Cut Point in Immunogenicity Testing: A Flawed Concept We Can Live Without

Area of Science:

• Immunology
• Bioanalytical Chemistry
• Pharmacology

Background:

• The standard method for anti-drug antibody (ADA) detection uses a tiered strategy with statistical cut points for classification.
• This approach compares individual responses to a population-based threshold, aiming for high sensitivity and specificity.

Purpose of the Study:

• To critically evaluate the scientific validity of using cut points in ADA detection.
• To propose an alternative, more reliable method for ADA classification.

Main Methods:

• Analysis of the statistical and experimental limitations of current ADA cut point determination.
• Proposal of a new detection strategy based on post-baseline signal changes and their correlation with clinical parameters.

Main Results:

• Cut points, particularly those at the 95th percentile, do not effectively reduce false negatives and may hinder ADA detection in a significant portion of the population.
• Discrepancies between conditions for cut point determination and actual sample testing compromise reliability.

Conclusions:

• The use of cut points and tiered testing strategies for ADA classification is scientifically flawed and should be abandoned.
• Adopting a method that analyzes post-baseline signal changes relative to pharmacokinetics, pharmacodynamics, efficacy, and safety will improve ADA detection and reduce laboratory workload.