Drug Removal Strategies in Competitive Ligand Binding Neutralizing Antibody (NAb) Assays: Highly Drug-Tolerant Methods and Interpreting Immunogenicity Data

Karayusuf, Elif Kabuloglu; Shyu, Gary; Georgaros, Camille; Torri, Albert; Sumner, Giane

doi:10.1208/s12248-020-00497-2

Cited by 7 publications

(4 citation statements)

References 31 publications

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“…Conversely, CPs that are too low can result in elevated false positive rates in baseline or placebo groups that may lead to questions about the selectivity of the assay (as well as unnecessary bioanalysis in confirmation, titer, and neutralizing antibody assays). In addition, low immunogenicity CPs may result in detection of positive responses in the assay that dilute the true positive responses, leading to a weaker correlation of the impact of ADA on clinical outcomes such as safety and efficacy (12)(13)(14)(15)(16).…”

Section: Discussionmentioning

confidence: 99%

“…These threshold values also help define the assay sensitivity, drug tolerance, and titers, so other stakeholders such as regulators and members of drug development teams have an interest in understanding how these crucial determinants of ADA positivity are established. In recent years, this has become more important with the increasing evidence that supersensitive ADA assays do not necessarily improve detection of impactful immunogenicity and may in fact weaken the correlation between ADA and clinical response (12)(13)(14)(15)(16).…”

Section: Introductionmentioning

confidence: 99%

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Statistical Approaches for Establishing Appropriate Immunogenicity Assay Cut Points: Impact of Sample Distribution, Sample Size, and Outlier Removal

Garlits

McAfee

Taylor

et al. 2023

AAPS J

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The statistical assessments needed to establish anti-drug antibody (ADA) assay cut points (CPs) can be challenging for bioanalytical scientists. Poorly established CPs that are too high could potentially miss treatment emergent ADA or, when set too low, result in detection of responses that may have no clinical relevance. We evaluated 16 validation CP datasets generated with ADA assays at Regeneron’s bioanalytical laboratory and compared results obtained from different CP calculation tools. We systematically evaluated the impact of various factors on CP determination including biological and analytical variability, number of samples for capturing biological variability, outlier removal methods, and the use of parametric vs. non-parametric CP determination. In every study, biological factors were the major component of assay response variability, far outweighing the contribution from analytical variability. Non-parametric CP estimations resulted in screening positivity in drug-naïve samples closer to the targeted rate (5%) and were less impacted by skewness. Outlier removal using the boxplot method with an interquartile range (IQR) factor of 3.0 resulted in screening positivity close to the 5% targeted rate when applied to entire drug-naïve dataset. In silico analysis of CPs calculated using different sample sizes showed that using larger numbers of individuals resulted in CP estimates closer to the CP of the entire population, indicating a larger sample size (~ 150) for CP determination better represents the diversity of the study population. Finally, simpler CP calculations, such as the boxplot method performed in Excel, resulted in CPs similar to those determined using complex methods, such as random-effects ANOVA. Graphical Abstract

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Statistical Approaches for Establishing Appropriate Immunogenicity Assay Cut Points: Impact of Sample Distribution, Sample Size, and Outlier Removal

Garlits

McAfee

Taylor

et al. 2023

AAPS J

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, neutralizing responses are a subset of ADA and it is expected that NAb assays will be less sensitive because the methods detect a secondary readout rather than a direct binding event. In addition, NAb assays also suffer from limitations in drug tolerance (10): the drug-tolerance level in this assay is less than the trough concentration of drug. Importantly, it is increasingly becoming clear that supersensitive and drug tolerant immunogenicity assays do not improve detection of clinically impactful immunogenicity (10)(11)(12).…”

Section: Discussionmentioning

confidence: 99%

“…In addition, NAb assays also suffer from limitations in drug tolerance (10): the drug-tolerance level in this assay is less than the trough concentration of drug. Importantly, it is increasingly becoming clear that supersensitive and drug tolerant immunogenicity assays do not improve detection of clinically impactful immunogenicity (10)(11)(12).…”

Section: Discussionmentioning

confidence: 99%

Interference in a Neutralizing Antibody Assay for Odronextamab, a CD20xCD3 Bispecific mAb, from Prior Rituximab Therapy and Possible Mitigation Strategy

Irvin

D’Orvilliers

Bloch

et al. 2022

AAPS J

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A cell-based assay was developed to detect neutralizing anti-drug antibodies (NAbs) against odronextamab, a CD20xCD3 bispecific monoclonal antibody (mAb) under investigation for treatment of CD20+ B cell malignancies. In this assay, odronextamab bridges between two cell types, CD20-expressing HEK293 cells and CD3-expressing Jurkat T cells that generate a luciferase signal upon CD3 clustering. Patient samples containing NAbs directed to either arm of the bispecific drug block the odronextamab bridge formation between the cell lines thus preventing the generation of the luciferase signal. We determined that other anti-CD20 therapeutics also block bridge formation, resulting in false-positive results. In patient samples from odronextamab clinical trials, approximately 30% of baseline samples had a strong false-positive NAb signal that correlated with the presence of prior rituximab (anti-CD20) therapy. We determined that rituximab interference can be minimized by the addition of anti-rituximab antibodies in the NAb assay. Understanding and mitigating the impact of prior biologic exposure is increasingly important for implementing a successful bioanalytical strategy to support clinical drug development, especially in the immuno-oncology field. Graphical Abstract Odronextamab neutralizing antibody assay, interference, and mitigation. A Design of the odronextamab neutralizing antibody (NAb) assay where anti-CD20xCD3 drug bridges between CD20-expressing HEK293 cells and Jurkat T cells expressing an NFAT response element and luciferase reporter. True NAb prevents odronextamab from bridging between target and effector cells, thus preventing the expression of luciferase. B Interference with odronextamab from other anti-CD20 therapeutic antibodies (e.g., rituximab) from prior disease treatment generates a false-positive NAb result. Assay interference can be mitigated with an anti-idiotypic antibody against the interfering therapy.

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Highly drug/target-tolerant neutralizing antibody (NAb) assay development through target-based drug depletion and drug-based NAb extraction for an anti-EGFR therapeutic monoclonal antibody

Fu,

Xu,

Guo

et al. 2024

Journal of Pharmaceutical and Biomedical Analysis

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Drug Removal Strategies in Competitive Ligand Binding Neutralizing Antibody (NAb) Assays: Highly Drug-Tolerant Methods and Interpreting Immunogenicity Data

Cited by 7 publications

References 31 publications

Statistical Approaches for Establishing Appropriate Immunogenicity Assay Cut Points: Impact of Sample Distribution, Sample Size, and Outlier Removal

Statistical Approaches for Establishing Appropriate Immunogenicity Assay Cut Points: Impact of Sample Distribution, Sample Size, and Outlier Removal

Interference in a Neutralizing Antibody Assay for Odronextamab, a CD20xCD3 Bispecific mAb, from Prior Rituximab Therapy and Possible Mitigation Strategy

Highly drug/target-tolerant neutralizing antibody (NAb) assay development through target-based drug depletion and drug-based NAb extraction for an anti-EGFR therapeutic monoclonal antibody

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