An NMR-Based Similarity Metric for Higher Order Structure Quality Assessment Among U.S. Marketed Insulin Therapeutics

Comprehensive characterization of higher order structure changes in methionine oxidized monoclonal antibodies via NMR chemometric analysis and biophysical approaches

The higher order structure (HOS) of monoclonal antibodies (mAbs) is an important quality attribute with strong contribution to clinically relevant biological functions and drug safety. Due to the multi-faceted nature of HOS, the synergy of multiple complementary analytical approaches can substantially improve the understanding, accuracy, and resolution of HOS characterization. In this study, we applied one- and two-dimensional (1D and 2D) nuclear magnetic resonance (NMR) spectroscopy coupled with chemometric analysis, as well as circular dichroism (CD), differential scanning calorimetry (DSC), and fluorescence spectroscopy as orthogonal methods, to characterize the impact of methionine (Met) oxidation on the HOS of an IgG1 mAb. We used a forced degradation method involving concentration-dependent oxidation by peracetic acid, in which Met oxidation is site-specifically quantified by liquid chromatography-mass spectrometry. Conventional biophysical techniques report nuanced results, in which CD detects no change to the secondary structure and little change in the tertiary structure. Yet, DSC measurements show the destabilization of Fab and Fc domains due to Met oxidation. More importantly, our study demonstrates that 1D and 2D NMR and chemometric analysis can provide semi-quantitative analysis of chemical modifications and resolve localized conformational changes with high sensitivity. Furthermore, we leveraged a novel 15N-Met labeling technique of the antibody to directly observe structural perturbations at the oxidation sites. The NMR methods described here to probe HOS changes are highly reliable and practical in biopharmaceutical characterization.

Characterization of Higher Order Structural Changes of a Thermally Stressed Monoclonal Antibody via Mass Spectrometry Footprinting and Other Biophysical Approaches

Characterizing changes in the higher order structure (HOS) of monoclonal antibodies upon stressed conditions is critical to gaining a better understanding of the product and process. One single biophysical approach may not be best suited to assess HOS comprehensively; thus, the synergy from multiple, complementary approaches improves characterization accuracy and resolution. In this study, we employed two mass spectrometry (MS )-based footprinting techniques, namely, fast photochemical oxidation of proteins (FPOP)-MS and hydrogen-deuterium exchange (HDX)-MS, supported by dynamic light scattering (DLS), differential scanning calorimetry (DSC), circular dichroism (CD), and nuclear magnetic resonance (NMR) to study changes to the HOS of a mAb upon thermal stress. The biophysical techniques report a nuanced characterization of the HOS in which CD detects no changes to the secondary or tertiary structure, yet DLS measurements show an increase in the hydrodynamic radius. DSC indicates that the stability decreases, and chemical or conformational changes accumulate with incubation time according to NMR. Furthermore, whereas HDX-MS does not indicate HOS changes, FPOP-MS footprinting reveals conformational changes at residue resolution for some amino acids. The local phenomena observed with FPOP-MS indicate that several residues show various patterns of degradation during thermal stress: no change, an increase in solvent exposure, and a biphasic response to solvent exposure. All evidences show that FPOP-MS efficiently resolves subtle structural changes and novel degradation pathways upon thermal stress treatment at residue-level resolution.

Application of NMR and Chemometric Analyses to Better Understand the Quality Attributes in pH and Thermally Degraded Monoclonal Antibodies

PURPOSE

Nuclear magnetic resonance (NMR) spectroscopy provides the sensitivity and specificity to probe the higher order structure (HOS) of monoclonal antibodies (mAbs) for potential changes. This study demonstrates an application of chemometric tools to measure differences in the NMR spectra of mAbs after forced degradation relative to the respective unstressed starting materials.

METHODS

Samples of adalimumab (Humira, ADL-REF) and trastuzumab (Herceptin, TRA-REF) were incubated in three buffer-pH conditions at 40°C for 4 weeks to compare to a control sample that was left unstressed. Replicate 1D 1H and 2D 1H-13C HMQC NMR spectra were collected on all samples. Chemometric analyses such as Easy Comparability of HOS (ECHOS), PROtein FIngerprinting by Lineshape Enhancement (PROFILE), and Principal Component Analysis (PCA) were applied to capture and quantitate differences between the spectra.

