Precision and robustness of 2D-NMR for structure assessment of filgrastim biosimilars

To the Editor:

With the advent of biosimilar versions of brand biologics, regulatory authorities in all major jurisdictions throughout the world have developed guidance documents to facilitate their approval1,2,3,4. The common theme in the new documents is the stipulation that sponsors must demonstrate biosimilarity between their proposed product and an approved reference product using state-of-the-art analytical technologies. In the US guidance documents, a “totality of evidence” approach is described that can be used to establish the degree of similarity and guide regulatory decision-making3,4.

Higher-order structure is an important quality attribute of biosimilars that must be assessed by comparison to the reference licensed drug. To date, higher-order structure has been evaluated with low-resolution techniques, such as circular dichroism, Fourier transform infrared and Raman spectroscopies, and indirectly with several biological and stability assays5. In 2008, a two-dimensional nuclear magnetic resonance (2D-NMR) spectroscopy approach was first applied to the high-resolution assessment of the higher-order structure of a native recombinant protein therapeutic6. The technique resolves, in a 2D frequency map, the positions of proton–nitrogen atom pairs from each amide and amino group in a biologic molecule. Each signal correlates to the specific local chemical and structural environment of the atom pair; thus, the entire spectrum provides a comprehensive readout of the drug substance conformation along the polypeptide chain at atomic resolution, providing a potentially useful tool to establish drug substance consistency across manufacturing changes or comparability of the higher-order structure of biosimilars.

In this work, an interlaboratory comparative study was performed on filgrastim (methionyl granulocyte colony-stimulating factor; Met-G-CSF) to demonstrate the precision and robustness of the 2D-NMR approach. Filgrastim was selected because of its therapeutic importance, because the drug had been characterized by NMR7 and because a number of filgrastim biosimilars have already been approved in Europe, the United States and other jurisdictions. Here, a US-approved originator product (Neupogen) and three unapproved, non-US-sourced filgrastim products were used in their fully formulated states (Supplementary Table 1) to prepare a set of four samples for analysis using heteronuclear 2D-NMR correlation at 15N natural isotopic abundance. Spectra were acquired on the same samples on six different spectrometers, at four different field strengths ranging from 500 MHz to 900 MHz, in four different laboratories (for instrument specifications and experimental parameters, see Supplementary Tables 2–9). All the NMR data were analyzed and evaluated using the same software packages for visual evaluation, chemical shift analysis and principal-component analysis (PCA) to assess spectral similarity through multiple approaches.

The interlaboratory study data show that the resolution of the NMR method allows one to quickly visualize the high degree of similarity of the spectral patterns obtained from the 2D-NMR experiments run on different spectrometers. In this respect, visual comparison of spectral overlays allows an operator to directly assess sample similarity (Fig. 1a, Supplementary Table 10 and Supplementary Figs. 1–4).

Figure 1: Spectral and statistical comparisons of NMR data.
figure1

(a) Overlay plot of the same region on the same sample from Amgen at four fields and six instruments: NIST 900 (purple), NIST 600 (cyan), HC 700 (black), HC 600 (red), FDA 500 (green) and MPA 600 MHz (blue). Note that all resonances except data from HC 700 and HC 600 are perfectly overlaid under the blue peaks. This is highlighted in the upper left side inset showing an expansion of the regions containing signals from the amides of Gln134, Gln70, Leu71 and Ala6. In the lower right inset, a weaker peak is plotted using different contours to show that it is observed in all spectra. Additional peaks in the lower right corner of the spectra arise from unsuppressed residual signal from water in some spectra. (b) An example of the combined chemical shift difference (CCSD) plots for the system suitability sample, 15N-met-G-CSF, as a function of sequence (NIST 900 (plus), NIST 600 (star), HC 700 (circle), HC 600 (square), FDA 500 (diamond) and MPA 600 (triangle)) with the sample temperature difference on the HC instruments. (c) Same as b after temperature calibration. The reference chemical shift was based on average shift from NIST, FDA and MPA. The horizontal bar indicates the measured experimental precision limit of 8 p.p.b. (d) A plot of the result of the principal-component analysis performed on data of the four drug products recorded at the four laboratories on six instruments, FDA 500 (dark blue); NIST 900 (blue, the cluster at ORIGIN); NIST 600 (turquoise); HC 700 (green); HC 600 (yellow); and MPA 600 (orange). Dashed ellipses show the relative clustering of data from each laboratory. For this panel, the temperatures during collection of HC 600 and HC 700 data were not calibrated.

