Domitilla Del Vecchio: Finding a Link Between Car Accidents and Cancer
WHY YOU SHOULD CARE
This MIT engineer’s research could save lives by making 2-ton cars and tiny cells smarter.
By Melissa Pandika
Perhaps you’ve been there. You’re gliding through an intersection when, in the corner of your eye, a truck approaches, apparently oblivious to his red light. And now comes the instant, ugly choice — slam on the brakes and risk swerving into another lane, or push ahead and hope for the best.
Or does it have to work that way?
Deep in the basement of MIT’s Stata Center, in New England, sits a slight Italian woman who lost her own father in a car accident — and now has her hands on an algorithm that would avoid collisions, possibly putting Google’s own automated car system to shame. Meet engineer Domitilla Del Vecchio, who, by the way, is also conducting research that could one day allow us to detect and prevent cancer with innovations like glow-in-the-dark cells.
Engineered cells — that was what fascinated me.
— Domitilla del Vecchio, MIT
Cancer and car crashes have much more in common than you might think, and Del Vecchio, who works in systems and synthetic biology, can see this better than almost anyone else. For her, it has to do with the way individual units — whether cars at an intersection or the biological parts within a cell — communicate with one another, and what they do in response. Imagine if certain cells could detect cancer in their brethren cells — and secrete chemotherapy drugs when they did. Or if your car could communicate with that truck driver’s, so you’d know whether to push ahead or swerve. Your vehicles would dance through the intersection in seamless choreography.
With a National Science Foundation Career Award, a Nature Biotechnology paper and more under her belt, 39-year-old Del Vecchio is a pretty big name in both synthetic biology and control systems research, said Chris Myers, a mechanical engineer and bioengineer at the University of Utah. And she’s done what many early-career researchers wouldn’t dare do. Rather than sticking to her expertise — intelligent transportation systems — she started a second research group, in synthetic biology; if she had failed to publish solid research from both groups, she could have been denied tenure.
Del Vecchio has slightly frizzy, chestnut hair, a rigid nose and a penchant for collared shirts and sweaters. She lives in Somerville, a Boston suburb, but grew up in the sun-drenched hills outside Rome, where she tinkered with Legos and watched her father work in his engineering lab, entranced by its rows of brightly colored resistors and capacitors. He died in a car accident when Del Vecchio was 10, a tragedy that directs her research today.
She’s built an algorithm based on models that predict human driving behavior, allowing a car to maneuver itself to prevent a crash.
Del Vecchio earned a Ph.D. in control and dynamical systems at Caltech, where a bioengineering course sparked the idea of applying her engineering knowledge to cells. “Engineered cells — that was what fascinated me,” she says in her Italian-inflected staccato. In 2006, fresh out of grad school, Del Vecchio began an intelligent transportation systems lab while also collaborating with biologists at the University of Michigan. Four years later, she accepted a faculty position at MIT, where she continued her intelligent transportation systems research and started a biological circuits lab.
Del Vecchio is designing a semi-autonomous car system for the next few decades, when people will still drive themselves. It works like a “silent supervisor” — one that’s driver-controlled but intervenes when necessary. A fully autonomous car, like Google’s, runs completely on its own. But Del Vecchio’s algorithms for avoiding collisions could one day be built into driverless systems, too. So far, she’s built an algorithm based on models that predict human driving behavior, allowing a car to maneuver itself when necessary to prevent a crash. It enabled two Toyotas approaching an intersection to communicate wirelessly and cooperate.
That could offer an advantage over Google’s system, which uses only sensors to read its environment. Not only are the sensors pricey, relying only on them might also make a car drive too conservatively. For example, a Google car would probably come to a complete stop to avoid an oncoming vehicle — possibly endangering nearby cars. Automobiles relying on Del Vecchio’s wireless-based system, on the other hand, could coordinate maneuvers around each other. (When asked how its system compared to Del Vecchio’s, Google declined to comment.)
Using this strategy to build biological circuits is somewhat trickier — biological systems are more complex. Biological circuits in cells use signaling molecules to communicate, but as soon as one circuit loses a signaling molecule, it behaves differently than when it’s not communicating. So the entire circuit malfunctions. That’s one reason that scientists have been able to make biological circuits out of only a few parts. Del Vecchio’s solution? A device that churns out signaling molecules. It could enable scientists to build circuits that are much larger and complex — and possibly able to fight cancer.
Of course, it’ll be several years before biological circuits appear in the clinic. Today’s circuits are crude and finicky. Traditionally trained biologists are skeptical of them and synthetic biology in general; the field has generated little original research, not quite living up to media hype, Myers said. For Del Vecchio, who says she likes to test “the limits of what technology can do,” the challenge is part of the fun. “Only when you understand natural systems can you engineer them.”
Photography by Rachel Tine for OZY
- Melissa Pandika Contact Melissa Pandika