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1.
MAbs ; 15(1): 2152526, 2023.
Article in English | MEDLINE | ID: covidwho-2151559

ABSTRACT

To combat the COVID-19 pandemic, potential therapies have been developed and moved into clinical trials at an unprecedented pace. Some of the most promising therapies are neutralizing antibodies against SARS-CoV-2. In order to maximize the therapeutic effectiveness of such neutralizing antibodies, Fc engineering to modulate effector functions and to extend half-life is desirable. However, it is critical that Fc engineering does not negatively impact the developability properties of the antibodies, as these properties play a key role in ensuring rapid development, successful manufacturing, and improved overall chances of clinical success. In this study, we describe the biophysical characterization of a panel of Fc engineered ("TM-YTE") SARS-CoV-2 neutralizing antibodies, the same Fc modifications as those found in AstraZeneca's Evusheld (AZD7442; tixagevimab and cilgavimab), in which the TM modification (L234F/L235E/P331S) reduce binding to FcγR and C1q and the YTE modification (M252Y/S254T/T256E) extends serum half-life. We have previously shown that combining both the TM and YTE Fc modifications can reduce the thermal stability of the CH2 domain and possibly lead to developability challenges. Here we show, using a diverse panel of TM-YTE SARS-CoV-2 neutralizing antibodies, that despite lowering the thermal stability of the Fc CH2 domain, the TM-YTE platform does not have any inherent developability liabilities and shows an in vivo pharmacokinetic profile in human FcRn transgenic mice similar to the well-characterized YTE platform. The TM-YTE is therefore a developable, effector function reduced, half-life extended antibody platform.


Subject(s)
COVID-19 , SARS-CoV-2 , Animals , Mice , Humans , SARS-CoV-2/genetics , Pandemics , Antibodies, Neutralizing
2.
J Immunol Methods ; 496: 113099, 2021 09.
Article in English | MEDLINE | ID: covidwho-1292808

ABSTRACT

Bispecific antibodies (BsAbs) are engineered to simultaneously bind two different antigens, and offer promising clinical outcomes for various diseases. The dual binding properties of BsAbs may enable superior efficacies and/or potencies compared to standard monoclonal antibodies (mAbs) or combination mAb therapies. Characterizing BsAb binding properties is critical during biotherapeutic development, where data is leveraged to predict efficacy and potency, assess critical quality attributes and improve antibody design. Traditional single-target, single-readout approaches (e.g., ELISA) have limited usefulness for interpreting complex bispecific binding, and double the benchwork. To address these deficiencies, we developed and implemented a new dual-target/readout binding assay that accurately dissects the affinities of both BsAb binding domains directly and simultaneously. This new assay uses AlphaPlex® technology, which eliminates traditional ELISA wash steps and can be miniaturized for automated workflows. The optimized BsAb AlphaPlex assay demonstrates 99-107% accuracy within a 50-150% linear range, and detected >50% binding degradation from photo- and thermal stress conditions. To the best of our knowledge, this is the first instance of a dual-target/readout BsAb AlphaPlex assay with GMP-suitable linear range, accuracy, specificity, and stability-indicating properties. As a highly customizable and efficient assay, BsAb AlphaPlex may be applicable to numerous bispecific formats and/or co-formulations against a variety of antigens beyond the clinical therapeutic space.


Subject(s)
Antibodies, Bispecific/immunology , Antibody Specificity , Antigens/immunology , CTLA-4 Antigen/immunology , Immunoassay , Programmed Cell Death 1 Receptor/immunology , Antibodies, Bispecific/metabolism , Antigen-Antibody Complex , Antigens/metabolism , Binding Sites, Antibody , Buffers , CTLA-4 Antigen/metabolism , Enzyme-Linked Immunosorbent Assay , Epitopes , Humans , Hydrogen-Ion Concentration , Kinetics , Predictive Value of Tests , Programmed Cell Death 1 Receptor/metabolism , Protein Binding , Reproducibility of Results
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