By John Russell
March 10, 2010 | Working in 2010, it is easy to forget the bumpy road first travelled by microarray technology to win respect. In 2001--when Expression Analysis (EA) was formed--the hopes for microarray technology were high but so was skepticism. Steve McPhail, EA’s CEO, remembers the rugged road well.
“Most of the articles you saw back in the 2002-2003 time frame were of the ilk that you could not compare microarray data on different platforms, moreover you couldn’t compare data generated on the same platform in different facilities because of protocol differences, and further you couldn’t compare data generated in the same facility over time because of the variability of data sets,” he says.
“We thought that was pretty silly and that if it were the case then we should shoot the technology in the head and move on to something better. So we set out to prove that the data was indeed comparable.” No doubt much work was still needed to develop microarray standards, and EA was in the thick of those efforts, for example, serving on the MicroArray Quality Control Consortium (MQCC).
Pioneers are famously bloodied by volleys of arrows from naysayers and inevitable missteps, but they also often garner reputation-building firsts, of which EA has several including being the first to submit microarray data to FDA electronically (2003).
There were also speed bumps. EA was formed as a spinout of the Duke University core microarray facility, which was originally supported by the Howard Hughes Medical Institute. When HHMI decided to get out of this kind of activity, “we kept Duke as our first client. We felt like the company would be able to apply this model other academic institutions and that failed miserably for a variety of reasons,” says McPhail.
Today EA is flourishing. Diligent work with standards groups, an early adopter attitude, and a vigorous added push into non-academic markets has helped EA become a leader in offering genomics services. Through 2005, EA offered only Affymetrix expression profiling arrays. In late 2005 the company began to offer genotyping services and early 2007 acquired a variety of different platforms from Applied Biosystems (Now part of Life Technologies) as well illumina core array technology.
Since then, EA has added next generation sequencing. The goal is not to compete with the likes of Complete Genomics and genome centers that are very interested in doing whole genome sequencing, says McPhail.
“We’re much more interested in candidate gene resequencing. We feel this fits our business model very well since we do a lot of genome wide association (GWA) studies that identify areas of linkage disequilibrium that may be associated with a disease process or a trait. Genome enrichment and candidate gene re-sequencing in a next generation sequencer allows us to really dig into those areas to try to get to the biology of the trait and the causal variant faster than we’ve been able to accomplish before.“
Looking back at genomics services’ early rocky road, McPhail says EA started to see market attitudes change as well as its own fortune around early 2004, which was when EA struck its first contract with a pharmaceutical company, Wyeth. “[That] was to generate genomic data for their clinical trials which they hoped would help them understand efficacy and really be able to understand which patients in these studies would benefit from their therapeutics.”
Between 2005 and 2008, says McPhail, the MQCC generated data “that said yes indeed these, platforms are comparable and here’s a control data set that you can use to normalize datasets over time. Now the entire market has evolved.”
EA recognized the importance of informatics early on, says McPhail: clients would send in 40 or 50 samples, EA would send back the data, “and it would take them a year to analyze the data.” EA hired its first Ph.D. bioinformaticist in 2002.
“We decided it was probably in our best interest to get someone that could help provide them [clients] a data set that was more actionable. Since then our bioinformatics team has become expert in analysis of expression profiling data sets of genotyping data sets and of next generation sequencing data sets,” he says.
Over the next 18 months, sequencing-related business will comprise “probably 50 percent” of EA’s business. “I don’t necessary see that any time in the next 24 to 36 months sequencing will replace arrays,” he says. “The cost of arrays has come down to a point that it still makes sense to utilize both expression and genotyping arrays to screen populations. I think as the cost of sequencing continues to come down, eventually sequencing will encroach into the territory that’s been owned by microarrays for the last ten years.”
So far, EA remains focused on genomics, and steers clear of expanding into other areas, but McPhail says EA would consider helping clients with a specific request such as a protein assays performed on an ELISA.
He is excited about new sequencing technologies and compares their potential to what happened to microarrays.
“Microarrays revolutionized how we think about nucleic acid applications. Even going back further to when PCR was first introduced, one could not imagine the types of applications that would become available through utilization of that technology. I once had a client tell me that expression analysis begets more expression analysis [as people look at the data and understand more ways to use it]."
“I think over the next five years that same thing will apply to next generation sequencing. At this point some of the third generation technologies will give us the capability to do things that we haven’t been able to imagine in the past. [Consider] long-read technology. When we start to get to 10,000-base reads the things we’ll be able to do are absolutely phenomenal. I think this will lead to applications that sitting here I can’t imagine.”
EA’s formula seems to be working. Client retention is one much-watched measure. Clients in 2006 and 2007 that represented about 90% of EA revenue were still clients in 2008 and 2009, reports McPhail. Head count grew 20 percent last year to about 40 and the EA CEO anticipates another 20 percent staff growth this year. His revenue growth target is even more ambitious – 40 percent.
“Our company has actually begun to morph into providing not just data that will improve the diagnosis, management and treatment of complex diseases but also providing data that has a commercial application in [Ag-Bio]. We have initiated some recent contracts with animal health companies and we believe that some of these could become exceptionally large agreements over time. The average unit price associated with the sale of our services is lower to these individuals but the volume of specimens could be much, much larger.”
Currently, pharmaceutical customers represent about 60 percent of EA’s business with the remainder split among biotechs, diagnostics companies, academia and the federal government. Project sizes vary widely. A small one might entail 50 samples. A very large one could involve 25,000 samples analyzed over a multi-year contract. EA accepts a variety of specimen types (e.g., tissues, blood, FFPE tissue, RNA, and DNA).
McPhail is quick to say EA prides itself on being an early adopter. “We tend to jump into new technologies quickly, and try to make them work. If they don’t than we move on.”
The central business model, at least now, is a services play. But McPhail agrees EA has aspirations for IP ownership and says, “I think that we’ll see more of that come to bear with new sequencing technologies. We’re beginning to talk to numerous diagnostics companies about partnerships to perform research and development around clinical diagnostic applications they can then take and package and sell. Or to assist a pharmaceutical company in developing genomic signatures that can be utilized in a phase three clinical trial.”