Digital Immunology: Integrating AI into Immune Profiling
DOI:
https://doi.org/10.61424/w3zt6493Keywords:
Artficial intelligence; Digital immunology; Immune analysis; Precision immunology; Multi-omic; Digital pathology; Immunotherapy; Precision medicineAbstract
As the rapid expansion of immunological data with diverse modalities in both dimensions through high throughput sequencing, single-cell technology, spatial omics, digital pathology and immunogenomics, immune profiling has emerged as a data-rich science that heavily relies on computational approaches as well as multi-dimensional multi-modal data integration to extract meaningful biological knowledge. Artificial intelligence (AI) has become one of the most powerful approaches in the integration and interpretation of these multi-dimensional data for complex immune heterogeneity, biomarker discovery, disease classification and therapy prediction. Here, we review the applications of AI in the evolution of digital immunology and translate how AI integrates with immune profiling. The paper also discusses the data-driven AI-powered frameworks used for immune cell profiling and multimodal integration for immune classification. Last but not least, the clinical implementations of AI-assisted immune profiling in various fields such as cancer, autoimmunity, transplantation, allergy and clinic immunology as well as the emerging digital immune twins are discussed. Challenges and limitations in AI-assisted immune profiling, such as need for standardized datasets, model transparency, interoperability, clinical validation and ethical concerns, are systematically discussed. Our findings highlight that the future of AI-powered immune profiling has positively contributed to the advance of digital immunology, thus fulfilling its promise in personalized immune diagnosis and therapy.
References
Abuhassan, Q., Al-Ameer, H. J., Balogh, Z., Rekha, M. M., Sahoo, S., Bavanilatha, M., & Khazratov, A. (2026). Digital immune twins and ai-integrated multi-omic biomarkers: Redefining personalized immunotherapy in non-small cell lung cancer. Iranian Journal of Basic Medical Sciences, 29(5), 688.
Adenike, A. (2025). Artificial Intelligence (AI)-Driven Fraud Detection in Commercial Banking: Outcomes From Central Bank Of Nigeria (CBN) Regulatory Sandbox in Global Fintech Context Including Us Federal Reserve Pilots. Stout in Business and Management, 1(1), 80-89. https://doi.org/10.61424/5ff9ce53
Alshorman, J., Mehran, M. J., Bahrami, Y., Mohammadzadeh, S., Barzigar, R., Morshedi, M., & Wang, Y. (2026). Artificial intelligence in immunotherapy: revolutionizing diagnostic and therapeutic applications in cancer and autoimmune diseases. Clinical and Experimental Medicine, 26(1), 185.
Atsaves, V., Lekakis, L., Feretzaki, M., Leventaki, V., Liakou, C., Drakos, E. & others, (2009). JunB oncogenic activity in anaplastic large cell lymphoma. Laboratory Investigation, 89, p.254A.
Bilal, M., Nimir, M., Snead, D., Taylor, G. S., & Rajpoot, N. (2023). Role of AI and digital pathology for colorectal immuno-oncology. British journal of cancer, 128(1), 3-11.
Chang, L., Liu, J., Zhu, J., Guo, S., Wang, Y., Zhou, Z., & Wei, X. (2025). Advancing precision medicine: the transformative role of artificial intelligence in immunogenomics, radiomics, and pathomics for biomarker discovery and immunotherapy optimization. Cancer Biology & Medicine, 22(1), 33-47.
Chen, Y. M., Hsiao, T. H., Lin, C. H., & Fann, Y. C. (2025). Unlocking precision medicine: clinical applications of integrating health records, genetics, and immunology through artificial intelligence. Journal of Biomedical Science, 32(1), 16.
Curion, F., & Theis, F. J. (2024). Machine learning integrative approaches to advance computational immunology. Genome Medicine, 16(1), 80.
Dhar, S. (2025). Advances in clinical immunology. Prem J Immunol, 2, 100004.
Dratva, L. M., Teichmann, S. A., & Kretschmer, L. (2026). Decoding Human T Cell Immunity with Artificial Intelligence and Single-Cell Genomics. Annual Review of Immunology, 44(1), 381-405.
Elshikh, M.S., Alwahibi, M.S., Alexiou, A., Papadakis, M. & others, (2024). Soil pollution: an agricultural and environmental problem with nanotechnological remediation opportunities and challenges. Discover [Journal Name]. Springer.
Farzan, R. (2024). Artificial intelligence in Immuno-genetics. Bioinformation, 20(1), 29.
