Structural identification and absolute quantification of monoclonal antibodies in suspected counterfeits using capillary electrophoresis and liquid chromatography-tandem mass spectrometry

Development of Analytical Method for the Quantitation of Monoclonal Antibodies Solutions via Raman Spectroscopy: The Case of Bevacizumab

Personalized dosages of monoclonal antibodies are being used more regularly to treat various diseases, rendering their quantitation more essential than ever for the right dose administration to the patients. A promising alternative, which overcomes the obstacles of the well-established chromatographic techniques regarding the quantification of biopharmaceuticals, is Raman spectroscopy. This study aimed to develop and validate a novel analytical method for the quantitation of bevacizumab in solutions via Raman spectroscopy. For this purpose, a droplet of the solution was left to dry on a highly reflective carrier and a home-made apparatus was employed for rotation of the sample. Hence, each recorded Raman spectrum was the average of the signal acquired simultaneously from multiple points on a circular circumference. The method was validated, and the detection limit of the antibody was found to be 1.06 mg/mL. Bevacizumab was found to be highly distributed at the formed coffee ring of the dried droplet, though this was a function of solution concentration. Finally, Raman spectra at different distances on the coffee ring were obtained from the four quarters. The lowest bevacizumab detection limit was found at a distance of 75 μm from the external side of the coffee ring and it was determined to be equal to 0.53 mg/mL.

Simultaneous quantification and structural characterization of monoclonal antibodies after administration using capillary zone electrophoresis-tandem mass spectrometry

Monoclonal antibodies (mAbs) are demonstrating major success in various therapeutic areas such as oncology and the treatment of immune disorders. Over the past two decades, novel analytical methodologies allowed to address the challenges of mAbs characterization in the context of their production. However, after administration only their quantification is performed and insights regarding their structural evolution remain limited. For instance, clinical practice has recently highlighted significant inter-patient differences in mAb clearance and unexpected clinical responses, without providing alternative interpretations. Here, we report the development of a novel analytical strategy based on capillary zone electrophoresis coupled to tandem mass spectrometry (CE-MS/MS) for the simultaneous absolute quantification and structural characterization of infliximab (IFX) in human serum. CE-MS/MS quantification was validated over the range 0.4-25 µg·mL^-1 corresponding to the IFX therapeutic window and achieved a LOQ of 0.22 µg·mL^-1 (1.5 nM) while demonstrating outstanding specificity compared to the ELISA assay. CE-MS/MS allowed structural characterization and estimation of the relative abundance of the six major N-glycosylations expressed by IFX. In addition, the results allowed characterization and determination of the level of modification of post-translational modifications (PTMs) hotspots including deamidation of 4 asparagine and isomerization of 2 aspartate. Concerning N-glycosylation and PTMs, a new normalization strategy was developed to measure the variation of modification levels that occur strictly during the residence time of IFX in the patient's system, overcoming artefactual modifications induced by sample treatment and/or storage. The CE-MS/MS methodology was applied to the analysis of samples from patients with Crohn's disease. The data identified a gradual deamidation of a particular asparagine residue located in the complementary determining region that correlated with IFX residence time, while the evolution of IFX concentration showed significant variability among patients.

Modeling study of long-term stability of the monoclonal antibody infliximab and biosimilars using liquid-chromatography-tandem mass spectrometry and size-exclusion chromatography-multi-angle light scattering

Monoclonal antibodies (mAbs) represent a dynamic class of biopharmaceutical products, as evidenced by an increasing number of market authorizations for mAb innovator and biosimilar products. Stability studies are commonly performed during product development, for instance, to exclude unstable molecules, optimize the formulation or determine the storage limit. Such studies are time-consuming, especially for mAbs, because of their structural complexity which requires multiple analytical techniques to achieve a detailed characterization. We report the implementation of a novel methodology based on the accelerated stability assessment program (ASAP) in order to model the long-term stability of mAbs in relation to different structural aspects. Stability studies of innovator infliximab and two different biosimilars were performed using forced degradation conditions alongside in-use administration conditions in order to investigate their similarity regarding stability. Thus, characterization of post-translational modifications was achieved using liquid-chromatography-tandem mass spectrometry (LC-MS/MS) analysis, and the formation of aggregates and free chain fragments was characterized using size-exclusion chromatography-multi-angle light scattering (SEC-MALS-UV/RI) analysis. Consequently, ASAP models were investigated with regard to free chain fragmentation of mAbs concomitantly with N57 deamidation, located in the hypervariable region. Comparison of ASAP models and the long-term stability data from samples stored in intravenous bags demonstrated a relevant correlation, indicating the stability of the mAbs. The developed methodology highlighted the particularities of ASAP modeling for mAbs and demonstrated the possibility to independently consider the different types of degradation pathways in order to provide accurate and appropriate prediction of the long-term stability of this type of biomolecule.

Extreme Point Sort Transformation Combined With a Long Short-Term Memory Network Algorithm for the Raman-Based Identification of Therapeutic Monoclonal Antibodies

Therapeutic monoclonal antibodies (mAbs) are a new generation of protein-based medicines that are usually expensive and thus represent a target for counterfeiters. In the present study, a method based on Raman spectroscopy that combined extreme point sort transformation with a long short-term memory (LSTM) network algorithm was presented for the identification of therapeutic mAbs. A total of 15 therapeutic mAbs were used in this study. An in-house Raman spectrum dataset for model training was created with 1,350 spectra. The characteristic region of the Raman spectrum was reduced in dimension and then transformed through an extreme point sort transformation into a sequence array, which was fitted for the LSTM network. The characteristic array was extracted from the sequence array using a well-trained LSTM network and then compared with standard spectra for identification. To demonstrate whether the present algorithm was better, ThermoFisher OMNIC 8.3 software (Thermo Fisher Scientific Inc., U.S.) with two matching modes was selected for comparison. Finally, the present method was successfully applied to identify 30 samples, including 15 therapeutic mAbs and 15 other injections. The characteristic region was selected from 100 to 1800 cm⁻¹ of the full spectrum. The optimized dimensional values were set from 35 to 53, and the threshold value range was from 0.97 to 0.99 for 15 therapeutic mAbs. The results of the robustness test indicated that the present method had good robustness against spectral peak drift, random noise and fluorescence interference from the measurement. The areas under the curve (AUC) values of the present method that were analysed on the full spectrum and analysed on the characteristic region by the OMNIC 8.3 software’s built-in method were 1.000, 0.678, and 0.613, respectively. The similarity scores for 15 therapeutic mAbs using OMNIC 8.3 software in all groups compared with that of the relative present algorithm group had extremely remarkable differences (p < 0.001). The results suggested that the extreme point sort transformation combined with the LSTM network algorithm enabled the characteristic extraction of the therapeutic mAb Raman spectrum. The present method is a proposed solution to rapidly identify therapeutic mAbs.