Principal component analysis for automated classification of 2D spectra and interferograms of protein therapeutics: influence of noise, reconstruction details, and data preparation.

Protein therapeutics have numerous critical quality attributes (CQA) that must be evaluated to ensure safety and efficacy, including the requirement to adopt and retain the correct three-dimensional fold without forming unintended aggregates. Therefore, the ability to monitor protein higher order structure (HOS) can be valuable throughout the lifecycle of a protein therapeutic, from development to manufacture. 2D NMR has been introduced as a robust and precise tool to assess the HOS of a protein biotherapeutic. A common use case is to decide whether two groups of spectra are substantially different, as an indicator of difference in HOS. We demonstrate a quantitative use of principal component analysis (PCA) scores to perform this decision-making, and demonstrate the effect of acquisition and processing details on class separation using samples of NISTmAb monoclonal antibody Reference Material subjected to two different oxidative stress protocols. The work introduces an approach to computing similarity from PCA scores based upon the technique of histogram intersection, a method originally developed for retrieval of images from large databases. Results show that class separation can be robust with respect to random noise, reconstruction method, and analysis region selection. By contrast, details such as baseline distortion can have a pronounced effect, and so must be controlled carefully. Since the classification approach can be performed without the need to identify peaks, results suggest that it is possible to use even more efficient measurement strategies that do not produce spectra that can be analyzed visually, but nevertheless allow useful decision-making that is objective and automated.

Utility of High Resolution NMR Methods to Probe the Impact of Chemical Modifications on Higher Order Structure of Monoclonal Antibodies in Relation to Antigen Binding.

PURPOSE: An understanding of higher order structure (HOS) of monoclonal antibodies (mAbs) could be critical to predicting its function. Amongst the various factors that can potentially affect HOS of mAbs, chemical modifications that are routinely encountered during production and long-term storage are of significant interest. METHODS: To this end, two Pfizer mAbs were subjected to forced deamidation stress for a period of eight weeks. Samples were aliquoted at various time points and high resolution accurate mass liquid chromatography-mass spectrometry (LC-MS/MS) was performed using low-artifact trypsin digestion (LATD) peptide mapping to identify and quantify chemical modifications. 2D backbone amide and sidechain methyl NMR spectra were acquired to gauge the effect of HOS changes upon chemical modification. Differential scanning calorimetry was also performed to assess the effect of thermal stability of mAbs upon modification. Finally, functional studies via target-binding based ELISA were performed to connect HOS changes to any loss of potency. RESULTS: The extent of deamidation in the mAb domains were quantified by LC-MS/MS. The HOS changes as obtained from 2D NMR were mostly localized around the affected sites leaving the overall structure relatively unchanged. The antigen-antibody binding of the mAbs, in spite of deamidation in the Fab region, remains unchanged. CONCLUSION: This case study provides an integrated approach of relating chemical modifications in mAb domains with possible changes in HOS. This can be potentially used to assess a possible loss of potency within the structure-function paradigm of proteins in an orthogonal manner.

A systematic and sensitive method for critical reagent antibody evaluation with PCA technology.

Background: Quality control of critical reagents is essential in basic research and in drug discovery and development. Protein conformational array (PCA) is an ELISA-based technology that has been successfully used for the development of novel and biosimilar biologics with excellent sensitivity and accuracy. Methodology & results: PCA ELISA is able to monitor higher order structure changes of mouse and rabbit antibodies under various stress and storage conditions. This study focused on the short- and long-term storage of antibodies and antiserum as well as the effect of multiple freeze-thaw cycles on the impact of antibody higher order structure. Conclusion: These results suggest that PCA ELISA can be used as a valuable method for quality testing of antibodies.

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

Protein or peptide higher order structure (HOS) is a quality attribute that could affect therapeutic efficacy and safety. Where appropriate, the HOS similarity between a proposed follow-on product and the reference listed drug should be demonstrated during regulatory assessment. Establishing quantitative HOS similarity for 2 drug substances, manufactured by different processes, has been challenging. Herein, HOS differences among U.S. marketed insulin drug products (DPs) were quantified using nuclear magnetic resonance spectra and principal component analysis (PCA). Then, the unitless Mahalanobis distance (DM) in PCA space was calculated between insulin analog reference listed drugs and their recently approved follow-on products, and all DM values were 3.29 or less. By contrast, a larger DM value of 20.5 was obtained between the 2 insulin human DPs independently approved. However, upon mass-balanced and reversible dialysis of the 2 insulin human DPs against the same buffers, the DM value was reduced to 1.19 or less. Thus, the observed range of nuclear magnetic resonance-PCA-derived DM values can be used as a robust and sensitive measure of HOS similarity. Overall, the DM values of 3.3 for DP and 1.2 for drug substances using insulin therapeutics represented realistic and achievable similarity metrics for developing generic or biosimilar drugs, quality assurance, or control.

A simple MS method to characterize the higher order structures of antibody therapeutics.

A scheme with enhanced throughput using the hydroxyl radical foot-printing technique to map the higher order structures (HOSs) of antibody therapeutics was developed. This method takes advantage of the simplicity of multiple reaction monitoring (MRM) by monitoring the remaining unmodified peptides, thus overcoming the complexity of the data analysis of the conventional free radical foot-printing technique, wherein various oxidized forms of the peptides are measured. In this study, a preliminary method validation was carried out to show that the technique has good specificity, sensitivity, and repeatability. Finally, we were able to use the method to differentiate the HOSs of the disulfide isoforms of the IgG2 antibody, provide site-specific structural differences between IgG1 and its deglycosylated counterpart, and determine similarities between a biosimilar candidate and the originator product.