{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T15:19:35Z","timestamp":1787757575715,"version":"build-2784847793"},"reference-count":60,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T00:00:00Z","timestamp":1787702400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T00:00:00Z","timestamp":1787702400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Xenotransplantation"],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Xenotransplantation represents a potential solution to the persistent global organ shortage, yet its clinical application remains stalled by complex immunologic responses, coagulation dysregulation, species\u2010specific biology, and infectious risks. Artificial intelligence (AI) could enhance safety, accelerate decision\u2010making, and enable precision medicine initiatives within this rapidly evolving field. However, effective implementation of AI in xenotransplantation requires approaches specifically adapted to the biological and operational complexities of cross\u2010species transplantation. Here, we present our suggestion of a prioritized roadmap for integrating AI into early clinical xenotransplantation, based on clinical need, data availability, technical readiness, feasibility of clinician\u2010supervised implementation, and potential impact on graft assessment and safety monitoring. Priority domains include digital pathology and imaging, machine perfusion\u2013based viability monitoring, multimodal and multi\u2010omics detection of graft injury and rejection, and surveillance for potential xenozoonotic infections. One of the essential prerequisites to ensure the development of reliable AI in xenotransplantation is to develop standardized definitions of xenograft injury phenotypes and ground truth datasets, which in this emerging field are currently lacking. The limitations to the application of AI in xenotransplantation, which include the lack of clinical data, species\u2010specific differences, and delays in annotations and regulations, can be addressed via data sharing, federated learning, fairness, and validation. By combining gene\u2010edited donors and refined immunosuppression regimens with clinically supervised, auditable, and transplant\u2010specific, AI\u2010based support systems, xenotransplantation could be made safer and more reproducible in the clinical arena.<\/jats:p>","DOI":"10.1111\/xen.70162","type":"journal-article","created":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T14:32:29Z","timestamp":1787754749000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Artificial Intelligence in Xenotransplantation: A Prioritized Roadmap for Early Clinical Translation, Opportunities and Challenges"],"prefix":"10.1111","volume":"33","author":[{"given":"Kasra","family":"Shirini","sequence":"first","affiliation":[{"name":"Department of Surgery Johns Hopkins University School of Medicine  Baltimore Maryland USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zoe","family":"Hahn","sequence":"additional","affiliation":[{"name":"Department of Surgery Johns Hopkins University School of Medicine  Baltimore Maryland USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joseph M.","family":"Ladowski","sequence":"additional","affiliation":[{"name":"Department of Surgery Duke University School of Medicine  Durham North Carolina USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexander","family":"Schulick","sequence":"additional","affiliation":[{"name":"Department of Surgery Johns Hopkins University School of Medicine  Baltimore Maryland USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saghar","family":"Babadi","sequence":"additional","affiliation":[{"name":"Department of Surgery Johns Hopkins University School of Medicine  Baltimore Maryland USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexandre","family":"Loupy","sequence":"additional","affiliation":[{"name":"Paris Institute for Transplantation and Organ Regeneration (PITOR) Universit\u00e9 Paris Cit\u00e9 PARCC INSERM  Paris France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kazuhiko","family":"Yamada","sequence":"additional","affiliation":[{"name":"Department of Surgery Johns Hopkins University School of Medicine  Baltimore Maryland USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9050-0436","authenticated-orcid":false,"given":"Raphael P. 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