RESULTS

Visual and statistical inspection of the 2D 1H-13C HMQC spectra of adalimumab and trastuzumab after forced degradation conditions shows no changes in the spectra relative to the unstressed material. Chemometric analysis of the 1D 1H NMR spectra shows only minor changes in the spectra of adalimumab after forced degradation, but significant differences in trastuzumab.

CONCLUSION

The chemometric analyses support the lack of statistical differences in the structure of pH-thermal stressed adalimumab, however, it reveals conformational changes or chemical modifications in trastuzumab after forced degradation. Application of chemometrics in comparative NMR studies enables HOS characterization and showcases the sensitivity and specificity in detecting differences in the spectra of mAbs after pH-thermal forced degradation with respect to local and global protein structure.

Structural Fingerprinting of Antisense Oligonucleotide Therapeutics by Solution NMR Spectroscopy

PURPOSE

Antisense oligonucleotide (ASO) therapeutics are an emerging class of biopharmaceuticals to treat and prevent diseases, particularly those involving "undruggable" protein targets. Impurities generated throughout the ASO drug manufacturing and formulation pipeline can be detrimental to drug safety and efficacy. Therefore, analytical techniques are needed to rigorously characterize these molecules for quality assurance purposes.

METHODS

We demonstrate 1D and 2D nuclear magnetic resonance (NMR) spectroscopy methods that can generate high-resolution structural "fingerprints" of ASOs.

RESULTS AND CONCLUSIONS

1D 1H and 31P measurements are shown to provide rapid initial assessment of the ASO integrity. In particular, a well-resolved pair of 31P signals arising from the 5´-end of the phosphorodiamidate morpholino oligomer (PMO) are sensitive to complex formation and oligomerization state. 2D 1H-1H, 1H-13C, and 1H-15 N experiments, although less sensitive, are further shown to enable resonance assignment, which will allow the tracking of structural changes at high-resolution during the drug development and manufacturing processes. We further anticipate that the described NMR approaches will be broadly applicable to fully formulated ASO therapeutics, including modalities other than PMOs.

Direct Assessment of Oligomerization of Chemically Modified Peptides and Proteins in Formulations using DLS and DOSY-NMR

PURPOSE

Protein higher order structure (HOS) including the oligomer distribution can be critical for efficacy, safety and stability of drug products (DP). Oligomerization is particularly relevant to chemically modified protein therapeutics that have an extended pharmacokinetics profile. Therefore, the direct assessment of protein oligomerization in drug formulation is desired for quality assurance and control.

METHODS

Here, two non-invasive methods, dynamic light scattering (DLS) and diffusion ordered spectroscopy (DOSY) NMR, were applied to measure translational diffusion coefficients (Ddls and Dnmr) of proteins in formulated drug products. The hydrodynamic molecular weights (MWhd), similar to hydrodynamic size, of protein therapeutics were derived based on a log(Ddls) vs log(MWhd) correlation model established using protein standards.

RESULTS

An exponent value of -0.40 ± 0.01 was established for DLS measured log(D) vs. log(MWhd) using protein standards and a theoretical exponent value of -0.6 was used for unstructured polyethylene glycol (PEG) chains. The analysis of DLS derived MWhd of the primary species showed the fatty acid linked glucagon-like peptide 1 (GLP-1) was in different oligomer states, but the fatty acid linked insulin and PEG linked proteins were in monomer states. Nevertheless, equilibrium and exchange between oligomers in formulations were universal and clearly evidenced from DOSY-NMR for all drugs except peginterferon alfa-2a.

CONCLUSION

The correlation models of log(D) vs. log(MWhd) could be a quick and efficient way to predict MWhd of protein, which directly informs on the state of protein folding and oligomerization in formulation.

