Allergen Immunotherapy (AIT) represents one of the pillars in the treatment of allergic diseases. AIT is the only therapeutic strategy with curative potential, promoting the reduction of drug use and long-term symptom control even after the end of the treatment. The European Academy of Allergy, Asthma and Immunology (EAACI) guidelines, position papers of World Allergy Organization (WAO), and the US Practice Parameters are the leading official documents that set scientific standard for the use of AIT in the world. The use of AIT in Brazil has specific regional conditions due to the pattern of allergen sensitization, as well as genetic, socioeconomic, and cultural characteristics, climate conditions, and the availability of allergenic extracts. The most prevalent house dust mites are Dermatophagoides pteronyssinus, Dermatophagoides farinae and their allergens have the highest clinical relevance. Blomia tropicalis is also very frequent. This position paper has been prepared by the Brazilian Association of Allergy and Clinical Immunology (ASBAI) Taskforce on AIT for respiratory allergy and Hymenoptera venom allergy.

Artificial and augmented intelligence (AI) and machine learning (ML) methods are expanding into the health care space. Big data are increasingly used in patient care applications, diagnostics, and treatment decisions in allergy and immunology. How these technologies will be evaluated, approved, and assessed for their impact is an important consideration for researchers and practitioners alike. With the potential of ML, deep learning, natural language processing, and other assistive methods to redefine health care usage, a scaffold for the impact of AI technology on research and patient care in allergy and immunology is needed. An American Academy of Asthma Allergy and Immunology Health Information Technology and Education subcommittee workgroup was convened to perform a scoping review of AI within health care as well as the specialty of allergy and immunology to address impacts on allergy and immunology practice and research as well as potential challenges including education, AI governance, ethical and equity considerations, and potential opportunities for the specialty. There are numerous potential clinical applications of AI in allergy and immunology that range from disease diagnosis to multidimensional data reduction in electronic health records or immunologic datasets. For appropriate application and interpretation of AI, specialists should be involved in the design, validation, and implementation of AI in allergy and immunology. Challenges include incorporation of data science and bioinformatics into training of future allergists-immunologists.

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Sofia
Journal Co-ordinator
Journal of Medical Research and Health Education