Micro-flow imaging multi-instrument evaluation for sub-visible particle detection.

Sub-visible particles (SVPs) in pharmaceutical products are a critical quality attribute, and therefore should be monitored during development. Although light obscuration (LO) and microscopic particle count tests are the primary pharmacopeial methods used to quantify SVPs, flow imaging methods like Micro-Flow Imaging (MFI™) appear to overcome shortcomings of LO such as limited sensitivity concerning smaller translucent SVPs in the size range < 10 µm. Nowadays, MFI™ is routinely utilized during development of biologicals. Oftentimes multiple devices are distributed across several laboratories and departments. This poses challenges in data interpretation and consistency as well as in the use of multiple devices for one purpose. In this study, we systematically evaluated seven MFI™ instruments concerning their counting and size precision and accuracy, using an inter-comparable approach to mimic daily working routine. Therefore, we investigated three different types of particles (i) NIST certified counting standards, (ii) protein-coated particles, and (iii) stress-induced particles from a monoclonal antibody. We compared the results to alternative particle detection methods: LO and Backgrounded Membrane Imaging (BMI). Our results showed that the precision and accuracy of particle count and size, as well as the comparability of instruments, depended on the particle source and its material properties. The various MFI™ instruments investigated showed high precision (<15 %) and data generated on different instruments were of the same order of magnitude within pharmacopeial relevant size ranges for NIST certified counting standards. However, we found limitations in the upper and lower detection limits, contrary to the limits claimed by the manufacturer. In addition, proteinaceous and protein-containing particles showed statistically significant differences in particle counts, while the measured particle diameters of all sizes were quite consistent.