Implementing digital twin technology in organ transplantation: Concepts, emerging evidence, and clinical translation pathways

Digital twins are emerging as transformative tools in modern healthcare, representing a paradigm shift toward precision medicine by offering living, data-driven computational replicas of patients or organs that evolve with real-time information. As solutions to the growing demand for personalised, precision-based therapeutic approaches, digital twins play a particularly significant role in transplantation, which is characterised by its data-rich care pathway, time-critical decisions, and complex lifelong immunologic management, making it an ideal environment for precision medicine applications. This narrative review examines how digital twins are being conceptualised and applied across the entire transplant lifecycle, from donor assessment and organ preservation through to operative planning, immunosuppression management, and long-term surveillance, while proposing a pragmatic roadmap for clinical translation. We conducted targeted literature searches between June and October 2025, focusing on digital twin applications in transplantation, machine perfusion technologies, precision immunosuppression dosing, immune modelling, and virtual organ systems. We prioritised scoping reviews, mechanistic studies, clinical investigations, and authoritative technology sources. Foundational applications include liver virtual twins for living donor transplantation, data streams from normothermic machine perfusion platforms enabling organ quality assessment, model-informed precision dosing systems for tacrolimus approaching closed-loop control, and conceptual immune system twins for rejection risk prediction. Evidence ranges from mechanistic simulations and preprints to early clinical pharmacokinetic and pharmacodynamic studies, though rigorous prospective validation remains limited. Digital twins hold substantial promise for augmenting transplant decisions throughout the clinical pathway, but require rigorous validation, interoperable data infrastructure, and governance frameworks aligned with safety and equity principles before widespread adoption.