Gkagkaris, L., Papadakis, M. & others, (2022). The revolutionary Gustav Adolf Neuber: a tribute to the father of aseptic surgery. Surgical [Journal Name]. Sage Journals.
Gogali, F., Paterakis, G., Rasidakis, G., Kaltsas, G., Gousis, P., Neonakis, E. & others, (2011). T regulatory lymphocytes (Tregs) and NK cell interaction in thyroid papillary cancer (PTC): immunotherapy perspectives. Basic & Clinical Pharmacology & Toxicology, 109, p.29.
Goktas, P., & Damadoglu, E. (2025). Future of allergy and immunology: is artificial intelligence the key in the digital era?. Annals of Allergy, Asthma & Immunology, 134(4), 396-407.
Huss, R., Raffler, J., & Märkl, B. (2023). Artificial intelligence and digital biomarker in precision pathology guiding immune therapy selection and precision oncology. Cancer Reports, 6(7), e1796.
Jariwala, M. (2025). Ai-driven decision support systems for immunological disorders: Bridging big data, omics, and precision medicine. In AI-Assisted Computational Approaches for Immunological Disorders (pp. 353-392). IGI Global Scientific Publishing.
Kitonakis, N. & Kontis, A., (2008). The determinants of Greek foreign direct investments in Southeast European countries. Southeast European and Black Sea Studies, Taylor & Francis.
Koelzer, V. H., Sirinukunwattana, K., Rittscher, J., & Mertz, K. D. (2019). Precision immunoprofiling by image analysis and artificial intelligence. Virchows Archiv, 474(4), 511-522.
Kumar, R. M. H. (2024). AI-augmented immuno-oncology: Foundation models for predicting immune response, resistance, and precision immunotherapy. Power System Protection and Control, 52(2), 193-208.
Lei, Y., & Tsang, J. S. (2025). Systems human immunology and AI: Immune setpoint and immune health. Annual Review of Immunology, 43(1), 693-722.
Lei, Y., & Tsang, J. S. (2025). Systems human immunology and AI: Immune setpoint and immune health. Annual Review of Immunology, 43(1), 693-722.
Liakou, A.I., Arabatzi, K., Liakou, C.I. & Theodorakis, M.J. (2008) Impact of obesity on cytokine secretion patterns following an oral glucose tolerance test in individuals with normal glucose tolerance, Review of Clinical Pharmacology and Pharmacokinetics - International Edition.
Liakou, A.I., Arabatzi, K., Liakou, C.I. & Theodorakis, M.J., (2008). Impact of obesity on cytokine secretion patterns following an oral glucose tolerance test in individuals with normal glucose tolerance. Review of Clinical Pharmacology and Pharmacokinetics - International Edition.
Liakou, A.I., Liakou, C.I. & Zouboulis, C.C., (2012). Acne and nutrition. Handbook of Diet, Nutrition and the Skin, pp.413-422.
Liakou, C.I. and Plytas, M. (2025) Patient access to high-risk devices for unmet medical needs, International Journal of Engineering Technology and Research Management, 9(3), pp. 41–46. Available at: https://ijetrm.com/issues/files/Mar-2025-07-1741357556-MAR06.pdf.
Liakou, C.I., Papadakis, M. and Plytas, M. (2025) Clinical evaluation of immunotherapy vaccines as medical devices: Regulatory challenges and assessment strategies, International Journal of Engineering Technology and Research Management, 9(3), pp. 32–31. Available at: https://ijetrm.com/issues/files/Mar-2025-07-1741355709-MAR04.pdf.
Liakou, C.I., Papadakis, M. and Plytas, M. (2025) The challenges for manufacturers of the increased clinical evaluation requirements under the European Union medical device regulations, International Journal of Engineering Technology and Research Management, 9(3), pp. 32–40. Available at: https://ijetrm.com/issues/files/Mar-2025-07-1741356854-MAR05.pdf.
Negut, I., & Visan, A. I. (2025). AI-Enhanced Diagnosis for Immunological Disorders. In AI-Assisted Computational Approaches for Immunological Disorders (pp. 63-106). IGI Global Scientific Publishing.
Papadakis, M., Rahmanian-Schwarz, A. & others, (2017). Negative-pressure wound therapy and early pedicle flap reconstruction of the chest wall after epirubicin extravasation. The Journal of [Journal Name]. Sage Journals.
