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Affymetrix Service Provider Expression Analysis Wants to Do Experiments for You


Like laundry and taxes, microarray experiments can sometimes be too trying to do by yourself. Enter Affymetrix service provider Expression Analysis (EA) of Durham, NC, which is building its business around what it sees as a growing demand to outsource microarray processing. The company takes researchersby the hand and performs every step for them, from experiment design and RNA sample prep, to advanced data mining.

“They ship the RNA to me, and then I sent them the resulting data on a CD-ROM,” said Steve Casey, EA’s chief operating officer. “But before the RNA is sent to us, we have in-depth conversations with our clients to understand where they are going with their experiments and help them design the most effective experiment with this technology.”

Last week, the emerging company landed a service contract with neighbor Duke University Medical Center, adding to its roster of approximately 20 customers. As part of this contract, EA has set up the EA Institute LLC, a division to exclusively service Duke. Holly Dressman, director of the Duke University Medical Center Microarray Facility, is overseeing the collaboration between Duke and the EA Institute.

This new contract comes out of EA’s intimate ties with the Duke medical center: Until recently, Casey served as a Howard Hughes Medical Institute administrator at the Duke campus.

“One of my responsibilities was finding a connection between us and array facilities,” Casey said. “Through casual conversations, it came to my attention that there was absolutely a shortage of resources to take advantage of the technology, and an absolute lack of a pure service provider.”

Core facilities, which have been playing the role of service provider, “aren’t geared up to do commercial work,” in Casey’s view. And while other companies do provide Affymetrix microarray processing, this is a “sideline” to their core business, he said.

So Casey shared his idea for a pure microarray service business with Don Holzworth, president and CEO of the privately-owned, Durham-based science and technology contract research company Analytical Sciences. Holzworth, who now serves as acting CEO of EA, gathered a core group of angel investors to raise about $1 million in startup financing for this venture and agreed to incubate EA at his company. Meanwhile, Casey arranged to get a license to use the technology from Affymetrix.

Since then, EA has dug into its Duke ties to enlist for its scientific advisory board three Duke researchers: Joseph Nevins, chairman of the Department of Genetics; Mike West, director of Duke’s Institute of Statistics and Decision Sciences; and Larry Katz, professor of neurobiology. Wing Wong, the Harvard School of Public Health biostatistician and microarray analysis expert, also serves on the board.

In its three months of operation, EA has been busy, according to Casey. The company, which has a staff of six not including administrative and financial support, can run about 60 to 70 arrays per week. Organizations with their own core facilities are using EA’s service due to their overflow needs, and a big chunk of EA’s business comes from the NIH. “NCI is a big user,” Casey said. Other individual users want to use Affymetrix arrays but cannot afford to invest in their own instrumentation platform. Still others, according to Casey, are attracted by the timeliness of EA’s array processing: The company guarantees it will complete the experiment and analysis within 15 days.

While it’s not cheap to use Affymetrix arrays, EA can offer small users the financial advantages of its bulk pricing plan, as well as its streamlined processing costs, said Holzworth. “The fact is that most core facilities don’t have a good grasp of what the actual costs are, and don’t take a lot of things into consideration that a commercial business would.”

On the bioinformatics end, EA is also working to develop expertise that many core facilities lack. The company uses a variety of programs, such as Wong’s d-chip, and employs algorithms such as principal components analysis, clustering, and singular value decomposition to “tease out the patterns and understand relationships in the data,” said Rich Cohn, director of statistical sciences at EA. The ultimate aim is to connect these relationships to a framework of biological relevance. Sometimes the analysis team will go back and look at the raw image rather than Affymetrix’s measures of expression, then generate its own measures of intensity and expression based on “other statistical models that researchers have developed,” Cohn said.

All this analysis is done in consultation with the client, based on the client’s needs, and may require several iterations to get right, Cohn said. EA also plans to release a set of analysis tools into the (already flooded) microarray marketplace in the coming months.

Though it is far too early to tell whether EA’s service model is a success, initial results are looking up. The company is expecting to have positive cash flow in the second quarter, and is busy doubling its capacity. “People are very pleased with the results,” said Casey. “It’s a tremendous opportunity.”


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