Sergey Brin’s Search for a Parkinson’s Cure

After discovering that he held the LRRK2 mutation on his twelfth chromosome (indicating that his lifetime risk of developing Parkinson’s disease is 30-75% rather than the typical 1%), Google co-founder Sergey Brin became one of the first philanthropists to fund research into a disease based on the results of a genetic test.

In Thomas Goetz’s comprehensive profile of Brin and his fight against Parkinson’s disease and Parkinson’s science, we are shown how Sergey Brin wants to change how disease research is conducted:

Most Parkinson’s research, like much of medical research, relies on the classic scientific method: hypothesis, analysis, peer review, publication. Brin proposes a different approach, one driven by computational muscle and staggeringly large data sets. It’s a method that draws on his algorithmic sensibility—and Google’s storied faith in computing power—with the aim of accelerating the pace and increasing the potential of scientific research. “Generally the pace of medical research is glacial compared to what I’m used to in the Internet,” Brin says. “We could be looking lots of places and collecting lots of information. And if we see a pattern, that could lead somewhere.’ […]

In Brin’s way of thinking, each of our lives is a potential contribution to scientific insight. We all go about our days, making choices, eating things, taking medications, doing things—generating what is inelegantly called data exhaust. A century ago, of course, it would have been impossible to actually capture this information, particularly without a specific hypothesis to guide a researcher in what to look for. Not so today. With contemporary computing power, that data can be tracked and analyzed. “Any experience that we have or drug that we may take, all those things are individual pieces of information,” Brin says. “Individually, they’re worthless, they’re anecdotal. But taken together they can be very powerful.” […]

“Even if any given individual’s information is not of that great quality, the quantity can make a big difference. Patterns can emerge.” […]

This is what Jim Gray, the late Microsoft researcher and computer scientist, called the fourth paradigm of science, the inevitable evolution away from hypothesis and toward patterns. Gray predicted that an “exaflood” of data would overwhelm scientists in all disciplines, unless they reconceived their notion of the scientific process and applied massive computing tools to engage with the data. “The world of science has changed,” Gray said in a 2007 speech–from now on, the data would come first.

The profile is notable for other reasons, too–particularly in showing how Brin has dealt with learning of his high risk of developing Parkinson’s in a very calculated way and how the idea that one’s genetic information is “toxic knowledge” is becoming a dated one.

I was also intrigued to learn that this proposed method of science–large-scale personal tracking to create huge data sets in order to discover possible meaningful associations–is very similar to the topic of Brin’s unfinished Stanford PhD.