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With a Slimmed-Down Strategy, Predictive Patterns Picks up Where MMC Left off


It didn’t take long for Molecular Mining’s software to find a new home following the company’s closure in March. Tom Radcliffe and Mark Chatterley, the former director and manager of software development at Molecular Mining, respectively, jumped at the opportunity to launch a new bioinformatics company around the GeneLinker microarray analysis platform.

Radcliffe, who joined Molecular Mining “exactly a year and a day before we closed” and “rapidly fell in love” with the software, said the entrepreneurial urge came on strong after the company ceased operations. Realizing that “there’s a value proposition there if we can deliver GeneLinker to individual researchers at a cost they can afford,” he and Chatterley wasted no time negotiating a non-exclusive license to sell, support, and develop new versions of the software from Parteq Innovations, the Queens University tech transfer company that retained rights to the technology following the closure of Molecular Mining.

Despite the familiar faces, the software is in quite a different environment than its former home: It will be living on the web. The two-person company does not plan to hire a sales force, but is marketing the software solely through its website.

Radcliffe said that a key part of this strategy is ensuring a high ranking in search engines; and sure enough, the young firm’s website appears at the top of the hit list for a Google search on “gene expression analysis software” [typing in the phrase without quotes yields a second-place spot, just below the web page for Michael Eisen’s lab.]

“Web-based selling is obviously going to be considerably cheaper in terms of cost of sales than running a large sales force,” Radcliffe said. “We will see whether or not it’s successful.”

Even if Google doesn’t turn out to be the most effective marketing tool, Radcliffe said that Predictive Patterns’ narrowness of focus should help it survive in a highly competitive marketplace where its predecessor failed. “MMC had this three-legged business model [software, services, and research collaborations], and for a small company it was difficult to cover that kind of broad perspective,” Radcliffe said. “We want to stay focused strictly on the software, and that’s probably our biggest difference.”

Unlike many bioinformatics software companies, Predictive Patterns has adopted a simple and transparent pricing structure that is “substantially lower” than the pricing model for the software under MMC.
The entry-level GeneLinker Gold 3.1 is $995 for a single-user license, while the high-end GeneLinker Platinum 2.1 is $4,995. Current MMC customers can purchase a service contract for GeneLinker Gold and Platinum for $495 and $2,495, respectively. All fees are for a perpetual license and include a year’s worth of upgrades.

The company does not offer an academic discount, but claims that its regular prices are “far below” its competitors’ academic discounts.

In another departure from Molecular Mining, Predictive Patterns has discontinued a version of GeneLinker platinum that was bundled with an IBM workstation. “People who are running high-end analyses often already have high-end hardware, and I didn’t see the need for that,” said Radcliffe.

The company’s website has been live since June 2, and “we’re starting to get fairly regular traffic in downloads,” Radcliffe said, with interest both from former MMC customers as well as potential new customers.

As far as new hires go, Radcliffe said that he and Chatterley are currently talking with several “senior members” of the former MMC development team, but the internally funded firm plans to “grow as resources permit.”

Future enhancements to the GeneLinker products include more scripting capability so that users can automate their analyses, as well as expanding the use of the technology into a broader application domain.

“One of the things that I spent quite a bit of time on at MMC was working on various proteomics problems,” said Radcliffe. “The software, as it stands, can operate on proteomics data just fine…So making people aware of the fact that they can use software in other areas is one direction we’d like to take.”

— BT

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