Fina Technologies Announces Completion of Series A Financing

Reed Elsevier Ventures Leads Round Which Includes Excel Venture Management

Contact:

Thomas Neyarapally
Gene Network Sciences
(617) 494-0492
tneyarapally@gnsbiotech.com

Cambridge, MA — December 10, 2009 — Fina Technologies, Inc. (Fina Technologies) today announced that it has completed a $4.5 million Series A financing, which includes a lead investment by Reed Elsevier Ventures, the venture capital arm of the multibillion dollar Anglo-Dutch media conglomerate Reed Elsevier, owner of such assets as Lexis-Nexis, and an investment from the venture capital firm Excel Venture Management.

“Firms that have unique platforms that address the explosion of data being generated across several industry verticals represent tremendous opportunities for growth,” said Kevin Brown, Partner at Reed Elsevier Ventures. “Fina Technologies has such a platform which we believe can make an impact in the world of quantitative financial trading and beyond.”

Fina Technologies was formed as a spin out from computational biotechnology company Gene Network Sciences, Inc. (GNS), of Cambridge, MA, which remains Fina’s largest shareholder following the financing. Fina Technologies has a license to GNS’s REFS^TM software platform, a supercomputer-driven model learning and simulation platform utilized by GNS for many years in collaborations with pharma and biotech companies such as Pfizer, Johnson & Johnson, and Biogen Idec. REFS^TM systematically turns multiple layers of disparate data types into an unprecedented view of a system of interest, rapidly performs billions upon billions of calculations to determine how the variables describing the system interact with and causally influence one another (Reverse Engineering). These computer-assembled models are then queried rapidly through billions of in silico experiments (Forward Simulation) to discover the most important variables driving the system’s behavior and to predict the system’s behavior under previously unobserved conditions.

“Reed Elsevier Ventures and Excel Venture Management bring to the table substantial capital, valuable industry-specific expertise, contacts through their portfolio companies and the experience of their principals,” said Josh Holden, CEO of Fina Technologies. “With these new resources we will be moving forward aggressively with the further development of REFS^TM in quantitative finance and exploring development for other business applications.”

“Fina Technologies represents the first of multiple opportunities for GNS to form separate companies that utilize our REFS^TM platform to rapidly extract actionable knowledge and insights from the onslaught of an exponential increase in data in several industry verticals,” said Colin Hill, Chairman of the Board of Directors of Fina Technologies and CEO of GNS. “Fina Technologies’ closing of a substantial Series A financing round with investments from groups of the caliber of Reed Elsevier Ventures and Excel Venture Management is a great vote of confidence. I’m very bullish on the ability of the hugely capable Fina management team to unleash the power of the REFS^TM platform for the quantitative finance markets.”

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About Fina Technologies

Fina Technologies, Inc. (Fina Technologies) is a spinoff of Gene Network Sciences (GNS) focused on applying the REFS^TM model learning and simulation platform and other machine-learning tools to large-data problems in the worlds of finance and e-Commerce. Fina Technologies applies massively parallel supercomputing technology combined with cutting edge machine learning techniques to create quantitative trading algorithms and deliver business solutions for a new class of massively data intensive applications. Fina Technologies is currently based in Cambridge, MA, and was formed in 2008.

About Gene Network Sciences

Founded in 2000, Gene Network Sciences ( http://www.gnsbiotech.com ) is a leader in biosimulation with its ability to derive molecular mechanisms of drugs and diseases directly from molecular profiling and clinical data. Based in Cambridge, Massachusetts, and Ithaca, New York, GNS uses its REFS^TM (reverse engineering and forward simulation) technology in pharmaceutical and healthcare settings to rapidly turn combinations of genetic, genomic, and clinical measurements into models of disease progression and drug response. These models are then simulated to discover both new targets for drug intervention and genetic markers of drug response that allow patients who will respond to a given drug treatment to be matched to a particular clinical trial and treatment option. By discovering how and why specific sets of genes and drug candidates impact human biology, GNS technology enables the rapid development of breakthrough drug and diagnostic products and the matching of patients to the optimal therapy.

For more information, contact Thomas Neyarapally, 617-494-0492.