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.
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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.
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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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