Pharmaceutical Particle Characterization

 

Detecting and Counting Silicone Oil Droplets Using MFI

Silicone is used as a lubricant on plungers and vial stoppers. It can slough off, or shed, and appear as micro-droplets in a drug formulation. These droplets can also serve as denaturing agents and nucleation centers in bio-pharmaceuticals. Detection of silicone oil droplets in a parenteral particle population is a challenge for obscuration and other traditional particle counting methods since they are unable to differentiate the droplet from other contaminants.

Micro-Flow Imaging (MFI) uses morphology-based software filters to identify and quantify silicone oil droplets. To illustrate, a parenteral sample contaminated with silicone oil droplets and high particle counts in the ≥10μm size range was analyzed using MFI. Using the MFI software, silicone droplets were visually identified and an appropriate software filter, based on intensity and aspect ratio, was created. This filter was then applied to the complete parenteral sample database to isolate the silicone droplet sub-population from the total particle population.

Using this morphology-based software filter, 61% of the 676 particles greater than 10µm detected in the contaminated parenteral sample were identified as silicone oil droplets.

How Does MFI Work? MFI captures images of suspended particles in a fluid sample. Images are displayed on the system monitor in real-time and are analyzed to produce a particle database including count, size, transparency and shape parameters. Morphology-based software filters can be created and applied to this database to produce particle size distributions and isolate sub-populations. Native images are also stored for further investigation and analy.

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