(Page 2 of 2)
get themselves in trouble focusing too much on how they’re going to exit a business,” he says. “If we take care of our customers and take care of each other, and really do this well and really ramp this company, we’ll have all kinds of opportunities for realizing the value of [it].”
Should such opportunities ultimately present themselves, it would serve as validation for an idea that began at Harvard, where two students at Harvard Business School—Eric Boutin and Paris Wallace—worked with scientists at the lab of genetics professor George Church to find a way to use next-generation sequencing to support a profitable business model.
The group decided on carrier testing—screening people’s genes for disease-causing mutations that could be passed along to their children. For recessive genetic disorders such as Tay-Sachs disease and cystic fibrosis, it’s possible to have such a mutation and not even know it, but if two carriers of the same mutation have a baby together there’s a one-in-four chance the child will get two copies of the mutation—and so, the disease itself.
Carrier testing has been around a long time, and it is a crowded market containing heavyweights such as LabCorp (NASDAQ: LH), Quest Diagnostics (NYSE: DGX), and others. But by pairing a next-generation sequencing system with a vast library of genetic and health information, Good Start believes that it has created a product that stands out. According to Hardison, Good Start’s system can efficiently run several patient samples on a sequencer at once, and can provide more detailed and accurate results than the competition, while charging the same price.
Hardison explains, for example, that in a typical screening test for cystic fibrosis, a pre-programmed chip or array will look for a specific set of mutations in a gene associated with the disease.
“But if it’s something outside [that set of] of mutations, it won’t be able to see them because the chip hasn’t been built to do that,” Hardison says.
Good Start’s selling point is that its system allows researchers to look at the entire gene and report on anything abnormal. The company claims on its website, for example, that its test can detect roughly 550 mutations for cystic fibrosis, while other tests can detect about 100.
Good Start used its initial round of cash to set up an array of tests to prove that the process worked and that its computer systems could handle the depth of information it was providing, putting studies together and presenting them at industry meetings such as the American Society for Reproductive Medicine’s annual gathering in 2011. It also explored ways to perform tests that the market was demanding but that weren’t commercially available at the time. By the time September 2012 rolled around, Good Start had tests for 23 genetic diseases—among them cystic fibrosis, fragile X syndrome, and spinal muscular atrophy.
By posting a comment, you agree to our terms and conditions.