AI in Organ Transplant Matching

In the United States, the Organ Procurement and Transplantation Network (OPTN) operates a national computerized network linking organ donors and transplant candidates. HRSA explains that matching considers factors such as blood type, body size, medical urgency, waiting time, and distance, with different rules by organ. A match run orders candidates under policy; transplant teams make clinical decisions and must evaluate whether an offered organ is suitable.

AI can support research into organ allocation, help estimate outcomes, or analyze policy effects, but it does not replace the current OPTN allocation policy. Matching is an ethical and operational process, not simply a prediction problem. Models must account for organ-specific compatibility, data quality, urgency, geography, and the consequences of changing priorities. A ranking that improves one metric may reduce access for another group.

Patients should understand that a place on a list or a model-generated estimate is not a guarantee of receiving a transplant. Allocation rules and organ availability change. Programs should monitor disparities and explain decisions using the applicable policy. Any AI used in allocation support needs transparent validation, human oversight, and governance consistent with federal requirements and OPTN policies. The offer process includes time-sensitive communication between organ procurement organizations and transplant programs. Candidates may be temporarily inactive or have organ-specific limitations, and policy contains detailed rules to handle these situations under policy.