GLOBAL CHALLENGES

Computer Algorithm Matches Kidney Donors with Those in Need

Rebecca Kutzer-Rice | Date: 11-23-10 | Comments

A newly developed computer algorithm is building a network of people in need of kidneys and potential donors. The technology could increase the number of kidney transplants, thereby saving thousands of lives per year.

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Computer Algorithm Matches Kidney Donors with Those in Need
By the end of 2009, there were over 86,000 people on the waitlist to receive a kidney donation. According to the Scientific Registry of Transplant Recipients, that waitlist has been increasing steadily each year, while the number of donors has remained relatively constant. Now, a computer algorithm developed by researchers at Carnegie Mellon University is matching transplant recipients with potential living donors. The technology, being used to create a national network, could save lives and lower the risks of organ rejection.

Kidneys for transplants can be either from living or deceased donors. Most people on the waitlist do not have compatible family members and are waiting for organs from deceased donors. But organs from living donors have higher success rates, since they are often closer matches to recipients' blood and tissue type, and the organs do not need to be transported over long distances.

Now, the Organ Procurement and Transplantation Network (OPTN), operated by the United Network for Organ Sharing (UNOS), is using a computer algorithm to match kidney recipients with potential donors. Using the technology, the OPTN has started a national pilot program to increase the number of kidney paired-donation (KPD) transplants.

Although the waitlist for kidneys continues to grow each year, the number of transplant surgeries has remained relatively constant (source: OPTN/SRTR).

Matching possible donors with recipients is a huge computational task. In 2006, the first algorithm that could successfully perform the equations on a nationwide scale�that is, with up to 10,000 pairs�was created by Tuomas Sandholm and Avrim Blum, both professors of Computer Science at Carnegie Mellon, and then-graduate student David J. Abraham. The algorithm has since been improved by Sandholm, with help from Ph.D. students Pranjal Awasthi, Erik Zawadzki and John Dickerson.

The main technological problem was computer memory, which could not handle the huge demand of the matching process. To circumvent this difficulty, the researchers' algorithm never records the entire process within the computer's memory. Instead, it only records those parts of the process that turn out to be relevant.

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