Combined Liquid-State and Solid-State Nuclear Magnetic Resonance at Natural Abundance for Comparative Higher Order Structure Assessment in the Formulated-State of Biphasic Biopharmaceutics

A higher-order structure (HOS) is critical to a biopharmaceutical drug as the three-dimensional structure governs its function. Even the partial perturbation in the HOS of the drug can alter the biological efficiency and efficacy. Due to current limitations in analytical technologies, it is imperative to develop a protocol to characterize the HOS of biopharmaceuticals in the native formulated state. This becomes even more challenging for the suspension formulations where solution and solid phases co-exist. Here, we have used a combinatorial approach using liquid (1D ¹H) and solid-state (¹³C CP MAS) NMR methodology to demonstrate the HOS in the biphasic microcrystalline suspension drug in its formulated state. The data were further assessed by principal component analysis and Mahalanobis distance (D_M) calculation for quantitative assessment. This approach is sufficient to provide information regarding the protein HOS and the local dynamics of the molecule when combined with orthogonal techniques such as X-ray scattering. Our method can be an elegant tool to investigate batch-to-batch variation in the process of manufacture and storage as well as a biosimilarity comparison study for biphasic/microcrystalline suspension.

Assessing the Structural and Functional Similarity of Insulin Glargine Biosimilars

BACKGROUND

A biosimilar product is expected to exhibit similar safety, efficacy, and quality as that of the approved reference product. Only a few reports of thorough evaluation of the quality of insulin glargine biosimilars are available in literature. Here, we examine the structural and functional similarity of biosimilars of insulin glargine, the first basal long-acting insulin analogue with respect to its innovator product (Lantus^® from Sanofi Aventis).

METHODS

Structural similarity was established using mass spectrometry, chromatographic, and spectroscopic techniques. Stability was compared by performing accelerated thermal stress studies. Functional similarity was established via in vitro assay.

RESULTS

Biosimilar 4 exhibited greater content of high molecular weight species (HMWs) (0.80%) and related substances (RS) (0.45±0.06%) vs others (HMWs of 0.04% and RS of 0.17%). Biosimilars 1 and 3 exhibited higher rate of impurity generation (0.78% and 0.73% per week, respectively), as compared with other drug products (0.02% to 0.43% per week). Furthermore, %aggregation at 14 days was found to statistically correlate (R²= 0.99, root mean square error (RMSE) = 0.095) with %aggregation at 0 day (linearly) and the number of months from expiry (nonlinearly), highlighting the overpowering impact of the latter.

CONCLUSIONS

While an overall structural and functional similarity was observed across insulin glargine biosimilars with respect to the innovator product, low amounts of product-related variants were seen in some biosimilars and these impact product stability. The %aggregation at 14 days exhibits statistical correlation with %aggregation at 0 day and the number of months from expiry. The order of biosimilarity was denoted as Lantus^®>Biosimilar 2>Biosimilar 4>Biosimilar 1>Biosimilar 3.

Taking the individual bias out of examining comparability of biosimilars: A case study on monoclonal antibody therapeutics

Biosimilar manufacturers need to perform analytical and functional similarity assessments against the reference product. Successful demonstration allows for an abbreviated clinical path, thereby translating to affordable biosimilars. Current practices for regulatory concurrence on analytical similarity data are based on chart visualization and open to individual (human) bias. Here, we present a novel, chemometric approach for assessing biosimilarity that aims to simplify assessment and eliminate individual bias from decision making through application of weighted principal component analysis. Through the proposed approach, chemical information across the analytical characterization platform and drug products can be collated into a single plot for quantitative biosimilarity assessment. The proposed one-plot analysis offers a holistic visualization of 1) inter-product variability (w.r.t reference product) in cases where multiple batches per product have been investigated and 2) intra-product variability for each critical quality attribute (CQA) wherein information from orthogonal tools can be incorporated within the same plot. This allows for numerical grading of similarity for biosimilars of any given reference product. Although the proposed statistical approach is novel, it builds on standardized measures of CQA, criticality, and analytical procedures, thus making this approach easy to incorporate within the existing regulatory framework.

