Abstract

Biological matrix interference in detection and quantitation immunoassays remains a major challenge in the field of bioanalysis. For example, circulating drug may interfere with the detection of anti-drug antibodies (ADA) and drug target, or ADA may interfere with quantitation of drug levels in PK/TK analysis. Monoclonal antibody drug interference, especially for human IgG4 drugs, presents an additional challenge for ADA analysis due to its longer half-life and higher dose. Assay tolerance to such interference may depend on assay platform and reagents. Various approaches have been used to improve drug tolerance in ADA analysis but limited success was observed. We have developed a breakthrough novel method that uses Precipitation and Acid dissociation (PandA) to overcome drug interference in the ADA assay. The method principle is based on four components for detection of total ADA (free ADA and drug bound ADA) in the presence of drug in patient samples: (1) use excess drug to saturate free ADA to form drug bound ADA as drug:ADA complexes, (2) precipitate the complex using an agent such as PEG, (3) acid dissociate ADA from drug and immobilize (capture) free ADA (and free drug) under acidic conditions (without neutralization) onto a large capacity surface, and (4) detect free ADA (not the captured drug) using specific anti-human Ig detection reagent.In this manuscript, we are describing case studies for three humanized monoclonal antibodies (an IgG1 and two IgG4 drugs). The three drug specific PandA ADA assays resulted in complete recovery of ADA in samples containing drug levels in excess of those expected in patients, in contrast to the commonly used acid dissociation approach in ECL bridging assays. This breakthrough novel method shows significant improvement over the current approaches. In fact, the drug interference or under detecting of ADA in all three cases was eliminated. This assay principle could be used not only for ADA assays but also PK and biomarker (drug target) analysis in the presence of interference factors.

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