(T1030-02-08) Systematic Optimization of ADA Assays for Complex Biologics: A Framework for Addressing Assay Challenges Across Modalities

Purpose: The development of anti-drug antibody (ADA) assays for biologics, including masked cytokines, ADCs, monoclonal, and bispecific antibodies, presents unique challenges such as false positive signals, high drug tolerance requirements, and elevated background noise. These obstacles hinder the accurate monitoring of immunogenicity in both clinical and preclinical studies. And therefore, ADA assays must be robust, sensitive, and tailored to the distinct properties of each biologic modality. This study aimed to establish a systematic optimization framework that addresses these challenges through buffer selection, acid dissociation techniques, and reagent quality improvements, enhancing assay sensitivity and reproducibility across diverse therapeutic modalities.

Methods: ADA assays for five therapeutic compounds representing a spectrum of biologic modalities were systematically evaluated to identify effective optimization strategies, and these assays were developed using an MSD-based drug-bridging electrochemiluminescence (ECL) immunoassay. Samples were pre-treated with buffer or acid at a minimal required dilution (MRD) to prepare for analysis. Following pre-treatment, 50 uL of samples were incubated with a master mix containing biotin labeled drug and ruthenium (Ru)-labeled drug to detect anti-drug antibodies. Confirmatory assays incorporated unlabeled drug into the master mix, allowing it to compete with antibodies for binding, thereby verifying assay specificity. And then, 50 uL of samples were transferred to streptavidin or avidin coated MSD plates for further incubation, followed by plate washing and addition of MSD read buffer. ECL signals were detected using an MSD plate reader, with signal intensity correlating to the presence of anti-drug antibodies. Specific optimization steps included buffer selection, acid dissociation techniques, and reagent quality improvement. Buffer optimization for Compounds 1 (Masked cytokines) and compound 2 (Antibody Drug Conjugate) evaluated various buffers, including SMC Wash, Casein, and Rexxip HX, to reduce background noise and minimize false positives caused by reagent aggregation. Acid dissociation techniques were applied to Compounds 3 (IgG Monoclonal Antibody) and compound 4 (Bispecific Antibody), with multiple acids tested to improve drug tolerance while maintaining positive control antibody’s stability. Reagent quality improvement for Compound 5 (IgG Monoclonal Antibody) compared first-generation labeled reagents with second-generation reagents made from a refined drug batch, aiming to reduce background signal and enhance assay performance. This streamlined approach allowed for systematic evaluation and optimization of assay parameters tailored to the unique requirements of each biologic compound.

Results: Buffer optimization using SMC wash buffer reduced background signals significantly for compound 1 and compound 2, effectively minimizing false positives caused by reagent aggregation. Acid dissociation with HCl increased drug tolerance for both compound 3 and compound 4, while maintaining stable signal response across monoclonal and polyclonal positive control antibodies. Comparative analysis of acid dissociation methods highlighted HCl’s superiority over others, particularly for biologics requiring high drug tolerance. For Compound 5, second-generation labeled reagents reduced assay background noise by roughly 60% compared to the first-generation reagents, addressing issues of false positives and significantly enhancing assay performance. Collectively, these results demonstrate the adaptability and effectiveness of the systematic optimization framework, highlighting its critical role in overcoming challenges inherent to ADA assay development for complex biologics. The findings also provide evidence of cross-applicability for these optimization strategies, supporting their relevance to novel therapeutic modalities.

Conclusion: This study establishes a systematic framework for optimizing ADA assays tailored to the specific needs of diverse biologic modalities. By systematically addressing challenges such as false positive signals, high drug tolerance requirement, and reagent quality issues, the proposed strategies significantly improve assay sensitivity, robustness, and reproducibility. The integration of optimized buffers, acid dissociation techniques, and high-quality reagents ensures reliable ADA monitoring in clinical and preclinical studies. This robust approach is applicable to current biologics and emerging therapeutic modalities. Future work will focus on extending this approach to address additional challenges in complex therapeutics.

Table 1. Evaluation of Assay Buffers

Table 2. Systematic Analysis of Acid Treatment and their impact on both drug tolerance samples and and positive control signals

Table 3. Comparison of Assay Results with First and Second Generation Reagents