Microwell Plate-Based Dynamic Light Scattering as a High-Throughput Characterization Tool in Biopharmaceutical...

Area of Science:

• Biopharmaceutical formulation development
• Analytical chemistry
• Protein aggregation analysis

Background:

• High-throughput light scattering instruments in multi-well plate formats are crucial for screening biopharmaceutical formulations.
• Plate readers assess aggregation tendency and colloidal stability using the diffusion self-interaction parameter (k).
• Concerns exist regarding the precision and variability of data obtained from plate readers.

Purpose of the Study:

• To statistically evaluate intra- and inter-plate variability for k analysis of protein and peptide solutions using 384-well plates.
• To identify factors influencing the reliability and precision of k measurements.
• To propose optimized plate designs for early-stage formulation development.

Main Methods:

• Statistical analysis, including ANOVA, was performed on k values from protein and peptide solutions in 384-well plates.
• Intra- and inter-plate variability were assessed based on sample replicate positions (center vs. edge wells).
• The effect of data point number on k variability was investigated.

Main Results:

• ANOVA indicated no significant differences between experimental runs.
• The reliability and precision of k values were significantly influenced by sample plate position and the sign of the k value.
• Positive k values exhibited lower variability (CV 8.9%) than negative k values (CV 13.4%).
• Using more data points (120 vs. 30) did not reduce k variability.
• k analysis using only center wells showed significantly lower CV (<2%) compared to edge wells (5-12%) or combined wells (2-5%).

Conclusions:

• The precision of k analysis in high-throughput plate formats is dependent on sample placement within the plate.
• Utilizing center wells exclusively for k analysis enhances data reliability and reduces variability.
• Optimized plate designs can facilitate efficient early formulation development, screening numerous formulations with minimal active pharmaceutical ingredient (API).