Multiplex Hybrid Antigen-Capture LC-MRM Quantification in Sera and Nasal Lining Fluid of AZD7442, a SARS-CoV-2-Targeting Antibody Combination.

AZD7442 (tixagevimab [AZD8895]/cilgavimab [AZD1061]) is a monoclonal antibody (mAb) combination in development for the prevention and treatment of coronavirus disease 2019. Traditionally, bioanalysis of mAbs is performed using ligand binding assays (LBAs), which offer sensitivity, robustness, and ease of implementation. However, LBAs frequently require generation of critical reagents that typically take several months. Instead, we developed a highly sensitive (5 ng/mL limit of quantification) method using a hybrid LBA-liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) approach for quantification of the two codosed antibodies in serum and nasal lining fluid (NLF), a rare matrix. The method was optimized by careful selection of multiple reaction monitoring, capture reagents, magnetic beads, chromatographic conditions, evaluations of selectivity, and matrix effect. The final assay used viral spike protein receptor-binding domain as capture reagent and signature proteotypic peptides from the complementarity-determining region of each mAb for detection. In contrast to other methods of similar/superior sensitivity, our approach did not require multidimensional separations and can be operated in an analytical flow regime, ensuring high throughput and robustness required for clinical analysis at scale. The sensitivity of this method significantly exceeds typical sensitivity of ∼100 ng/mL for analytical flow 1D LBA-LC-MS/MS methods for large macromolecules, such as antibodies. Furthermore, infection and vaccination status did not impact method performance, ensuring method robustness and applicability to a broad patient population. This report demonstrated the general applicability of the hybrid LBA-LC-MS/MS approach to platform quantification of antibodies with high sensitivity and reproducibility, with specialized extension to matrices of increasing interest, such as NLF.

Comprehensive performance evaluation of ligand-binding assay-LC-MS/MS method for co-dosed monoclonal anti-SARS-CoV-2 antibodies (AZD7442).

Aims: AZD7442 is a combination SARS-CoV-2 therapy comprising two co-dosed monoclonal antibodies. Materials & methods: The authors validated a hybrid ligand-binding assay-LC-MS/MS method for pharmacokinetic assessment of AZD7442 in human serum with nominal concentration range of each analyte of 0.300-30.0 µg/ml. Results: Validation results met current regulatory acceptance criteria. The validated method supported three clinical trials that spanned more than 17 months and ≥720 analytical runs (∼30,000 samples and ∼3000 incurred sample reanalyses per analyte). The data generated supported multiple health authority interactions, across the globe. AZD7442 (EVUSHELD) was approved in 12 countries for pre-exposure prophylaxis of COVID-19. Conclusion: The results reported here demonstrate the robust, high-throughput capability of the hybrid ligand-binding assay-LC-MS/MS approach being employed to support-next generation versions of EVUSHELD, AZD3152.

The measurement of antibodies in human body fluids (e.g., blood, serum) has historically been tied to laboratory tests that may face operational limitations, including susceptibility to interference from other blood components and a reliance on unique reagents that can take months to produce. As such, there is a pursuit of alternative analytical methods to more accurately detect and measure antibody drugs from complex matrices. In the method, the authors describe different techniques that once combined were used to capture, separate, filter, fragment and then detect and measure the co-dosed antibody drugs. This method has been validated in accordance with current health authority guidelines and has been used to support three clinical trials that spanned more than 17 months; that is, the validated method was used to analyze nearly 30,000 serum samples from more than 2000 patients. Collectively, the results reported here demonstrate the robustness and high-throughput capability of this analytical approach.