![]() Article from The New York Times, The Great American Kidney Swap "Directed by the algorithm, Broussard’s kidney ended up inside a complete stranger, a 26-year-old factory worker, Oswaldo Padilla, with a 6-year-old daughter, setting off the 12-person chain that included Kim and his sister and ended with an interior designer named Verle Breschini." Each chain starts with a completely altruistic donor, someone who expects nothing in return. In the case of the San Francisco chain, that person was Zully Broussard, a 55-year-old mental-health nurse who works in a prison. Broussard lost her 21-year-old son to bone-cartilage cancer in 2001. Then, in 2013, her husband died of colon cancer. “I know what it is to want an extra hour, an extra day, with someone you love,” she told me. Directed by the algorithm, Broussard’s kidney ended up inside a complete stranger, a 26-year-old factory worker, Oswaldo Padilla, with a 6-year-old daughter, setting off the 12-person chain that included Kim and his sister and ended with an interior designer named Verle Breschini. Economists call an arrangement like this a matching market. “It is not fundamental to economic theory to assume people are selfish,” Alvin E. Roth, an economist who teaches at Stanford University, told me. Roth won the Nobel Prize in economics in 2012 for his work using game theory to design matching markets, which pair unmatched things in mutually beneficial ways — students with public schools and doctors with hospitals. In such markets, money does not decide who gets what. Instead, these transactions are more akin to elaborate courtships. The classic example of a matching market is the college-admissions process. Every year, tens of thousands of students apply to Harvard University. But just because a student wants a spot in the freshman class and can afford tuition does not mean he gets in. Harvard must also want him to attend. In the case of kidney exchange, this matchmaking happens at a microcellular level. White blood cells contain genetic markers, proteins that help our immune systems distinguish between our bodies and foreign invaders. The more closely a transplant recipient’s genetic markers match a donor’s, the more likely the body is to adopt that foreign kidney as its own rather than attacking it. All these genetic variables mean that linking unrelated donors and recipients requires the kind of computational heft humans can’t manage with pen and paper. For example, BiologicTx currently has 72 people in a computer database waiting to give or receive a kidney. Run the software to find biologically compatible matches among those 72 people, and you get 105,716 possible configurations — some long chains, others short. Some people in the database have no possible matches. Others, genetically blessed, have thousands of potential matching options within the pool. The software ranks those possible pairings based on hundreds of different immunological, genetic and demographic criteria, while also aiming to create longer chains of harder-to-match people which will ultimately result in more transplants. Full story can be found here
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