Ron Ranauro spent the better part of two decades in the computer industry, watching as the personal computer and the Internet transformed the business. It’s growing maturity coincided with early efforts to sequence the human genome, leading Ranauro in the late 1990s to apply his computing chops to the life science scene.

MassDevice spoke with Ranauro as GenomeQuest launched an application programming interface that allows developers to customize apps for their labs’ research programs. We asked him about the API, what sets his venture apart from other sequencing data management firms (hint: it’s in the clouds) and got his take on the ethical implications of widespread access to genome sequencing technology.

MassDevice: GenomeQuest announced the release of its API for sequence data management today. In layman’s terms, why is this an important step for genomics researchers?

Ron Ranauro: Pharmaceutical and biotech firms are interested in sequencing the genome of the organisms that they study. In the case of human health, it’s obviously human genomes, and they’re interested in measuring the response to their drugs. It’s the foundation of personalized medicine. What’s enabling this is the sequencing instruments themselves, the machinery that turns a biological sample into a computer file, in the past three years has undergone a dramatic transformation. What you can do for $10,000 today is produce something on the order of 10,000 to 100,000 times more data for the same investment. In computer industry terms, that had taken 30 or 40 years, for computers to go through that much acceleration and miniaturization. So you’re seeing Moore’s Law now hitting life science.

Where we play in the value chain is once that data’s been generated, it’s an enormous file that makes no sense to anybody until you run it through a software program. Basically we distill that knowledge and refine it into something more informative. That’s the basic value proposition, managing that data and delivering it into information and letting the end user take it into knowledge.

The API is so important because any research lab has a number of end user consumers, but also they’re supported by a developer community who writes specific applciations that are unique to that lab. Now with the API, we’re able to engage the developers target market, so developers can use our platform to build their own apps. It really unlocks the market.

MassDevice: Can you give us a primer on GenomeQuest’s SDM platform? How is it different from other sequence data management offerings?

RR: The big differentiator is, first of all, our platform was built from the beginning to be aware of cloud computing models as a basic computational paradigm. What I mean by that is our system is highly parallel, which means it can scale; as the data sets get larger there are no bottlenecks. So scalability was a big driver of our technology and what really separates us. Having the foresight to build a distributed application formed the basis of our technology. Cloud computing is really becoming a trend in pharma and biotech, so we’re kind of catching that wave as this data generation is getting cheaper and cheaper by the day.

The scalability enables ease of use and enables the ability to ask questions you might not have anticipated before you generated the data, all kinds of interesting creative outputs that aren’t always visible before you get into it.

MassDevice: How did you personally come to be involved in the software side of genomics?

RR: I’m more or less a product of the computer industry. I worked in the mini-computer business back in the ’80s at Data General, and then got involved in electronic design automation software in the late ’80s and early ’90s, during kind of a renaissance period in that industry, really driving the Internet and what we’re see today in hand-held computing.

In the late ’90s I had a business that was building grid computing networks in the design automation industry. At about that time the Human Genome Project was getting into full gear, coincident with the Internet explosion. That got me into the life science domain. I’ve been applying my expertise building businesses and software models in the genomics domain for a little more than a decade now.

MassDevice: Where do you see the next big advance in genomics?

RR: I think were in a phase now sort of like where we were in the early ’90s with the Internet. In the early ’90s there were a lot of firms that did searching of the Internet, but no one really distanced themselves because the number of users of the Internet and the number of websites that there were to index weren’t really at a critical mass. I think over the next three to five years we’ll have a critical mass of publicly sequenced human genome data to use as a reference for privately sequenced human genome data. We will be seeing pharmaceutical businesses looking to optimize their clinical trials by stratifying their patients and trying to weed out non-responders or patients that might experience toxic side effects. I think it’ll be a gradual but inexorable move.

MassDevice: How cheap will personal genome sequencing have to become before it sees widespread adoptions? And what are the ethical implications of that? Are we ready to handle wide-spread access to that knowledge?

RR: Great question. I’m not an ethicist, I’m a businessman, but we are playing in the space so I have to pay attention to it and think about it.

The information is going to be available. Right now, to do the sequencing and get the genome data out, if you read the instrument vendors they say they can do it now for about $10,000, which is down buy a factor of 10 in 18 to 24 months. That doesn’t really pay for analysis and making sense of the data, so just the data generation is coming down and is sort of already in range where the pharmaceuticals can consider it for looking at their patients in clinical trials. That’s partly because you don’t have to sequence the whole genome; typically a therapy is only targeting a small number of genes implicated in the pathway, so the price is almost already at that place.

From the point of view of when will payers think its better to reimburse for having their patients get their genomes sequenced, people have put the $1,000 number out there as the magic number. And again, it’s within sight if you just focus on the data generation. It’s the data analysis, which is actually where we play, where maybe the bigger problems lie and where we can make the biggest contribution.

So having said all that, what do I think of the ethical implications of it? Clearly it’s a problem if your genome sequence is predicting that you’re predisposed for a disease and an insurance company gets wind of that. You may become uninsurable. Those are huge questions for the policy makers. I think we’ll sort that out, exactly how that’s done. I think people are entitled to know about their genome. More information is always better than less, and I think that’s going to continue unabated.

As we get more genomes, the actual statistics will change. So if you go to 23andMe today and it says you have a 17 percent chance of getting early-onset Alzheimer’s, well first of all 17 percent isn’t very satisfying. What does that mean? So you might make some lifestyle changes here and there, but we might found out after 100,000 genomes or a million genomes that 17 percent isn’t the number. The numbers are going to change over time, so it might be suspect for an insurance company or a payer or anybody to make really big decisions until we have a lot of data, and that’s probably a decade or more away.