Tracking the physical stability of fluorescent-labeled mAbs under physiologic in vitro conditions in human serum and PBS.

In recent years, the stability of biotherapeutics in vivo has received increasing attention. Assessing the stability of biotherapeutics in serum may support the selection of adequate molecule candidates. In our study, we compared the physical stability of 8 different monoclonal antibodies (mAbs) in phosphate-buffered saline (PBS) and human serum. mAbs were Alexa Fluor 488-labeled and characterized with respect to fragmentation, aggregation, and proteinaceous particle formation. Samples were analyzed using size-exclusion chromatography, light obscuration, and flow imaging. In addition, novel methods such as flow cytometry and fluorescence microscopy were applied. mAbs were selected based on their hydrophobicity and isoelectric point. All mAbs studied were inherently less stable in human serum as compared to PBS. Particle size and particle counts increased in serum over time. Interestingly, certain mAbs showed significant levels of fragmentation in serum but not in PBS. We conclude that PBS cannot replicate the physical stability measured in serum. The stability of labeled mAbs in human serum did not correlate with their hydrophobicity and isoelectric point . Serum stability significantly differed amongst the tested mAbs.

Extraction of indirectly captured information for use in a comparison of offline pH measurement technologies.

Understanding the causes of discrepancies in pH readings of a sample can allow more robust pH control strategies to be implemented. It was found that 59.4% of differences between two offline pH measurement technologies for an historical dataset lay outside an expected instrument error range of ±0.02pH. A new variable, OsmoRes, was created using multiple linear regression (MLR) to extract information indirectly captured in the recorded measurements for osmolality. Principal component analysis and time series analysis were used to validate the expansion of the historical dataset with the new variable OsmoRes. MLR was used to identify variables strongly correlated (p<0.05) with differences in pH readings by the two offline pH measurement technologies. These included concentrations of specific chemicals (e.g. glucose) and OsmoRes, indicating culture medium and bolus feed additions as possible causes of discrepancies between the offline pH measurement technologies. Temperature was also identified as statistically significant. It is suggested that this was a result of differences in pH-temperature compensations employed by the pH measurement technologies. In summary, a method for extracting indirectly captured information has been demonstrated, and it has been shown that competing pH measurement technologies were not necessarily interchangeable at the desired level of control (±0.02pH).