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Optimization of Flow Imaging Microscopy Setting Using Spherical Beads with Optical Properties Similar to Those of Biopharmaceuticals.
- Source :
-
Journal of Pharmaceutical Sciences . Dec2023, Vol. 112 Issue 12, p3248-3255. 8p. - Publication Year :
- 2023
-
Abstract
- Flow imaging microscopy (FIM) is widely used to characterize biopharmaceutical subvisible particles (SVPs). The segmentation threshold, which defines the boundary between the particle and the background based on pixel intensity, should be properly set for accurate SVP quantification. However, segmentation thresholds are often subjectively and empirically set, potentially leading to variations in measurements across instruments and operators. In the present study, we developed an objective method to optimize the FIM segmentation threshold using poly(methyl methacrylate) (PMMA) beads with a refractive index similar to that of biomolecules. Among several candidate particles that were evaluated, 2.5-µm PMMA beads were the most reliable in size and number, suggesting that the PMMA bead size analyzed by FIM could objectively be used to determine the segmentation threshold for SVP measurements. The PMMA bead concentrations measured by FIM were highly consistent with the indicative concentrations, whereas the PMMA bead size analyzed by FIM decreased with increasing segmentation threshold. The optimal segmentation threshold where the analyzed size was closest to the indicative size differed between an instrument with a black-and-white camera and that with a color camera. Inter-instrument differences in SVP concentrations in acid-stressed recombinant adeno-associated virus (AAV) and protein aggregates were successfully minimized by setting an optimized segmentation threshold specific to the instrument. These results reveal that PMMA beads can aid in determining a more appropriate segmentation threshold to evaluate biopharmaceutical SVPs using FIM. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00223549
- Volume :
- 112
- Issue :
- 12
- Database :
- Academic Search Index
- Journal :
- Journal of Pharmaceutical Sciences
- Publication Type :
- Academic Journal
- Accession number :
- 173607103
- Full Text :
- https://doi.org/10.1016/j.xphs.2023.10.007