Biophysical Characterization for Product Comparability - Spectroscopic methods such as circular dichroism can detect subtle differences in higher order structure before and after changes in process


Biophysical Characterization for Product Comparability
Spectroscopic methods such as circular dichroism can detect subtle differences in higher order structure before and after changes in process and formulation.

BioPharm International Supplements

Case Study 1

Analysis of Higher Order Structure Following Process and Formulation Changes

Figure 1. The far (A) and near (B) UV CD spectra for IgG2 drug substance lots. Lot 1 was made using the early process, and Lots 2 and 3 were made using the new process and with the new formulation matrix. Lot 2* was a significant dilution of Lot 2 material with the early formulation matrix used for Lot 1. All spectra represent the average of three replicates.
The far and near UV CD spectroscopy techniques were applied to probe the secondary and tertiary structures of an IgG2 antibody after changes were made in both the downstream processes and the formulation matrix. As shown in Figure 1, the far (panel A) and near (panel B) UV CD spectra of the drug substance lot before the changes (Lot 1) are visually different from the spectra of the two lots after the changes (Lot 2 and Lot 3). This indicates that some degree of change in the IgG2 higher order structure might have occurred in response to process or formulation changes. However, the potential structural changes appeared to be reversible because diluting Lot 2 material with the early formulation matrix (referred to as Lot 2*) resulted in far and near UV CD spectra very comparable to those of Lot 1. No difference was found when the drug substance batches from the early and modified processes were tested for function using an ELISA binding assay, which required substantial dilution in the assay buffer.

The comparison of CD spectra often is made by visual inspection. It is to some degree subjective, and therefore, may not always be conclusive or straightforward to describe. Here, we demonstrate the use of root mean square deviation (RMSD) to evaluate the similarity of CD spectra. RMSD is widely used in biostatistics and bioinfomatics. It is used to assess the similarity of three-dimensional structures of homologous proteins. The differences in all coordinates of all atoms from the structures in comparison are accounted for with a single RMSD value. The same idea can be applied to spectral comparisons, i.e., the differences in optical signals at all wavelengths can be calculated using the same RMSD formula:

in which NRMSD is the RMSD normalized against the total scale of the reference spectrum, X and X ref are the CD signals for the test and the reference spectrum, respectively, and n is the number of data points. When using the far UV CD spectrum of Lot 2 as the reference, Lot 1 exhibited a higher NRMSD value (6.2%) than Lot 3 (2.3%), suggesting a more significant difference from Lot 2. The buffer change for Lot 2, giving rise to Lot 2*, caused a significant increase in the NRMSD value to 6.6%. A similar trend was observed for the NRMSD analysis on near UV CD spectra (5.1%, 0.9%, and 4.7% for Lot 1, Lot 3, and Lot 2*, respectively). In this case of evaluating the similarity of CD spectra, the result of RMSD analysis is consistent with the visual inspection.

Because a far UV CD spectrum of a protein reflects combined contributions of all secondary structure elements, estimating the structural components by deconvoluting a spectrum potentially can provide another means for semi-quantitative comparison of the far UV CD spectra. There are many algorithms available for the deconvolution based on empirical analysis of model structures.5 It is still debatable how accurate these calculations are.6,7 Several algorithms in the CDPRO package were evaluated to differentiate the far UV CD spectra shown in Figure 1A, and none were found to be sufficiently sensitive to distinguish the differences in the spectra.5 The average calculated fraction of β-sheet is around 45.6%, with a relative standard deviation of 0.3%. We therefore conclude that, even though spectral deconvolution may provide valuable structural information at low resolution, it is not suitable for comparability analyses.

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