Application of analytical detection concepts to immunogenicity testing.

Area of Science:

• Analytical Chemistry
• Immunology
• Biotechnology

Background:

• Assay cut points and detection limits are critical for immunogenicity testing of therapeutic proteins.
• Current methods primarily focus on Type I (false positive) error rates, neglecting Type II (false negative) errors.

Purpose of the Study:

• To propose a more rigorous analytical chemistry definition for assay detection capability.
• To advocate for the inclusion of both Type I and Type II error rates in establishing assay cut points and detection limits.
• To present statistically sound methods for managing assay error rates.

Main Methods:

• Utilizing the Hubaux-Vos technique for calculating cut points and limits of detection from calibration curves.
• Employing receiver-operator characteristic (ROC) curves to manage Type I and Type II error rates.
• Illustrating potential false positives using Biacore methodology with a soluble receptor (sMUC18) and a therapeutic monoclonal antibody (mAb ABX-MA1).

Main Results:

• The Hubaux-Vos technique provides a statistically rigorous approach to defining assay detection capabilities.
• ROC curves effectively manage both false positive and false negative error rates in immunogenicity assays.
• Soluble receptors can lead to false positives in primary screening, highlighting the need for careful assay design.

Conclusions:

• A comprehensive approach considering both Type I and Type II errors is essential for adequate immunogenicity assay validation.
• Statistically rigorous methods like Hubaux-Vos and ROC curve analysis improve assay reliability.
• Careful experimental design, especially in confirmatory testing, is crucial to minimize both false positives and false negatives while maintaining detection limits.