that a Big Pharma company might have 200 people highly skilled at bioinformatics, and several thousand biologists, so the average queries would pile up and get stale. Since researchers had to send an e-mail with a query and then wait for weeks to get an answer, they often didn’t bother to ask questions in the first place, Akhtari says.
“We noticed this created quite a bottleneck,” Akhtari says. “We wanted to change the dynamic, so any researcher or doctor could go to NextBio, form a query, and get their results right away.”
Of course, this is easier said than done. Real work had to be done to bring together and process the raw data from a number of public repositories. This involved a lot of indexing and semantic tagging to help people tap into correlations that would otherwise be missed.
Making the public data really useful and “normalized” is part of the challenge, since different sequencing machines create different sets of data, and different statistical analyses. But the real edge is in taking that cleaned up public data and marrying it with the unpublished, private data that Big Pharma companies have, Akhtari says.
“The core of the platform is the content, based on public data that’s normalized and in a useful format. That is the yin, but the yang comes from clients’ data,” Akhtari says. “The major pharma companies have a ton of internal data that they never publish. They have large volumes of genomics data, and they can pump all of it into NextBio and correlate it with public content.”
NextBio had to spend a lot of time, and $20 million of investors’ money, building up the capacity to merge this data. The model is essentially software-as-a-service. NextBio has its own secure servers that support the data, and the company provides customers with a secure login and password they use to access their data over the web. The customer agrees to send its data through an FTP connection, where it gets combined with the publicly available data, so the NextBio “correlation engine” can do its job. NextBio doesn’t say how much it charges for access to this data pool, but it has “several multi-million dollar deals” with Big Pharma customers and offers academic researchers a discount, Akhtari says.
So far, NextBio has built up an impressive list of customers. The group includes Merck, Johnson & Johnson, and Pfizer, as well as academic leaders like The Scripps Research Institute, Stanford University, and the Sanford-Burnham Medical Research Institute.
There are still some small bioinformatics companies out there, and lots of academic research groups that write their own specialized “home brew” bioinformatics software. Much of that work goes on “upstream,” doing the primary, secondary, and tertiary analysis of raw data that needs to happen before NextBio does its thing, Akhtari says. Even at the point where NextBio’s service enters the equation, it’s competing against what customers try to develop internally. Apparently, though, that doesn’t concern Akhtari very much.
“A lot of firms have developed internal tools with chicken wire and duct tape primarily for the bioinformatics experts,” Akhtari says. “We have no head-to-head competitors.”
The market for computational analysis of genomic data is still small, of course, but the potential over time could run “into the billions,” Akhtari says. Already, sophisticated cancer research centers like Stanford are seeking to stratify patients into certain groups, with treatment that’s tailored to their individual tumor types, based on looking at the activity of thousands of genes, not just one. Over time, more drugs like Roche’s trastuzumab (Herceptin) will be developed with a companion diagnostic that determines which patients are likely to respond, and which won’t. Someone will need to provide IT to help crunch data for all these experiments that are bound to be run, he says.
When it happens, Akhtari wants to be one of those key behind-the-scenes players making it happen. If that comes to pass, there will probably be some new buzzword people use to describe what NextBio does.
“Our goal is to expand into clinical applications, it’s really exciting,” Akhtari says. “That’s my dream, to see genomics really bring about preventive, personalized medicine.”
