Details

Autor(en) / Beteiligte

• Helbig, Constanze
• Ammann, Gregor
• Menzen, Tim
• Friess, Wolfgang
• Wuchner, Klaus
• Hawe, Andrea

Titel

Backgrounded Membrane Imaging (BMI) for High-Throughput Characterization of Subvisible Particles During Biopharmaceutical Drug Product Development

Ist Teil von

• Journal of pharmaceutical sciences, 2020-01, Vol.109 (1), p.264-276

Ort / Verlag

United States: Elsevier Inc

Erscheinungsjahr

2020

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• Backgrounded membrane imaging (BMI) is a novel automated, 96-well plate-based microscopic approach for subvisible particle analysis. We scientifically evaluated BMI with respect to sizing and counting accuracy, working range, impact of refractive index, and interferences by silicone oil droplets, and compared BMI to state-of-the-art dynamic image analysis (DIA). Image quality was found to be comparable to current DIA methodologies. However, with the first versions of BMI image analysis software, an undersizing of polystyrene beads was observed. BMI linear concentration range was found to reach an upper limit (7.1 × 105 particles/mL) similar to DIA. In the absence of silicone oil droplets, BMI and DIA showed good agreement in total particle concentrations (particle diameter ≥2 μm) but differences in size distributions for particle sizes ≥4 μm. Analyses of prefilled syringe products and silicone oil emulsions demonstrated the removal of silicone oil in BMI sample processing. In contrast to DIA, particle counting by BMI remained unaffected by changes in refractive index. Overall, we demonstrated BMI to be a promising orthogonal method for subvisible particle characterization. Aspects like low required sample volume, high throughput, and ease of handling can make BMI a valuable alternative or complement to DIA in particular for formulation screening.