Structural Fingerprinting of Short Interfering RNA Therapeutics by Solution Nuclear Magnetic Resonance Spectroscopy

Nucleic acids are an increasingly popular platform for the development of biotherapeutics to treat a wide variety of illnesses, including diseases where traditional drug development efforts have failed. To date, there are 14 short oligonucleotide therapeutics and 2 messenger RNA (mRNA) vaccines approved by the U.S. Food and Drug Administration (FDA), which demonstrates the potential of nucleic acids as a platform for the development of safe and effective medicines and vaccines. Despite the increasing popularity of nucleic acid-based drugs, there has been a paucity of high-resolution structural techniques applied to rigorously characterize these molecules during drug development. Here, we present application of nuclear magnetic resonance (NMR) methods to structurally "fingerprint" short oligonucleotide therapeutics at natural isotope abundance under full formulation conditions. The NMR methods described herein leverage signals arising from the native structural features of nucleic acids, including imino, aromatic, and ribose resonances, in addition to non-native chemistries, such as 2'-fluoro (2'-F), 2'-O-methyl (2'-OMe), and phosphorothioate (PS) modifications, introduced during drug development. We demonstrate the utility of the NMR methods to structurally "fingerprint" a model short interfering RNA (siRNA) and a sample that simulated the drug product Givosiran. We anticipate broad applicability of the NMR methods to other nucleic acid-based therapeutics due to the generalized nature of the approach and ability to monitor many quality attributes simultaneously.

Analytical Similarity Assessment of Biosimilars: Global Regulatory Landscape, Recent Studies and Major Advancements in Orthogonal Platforms

Biopharmaceuticals are one of the fastest-growing sectors in the biotechnology industry. Within the umbrella of biopharmaceuticals, the biosimilar segment is expanding with currently over 200 approved biosimilars, globally. The key step towards achieving a successful biosimilar approval is to establish analytical and clinical biosimilarity with the innovator. The objective of an analytical biosimilarity study is to demonstrate a highly similar profile with respect to variations in critical quality attributes (CQAs) of the biosimilar product, and these variations must lie within the range set by the innovator. This comprises a detailed comparative structural and functional characterization using appropriate, validated analytical methods to fingerprint the molecule and helps reduce the economic burden towards regulatory requirement of extensive preclinical/clinical similarity data, thus making biotechnological drugs more affordable. In the last decade, biosimilar manufacturing and associated regulations have become more established, leading to numerous approvals. Biosimilarity assessment exercises conducted towards approval are also published more frequently in the public domain. Consequently, some technical advancements in analytical sciences have also percolated to applications in analytical biosimilarity assessment. Keeping this in mind, this review aims at providing a holistic view of progresses in biosimilar analysis and approval. In this review, we have summarized the major developments in the global regulatory landscape with respect to biosimilar approvals and also catalogued biosimilarity assessment studies for recombinant DNA products available in the public domain. We have also covered recent advancements in analytical methods, orthogonal techniques, and platforms for biosimilar characterization, since 2015. The review specifically aims to serve as a comprehensive catalog for published biosimilarity assessment studies with details on analytical platform used and critical quality attributes (CQAs) covered for multiple biotherapeutic products. Through this compilation, the emergent evolution of techniques with respect to each CQA has also been charted and discussed. Lastly, the information resource of published biosimilarity assessment studies, created during literature search is anticipated to serve as a helpful reference for biopharmaceutical scientists and biosimilar developers.

Principal Component Analysis of 1D 1H Diffusion Edited NMR Spectra of Protein Therapeutics

The one-dimensional (1D) diffusion edited proton NMR method, Protein Fingerprint by Lineshape Enhancement (PROFILE) has been demonstrated to be suitable for higher order structure (HOS) characterization of protein therapeutics including monoclonal antibodies. Recent reports in the literature have demonstrated its advantages for HOS characterization over traditional methods such as circular dichroism and Fourier-transform infrared spectroscopy. Previously, we have demonstrated that the PROFILE method is complementary with high resolution 2D methyl correlated NMR methods and how both may be deployed as a multi-modal platform to further the utility of NMR for HOS characterization. A major limitation of the PROFILE method remains its need for high signal to noise data due to its reliance on convolution difference processing and linear correlation metrics to assess spectral similarity. Here we present an alternative method for analyzing 1D diffusion edited spectra, which overcomes this limitation by using nonlinear iterative partial least squares (NIPALS) principal component analysis, and which we dub PROtein Fingerprint Observed Using NIPALS Decomposition (PROFOUND). We demonstrate that results from the PROFOUND method are robust with respect to instrument, operator and in the presence of high experimental noise and how it may be employed to provide quantitative assessment of spectral similarity.

