Rapidly Distinguish Protein from Non-Protein Particles in Biologic Formulations

Importance of the Topic

Subvisible particles in biopharmaceutical formulations are a key quality attribute that influence product stability, safety, and efficacy. Protein aggregates can reduce shelf life and increase immunogenic risk. Differentiating proteinaceous particles from non-protein contaminants is essential for early development, regulatory compliance, and robust quality control.

Objectives and Study Overview

The application note introduces Fluorescence Membrane Microscopy (FMM) as an orthogonal, high-throughput method to rapidly distinguish protein from non-protein particles. The study evaluates FMM performance on monoclonal antibody aggregates, standardized plastic particles (ETFE), and common formulation contaminants, demonstrating its throughput, specificity, and quantitative capability.

Methodology and Instrumentation

Fluorescence Membrane Microscopy builds on Backgrounded Membrane Imaging (BMI) by adding a fluorescence detection step to identify chemical composition. Key steps include:

• Membrane Phase Staining: particles are trapped on a specialized 96-well filter plate, then stained on-membrane with Thioflavin T (ThT) for protein aggregate detection.
• BMI Detection: brightfield imaging detects and sizes particles from 1 µm to 5 mm, generating a particle mask for each well.
• FMM Analysis: fluorescence imaging is performed only at particle mask locations to confirm ThT binding.

Used Instrumentation

• Aura System with integrated BMI and FMM
• Horizon® instrument for BMI
• 96-well fluorescence membrane plates
• Particle Vue Software with Expression Engine for data analysis

Main Results and Discussion

FMM using ThT selectively labels protein aggregates, producing strong fluorescence signals within 1 minute of on-membrane incubation. In case studies:

• hIgG aggregates versus ETFE reference particles were morphologically indistinguishable by brightfield, but separated clearly by ThT fluorescence and side-illumination scattering.
• Serial mixtures of hIgG and ETFE showed accurate quantification of protein and non-protein fractions, with <1% false positives on ETFE and >90% correct protein identification for hIgG aggregates.
• Additional controls (palmitic acid, cryovial plastic delaminants, stainless steel) exhibited negligible ThT staining, confirming assay specificity.

Scatter plots and software Expression Engine thresholds enabled single-particle classification and whole-well statistical reporting, with complete 96-well analysis in under two hours.

Benefits and Practical Applications

FMM offers:

• High throughput analysis of millions of particles with low sample volumes
• Rapid, specific identification of proteinaceous particles within standard QC workflows
• Compatibility with regulatory guidelines requiring orthogonal subvisible particle characterization
• Integration into existing membrane microscopy protocols (USP 788 Method 2)

Future Trends and Opportunities

Emerging directions include:

• Multiplexed fluorescence assays to identify diverse particle chemistries simultaneously
• Automation and AI-driven image analysis for real-time process monitoring
• Expansion of dye chemistries targeting other aggregate types or excipient residues
• Integration into continuous manufacturing lines for in-line particle characterization

Conclusion

Fluorescence Membrane Microscopy with Thioflavin T on the Aura System provides a rapid, sensitive, and specific method to distinguish protein from non-protein particles in biologic formulations. Its high throughput, low false positive rate, and compatibility with established membrane microscopy deliver a practical solution for comprehensive subvisible particle analysis.

Reference

1. Guidance for Industry Immunogenicity Assessment for Therapeutic Protein Products, US FDA, 2014.
2. Industry Perspective on the Medical Risk of Visible Particles in Injectable Drug Products, Parenteral Drug Association, 2014.
3. Naiki H et al., Fluorometric determination of amyloid fibrils using Thioflavine T, Anal. Biochem., 1989;177:244–249.
4. Levine III H., Thioflavin T interaction with Alzheimer’s β-amyloid peptides, Protein Sci., 1993;2:404–410.
5. Groenning M et al., Study of ThT binding to β-sheet cavities, J. Struct. Biol., 2007;158:358–369.
6. Kiyoshi M et al., Analysis of subvisible particles using flow imaging and light obscuration, J. Pharm Sci., 2019;108(2):832–841.