It’s getting cheaper by the day to sequence the entire string of 6 billion chemical units of DNA that make up an individual human being. Yesterday, Complete Genomics of Mountain View, CA unveiled plans for what amounts to a democratization of genomics. It will offer a service to sequence full human genomes for just $5,000, beginning in the second quarter of 2009.
At Xconomy, we normally focus on companies based in Boston, Seattle, and San Diego, but we couldn’t resist digging into this one, because it has multiple connections to our network cities. Complete Genomics raised its seed capital in 2006 from OVP Venture Partners in Kirkland, WA, and Enterprise Partners in San Diego. It also counts a pair of Xconomists, Leroy Hood of the Institute for Systems Biology in Seattle, and George Church of Harvard Medical School, as scientific advisers.
So we tracked down OVP managing director (and Xconomist) Chad Waite to find out why he decided to invest in this technology versus all the other sophisticated instruments made by companies like Applied Biosystems, Illumina, 454 Life Sciences, and Helicos Biosciences. (He proudly pointed out that his Harvard Business School connection to CEO Clifford Reid gave him the inside track on this investment, and he invited Drew Senyei of Enterprise in on the action, but more on that later.)
It turns out Waite was sold on Complete Genomics because it has a fundamentally different vision of the market from its rivals. Instead of trying to sell a machine to pharmaceutical companies and top academic labs for hundreds of thousands of dollars, Complete Genomics plans to keep the work in-house on its own proprietary machines and offer sequencing as a service. The company plans to open 10 sequencing centers around the world over the next five years, with the capacity to sequence 1 million complete human genomes. It will have enough bandwidth to sequence an entire genome for $5,000 in about four days, compared with $100,000 and six weeks to six months on currently marketed instruments, Waite says.
“We’re disruptive on technology, and on the business model,” Waite continues. “We’re not going out and trying to sell million-dollar machines. Is there really a competitive advantage for a pharmaceutical company to have the machine? The advantage for them is in the data. They want the data.”
So how might that be really useful for companies or academics? At that high speed and low price, it’s conceivable that drug companies will want to sequence every patient who enters a clinical trial to provide clues as to why some patients respond differently than others to experimental drugs, Waite says. Or, they might want to run big experiments that compare the genomes of 1,000 patients with diabetes to 1,000 other people as healthy controls, to look for tiny genetic variations that might offer clues. They could look at a bunch of prostate cancer tumor samples to try to find genomic markers that explain why the disease spreads more quickly in some people than in others, Waite says.
These concepts are truly mind-boggling when you look at the recent history of
