle Counting

PETER OMA,1 DEEPAK K. SHARMA,1 DAVID KING1

1ProteinSimple Technologies Inc., Ottawa, Ontario CANADA, K2M2B2

PUBLICATION: USP Pharmacopeial Forum. 36(1): 311-320. (2010)

ABSTRACT: USP General Chapter Particulate Matter in Injections <788> sets limits and cites two enumeration procedures for subvisible particulate matter in parenteral products. Although <788> does not specifically target intrinsic sources of particulate matter such as protein aggregates, micelles, or precipitates, the <788> procedures can detect and enumerate these types of particles. The <788> procedure’s performance (efficiency, reliability, and repeatability) for these particle types is unknown. Artifacts such as immiscible liquids, primarily silicone oil droplets, and air bubbles are counted by light obscuration but do not contribute to membrane microscopic counts. Protein-based pharmaceuticals may contain sizeable populations of aggregated or precipitated active ingredient in the size range of concern. The physical and optical properties of these particles can present challenges to light-obscuration procedures in achieving reliable detection and sizing. Because the light-obscuration <788> test procedures do not easily differentiate particle types, an alternative test procedure may be useful in differentiating foreign from intrinsic particulate matter to facilitate product improvement efforts and compliance with the limits specified by <788>. Flow microscopy is an imaging-based technology that uses automated classification algorithms to characterize suspended particle populations. The technology is currently used in an increasing number of applications in the formulation development phase of parenteral and biopharmaceutical development. The system operates by capturing an image of each particle in a flowing sample. Automated image analysis can differentiate subpopulations of foreign particles (e.g., metal, glass, rubber, and fibers) and intrinsic particles. This allows protein aggregates or other intrinsic particles to be considered separately from the total particle count to provide a more accurate representation of the foreign particle load. In addition, the particle images gathered by the system provide morphology information that can be used to determine the origin of contaminants and to monitor intrinsic particle populations.

LINK TO ARTICLE: http://www.usp.org/pdf/EN/USP