Nanoplasmonic Avidity-Based Detection and Quantification of IgG AggregatesShow others and affiliations
2022 (English)In: Analytical Chemistry, ISSN 0003-2700, E-ISSN 1520-6882, Vol. 94, no 45, p. 15754-15762Article in journal (Refereed) Published
Abstract [en]
Production of therapeutic monoclonal antibodies (mAbs) is a complex process that requires extensive analytical and bioanalytical characterization to ensure high and consistent product quality. Aggregation of mAbs is common and very problematic and can result in products with altered pharmacodynamics and pharmacokinetics and potentially increased immunogenicity. Rapid detection of aggregates, however, remains very challenging using existing analytical techniques. Here, we show a real-time and label-free fiber optical nanoplasmonic biosensor system for specific detection and quantification of immunoglobulin G (IgG) aggregates exploiting Protein A mediated avidity effects. Compared to monomers, IgG aggregates were found to have substantially higher apparent affinity when binding to Protein Afunctionalized sensor chips in a specific pH range (pH 3.8-4.0). Under these conditions, aggregates and monomers showed significantly different binding and dissociation kinetics. Reliable and rapid aggregate quantification was demonstrated with a limit of detection (LOD) and limit of quantification (LOQ) of about 9 and 30 mu g/mL, respectively. Using neural network-based curve fitting, it was further possible to simultaneously quantify monomers and aggregates for aggregate concentrations lower than 30 mu g/mL. Our work demonstrates a unique avidity-based biosensor approach for fast aggregate analysis that can be used for rapid at-line quality control, including lot/batch release testing. This technology can also likely be further optimized for real-time in-line monitoring of product titers and quality, facilitating process intensification and automation.
Place, publisher, year, edition, pages
AMER CHEMICAL SOC , 2022. Vol. 94, no 45, p. 15754-15762
National Category
Analytical Chemistry
Identifiers
URN: urn:nbn:se:liu:diva-190352DOI: 10.1021/acs.analchem.2c03446ISI: 000884793100001PubMedID: 36318700OAI: oai:DiVA.org:liu-190352DiVA, id: diva2:1716608
Note
Funding Agencies|Swedish Innovation Agency (VINNOVA); Swedish Research Council [2016-04120, 2019-00130]; European Union [841373]
2022-12-062022-12-062023-11-07Bibliographically approved