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Multiplexed monitoring of therapeutic antibodies for inflammatory diseases using Fab-selective proteolysis nSMOL coupled with LC-MS.

Journal of immunological methods | 2019

Monoclonal antibodies have accelerated the availability of treatment options for many diseases in which the molecular mechanism has been elucidated in detail. Therefore, an assay that can universally analyze antibodies for clinical pharmacokinetics and cross-sectional studies would be indispensable. We have developed a universal antibody bioanalysis with a Fab-selective tryptic reaction, named nano-surface and molecular-orientation limited (nSMOL) proteolysis, that collects the specific antibody signature peptides in biological samples. Using the nSMOL method, we have fully validated the bioanalysis of many antibodies, Fc-fusion proteins, and their biosimilars. Inflammatory immune diseases often require long-term clinical management because of the remission and relapse observed. Accurate antibody monitoring in systemic circulation could contribute to the improvement of clinical outcomes. Because several biopharmaceuticals can be selected as practical treatment options, the assay development that quantitates many antibodies simultaneously would be applicable in many theraprutic monitoring. In this study, we have validated the LC-MS bioanalysis method for seven-mixed antibodies (Infliximab, Adalimumab, Ustekinumab, Golimumab, Eculizumab, Etanercept, and Abatacept) using the nSMOL normal reaction condition and two-mixed antibodies (Tocilizumab and Mepolizumab) using the acidified reduction acceleration condition, as reported in our previous papers. Moreover, this multiplexed assay has been verified using clinical patient samples. The nSMOL approach enables the quantitation of several immunosuppressive antibodies simultaneously in human serum, and nSMOL can potentially be applicable to the drug-drug interaction assays or therapeutic antibody monitoring of several inflammatory immune diseases to optimize administration.

Pubmed ID: 31201793 RIS Download

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