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Silicon Genetics Alums Launch NextBio to Simplify Integration, Querying for End-User Biologists

NextBio, a Cupertino, Calif.-based startup founded in 2004, this week launched its first product – a system for integrating information from public resources with experimental data generated in customer labs.
According to company officials, the system, called the NextBio platform, differs from previous bioinformatics data-integration platforms in an important area: its emphasis is on usability.
NextBio co-founders Saeid Akhtari and Ilya Kupershmidt formed the company after their former firm, Silicon Genetics, was acquired by Agilent Technologies in 2004.
Akhtari, NextBio’s president and CEO, was CEO of Silicon Genetics, while Kupershmidt, NextBio’s vice president of product management, was Silicon’s director of professional services.
Akhtari told BioInform that after the acquisition, he and Kupershmidt “decided to take a whole new approach in the space.” He said one thing they had noticed at Silicon Genetics, as well as other firms in the bioinformatics sector “was that the tools that people typically use to better understand the data are only used by a small number of people.”
Most bioinformatics tools are “just too difficult to use, too difficult to learn,” he said.
The NextBio platform is built upon a database of integrated public domain data that is “designed to make it very easy to connect diverse pieces of information, even though originally they were designed for completely different studies, different projects, different organisms,” Kupershmidt said.
This database serves as a baseline for customers to view and analyze their own data. The system is designed “to pull in the key most important study results, and they get correlated to all other pieces of information,” Kupershmidt said. “Once the data gets integrated into our system, any scientist in any part of the enterprise is able to easily find the link to that data and also correlate his study to the data that was just uploaded”.
Another component of the platform, Kupershmidt said, is the ability to perform “search-engine-like” queries. “You can go into our system, type in your question, and in one go search and correlate hundreds of diverse studies, hundreds of diverse data sets,” he said.
Kupershmidt emphasized that NextBio is not competing with LIMS vendors or bioinformatics analysis packages because the platform doesn’t work with raw data. “We’re focusing on data that has been processed by experts, by statisticians, by computational biologists. We believe there are plenty of great solutions for dealing with raw data, and we don’t want to recreate that paradigm,” he said.
Akhtari said that the company released a beta version of the system to a handful of early-access customers earlier this year. These customers include Scripps Florida, the University of California Davis, Stanford University, Princeton University, Yale University, the University of Florida, the Institute for Systems Biology, Genentech, the Burnham Institute, and Pioneer Hi-Bred International.
Early users appear to be pleased. Nick Tsinoremas, senior director of informatics at Scripps Florida, told BioInform that his group is using NextBio to store all of its microarray data.

Most bioinformatics tools are “just too difficult to use, too difficult to learn.”

Scripps researchers use the system to compare the results of their experiments to other experiments conducted within Scripps as well as data from the public domain, Tsinoremas said. One immediate benefit of the platform, he noted, is that it frees up his bioinformatics team to work on new problems, rather than spending most of its time downloading, reformatting, and comparing multiple microarray datasets on a “one-by-one” basis.
“So far, there is no other system out there that allows us to do that,” he said.
Mostafa Ronaghi, principal investigator at Stanford University, recently told BioInform’s sister publication Genome Technology that his group uses NextBio to help validate its microarray experiments. “We start with importing our dataset into the NextBio system and then immediately we can compare our dataset with a large number of studies available there,” he said. “The cool thing here is that suddenly we can put our work in the context of what other people have done.”
The system isn’t limited to microarray data, according to Kupershmidt, who noted that it was designed for “anything that generates information in large numbers,” including protein expression, RNAi, and high-throughput screening data.
NextBio currently employs around 20 people. The firm raised a round of Series A funding in 2004, and was recently awarded a $157,299 Small Business Innovation Research grant from the National Institute for General Medical Sciences for a project titled, “Cross-species meta-analysis tool for high-throughput genomic research.” [BioInform 09-26-06
The company sees a broad potential customer base for the system. While NextBio expects the platform to initially appeal to bench biologists, the firm eventually hopes to capture chemists and then clinicians – a potential “multi-billion dollar market,” Akhtari said.
In line with its goal of moving the platform closer to the clinic, Akhtari said that NextBio has a collaboration with the Stanford University School of Medicine to integrate patient data into the system. He declined to provide further details on that effort, however.
“We want to finish the job before blowing our horn,” he said.

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