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Sequenom Enters Gene-Expression Market On BU Grad Student Ding s Eureka Moment


For San Diego-based Sequenom, gene-expression profiling is a new line of business, and one that is potentially profitable.

For a Boston University PhD student, Chung Ming Ding, Sequenom’s gene-expression profiling application means he is another step closer to getting his sheepskin.

Earlier this week, Sequenom issued financial guidance reports and gave details on its plans to enter the gene-expression profiling business, using its powerful and well-established MassArray technology platform, which is akin to an automated mass spectrometer with powerful software and full automation. The company maintains the 200K MassArray system, a giant application of its software, and is rolling out the 20K system, a smaller installation of the technology that was introduced in October.

With its Precision Expression Profiling product, the company combines its MassArray platform of proprietary enzymatic reactions, bioinformatics, and a miniaturized chip-based format, with its Quantitative Gene Analysis software for high-throughput gene expression tools and, suddenly, enters a market that it estimates at $500 million, rather than the estimated $200 million a year market for genotyping.

Charles Cantor, the company’s chief science officer and also a Boston Unversity professor of biomedical engineering and pharmacology, gives the credit for enabling this leap to Ding, who is Cantor’s PhD student. Ding figured out a way for the MassArray technology to support gene expression analysis. The company, however, is not releasing details of the process, pending publication in a peer-reviewed journal, said Cantor.

However, Cantor said the technique involves introducing a fake allele into Sequenom’s standardized assay process.

“[Ding] realized that if he just makes a fake allele, and throws it into cDNAs as a standard, then nothing else in the process changes, everything is the same, the same reactions, the same software,” Cantor told BioArray News. “The interpretation is an expression level rather than a genotype level. And, because you are using an internal standard, you know the number of molecules that you added, therefore you can compute the number of molecules that were in the sample.”

It’s trivial to implement, Cantor said. In fact, Sequenom customers who already have the equipment for genotyping, can now do gene-expression profiling on the same equipment. Sequenom’s client list includes GlaxoSmithKline and Incyte.

The day the paper is accepted for publication, Sequenom will send a note of explanation to its customers, Cantor said.

This new application, piggybacked on top of the MassArray technology and other new applications to come, should help increase sales by approximately 40 percent in 2003, Toni Schuh, Sequenom’s president and chief executive officer, said in a statement. That translates into the goal of cash-flow breakeven by the fourth quarter and a revenue target of $46 million, the company said

Sequenom will also be able to reap revenues from the reagents and other consumables from this application, and others, who might have hesitated before entering the gene-expression arena, will now be tempted, he said.

“Our customers will use more consumables,” Cantor said, adding, “We think that people will buy the hardware to do gene expression analysis who weren’t convinced to do genotyping because the performance is superior.”

The competition is the Taqman and Light cycler processes, and, maybe, companies with gene expression platforms such as Lynx Therapeutics, Cantor said.

Ding will receive a reward in the form of a gift to Boston University of a Sequenom technology platform worth a half a million dollars. It should help him to finish his thesis, Cantor said.



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