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Ideas 2003: Big gene machine

Ideas 2003: Big gene machine

Eugene Chan gave up a promising medical career for the capricious future of a biotech startup.

Five years ago, when Eugene Chan, then 24, announced that he was dropping out of Harvard Medical School to pursue the lodestar of faster, more powerful DNA analysis, friends and family asked, "Eugene, are you crazy?"

Chan was giving up a promising medical career for the capricious future of a biotech startup. And who knew if the idea he carried around in his head -- that a machine could mimic nature's own method of instantaneous DNA replication -- would ever translate into a workable technology.

Chan knew. Early this year, Chan's now 45-employee company, US Genomics, will begin selling the GeneEngine, a device that can analyze 200,000 base pairs of DNA in seconds and thus "read" as many as 10 million base pairs of DNA a day. That's a quantum leap over existing sequencing technologies that permit researchers to scan a mere 500,000 base pairs per day by breaking the DNA down into small chunks. The GeneEngine, essentially a nanochip hooked up to a supercomputer, scans strands of DNA in a linear fashion, like a ticker tape, with no limit on the size of DNA that can be read in each run.

The ramifications of more rapid DNA analysis are enormous. According to Robert Langer, a professor of chemical and biomedical engineering at MIT who was among the first to hear Chan's idea, it will bring scientists that much closer to the Holy Grail: a detailed understanding of diseases such as diabetes and cancer caused by the interaction of a number of genes. And that, in turn, should lead to the tailoring of more effective medicines for patients based on their individual genomic information.

It was that potential that beguiled the young Chan as he pondered his future. "If I had stayed in medical school, this never would have happened," says Chan, sprawled in jeans and a blue polo shirt on a chair in his company's nondescript office, squirreled away in the back of a Woburn, Mass., office park.

Chan has never been the type to sit and wait for destiny. As a high school sophomore growing up in a small town 15 miles from Morristown, N.J., he began reading books on physics even before he took the required course in school. He fell in love with the challenge of solving problems and soon started winning statewide physics contests against students who had taken college-level courses. That taught him that one didn't always have to follow a well-marked road to achieve success. It was possible to improvise.

"I was one of those people who never turned up in class, but I always aced the test," says Chan with a matter-of-fact certitude that somehow avoids boastfulness.

Chan's impatience with the established order of things would haunt him when he dropped out of medical school and began looking for the financing to pursue his idea. "Obtaining venture capital was a huge barrier because I was competing against people with advanced degrees," Chan admits. But with the help of connections he had made at MIT (while in the joint Health Science Harvard and MIT program), Chan got enough funding to at least try to prove that his concept could work. His success, he recalls, had a lot to do with his knowledge of physics and his ability to use mathematical algorithms to illustrate the feasibility of mimicking nature's trick.

And sure enough, six months later, Chan showed the scientific world that tightly coiled strands of DNA could indeed be unrolled and read in a linear fashion. It took the next four years to build a device that worked. Chan and his colleagues at US Genomics painstakingly constructed a nanochip containing microscopic "obstacles" (much like the pins in a pinball machine) that are 10,000 times smaller than the width of a human hair and can unfurl DNA. The linear DNA is then read by microscopic lasers.

Biotech hotshots like Craig Venter (president of the first company to map an entire human genome) sit on the board of US Genomics, and the company has so far been funded to the tune of US$25 million. All because an impatient 24-year-old with a knack for problem-solving trusted what he knew he knew.

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