ArtusLabs is a phoenix of sorts. Rising from the ashes of Electronic Lab Notebook (ELN) supplier Synthematix, ArtusLabs is focused on creating data analysis tools for its core informatics platform, the Ensemble for Life Sciences. The North Carolina company has 15 employees and has received $3.1 million in first round funding.

Robin Smith, CEO of ArtusLabs, formed the company in 2007, two years after selling Synthematix to Symyx Technologies (see IBO 2/28/05). Mr. Smith had identified a need for an informatics system that could make decisions based on data stored in LIMS, Scientific Data Management Systems (SDMS) and ELNs.

The Ensemble for Life Sciences software connects structured and unstructured data across all lab information systems, including SDMS, ELNs and LIMS. Available in LIMS-like and ELN-like configurations, the Ensemble competes with LIMS and ELNs, as well as with master data management and collaborative technology platforms. The Ensemble takes unstructured data from a document, such as a molfile (which contains a molecule’s properties), and inserts it into a structured database. It then associates the data with a project or piece of analytical data, such as a molecule of interest. Mr. Smith told IBO that standard LIMS generally deal with structured data. ”LIMS fall down because although you may have a lot number, you may want to find where the materials safety data sheet is, or some other kind of document associated with the data. To do this, you need to reach into the document management system,” he said.

The company modeled how the Ensemble associates data on social-networking platforms, which suggest relationships based on existing relationships within a network. “The Ensemble can tell a researcher ‘X biological screening result may belong to Y molecule.’ Nobody has made that attempt yet to apply social-networking algorithms to [research] data,” said Mr. Smith. Users range from metabolomics and proteomics researchers to legal groups checking for infringement of intellectual property.

The Ensemble’s LIMS-like and ELN-like configurations differ in their user interfaces and content layouts. The LIMS-like configuration’s interface focuses on search tools for specific data. The ELN-like configuration focuses on a project’s workflow, including witnessing and signing. According to Mr. Smith, the LIMS-like configuration can work with large molecules. “A lot of the times, LIMS don’t have the capability of handling large molecules, such as peptides, proteins or enzymes. So, for example, we have one implementation where people can track and correlate data to those large molecules. This really isn’t available in the market today,” he said.

Perhaps the best example of ArtusLabs’ effort to make sense of stored data is the MethodGenius. Using Ensemble, the MethodGenius can suggest the best separation and deconvolution methods based on pre-existing separation and deconvolution data. As described by Mr. Smith, the MethodGenius “spits back empirical methods from the historical archives of an organization to say ‘if you use these methods with this detector, this flow rate and this column, you’re highly likely to get separation between these molecules.’ It’s not theoretical, it’s all empirical.”