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Differences between two spectral patterns can result from variation in solution conditions (such as pH or ionic strength), variation in the temperature of the sample, and/or differences in the higher-order structure of the protein. As an example, in our study, the overlay of spectra acquired for the same filgrastim sample on two spectrometers revealed a number of peak signal deviations that could be mapped to solvent-exposed residues (Fig. 1a, inset). Four representative residues in loop regions that exhibited these deviations are shown in Supplementary Figure 2b. We found that these differences could be explained by differences in temperature of 2 °C and 4 °C for the HC 700 and HC 600 spectrometers, respectively. The change of temperature does not affect all amide resonances equally7 and has been described by Baxter and Williamson8. Proper instrument calibration removed these discrepancies (Supplementary Fig. 2c).

For a more quantitative analysis, chemical shifts of each individual signal in the 2D map were compared using a root mean square deviation (RMSD) analysis or combined chemical shift difference (CCSD) methods (Fig. 1b,c, Supplementary Figs. 5 and 6, and Supplementary Tables 11 and 12; refs. 9,10). The chemical shift of each nucleus is an absolute frequency position, and perturbations in the higher-order structure, such as altered hydrogen bonding, can influence the local electronic environments of nuclei, leading to changes in chemical shifts. Thus, amide 1HN and 15N chemical shift changes can be assessed individually using RMSD from the average values or in aggregate by CCSD (which involves taking a weighted average of the observed changes in 1HN and 15N shift values9). With either of these methods, the chemical shift assignment of the primary sequence allows atomic-level mapping of spectral signals to a known protein structure, but this is not required for the method to be useful. From RMSD and CCSD analyses, an experimental precision of 8 p.p.b. was determined across the six spectrometers in the four laboratories. Notably, 8 p.p.b. is close to the digital resolution of approximately 5 p.p.b. of an individual spectrum (see Supplementary Methods), which establishes a threshold for the precision of the measurement. Similarly, an intralaboratory precision of approximately 4 p.p.b. was found that falls well within the digital resolution of a spectrum (Supplementary Table 12), and a related study found an experimental precision for the same sample of 2.4 p.p.b.10. These precision limits are well below any chemical shift changes that could be induced by a significant structural change (such as a point mutation or a modification of a residue by oxidation or local conformational change). These approaches also readily identify the temperature deviation of the non-calibrated spectrometers (Fig. 1b), further demonstrating the need for matched experimental conditions if the method is to be used as a structure comparability tool. As expected, the recalibrated spectra were well within the determined experimental precision (Fig. 1c).

Although comparison of spectral overlays and chemical shifts provides the most straightforward method for the analysis of two or three samples, it can be cumbersome when large numbers of datasets need to be compared, as in the monitoring of lot-to-lot consistency; in such instances a multivariate statistical analysis approach may be more appropriate. Here, we used PCA because it provides a single readout of variance in all 2D-NMR spectra collected for filgrastim. The PCA plot shown in Figure 1d was calculated with all peaks in the 2D-NMR spectrum with a defined intensity threshold (see Supplementary Methods). This analysis included peak shifts due to sample temperature differences, the presence of impurities (for example, oxidized species in the system suitability sample) and variation in signal intensities resulting from spectrometer-dependent line widths. For each spectrometer except the MPA 600, all drug products are tightly clustered because of the high similarity of the higher-order structure. The slightly wider spread of the MPA 600 data is attributed to a difference in the performance of the pulsed NMR method chosen to obtain the 2D map on this spectrometer as well as to aging of the samples over time (Supplementary Table 8). NIST 900 data re-collected after one year on the same samples confirmed this interpretation (Supplementary Fig. 7). Similar to the chemical shift–based analysis, the PCA test clearly distinguishes the two samples with temperature deviation, whereas the 15N-GCSF system suitability sample is found to cluster in its own region mainly because of the differences in protein impurities.

To our knowledge, this is the first reported interlaboratory study of a high-resolution 2D-NMR method to assess biotherapeutic higher-order structure. The results clearly demonstrate both the precision and the robustness of 2D-NMR as a multifrequency-based higher-order structure assessment tool. The data acquired during this study show minimal measurement drift attributable to the nine-month period of the study and across the various instruments and laboratories. As traceable reference values are established using this technique, a comparability exercise on the higher-order structure of a recombinant protein therapeutic could be performed using the NMR signature of a comparator from a validated database without the need to record its spectra again. Utilization of NMR spectral analyses by both sponsors of biosimilars and originators will provide greater assurance of drug product quality to the regulatory agencies.

Disclaimers

The findings and conclusions in this article have not been formally disseminated by the Food and Drug Administration and should not be construed to represent any Agency determination or policy. Certain commercial equipment, instruments and materials are identified in this paper in order to specify the experimental procedure. Such identification does not imply recommendation or endorsement by the National Institute of Standards and Technology, nor does it imply that the material or equipment identified is necessarily the best available for the purpose.

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Correspondence to John P Marino or Yves Aubin or David A Keire.

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Ghasriani, H., Hodgson, D., Brinson, R. et al. Precision and robustness of 2D-NMR for structure assessment of filgrastim biosimilars. Nat Biotechnol 34, 139–141 (2016). https://doi.org/10.1038/nbt.3474

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