Current perspectives and challenges of using artificial intelligence in immunodeficiencies - 03/10/25

Doi : 10.1016/j.jaci.2025.06.015

Jacques G. Rivière, MD, MSc ^a,^b,^c,^d, Roser Cantenys-Saba, MSc ^e,^f, Gerard Carot-Sans, PhD ^e,^f, Jordi Piera-Jiménez, PhD ^e,^f, Manish J. Butte, MD, PhD ^g,^h,ⁱ, Pere Soler-Palacín, MD, PhD ^a,^b,^c,^d,^⁎ , Xiao P. Peng, MD, PhD ^j,^k,^l,^⁎

^a Universitat Autònoma de Barcelona, Barcelona, Spain

^b Infection and Immunity in Pediatric Patients Research Group, Vall d’Hebron Institut de Recerca, Barcelona, Spain

^c Pediatric Infectious Diseases and Immunodeficiencies Unit, Hospital Infantil i de La Dona Vall d’Hebron, Vall d’Hebron Barcelona Hospital Campus, Barcelona, Spain

^d Jeffrey Modell Diagnostic and Research Center for Primary Immunodeficiencies, Barcelona, Spain

^e Catalan Health Service, Barcelona, Spain

^f Digitalization for the Sustainability of the Healthcare System (DS3) Research Group, Barcelona, Spain

^g Division of Immunology, Allergy, and Rheumatology, Department of Pediatrics, University of California, Los Angeles, Calif

^h Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Calif

ⁱ Department of Human Genetics, University of California, Los Angeles, Calif

^j Division of Pediatric Genetic Medicine, Department of Pediatrics, Children’s Hospital at Montefiore, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY

^k Department of Genetics, Albert Einstein College of Medicine, Bronx, NY

^l New York Center for RDs, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY

^∗ Corresponding authors: Pere Soler-Palacín, MD, PhD, Medical School, M Building, Universitat Autònoma de Barcelona, Av de Can Domènech, 08193, Bellaterra, Barcelona, Catalonia, Spain. Medical School, M Building, Universitat Autònoma de Barcelona Av de Can Domènech, 08193, Bellaterra Barcelona Catalonia Spain ^∗ Xiao P. Peng, MD, PhD, 3411 Wayne Ave, Room 904, Bronx, NY 10467. 3411 Wayne Ave, Room 904 Bronx NY 10467

Abstract

The rapid growth of artificial intelligence (AI) in health care is promising for screening and early diagnosis in settings that heavily rely on professional expertise, such as rare diseases like inborn errors of immunity (IEI). However, the development of AI algorithms for IEI and other rare diseases faces important challenges such as dataset sizes, availability and harmonization. Similarly, the implementation of AI-based strategies for screening and diagnosis of IEI in real-world scenarios is hampered by multiple factors including stakeholders’ acceptance, ethical and legal constraints, and technologic barriers. Consequently, while the body of literature on AI-based solutions for early diagnosis of IEI continues to expand, clinical utility and widespread implementation remain limited. In this review, we provide an up-to-date comprehensive review of current applications and challenges facing AI use for IEI diagnosis and care.

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Key words : Artificial intelligence, machine learning, inborn errors of immunity, primary immunodeficiency, secondary immunodeficiency, predictive modeling, genomics, electronic health records, clinical decision support, implementation science, screening algorithm

Abbreviations used : AI, CNN, EHR, IEI, ML, RD, SID

Plan

Clinically facing applications of AI use in immunodeficiencies

Screening and identification of individuals with immunodeficiencies

Examples from other rare disease domains

Molecular diagnostic applications of AI use in immunodeficiencies

AI use for rare genetic disease diagnoses

Current AI applications in genomic data processing and analysis

Implementation challenges

Implementation gap

Regulation in AI development and implementation

Stakeholder barriers

Data integration and harmonization

Future directions

Emerging applications based on generative approaches

Technologic evolution for AI implementation

Conclusions

	The first 2 authors contributed equally to this article, and both should be considered first author. The last 2 authors contributed equally to this article, and both should be considered senior author.
	This article is part of a special issue entitled: Artificial Intelligence (AI) in Allergy/Immunology published in the Journal of Allergy and Clinical Immunology .

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Vol 156 - N° 4

P. 878-888 - octobre 2025 Retour au numéro

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Current perspectives and challenges of using artificial intelligence in immunodeficiencies - 03/10/25

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