Novel data analysis methods to overcome cut point challenges and enable comprehensive assessment of antidrug binding activity in confirmatory assays

Immunogenicity assessments in response to drug treatment are commonly performed using a tiered approach strategy. All samples are initially tested in a screening assay followed by the evaluation of the screened positive samples in a confirmatory assay. Percent inhibition of signal intensity by the competing unlabeled drug in a confirmatory assay is typically used to measure the specificity of antidrug binding activity in samples, and has been successfully applied to most immunogenicity assays. However, the percent inhibition approach may not be suitable in cases where broadly distributed and high percent inhibition values are observed in drug-naïve subjects or when persistent operator-dependent differences in assay performance are encountered. Herein, we present the case studies faced with such challenges and provide appropriate solutions by introducing two novel data analysis methods: (1) Reference Delta, and (2) Reference Percent Inhibition, - in which relative-to-baseline signal inhibition is calculated for each sample. These novel methods significantly improve the confirmatory assay's ability to detect the samples positive for antidrug antibodies (ADA), especially when challenges are encountered using the traditional percent inhibition approach. Furthermore, both methods can be implemented in parallel with the percent inhibition method, enabling not only confirmation of ADA specificity, but also providing additional insights about the relevance of this antidrug binding activity to drug treatment.