Big Data-Driven Evolution of a Diagnostic Multiplex IgE-Test: Enhancing Accuracy and Efficacy in Allergy Diagnostics

Area of Science:

• Allergy diagnostics
• Immunology
• Bioinformatics

Background:

• The ALEX²-test is a multiplex IgE assay detecting IgE to 178 allergens and 117 extracts.
• Real-world data from over 90 countries are stored on a GDPR-compliant server for surveillance and support.
• Continuous improvement is essential for diagnostic test panels.

Purpose of the Study:

• To update the ALEX² allergen panel to ALEX³ for improved global exposome coverage and diagnostic sensitivity.
• To refine the multiplex IgE assay based on extensive real-world data analysis and scientific literature.

Main Methods:

• Analysis of nearly 400,000 ALEX² test results to understand allergen prevalence, IgE levels, extract coverage, and co-reactivity.
• Selection of new allergens based on scientific literature and clinical studies.
• Discontinuation of low-prevalence or redundant allergens and extracts.

Main Results:

• The ALEX³ panel includes 218 allergens and 82 extracts, featuring 52 new allergens.
• New allergens include cyclophilins, alpha-gal, and markers for respiratory and food allergies.
• The update reflects a data-driven strategy for enhancing diagnostic capabilities.

Conclusions:

• The transition from ALEX² to ALEX³ demonstrates a targeted, data-driven improvement of a diagnostic IgE-macroarray.
• This enhancement aims to provide more comprehensive and sensitive allergy diagnostics.
• The updated panel expands coverage of allergens and improves diagnostic accuracy.