Spiral Genetics: clarifying the gene pool

Knowledge of human genes and their role in driving diseases has become increasingly important in the development of personalised medicines. Genetic sequencing has come on leaps and bounds since the international Human Genome Project (HGP) was completed in 2003—after 13 years and three billion base pairs it had succeeded, two years ahead of schedule, in identifying every gene in the human genome for study.

There are two parts of genetic analysis, explains Adina Mangubat, chief executive of Spiral Genetics, which provides software packages for genetic analysis, or next generation sequencing.

The first part of the analysis is the chemistry phase, the second is computational. In the chemistry phase of the sequencing process, instead of ‘reading’ the three billion base pairs that make up the human genome from beginning to end as was done in the HGP, which is not particularly efficient, the string of information is broken down into 100 base pair-long chunks to make the analysis more manageable.

The sequencer yields thousands of text files, albeit with no way of knowing where each part of the genome came from.

Spiral Genetics provides the computational side of the analysis. Using a set of algorithms and computational methods it can reassemble the genome and compare it to others to find out what the genetic variations are. The information yielded can assist in the development of personalised medicines—treatments tailored to individual patients.

Spiral Genetics and the industry

“Historically our service has been used by a lot of academic laboratories, individual researchers at universities and academic research institutions that are trying to conduct basic research, trying to find out what are the genes that are causing autism or breast cancer, for example,” says Mangubat.

She adds that core laboratories, or outsourcing laboratories, are increasingly using the Spiral Genetics system. Are pharmaceutical companies getting in on the act?

“To be totally honest, at this point, pharmaceutical companies are only starting to dip their toes into next generation sequencing,” Mangubat says.

“If you look at the historical adoption patterns for any genetic technology, because there are ways to look at DNA before next generation sequencing, the progression always goes from academic institutions to core laboratories or clinical laboratories to pharmaceutical companies. It’s always that progression,” she explains.

Biofuel and agriculture

While Mangubat recognises the importance of developing personalised medicines, she encourages people to consider agriculture and plant genomics, explaining that next generation sequencing can play a significant role in developing these industries.

By using the information gleaned from sequencing plant genomes, it is possible to improve crop production and develop biofuel, a sustainable alternative to fossil fuels. Certain strains of algae and the oil seed plant jatropha have been shown to produce biofuels: “If you can sequence all of these strains of all of these different plant species, you can figure out which ones produce the most oil and why, which will help people produce biofuel in a much more efficient way,” Mangubat says.

IP

Spiral Genetics has a number of pending patents, and trade secrets that are being converted into patents as they ‘mature’. There are many innovations Spiral Genetics could patent, Mangubat says, though most efforts are based around the computational methods that facilitate Spiral’s rapid genome analysis.

“We can analyse a whole human genome, from the raw data that comes off the sequencer to getting the list of genetic variants, in three hours, which compared to other groups is really fast,” she says. By quickly processing the data as it emerges from the chemistry phase of analysis, scientists can avoid data backlog, she adds.

Speed and efficiency: the algorithms

Spiral Genetics’ computational methods for manipulating data during genetic analysis ‘plug in’ to its underlying distributed computing framework. To analyse the raw data, Spiral makes use of open source, peerreviewed algorithms which it puts on top of the patented framework to accelerate how fast they work.

The company hasn’t in-licensed any IP, nor licensed its own patents to others: “It’s not really part of our strategy right now, though it could be in the future,” she says.

“It’s not something that we’ll ever rule out but it’s not something we’re actively pursuing.”

She describes the Spiral Genetics IP portfolio as a “smattering”—some patents were filed around the time the company was established in 2009 and others more recently. There are currently three patents and others pending.

“There’s some prior art, for sure, but it’s been good in terms of being able to get a strong foothold in a pretty defensible place.”

