Cost of Gene Sequencing Falls, Raising Hopes for Medical Advances
In Silicon Valley, the line between computing and biology has begun to blur in a way that could have enormous consequences for human longevity.
Bill Banyai, an optical physicist at Complete Genomics, has helped make that happen. When he began developing a gene sequencing machine, he relied heavily on his background at two computer networking start-up companies. His digital expertise was essential in designing a factory that automated and greatly lowered the cost of mapping the three billion base pairs that form the human genome.
The promise is that low-cost gene sequencing will lead to a new era of personalized medicine, yielding new approaches for treating cancers and other serious diseases. The arrival of such cures has been glacial, however, although the human genome was originally sequenced more than a decade ago.
Now that is changing, in large part because of the same semiconductor industry manufacturing trends that opened up consumer devices like the PC and the smartphone: exponential increases in processing power and transistor density are accompanied by costs that fall at an accelerating rate.
As a result, both new understanding and new medicines will arrive at a quickening pace, according to the biologists and computer scientists.
“For all of human history, humans have not had the readout of the software that makes them alive,” said Larry Smarr, director of the California Institute of Telecommunications and Information Technology, a research center that is jointly operated by the University of California, San Diego, and the University of California, Irvine, who is a member of the Complete Genomics scientific advisory board. “Once you make the transition from a data poor to data rich environment, everything changes.”
Complete Genomics, based in Mountain View, is one of more than three dozen firms hastening to push the cost of sequencing an entire human genome below $1,000. The challenge is part biology, part chemistry, part computing, and in Complete Genomics’ case, part computer networking.
Complete Genomics is a classic Silicon Valley start-up story. Even the gene sequencing machines, which are housed in a 4,000-square-foot room bathed in an eerie blue light, appear more like a traditional data center than a biology lab.
In 2005 ,when Clifford Reid, a successful Silicon Valley software entrepreneur, began to assemble his team, he approached Dr. Banyai and asked if he was interested in joining a gene sequencing start-up. Dr. Reid, who was also trained in physics and math, had spent a year as an entrepreneur-in-residence at the Massachusetts Institute of Technology, where he had become a convert to bioinformatics, the application of computer science and information technologies to biology and medicine.
Dr. Banyai had even less experience in biology.
Formerly with the Internet networking start-ups GlimmerGlass and Silicon Light Machines, he in turn began by reading a pioneering 2005 article in the journal Science in which a group of researchers in George Church’s genetics laboratory at Harvard describe a new technique intended to speed gene sequencing.
Today Dr. Banyai is finishing the second generation of a machine that blends robotics, chemistry, optics and computing. It is emblematic of the serendipitous changes that take place when a manufacturing process is transformed: performance increases and cost falls at an accelerating rate.
“Genomes are now being sequenced incredibly cheaply,” said Russ B. Altman, who is a founder of Personalis, a start-up based in Palo Alto, Calif., that is developing software to interpret genomes. “On the discovery and science side we will be able to do clinical trials. We’ll be able to check the entire genome.”
Recently, on the company’s Web site, Dr. Reid predicted that the cost of gene sequencing could eventually be as low as that of a blood test: “I believe that the impact on the medical community of whole human genome sequencing at a cost comparable to a comprehensive blood test will be profound, and it will raise a host of public policy issues (privacy, security, disclosure, reimbursement, interpretation, counseling, etc.), all important topics for future discussions,” he wrote.