Artificial intelligence in food allergy and drug allergy

Artificial intelligence revolutionizes food and drug allergy care. In food allergy, it predicts risks via microbiome/IgE data, diagnoses via multi-modal analytics, optimizes therapies (OIT), and manages allergens (biosensors, hypoallergenic products). For drug allergy, AI predicts hypersensitivity (β-lactam risk), diagnoses via EHR NLP, explores therapeutic targets, and streamlines management (ADR classification, anaphylaxis surveillance). Despite progress, gaps remain: underrepresented population models, immunocompromised diagnosis, and global data standardization. AI drives precision in allergy prediction, diagnosis, therapy, and management, but needs refinement to fully address clinical complexity. This review highlights how artificial intelligence is transforming the landscape of food and drug allergy research, from early risk prediction to personalized management, while also addressing the current limitations and future opportunities.