As next generation sequencing, or bioinformatics, is a fairly new field, patenting Spiral Genetics’ creations has been largely painless. “There’s some prior art, for sure, but it’s been good in terms of being able to get a strong foothold in a pretty defensible place on the patent side of things,” Mangubat says.

“We were essentially taking two technologies that have never really met each other before—when you marry those two you get technologies that people didn’t think of before so it’s been pretty good so far.”

The bioinformatics industry has changed dramatically since the company’s establishment, and the cost of sequencing has dropped significantly, Mangubat says. “Back when we started the company, the chemistry was at a much younger stage of development so to analyse a whole human genome sequence, just the chemistry stage would have $100,000 worth of chemical costs and about 30 days of chemical churning and processing just to get the raw data.

“Now with the new genome DNA sequencer you can do it in a day and it costs $2,000 to $3,000.”

Unsurprisingly, this fall in costs has opened the market, so how is Spiral Genetics using its IP strategy to stay ahead?

“By trying to offer the fastest and most accurate product possible,” Mangubat says.

The company continues to innovate on the computational process, and is developing new algorithms to use with the existing framework that allow for greater accuracy and allow researchers to see genetic variants that they perhaps hadn’t seen before.

Spiral Genetics’ use of peer-reviewed algorithms, as opposed to proprietary algorithms, may also give the company an edge. Scientists would prefer to use peer-reviewed algorithms so they know exactly what’s happening to their data, Mangubat explains.

“Scientists are really not fans of black boxes,” she says.

“They want to know what the inner workings are like, so being able to guarantee that what is happening to their data is known and has been reviewed by their peers, and being able to accelerate it, is really important.”

Myriad

In June this year the US Supreme Court ruled that human genes are no longer patenteligible. As a company whose bread and butter is supplying researchers lists of genetic variants with a view to creating personalised medicines, has it been affected by the ruling in any way?

“It hasn’t had an impact on us yet, but I think that it will in terms of new players in the market,” Mangubat says.

“As with many things, the Myriad ruling is a double-edged sword. The great thing about it is that all of a sudden many of the genes discovered to be highly correlated with particular diseases can now be tested for without licensing.”

She predicts “an explosion” of new diagnostic companies that will drive down the price of diagnostics for the consumer, and turn it into a process that is no longer only available to the very rich.

She says the ruling brings Spiral Genetics potential new customers too, although there is a downside. “As genes aren’t patentable any more, it really demotivates a lot of the corporate investment in research on these particular genetic markers because it’s really hard to monetise if everyone has access to it.”

She says that most of the genetic discovery is now in the hands of the academic researchers.

“They’re the groups that have done a lot on discovery in the past,” she says. “It really doesn’t make much sense for a company that’s for profit to try and do that research because there’s no guarantee of return on their investment.”

The future

With the industry evolving so rapidly, it isn’t easy to predict what direction Spiral will take next. Mangubat thinks that in 15 years’ time, everybody may have their gene sequence in their medical records, and personalised medicine will have taken off.

However, regulatory measures will always lag behind scientific innovation, she says, which could hinder progress in the industry. Striking a balance between ensuring people’s personal data is not compromised, or used maliciously, while allowing a certain degree of openness to allow for research will be challenging, though it could determine the shape of the industry and how it evolves.

The Health Insurance Portability and Accountability Act (HIPAA), which came into force in the US in 1996, allows for the protection of patient data, while the Genetic Informational Nondiscrimination Act, passed by US Congress in 2008, ensures that genetic information may not be used for discriminatory purposes—for example, by insurance companies looking for reasons not to cover an individual.

Mangubat says there are still some grey areas, however. “If you are a research subject—a participant in a research study—your data, as you’re not technically a patient, doesn’t technically fall under the jurisdiction of HIPAA. You are not guaranteed to be protected in the same way that you would be if you were a patient.”

Realistically, all genetic data will eventually be found to be identifying data and will therefore fall under the HIPAA jurisdiction, she says. “Because what is more identifiable than the code of who you are?”