AAAAI 2026 at a Glance
Get ready for AAAAI 2026. LucidQuest’s preview brings together the most relevant scientific and AI-driven advances in Allergy, Asthma and Immunology research, helping you focus on high-impact sessions and plan a clear, insight-driven agenda.
📅 Build your schedule around the topics that matter most.
📥 Download the AAAAI 2026_Preview_by_LucidQuest
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Key Topics from AAAAI 2026 Scientific Presentations
Asthma
Adherence-led biologics and tezepelumab personalization, guided by eosinophils/IgE, are set to improve control, cut exacerbations, and enable remission.
Atopic Dermatitis & Skin Barrier
Pediatric AD studies link microbiome imbalance (Staphylococcus-dominant lesions) to disease, while roflumilast cream is projected to sustain vIGA-AD 0/1 in 55%+ at week 52.
Chronic Rhinosinusitis & Upper Airway Disease
Dupilumab is expected to boost productivity and outperform omalizumab, with tezepelumab, verekitug, and depemokimab improving polyp scores, congestion, and surgery avoidance.
Eosinophilic, Mast Cell & Primary Immunodeficiency Disorders
Dupilumab will show sustained pediatric EoE symptom and histology gains, while bezuclastinib is anticipated to reduce NonAdvSM burden, GI symptoms, and bone complications.
Food Allergy, Anaphylaxis & Allergen Immunotherapy
Culinary-STEM education and milk-focused FEDs are set to drive pediatric EoC remission, alongside OIT desensitization and preferred needle-free epinephrine.
Urticaria & Hereditary Angioedema
Biologics and oral options (dupilumab, sebetralstat, donidalorsen, deucrictibant) are projected to improve QoL and lower HAE attack frequency, with SEP-631 exploring mast-cell modulation.
Artificial Intelligence and Machine Learning at AAAAI 2026
Epitope-Specific PN-OIT Models
IMPACT-trial ML predicts desensitization and remission, AUC 0.78 and 0.84, to guide patient selection.
Real-Time Pollen Monitoring
AI-based pollen identification reaches 96.1% accuracy, enabling scalable, near-real-time alerts for allergic airway disease management.
Food Allergy Q&A Bots
ChatGPT-like systems will answer food-allergy questions with higher-quality responses than allergists, achieving DISCERN 4.5.
Asthma Admissions Forecasting
ML combining Google search and environmental data predicts pediatric asthma admissions with F1 0.779, supporting hospital preparedness.
Atopic Dermatitis Digital Biomarkers
AI mines 47,000 patient posts to track emotional and clinical change, enabling personalized AD management signals.
Allergy Challenge Risk Prediction
ML uses sIgE plus clinical features to predict systemic reactions during oral food challenges, refining decision-making.
Food Allergy Biomarker Discovery
ML/DL boosts diagnostic accuracy by 10–15%, potentially reducing reliance on oral food challenges and skin-prick tests.
📅 Build your schedule around the sessions that matter most.
📥 Download the AAAAI 2026_Preview_by_LucidQuest
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