Microflow Imaging Analyses Reflect Mechanisms of Aggregate Formation: Comparing Protein Particle Data Sets Using the Kullback-Leibler Divergence.

Subvisible particles in therapeutic protein formulations are an increasing manufacturing and regulatory concern because of their potential to cause adverse immune responses. Flow imaging microscopy is used extensively to detect subvisible particles and investigate product deviations, typically by comparing imaging data using histograms of particle descriptors. Such an approach discards much information and requires effort to interpret differences, which is problematic when comparing many data sets.

High throughput prediction of the long-term stability of pharmaceutical macromolecules from short-term multi-instrument spectroscopic data.

Changes in the measurements of a macromolecular biopharmaceutical's physical form are often used to predict changes in the drug's long-term stability. These can in turn be used as important markers of changes to a drug's efficacy and safety. Such stability estimates traditionally require human judgment and are frequently tentative.

Studies of the aggregation of RNase Sa.

Thirty-eight mutants of RNase Sa (ribonuclease from Streptomyces aureofaciens) were examined for their structure, thermal sensitivity, and tendency to aggregate. Although a biphasic correlation was seen between the effect of temperature on structure and the free energy of transfer changes in many of the mutants, little correlation was seen between the time at which aggregation is initiated or the rate of aggregation and the thermal sensitivity of the mutants. It is hypothesized that the nature of contacts between protein molecules in the associated (aggregated) phase rather than structural changes dominates the aggregation process for these series of mutants.

Comparative signature diagrams to evaluate biophysical data for differences in protein structure across various formulations.

A solution to the problem of being able to show statistically significant differences in the measurements of various levels of higher-order protein structure has been an elusive one. We propose the use of comparative signature diagrams (CSDs) to this end. CSDs compare datasets from different biophysical techniques that fingerprint the secondary, tertiary, and quaternary structures of a protein molecule and display statistically significant differences in these datasets.