title: Novel in silico technology in combination with microarrays: a state-of-the-art technology for allergy diagnosis and management?
abstract: 'Allergen microarrays, in poly-sensitized allergic patients, represent a real value added in the accurate IgE profiling and in the identification of allergen(s) to administer for an effective allergen immunotherapy.' Allergen microarrays (AMA) were developed in the early 2000s to improve the diagnostic pathway of patients with allergic reactions. Nowadays, AMA are constituted by more than 100 different components (either purified or recombinant), representing genuine and cross-reacting molecules from plants and animals. The cost of the procedure had suggested its use as third-level diagnostics (following in vivo- and in vitro-specific IgE tests) in poly-sensitized patients. The complexity of the interpretation had inspired the development of in silico technologies to help clinicians in their work. Both machine learning techniques and expert systems are now available. In particular, an expert system that has been recently developed not only identifies positive and negative components but also lists dangerous components and classifies patients based on their potential responsiveness to allergen immunotherapy, on the basis of published algorithms. For these characteristics, AMA represents the state-of-the-art technology for allergy diagnosis in poly-sensitized patients.
authors.affiliation: Allergy and Respiratory Diseases, Department of Internal Medicine, IRCCS S.Martino-IST-University of Genoa, Largo Rosanna Benzi 10,16132, Genova, Italy.
authors.forename: Giovanni
authors.initials: G
authors.lastname: Melioli
authors.forename: Giovanni
authors.initials: G
authors.lastname: Passalacqua
authors.forename: Giorgio W
authors.initials: GW
authors.lastname: Canonica
mesh_terms: D001185:Artificial Intelligence; D006801:Humans; D006967:Hypersensitivity / Q000175:diagnosis*; D046228:Microarray Analysis / Q000379:methods*
keywords: allergen; allergy; artificial intelligence; component; expert systems; laboratory test; microarray