NMR Spectroscopy for Protein Higher Order Structure Similarity Assessment in Formulated Drug Products

Peptide and protein drug molecules fold into higher order structures (HOS) in formulation and these folded structures are often critical for drug efficacy and safety. Generic or biosimilar drug products (DPs) need to show similar HOS to the reference product. The solution NMR spectroscopy is a non-invasive, chemically and structurally specific analytical method that is ideal for characterizing protein therapeutics in formulation. However, only limited NMR studies have been performed directly on marketed DPs and questions remain on how to quantitively define similarity. Here, NMR spectra were collected on marketed peptide and protein DPs, including calcitonin-salmon, liraglutide, teriparatide, exenatide, insulin glargine and rituximab. The 1D ¹H spectral pattern readily revealed protein HOS heterogeneity, exchange and oligomerization in the different formulations. Principal component analysis (PCA) applied to two rituximab DPs showed consistent results with the previously demonstrated similarity metrics of Mahalanobis distance (D_M) of 3.3. The 2D ¹H-¹³C HSQC spectral comparison of insulin glargine DPs provided similarity metrics for chemical shift difference (Δδ) and methyl peak profile, i.e., 4 ppb for ¹H, 15 ppb for ¹³C and 98% peaks with equivalent peak height. Finally, 2D ¹H-¹⁵N sofast HMQC was demonstrated as a sensitive method for comparison of small protein HOS. The application of NMR procedures and chemometric analysis on therapeutic proteins offer quantitative similarity assessments of DPs with practically achievable similarity metrics.

Assessment of the Higher-Order Structure of Formulated Monoclonal Antibody Therapeutics by 2D Methyl Correlated NMR and Principal Component Analysis

Characterization of the higher-order structure (HOS) of protein therapeutics, and in particular of monoclonal antibodies, by 2D ¹ H-¹³ C methyl correlated NMR has been demonstrated as precise and robust. Such characterization can be greatly enhanced when collections of spectra are analyzed using multivariate approaches such as principal component analysis (PCA), allowing for the detection and identification of small structural differences in drug substance that may otherwise fall below the limit of detection of conventional spectral analysis. A major limitation to this approach is the presence of aliphatic signals from formulation or excipient components, which result in spectral interference with the protein signal of interest; however, the recently described Selective Excipient Reduction and Removal (SIERRA) filter greatly reduces this issue. Here we will outline how basic 2D ¹ H-¹³ C methyl-correlated NMR may be combined with the SIERRA approach to collect 'clean' NMR spectra of formulated monoclonal antibody therapeutics (i.e., drug substance spectra free of interfering component signals), and how series of such spectra may be used for HOS characterization by direct PCA of the series spectral matrix. © 2020 U.S. Government. Basic Protocol 1: NMR data acquisition Basic Protocol 2: Full spectral matrix data processing and analysis Support Protocol: Data visualization and cluster analysis.

Comparative Analysis of One-Dimensional Protein Fingerprint by Line Shape Enhancement and Two-Dimensional 1H,13C Methyl NMR Methods for Characterization of the Higher Order Structure of IgG1 Monoclonal Antibodies

The use of NMR spectroscopy has emerged as a premier tool to characterize the higher order structure of protein therapeutics and in particular IgG1 monoclonal antibodies (mAbs). Due to their large size, traditional 1H-15N correlation experiments have proven exceedingly difficult to implement on mAbs, and a number of alternative techniques have been proposed, including the one-dimensional (1D) 1H protein fingerprint by line shape enhancement (PROFILE) method and the two-dimensional (2D) 1H-13C methyl correlation-based approach. Both 1D and 2D approaches have relative strengths and weaknesses, related to the inherent sensitivity and resolution of the respective methods. To further increase the utility of NMR to the biopharmaceutical community, harmonized criteria for decision making in employing 1D and 2D approaches for mAb characterization are warranted. To this end, we have conducted an interlaboratory comparative study of the 1D PROFILE and 2D methyl methods on several mAbs samples to determine the degree to which each method is suited to detect spectral difference between the samples and the degree to which results from each correlate with one another. Results from the study demonstrate both methods provide statistical data highly comparable to one another and that each method is capable of complementing the limitations commonly associated with the other, thus providing a better overall picture of higher order structure.