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In June, at the Association for Computing Machinery’s Conference on Electronic Commerce in San Diego, Calif., the University team presented a working version of the algorithm with enough computational power to analyze as many as 10,000 patient-donor pairs. The software has been in use at the Alliance for Paired Donation since February.

Every two weeks, patient data from the alliance’s 56 transplant programs in 20 states is aggregated by Jonathan Kopke from the Institute for the Study of Health at the University of Cincinnati. Kopke, who developed the alliance’s Web-based software, e-mails this data to Abraham. After just a few seconds of processing, Abraham’s computer identifies potential exchanges among two, three, and four sets of donor-patient pairs. The software also factors altruistic donors into its calculations. The good Samaritans do not have patients associated with them, so their donations could trigger domino effects—like transplant cascades that continue ad infinitum—as long as no donor in a chain backs out.

Matt Jones set in motion the first such chain this summer, after the algorithm matched him with Barb Bunnell. Then it paired Barb’s husband, Ron, with Angie Heckman. Angie’s mother is next in line waiting for her match.

Jones’ good will received national media attention, piquing the interest of another 100 potential altruistic donors who contacted the Alliance for Paired Donation to express their desire to share a kidney.

“If we could turn each of those 100 kidneys into chains of 10, as long as no one cheats, we would get 1,000 people transplanted, and if we can make chains of 100, we could eventually get 10,000 people transplanted,” Rees says. “And Tuomas’ software is definitely a key part of making this happen.”

Perhaps more importantly, the algorithm also overcomes the technological barrier to forming a unified national kidney exchange, which ideally would be managed by UNOS, Rees says. “Now it’s more of a political problem. We just need to get everyone to play in the same sandbox, and that is no easy feat because everyone thinks they have the best way to do it.”

The high stakes of the work hasn’t escaped this team of computer scientists more used to dealing with theory and abstraction than real-world matters of life and death. “At first, it made us very nervous to do the match runs,” Abraham says. “In the back of your head, you are always worried there might be a bug in the software or something you overlooked.”

They have now developed a verification technique that ensures the accuracy of the results.

The reward of helping to orchestrate lifesaving miracles far outweighs the anxiety associated with such responsibility. “Medical doctors get used to saving lives—they do it all the time,” Sandholm says. “But for a computer scientist to be saving lives, that’s really fantastic.”

Barb Bunnell is one of those lives. Minutes after transplant surgeons pull Matt Jones’ kidney through a hole near his navel, they sew the healthy organ to the inside of Bunnell’s right pelvis. Soon afterward, the kidney begins the vital work of removing waste products from her bloodstream, taking over for her failing renal system. Several months later, Bunnell is almost recovered from the operation—and hopefully spared the future ravages of her illness, with a chance to watch her three grandchildren grow to have children of their own.

As an enduring reminder of his gift, Jones bears a J-shaped scar on his abdomen. Otherwise, life continues more or less as usual. He is back to school, working long hours for his rental car company and planning his wedding. He says the profound bond he formed with the Bunnells will last a lifetime. All three hope they become links in a chain of life that lasts even longer.

Jennifer Bails is a freelance writer and a former award-winning newspaper reporter.

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