Ravi, N., Tye, G. J., Dhaliwal, S. S., Musa, M. Y., Wong, M. T. J., & Lai, N. S. (2025). Immune profiling in oncology: bridging the gap between technology and treatment. Medical Oncology, 42(10), 446.
Rigamonti, A., Viatore, M., Polidori, R., Rahal, D., Erreni, M., Fumagalli, M. R., & Marchesi, F. (2024). Integrating AI-Powered digital pathology and imaging mass cytometry identifies key classifiers of tumor cells, stroma, and immune cells in Non–Small cell lung Cancer. Cancer Research, 84(7), 1165-1177.
Saboor, M., Haque, S., Farhana, A., Papadakis, M. & others, (2024). Natural products in the management of neurodegenerative diseases. Nutrition & [Journal Name]. Springer.
Sergeevna, K. T. (2022). Dynamic valuation models for tokenized economies. Актуальные исследования, 42.
Sharma, P., Liakou, C., Kamat, A., Chen, H., Ng Tang, D., Sun, J., Troncoso, P. & others, (2008). Immunological impact of anti-CTLA4 therapy in a neoadjuvant setting. Cancer Immunity, 8(Suppl_1).
Sharma, P., Liakou, C., Kamat, A., Chen, H., Ng Tang, D., Sun, J., Troncoso, P., et al. (2008) Immunological impact of anti-CTLA4 therapy in a neoadjuvant setting, Cancer Immunity, 8(Suppl_1).
Sharma, P., Liakou, C., Kamat, A., Tang, D.N., Chen, H., Sun, J., Troncoso, P. & others, (2008). CTLA-4 blockade increases interferon-gamma-producing CD4 (+) ICOS (HI) cells to shift the ratio of effector to regulatory T cells in cancer patients. Journal of Immunotherapy, 31(9), p.960.
Shen, Z., Brand, D., Simard, M., Levine, A. P., Hindocha, S., Mistry, T., & Collins-Fekete, C. A. (2025). AI-powered immune profiling from histopathology slides for chemo-radiotherapy outcome prediction in rectal cancer: a study using clinical trial and real-world cohorts. EBioMedicine, 122.
Shin, E., Song, E. Y., Kang, E. S., & Nam, M. (2026). Advances in HLA and Non-HLA Immune Profiling: Integrating Next-Generation Sequencing and Artificial Intelligence in Transplantation. Annals of Laboratory Medicine, 46(4), 362.
Sideris, A.C., Tsakiris, S., Messari, I., Liakou, C.I. & Carageorgiou, H. (2008) Effects of rivastigmine plus selegiline [(-) deprenyl)] on brain enzymes, antioxidant status and learning performance of aged rats, Review of Clinical Pharmacology and Pharmacokinetics - International Edition.
Sklavounos, D., Edoh, A. & Plytas, M., (2017). A statistical approach based on EWMA and CUSUM control charts for R2L intrusion detection. 2017 Cybersecurity and Cyberforensics Conference (CCC), pp.25-30.
Sonmez, G., Yazarkan, Y., & Cagdas, D. (2026). The digital keystone: how artificial intelligence is reshaping HLA research and clinical practice. Immunogenetics, 78(1), 6.
Stensballe, A. (2026). Toward Precision Health in Autoimmunity and Immune-Related Adverse Events: The Autoantibody Reactome, Spatial Omics, and Multimodal Data Integration. Biomedicines, 14(5), 1129.
Stensballe, A. (2026). Toward Precision Health in Autoimmunity and Immune-Related Adverse Events: The Autoantibody Reactome, Spatial Omics, and Multimodal Data Integration. Biomedicines, 14(5), 1129.
Tsagkaris, C., Papadakis, M. & others, (2023). Is it about time to develop social surgery? American Journal of Surgery. [online] Available at: [Accessed 9 Mar. 2025].
Tzamaria, M., Liakou, C. & Papadakis, M. (2025) CTLA-4 Treatment in Pancreatic Cancer, International Journal of Advanced Research in Engineering, Science & Management, 13(3), pp. 2826-2833. Available at: https://www.ijaresm.com/volume-13/issue-3-march-2025.
Xu, Y., Su, G. H., Ma, D., Xiao, Y., Shao, Z. M., & Jiang, Y. Z. (2021). Technological advances in cancer immunity: from immunogenomics to single-cell analysis and artificial intelligence. Signal Transduction and Targeted Therapy, 6(1), 312.
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Copyright (c) 2026 Chrysoula I. Liakou, Marios Papadakis, Markos Plytas (Author)
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