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Motorola Launches First High-density Human Array, Challenging Affymetrix

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Motorola Life Sciences has moved forward in its bid to enter the high-density array business with the August 15 public launch of its Uniset Human I bioarray at the Drug Discovery Technology 2001 conference in Boston.

The company said the array, which includes approximately 9,200 unique oligonucleotides representing human EST clusters, is the first in a series it is planning to introduce over the next several months.

“We are certainly going to be a head-to-head competitor with Affymetrix,” said Mike James, vice president of commercial operations at Motorola Life Sciences.

A 10K rat genome bioarray, aimed at companies studying rat toxicology, is positioned for an early September release, and a second 10K human bioarray called Uniset II, which will feature a different group of human genes than Uniset I, is planned to follow towards the end of the year, said James.

Additionally, the company plans to introduce a P450 array that is designed to detect 75 SNPs within the P450 gene family, representing 18 common alleles and covering 7 genes.

The company will design the arrays to be used with Motorola’s CodeLink software and database platform.

The company also faces competition from Incyte, which offers a set of Human Foundation LifeArrays with just over 9,200 cDNAs each, as well as Corning, which has had a 10,000-spot cDNA array in the works since September 2000.

But Motorola is not just going after researchers who already use pre-fabricated arrays.

“The biggest competitor is self-spotting arrayers,” said Bill Coty, Motorola Life Sciences’ director of product development, “People who have done a lot of work in their own labs and need to move to oligonucleotides from cDNA. Shifting to oligos is major change, and Motorola is working to help companies make the change.”

To win over customers, Motorola could try to produce a cheaper array — a strategy analysts have long speculated would help a player in the field grab some of the array pie away from Affymetrix. But the company is trying a different tactic, that of offering an array that it says offers higher performance than the competition.

While the gene content in Affymetrix chips is derived solely from the publicly available UniGene database, the content on Uniset 1 comes from sequence in the UniGene database, that is compared against Incyte’s LifeSeq database. Uniset II will use even more UniGene data in addition to data from Incyte, said Scott Magnuson, Motorola Life Sciences’ head of genomics and bioinformatics.

To minimize non-specific hybridizations and thus make its oligos work better to identify gene expression, Motorola has enlisted the oligo design services of Israeli bioinformatics and proteomics company Compugen. The company has used Compugen’s oligo selection algorithm, which took two years to design, to select three oligos for each gene or EST cluster, Magnuson said. These oligos were then spotted on a chip. After testing against biological samples, the results were compared to select the top performing oligo for the UniSet chip.

Motorola also uses outside partners for actual oligo production. The company obtains the oligos for spotting from vendors that have “extensive quality control in place,” said Coty. “We’ve worked to assure probe identity through mass spec, and probe purity, and tie our Oracle database for managing oligos to vendor computers that direct the oligonucleotide synthesis, so we have a direct link to what oligos get synthesized.”

The oligos are printed on an open glass slide and can be used with most chip readers and scanners, such as the Axon scanner. This open system allows researchers who already have a scanner in their do-it-yourself facility to get into the microarray field more easily, the company has said.

While the launch of Uniset is a bold step forward for Motorola, the company is planning to jump much deeper into both research and diagnostic areas in the future, said Coty.

“We see this as a first step in commercialization of a broad range of products, including tools for SNP genotyping and longer-term research in proteomics,” Coty said.

— KH

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