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In Silico Discovery Works With U Manchester To Add Semantics to K3 Integration Platform

In Silico Discovery, a data-integration middleware provider, plans to launch a new version of its K3 integration platform early next year that will include aspects of the TAMBIS (Transparent Access to Multiple Bioinformatics Information Sources) semantic search application developed at the University of Manchester. 
The upcoming system will bring together two influential academic data-integration research projects. K3 is built upon Kleisli, a federated data-integration technology that was developed at the University of Pennsylvania in the 1990s, while TAMBIS was one of the first projects to use ontologies as the basis for biological data integration.
The new release underscores the resilience of the Kleisli technology, which has appeared in numerous commercial iterations since the late 1990s: first as KRIS (Kleisli Related Integration System) from Kris Technology, then as K1 and later DiscoveryHub from GeneticXchange. Amersham Biosciences (now GE Healthcare) began marketing DiscoveryHub in 2003, but has since discontinued the product.
Brian Donnelly, formerly CEO of GeneticXchange, told BioInform that he founded In Silico Discovery several years ago to rewrite the Kleisli technology “from the ground up” in Java. The company joined an ongoing collaboration between the Penn developers and GlaxoSmithKline to develop a version of the system that was then called K2.
“GSK had been using software from the University of Pennsylvania for about the last eight years called K2,” Donnelly said. “But it was an academic prototype, and they essentially paid In Silico Discovery and the University of Pennsylvania to rewrite it from scratch to be quite a sophisticated Java data-integration platform.”
K3, the third generation of the technology, was completed in June 2005. The current version, K3 6, supports around 400 users at GSK and is also deployed at several other pharmaceutical companies that Donnelly said he could not name.
In August, In Silico Discovery signed a distribution agreement with IDBS to market K3 6 alongside its E-WorkBook technology and other tools.
Donnelly said that In Silico Discovery, which employs around a dozen developers located around the world, has identified the original equipment manufacturer model as the best form of marketing the K3 middleware.

“K3 has always been able to do powerful query data integration, but you have to write very complex SQL,” Donnelly said. “That’s not ideal for scientists.”

“We truly just want to be an OEM,” he said. “By providing our technology through IDBS, it’s fantastic. If people don’t really hear very much about In Silico Discovery and K3, it wouldn’t really matter because we’re letting the bigger company do all the work.”
Now the company is setting its sights on the launch of K3 7, which is currently in early access. The company expects to release it for general use at the end of the first quarter of 2007.
The new version is expected to overcome a key limitation in K3 by enabling more user-friendly querying. “K3 has always been able to do powerful query data integration, but you have to write very complex SQL,” Donnelly said. “That’s not ideal for scientists.”
Donnelly said that his team began working with the TAMBIS team at the University of Manchester in order to add ontology-enabled searching to the framework.
“We built a Tambis fused with K3, so we’ve got a complete ontological semantic search system,” he said. The new system reads in OWL ontologies in order to enable “very sophisticated queries” without writing SQL, Donnelly said.
Data integration has been a perennial challenge for biotech and pharmaceutical companies for years, but as Kleisli’s previous market failures demonstrate, high demand has not translated into commercial success for data-integration tool providers.
Donnelly is confident, however, that the new semantic capabilities of K3 will enable the platform to turn the corner and become widely adopted. “Every single big pharmaceutical company is engaged in some ontology and semantic search project,” he said. “They’re building the models, but the technology we’re providing will allow them to connect it all up.”
Donnelly added that he’s “pretty certain” that the company will have some “solid implementations” of the new system within the next two to three months.

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